OZCAR: The French Network of Critical Zone Observatories

Open Archive Toulouse Archive Ouverte OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible This is an author’s version published in: http://oatao.univ-toulouse.fr/20931 Official URL: https://doi.org/10.2136/vzj2018.04.0067 To cite this version: Gaillardet, Jerome and Braud, Isabelle and Gandois, Laure and Probst, Anne and Probst, Jean-Luc and Sánchez-Pérez, José Miguel and Simeoni-Sauvage, Sabine OZCAR: the French network of Critical Zone Observatories. (2018) Vadose Zone Journal, 17 (1). 1-24. ISSN 1539-1663 Any correspondence concerning this service should be sent to the repository administrator: [email protected] Page 1 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 281. 292. 303. 314. 325. 336. 347. 358. 369. 3710. 3811. 3912. 4013. 4114. Gaillardet J.1, Braud I. 2, Hankard F.1, Anquetin S.3, Bour O.4, Dorfliger N.5, de Dreuzy J.R.4, Galle S.3, Galy C.6, Gogo S.7, Gourcy L.5, Habets F8., Laggoun F.7, Longuevergne L.4, Le Borgne T.4, Naaim0Bouvet F.9, Nord G.3, Simonneaux V.10, Six D.3, Tallec T.10, Valentin C.11 Abril G.12, Allemand P.13, Arènes A.14, Arfib B.15, Arnaud L.3, Arnaud N.16,29, Arnaud P.17, Audry S.18, Bailly Comte V.19, Batiot C.20, Battais A.4, Bellot H.9, Bernard E.21, Bertrand C.22, Bessière H.5, Binet S.7, Bodin J.23, Bodin X.24, Boithias L.18, Bouchez J.1, Boudevillain B.3, Bouzou Moussa I.25, Branger F.2, Braun J. J.18, Brunet P.20, Caceres B.,26 Calmels D.27, Cappelaere B.20, Celle0Jeanton H.22, Chabaux F.28, Chalikakis K.29, Champollion C.30, Copard Y.31, Cotel C.28, Davy P.4, Deline P.24, Delrieu, G.3, Demarty J.20, Dessert C.1, Dumont M.32, Emblanch C.29, Ezzahar J.33, Estèves M.3, Favier V.3, Faucheux M.34, Filizola N.35, Flammarion P.36, Floury F.1, Fovet O.34, Fournier M.31, Francez A. J.37, Gandois L.46, Gascuel C.34, Gayer E.1, Genthon C.3, Gérard M. F.4, Gilbert D.22, Gouttevin I.32, Grippa M.18, Gruau G.4, Jardani A.31, Jeanneau L.4, Join J. L.38, Jourde H.20, Karbou F.32, Labat D.18, Lagadeuc Y.37, Lajeunesse E.1, Lastennet R.39, Lavado W.42, Lawin, E.47, Lebel T.3, Le Bouteiller, C.9, Legout C.3, Le Meur E.3, Le Moigne N.31, Lions J.5, Lucas A.1, Malet, J. P.41, Marais0Sicre C.11, Maréchal J. C.19, Marlin C.27,42, Martin P.43, Martins J.3, Martinez J. M.18, Massei N.31, Mauclerc A.5, Mazzilli N.29, Molénat, J.44, Moreira0Turcq P.18, Mougin E.3, Morin S.32, Ndam Ngoupayou J.45, Panthou G.3, Peugeot C.18, Picard G.3, Pierret M. C.28, Porel G.23, Probst A.46, Probst J. L.46, Rabatel A.3, Raclot D.44, Ravanel L.24, Rejiba F.31, René P.48, Ribolzi, O.18, Riotte J.18, Rivière A.49, Robain H.11, Ruiz L.34, Sanchez0Perez J. M.46, Santini W.18, Sauvage S.46, Schoeneich P.50, Seidel J. L.20, Sekhar M.51, Sengtaheuanghoung O.52, Silvera N.11, Steinmann M.22, Soruco A.53, Tallec G.54, Thibert E.9, Valdes Lao D.55, Vincent C.3, Viville D.28, Wagnon P.3, Zitouna R.56 Affiliations IPGP, Sorbonne Paris Cité, University Paris Diderot, CNRS, Paris 75231, France IRSTEA, UR RiverLy, centre de Lyon0Villeurbanne, 69625 Villeurbanne, France Université Grenoble Alpes, CNRS, IRD, Grenoble0INP, IGE, 38000 Grenoble, France Géosciences Rennes, UMR 6118, CNRS, Université Rennes 1, Rennes, France BRGM. Water Environment and Ecotechnologies Division. Orléans, France ANDRA Research and development division, 55290 Bure, France. UMR ISTO, CNRS, BRGM, Université d’Orléans, Orléans, France UMR Métis, Sorbonne Université, UPMC, CNRS, Paris 75252, France. Univ. Grenoble Alpes, Irstea, UR ETNA Centre d’Etudes Spatiales de la Biosphère, Toulouse, France iEES0Paris, SU, USPC, UPEC, CNRS, INRA, IRD, F093140 Bondy, France. UMR BOREA, MNHN, Paris, France. Université de Lyon, UCBL, ENSL, CNRS, LGL0TPE, 69622 Villeurbanne, France SOC 0 Société d’Objets Cartographiques, Paris, France 1 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 4215. 4316. 4417. 4518. 4619. 4720. 4821. 4922. 50 5123. 5224. 5325. 5426. 5527. 5628. 5729. 5830. 5931. 6032. 6133. 6234. 6335. 6436. 6537. 6638. 6739. 6840. 6941. 7042. 71 7243. 73 7444. 7545. 7646. 7747. 7848. 7949. 8050. 8151. 8252. 8353. 8454. 8555. 8656. Aix Marseille Univ, CNRS, IRD, Coll France, CEREGE, Aix0en0Provence, France CNRS INSU, Paris, France. IRSTEA, UR Recover, Aix en Provence, France Géosciences Environnement Toulouse (GET), CNRS, IRD, UPS, Toulouse, France BRGM, D3E, NRE, 1039 rue de Pinville, 34000 Montpellier, France, Hydrosciences Montpellier (HSM), Univ. Montpellier, CNRS, IRD, Montpellier, France Univ. Franche0Comte, Théma, Besançon, France Université Bourgogne/Franche0Comté, CNRS, Chrono0environnement0UMR 6249, Besançon, France IC2MP, CNRS Université de Poitiers, Poitiers France. Univ. Savoie, Edytem, le Bourget de Lac, France Univ. Abdou Moumouni (UAM), Niamey, Niger INAMHI, Quito, Ecuador GEOPS, Univ. Paris0Sud, CNRS, Université Paris0Saclay, Orsay, France UMR LHyGeS, EOST, Université de Strasbourg, Strasbourg, France UAPV, UMR1114 EMMAH, F084914 Avignon, France Géosciences Montpellier, CNRS, Université Montpellier, UA, F034095 Montpellier, France. Normandie Univ, UNIROUEN, UNICAEN, CNRS, M2C, 76000 Rouen, France Météo0France 0 CNRS, CNRM UMR 3589, Centre d'Etudes de la Neige, Grenoble, France Ecole Nationale des Sciences Appliquées (ENSA), Université Cadi Ayyad, Safi, Morocco UMR SAS, INRA, Agrocampus Ouest, Rennes, France Amazonas State University (UFAM), Geography Department, Manaus, Brazil IRSTEA Présidence, Antony, France Univ Rennes, CNRS, Ecobio 0 UMR 6553, F035000 Rennes, France. Université de la Réunion, Saint Denis de la Réunion, France. Université de Bordeaux, Laboratoire I2M, UMR 5295, France Peruvian National Service of Meteorology and Hydrology (SENAMHI), Lima, Peru IPGS, EOST, Strasbourg, France. Ministère de l’Enseignement Supérieur, la Recherche et l'Innovation, DGRI/SSRI, Paris, France. Université d'Avignon et des Pays de Vaucluse, UMR ESPACE 7300 du CNRS, 84029 Avignon cedex, France LISAH, Univ Montpellier, INRA, IRD, Montpellier SupAgro, Montpellier, France Department of Earth Sciences, University of Yaoundé 1, Yaoundé, Cameroon EcoLab, Université de Toulouse, CNRS, INPT, UPS, Toulouse, France Université d'Abomey Calavi, Benin Association Moraine, Luchon, France Mines ParisTech, PSL, géosciences. Fontainebleau, France. Univ. Grenoble Alpes, Pacte, Grenoble, France Indian Institute of Science and Indo0French Cell for Water Sciences, Bangalore, India. Department of Agricultural Land Management (DALaM), Vientiane, Lao PDR UMSA, University of La Paz, Bolivia IRSTEA, UR Hycar, 92 761 Antony, France UPMC Univ Paris 06, UMR 7619 METIS, 4 Place Jussieu, F075005 Paris, France INRGREF, Tunis, Tunisia 87 2 Page 2 of 103 Page 3 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 88 89 This paper presents the French Critical Zone initiative, called OZCAR (Observatoires de la 90 Zone Critique –Application et Recherche – Critical Zone Observatories – Application and 91 Research), a National Research Infrastructure (RI). OZCAR0RI is a network of instrumented 92 sites, organized in 21 pre0existing research observatories, or observation services, and 93 monitoring over the long term, different compartments of the zone situated between “the rock 94 and the sky”, the Earth’s skin or Critical Zone (CZ). These observatories are regionally0based 95 and all have their individual initial scientific questions, monitoring strategies, databases and 96 modeling activities. The diversity of OZCAR0RI observatories and sites is well representative 97 of the heterogeneity of the Critical Zone and of the scientific communities studying it. 98 Despite this diversity, all OZCAR0RI sites share a main overarching scientific question, 99 which is: how to monitor, understand and predict (“earthcast”) the fluxes of water, solutes, 100 gases and sediments of the Earth’s near surface and how they will change in response to the 101 “new climatic regime” (climate change, land use and land cover changes). 102 We describe in this paper a vision for OZCAR strategic development in the next decade, 103 aiming at designing an open infrastructure, building a national CZ community able to share a 104 common and systemic representation of CZ dynamics, and educating a new generation of 105 scientists more apt to tackle the wicked problem of the Anthropocene. We propose to 106 articulate OZCAR around the following main points: i) a set of common scientific questions 107 and cross0cutting scientific activities using the wealth of OZCAR0RI observatories along 108 gradients and the diverse disciplines, ii) an ambitious instrumental development program, iii) 109 a better interaction between data and models as a way of integrating the different time and 110 spatial scales as well as fostering dialogue between communities. 111 At the international level, OZCAR0RI aimed at strengthening the CZ community by providing 3 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 112 a model of organization for pre0existing observatories and by widening the range of CZ 113 instrumented sites. Embedded into the international CZ initiative, OZCAR is one of the 114 French mirrors of the European eLTER0ESFRI (European Strategy Forum on Research 115 Infrastructure) project. 116 117 : Critical Zone, Observatories, long0term observation, Earthcast, modeling, eLTER 118 119 120 121 We have entered the Anthropocene (Crutzen, 2002), a new period in which human activities 122 have become a geological force. Anthropogenic forcing affects many components of the Earth 123 system (Steffen et al., 2015) at a particularly high rate compared to the last million years since 124 have lived on the planet. This “great acceleration” (Lewis and Maslin, 2015) 125 has global manifestations, the more evident of which is the shifts in atmospheric greenhouse 126 gas concentrations and associated climate change, as well as accelerated land uses and land 127 cover changes due to urbanization and increased human pressure on the environment. This 128 “new climatic regime” is anticipated to have important implications at the regional scale, in 129 the “territories”, as defined by Latour (2018), where resources such as water, soil, and 130 biodiversity may dangerously be impacted, potentially leading to an unprecedented 131 degradation of human habitats, dramatic migrations or economic disasters. The terrestrial 132 surface, i.e. the zone located between the bedrock and the lower atmosphere, sustains basic 133 human needs such as water, food, energy (Banwart et al., 2013), and is critical for the 134 sustainability of the economical and recreational services they provide (Easterling, 2007; 135 Millenium Ecosystem Assessment Board, 2005). Achieving the Sustainable Development 4 Page 4 of 103 Page 5 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 136 Goals (UN, 2015) requires better understanding and prediction of the functions of this 137 “critical zone”. 138 The term “Critical Zone” (CZ) was defined by the U.S. National Research Council (NRC), as 139 the zone extending from the top of the canopy down to the base of the groundwater zone. 140 NRC listed the study of this “CZ” as one of the Basic Research Opportunities in the Earth 141 Sciences (U.S. National Research Council Committee on Basic Research Opportunities in the 142 Earth Sciences, 2001). The term “critical” emphasizes two notions. First is that the CZ is one 143 of the main planetary interfaces of Earth, i.e. the lithosphere0atmosphere boundary layer. It is 144 the layer where life has developed, where nutrients are released from rocks, and on which 145 ecosystems and food production rely. Almost by definition, the CZ is a planetary boundary, 146 shaped by both solar energy and internally0driven plate tectonics (mantle convection). This 147 geological vision of Earth’s surface is close to that developed one century ago by Vladimir 148 Vernadsky (1998), re0defining the term “biosphere” to denote the part of our planet that is 149 transformed by biogeochemical cycles triggered by the input of solar energy and by life 150 processes. The second notion implied by the term “critical” is that we need to take care of it. 151 The CZ is the human habitat in which we build our cities, from which we extract our food and 152 our water and where we release most of our wastes (Guo and Lin, 2016). As quoted by Latour 153 (2014), “under stress, it may break down entirely or shift to another state”. 154 The concept of the CZ offers a geological perspective on environmental questions, by 155 considering all transformation time scales from the million year to the second, and by 156 relocalizing environmental questions at the local/regional level, thus taking into account not 157 only global forcing but also local geological, ecosystemic, economic and societal constraints 158 (Arènes et al., 2018). The CZ initiative aims at fostering different scientific disciplines of 159 geosciences and biosciences (climatology, meteorology, glaciology, snow sciences, 160 hydrometeorology, hydrology, hydrogeology, geochemistry, geomorphology, geophysics, 5 Page 6 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 161 land surface interactions, pedology, agronomy, ecology, microbiology, 162 same questions, and at developing an integrated system0oriented understanding of the 163 habitable part of the planet (Brantley et al., 2017). 164 The Critical Zone Exploration Network (CZEN) initiative (http://www.czen.org/) was 165 proposed in 2003 under the leadership of the US National Science Foundation (Anderson et 166 al., 2004). CZEN aims to create a worldwide community of researchers and educators who 167 study the physical, chemical and biological processes shaping and transforming Earth’s CZ 168 through the development of Critical Zone Observatories (CZOs), i.e. well0instrumented and 169 well0characterized field sites in which the different scientific communities can collaborate to 170 better understand the transformations affecting this thin veneer coveringx Earth’s surface. 171 This integrated scientific approach must take into account short and long time scales, the 172 interaction between deep subsurface processes and their coupling with above ground 173 dynamics. 174 So far there is no “official” definition for how a CZO should be designed. Multidisciplinary 175 and systemic approaches (“the CZ as an entity”, Brantley et al., 2017) seem to be common 176 denominators of all the so0called CZOs. In the US, CZOs were first established in 2007 177 (Anderson et al., 2008; White et al., 2015) and presently feature nine instrumented sites, 178 generally river catchments or a whole landscape of limited size (Brantley et al., 2017). 179 Following the US CZO initiative, several countries successfully launched CZO programs. 180 This paper presents the French Critical Zone initiative, called OZCAR (Observatoires de la 181 Zone Critique –Application et Recherche – Critical Zone Observatories – Application and 182 Research), a National Research Infrastructure (RI). The aim of this paper is to provide an 183 overview of the OZCAR network, its objectives, components, scientific questions and data 184 management (section 2); the current status of instrumentation (section 3) along with that of 185 databases and metadatabases (section 4), and existing initiatives for linking data and models 6 ) to work on the Page 7 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 186 based on OZCAR data (section 5). The discussion (section 6) builds on the current 187 achievements to take a step forward and describe the ambitions of OZCAR and how this 188 initiative can be related to others worldwide. Most of the ideas in this paper were discussed 189 during the kickoff meeting of OZCAR held in Paris, Feb 7, 2017. 190 ! " 191 192 2.1. OZCAR, a network of networks 193 OZCAR is a Research Infrastructure launched in December 2015 with the support from the 194 French Ministry of Education and Research. OZCAR gathers and organizes more than 60 195 research observation sites in 21 pre0existing observatories that are operated by diverse 196 research institutions and initially created for a specific environmental question of societal 197 relevance, some of them, more than 50 years ago. The details of OZCAR constitutive 198 observatories and sites are in # 199 characteristic of being highly instrumented areas designed to answer a particular scientific and 200 societal question of local importance, generating continuous standardized series of 201 observations on water quality, discharge, ice and snow, soil erosion, piezometric levels, soil 202 moisture, gas and energy exchange between ground and atmosphere, and ecosystem 203 parameters (# 204 Over the last decade, considerable efforts have been made in France to encourage the various 205 research institutions to join together to monitor Earth’s surface. This was enabled through the 206 creation of the Alliance for Environmental studies “AllEnvi” (www.allenvi.fr) in 2010, 207 formally gathering all the research institutions in charge of studying Earth’s terrestrial surface. $ . All these observatories share however the same $ ). They cover different compartments of the CZ ( 208 209 2.2. The “building blocks” of OZCAR 7 !). Page 8 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 210 Below, we present a short description of the architecture, aims and significant results of the 211 different blocks composing the OZCAR infrastructure that is organized according to seven 212 thematic networks. A detailed description of the existing observatories and their most 213 significant scientific achievements are given in Appendix 1. 214 215 2.2.1. # 216 from zero order basins to the whole Amazon River system (see # 217 material for the details about site location, climate, geology, land use, main scientific 218 questions and measured variables). A number of them are shared with research institutions 219 from Southern Hemisphere countries. The common denominator is the use of catchments as 220 integrators of hydrological, biogeochemical or solid transport processes at different scales. 221 They constitute sentinels of land use/land cover and climate change at the regional level, some 222 of them for more than 40 years. They have all been designed to address a specific basic or 223 applied scientific question, span climate gradients ranging from the tropics to the temperate 224 zone, and cover a range of bedrock types ( 225 “pristine”, most of the RBV catchments are intensively cultivated or managed for forestry, the 226 extreme case being a peri0urban catchment draining into the Rhône River in Lyon. Well 227 represented in RBV are monitored karst systems as complex hydro0geol0ogic entities that are 228 characterized by strong surface/subsurface interactions and significant water, mass, energy, 229 and geochemical transport within the CZ. RBV also addresses larger scale (typically 230 continental issues such as the concurrent role of climate and land0use changes on the water 231 and energy budgets on the terrestrial surface in western Africa, continental hydrology and the 232 biogeochemistry of the Amazon, Orinoco and Congo basins, or the genesis of extreme 233 precipitation events and flash floods in southern France. The long term monitoring reveals 234 fast0changing environments, as illustrated for instance by the decrease of sulfate recorded in %& (Réseau des Bassins Versants) is constituted of catchments ranging $ in supplementary '). While some of them can be considered as 8 Page 9 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 235 the Strengbach stream since 1986 ( (; OHGE, Vosges, France). This decrease of sulfate in 236 the stream is an iconic case showing the virtue of continuous long term river monitoring and 237 the reduction of anthropogenic acidic emission by European and North American industries 238 since the 1980’s. 239 240 2.2.2. The )* observation service (hplus.ore.fr), created in 2002, is a network of 241 hydrogeological sites located in France and India, aimed at characterizing and modeling 242 flows, transport and reactivity in heterogeneous aquifers. The aim of H+ is the development 243 of characterization and modeling methods adapted to describe the strong heterogeneity (i.e. in 244 terms of permeability and thus residence times) that characterizes the deep CZ. Within this 245 framework, H+ scientists investigate the hydrological functioning and the reactive transport 246 aspects in heterogeneous reservoirs, including karstic aquifers (Larzac, HES Poitiers, LSBB, 247 Mallorca), altered fractured systems (Choutuppal, India, Ploemeur), and alluvial systems 248 (Auverwatch). H+ observatories have particularly developed a specific hydrogeophysical and 249 hydrochemical instrumentation approach for imaging and characterizing the hydrodynamics 250 and transport processes, for measuring residence time distributions but also for taking into 251 account heterogeneity within appropriate predictive models. 252 253 2.2.3. The + %$, - . observatory focuses on the cryosphere. It aims to answer the 254 following scientific questions: i) How will climate changes impact surface energy and mass 255 budgets of snow / ice0covered surfaces and permafrost ground temperature at different spatial 256 (local to regional) and temporal (seasonal to multidecadal) scales? ii) How will snow/climate 257 feedback mechanisms enhance or attenuate glacier, ice sheet and permafrost changes in the 258 near future? How can observations help to identify climate models weaknesses and to 259 improve the simulations of cryosphere components? iii) What is the future snow and ice0cover 9 Page 10 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 260 retreat and wastage and what will be the impact on water resources and sea level rise? iv) 261 How do glaciers, rock glaciers and ice sheet dynamics respond to changes in temperature, 262 surface mass balance and hydrological processes, and what are the impacts in terms of natural 263 hazards? In order to address these questions, the CRYOBS0CLIM network collects, archives 264 and disseminates a comprehensive and consistent set of observations on the main components 265 of the terrestrial cryosphere (glaciers, snow, permafrost) in a series of instrumented sites 266 located at high altitudes and high latitudes (European Alps, tropical Andes, Himalayas, 267 Antarctica, Svalbard). The monitored variables and research topics are described in # $ . 268 269 2.2.4. The 0 observatory is a network of four French instrumented sites 270 and one Siberian mire aimed at studying the effect of global change on the carbon sink 271 function and the hydrological budget of temperate and sub0boreal peatlands which are 272 ecosystems containing a third of the global surface carbon stock in an area accounting for 273 only 305% of the land surface. The French sites were set up in 200802010, according to a 274 climatic gradient (lowland to mountain climate), to ensure long0term monitoring of 275 greenhouse gases (GHG: CO2, CH4, H2O, N2O), dissolved and particulate organic carbon 276 (DOC, POC) fluxes as well as environmental variables that impact GHG, DOC and POC 277 fluxes, and to generate interoperable databases. /" 278 279 2.2.5. The 280 climate change and increasing anthropogenic pressures on the hydrologic and agro0ecologic 281 evolution of agricultural regions, at various spatial and temporal scales, in a perspective for 282 sustainable management of water and soil resources. The OSR concept is implemented in two 283 sites located in south0west France and in Morocco (Tensift Basin). The specific OSR 284 approach is the extensive use of remote sensing for surface characterization (land use, $ / 0 is documenting the long term effects of $1 10 Page 11 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 285 vegetation cover, evapotranspiration, soil moisture, snow cover, etc.) combined with a multi0 286 scale monitoring network of (1) continuous long0term monitoring of experimental plots (crop 287 and snow sites), (2) hundreds of plots annually monitored for surface state, land cover, etc., 288 and (3) experiments conducted at catchment scale with reinforced observations for water and 289 energy budget evaluation. 290 291 2.2.6. The $2$ (Observatory network for groundwater systems at French national level) 292 was initially set up to answer water management issues and was strengthened in the 293 framework of the implementation of the European Water Directive. It gathers more than 294 77 000 stations, with 74 000 groundwater quality0moniroring stations and 4400 monitoring 295 wells. All types of aquifers are monitored in Metropolitan territories as well as French 296 overseas 297 (http://www.ades.eaufrance.fr) managed by several governmental agencies. territories. All data are stored within the ADES database 298 299 2.2.7. "2 (Long0lasting Observatory of the Environment) focuses on a landscape in the 300 eastern part of the Paris Basin (a few hundred km²) around the site pre0selected as the French 301 deep geological repository of high0level and intermediate0level long0lived radioactive wastes. 302 OPE is currently constituted of a monitoring network, covering forest and agricultural areas 303 and measuring atmospheric, meteorological, soil, surface and ground water, land use and 304 biodiversity indicators, providing a unique opportunity to document the interactions between 305 human activities and the CZ around an industrial project scheduled to run over 100 years (if 306 accepted). 307 11 Page 12 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 308 2.3. Exploring the CZ with OZCAR observatories 309 As demonstrated in the above brief overview, OZCAR is a network of networks consisting of 310 highly instrumented sites: individual, nested or paired catchments, hydrogeological sites, 311 plots, glaciers, and lakes that are each monitored for a given set of parameters according to 312 the specific disciplinary question under which they have been designed. # 313 the current situation is quite diverse in terms of monitored CZ compartments and scales, and 314 measured variables. This diversity not only reflects the heterogeneity of the CZ but also the 315 span of scientific questions and communities and in turn, the diversity of institutional 316 environmental research. The disciplines represented in the OZCAR are hydrology, 317 hydrogeology, biogeochemistry, agronomy, pedology, glaciology, meteorology, climatology, 318 and snow sciences. 319 As shown in 320 France, they include sites in overseas territories like the tropical Caribbeans and Reunion 321 Island. OZCAR sites also exist in 18 other countries through partnerships between the French 322 Research Institute for sustainable Development (IRD) and national research institutions from 323 other countries (north Africa, west Africa, south0east Asia, India, and Amazonia, Andean, 324 Arctic, Antarctica, and Himalayan nations). The sites then cover a large range of climates 325 (oceanic, continental, mountainous, Mediterranean, tropical, polar), lithology (granites, 326 schists, volcanic rocks, limestone and sedimentary basins) and land use/land cover (tropical, 327 Mediterranean, mountainous forest; more or less intensive agriculture, peatland, urbanized 328 areas, snow0 and ice0covered areas). All sites have experienced several centuries, if not 329 millennia, of land management for agricultural practices, especially in the continental part of 330 France and in North Africa, Although focused on diverse scientific questions and variables, 331 all OZCAR observatories and sites can be considered as sharing the main overarching goal 332 which is how to monitor, describe and simulate the CZ evolution of a changing planet 3 and # $ shows that $ , the OZCAR sites are located all around the world. In 12 Page 13 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 333 (climate change, land use changes, changes in practices). 334 ' 4 335 336 All observatories integrated into OZCAR are highly instrumented. They have in common 337 standard field meteorological stations recording precipitation (liquid or solid), radiation, air 338 temperature 339 Hydrometeorological observatories use radars, rain gauge networks and disdrometers to 340 provide accurate estimates of rainfall fields (e.g. Boudevillain et al., 2016). In the case of 341 glaciers and snow observatories, conventional meteorological observations are complemented 342 by field and remote monitoring of snow and ice related variables such as snow water 343 equivalent (SWE), surface specific area, runoff and albedo, or ground temperature, etc. The 344 height and extent of the snow surface are measured by various means (ultrasonic snow depth 345 sensors, photogrammetry, LiDar, RADAR, UAV and satellite) for all sites. Specific 346 measurements of the cryosphere also include cosmic ray counts for SWE measurements 347 (Morin et al.,2012), Snow Particle counter for drifting snow flux measurements (Trouvilliez et 348 al., 2014), high spatial and temporal resolution spectroradiometer for monitoring surface 349 albedo, or radar and seismic method for mapping bedrock. Observatories focusing on the 350 exchange of energy and matter between the ground and the lower atmosphere (including those 351 on glaciers) are equipped with eddy covariance towers or manual and automatic accumulation 352 chambers producing high resolution measurements. 353 Water discharge is measured at standardized gauging stations with high resolution recording 354 by water level sensors of different types (floats, pressure sensors, radar sensors or ultrasound, 355 Nilometer digital scales). For gauging flood discharge, non0contact methods have been 356 developed and evaluated: surface radar, LS0PIV (Large Scale Particle Image Velocimetry) 13 and humidity, wind velocity and direction, atmospheric pressure. Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 357 based on images from fixed cameras or videos on YouTube (Dramais et al., 2014; Welber et 358 al., 2016; Le Boursicaud et al., 2016). For large rivers, satellite data or ADCP surveys are 359 used (e.g. Mangiarotti et al., 2013; Paris et al., 2016). 360 Ground water levels are monitored using pressure transducers. Depending on the process of 361 interest (hydrological cycle, tides, barometric effect, earthquakes) the frequency of 362 measurements varies from one per day to 1 Hz or even greater. These conventional 363 measurements are complemented using multiparameter probes and sampling to analyze major 364 chemical elements and isotopic ratios using a wide range of natural and anthropogenic tracers 365 for water residence time (Leray et al., 2012; Celle0Jeanton et al., 2014). The use of heat as a 366 groundwater tracer is currently tested on several H+ sites (Chatelier et al., 2011; Klepikova et 367 al., 2014). Precise borehole sampling and monitoring is achieved through multipacker 368 systems, well nests or well clusters. 369 The unsaturated zone is less frequently instrumented, usually by soil moisture probes (TDR 370 sensors) and lysimeters allowing soil solution sampling (i.e. one RBV site (OHGE) or OPE). 371 Chemical analyses of river water and suspended matter are usually performed on discrete 372 samples collected in the field manually or by automatic remotely0controlled samplers or 373 triggered to water level or turbidity thresholds, therefore allowing for capture of extreme 374 flood events. Only a limited number of chemical variables in OZCAR are measured at a high 375 frequency, using commercial probes (conductivity, water temperature, dissolved organic 376 matter with fluorimeter and nutrients). Suspended matter concentration is also indirectly 377 recorded continuously at a number of sites using turbidimeters. At the OPE, significant efforts 378 have been made to develop in0situ chemical probes to expand our present ability of high0 379 frequency chemical monitoring. 380 This brief overview of the in0situ instrumentation in OZCAR shows a large variety of 381 measurements, sensor types and frequencies of analysis, as well as the absence of 14 Page 14 of 103 Page 15 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 382 standardization. Different sub0networks inside OZCAR have however established common 383 measurement protocols. This is possible when relatively similar (homogeneous) 384 environmental settings are studied (like peatlands, hydrogeological sites, glaciers, permafrost 385 sites), but remains challenging for catchments of very different sizes or at sites studied from 386 the perspective of different disciplines each having different scientific conceptual views. As a 387 community effort, the RBV network (catchment approach) agreed upon a set of common 388 variables that should be measured in all observatories, meant to describe the CZ at the 389 catchment scale. The main difficulty of this exercise lies in the fact that all the required 390 disciplinary skills rarely exist in individual observatories. However, the advantage of 391 networking is that these disciplinary skills can be shared at the network level. # 392 the list of the 24 common parameters agreed upon and measured in small order catchments of 393 OZCAR. The variables cover all the measurable compartments of the CZ and are thought to 394 be the best compromise among the cost of measurements, the ease of implementation and 395 their scientific relevance. shows 396 In 2011, the two networks RBV and H+ launched CRITEX, a program funded (20120 397 2020) by the French Government (Equipex program) for developing innovative instruments to 398 monitor the CZ. The overall goal of CRITEX (Challenging equipments for the temporal and 399 spatial exploration of the Critical Zone at the catchment scale) was to build a shared and 400 centralized instrumental facility for the long0term monitoring and exploration of the CZ 401 complementing and over0performing the existing site0specific equipments of RBV and H+ 402 networks. The instruments proposed in CRITEX ( 403 “state0of0the0practice”, “state0of0the0research” and “state0of0the0science” (Robinson et al. 404 (2008). The “state0of0the0practice” instruments in CRITEX are well0established techniques 405 that are classically used to characterize the CZ (seismic, electric resistivity techniques, flux 406 towers, groundwater well equipements). They are typically used to characterize the OZCAR 15 5) can be grouped into three categories: Page 16 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 407 CZOs. The “state0of0the0science” instruments are innovative and emergent (scintillometry, 408 hydrogravimetry, hydrogeodesy, optical fiber sensors, UAV exploration, self0potential and 409 spectral0induced polarization electrical methods, isotopic tracing, reactive and inert gas tracer 410 experiments). Examples of such intrumental developments by the CRITEX community are 411 given by Read et al. (2014) on the use of fiber optic distributed temperature sensing down 412 boreholes, Pasquet et al. (2015) for the coupling between P and S wave velocities, Schuite et 413 al. (2015) for the use of ground surface deformation for deducing properties of fractured 414 aquifers, Chatton et al. (2017) for the use of CF0MIMS (Continuous Flow Membrane Inlet 415 Mass Spectrometer) to monitor in0situ N2, O2, CO2, CH4, N2O, H2, He, Ne, Ar, Kr, Xe) at 416 high frequency (1 measure every 1.5 seconds) for exploring the CZ, and Mazzilli et al. (2016) 417 for the use of Magnetic Resonance Sounding (MRS) in karst aquifers to identify the presence 418 of water and to reconstruct seasonal variations of water within the unsaturated zone. Finally, 419 the “state0of0the0research” instruments are not commercially available yet and have been 420 developed as prototypes or instrumental platforms (marked by a star in 421 academic and industrial collaborations. Such instruments include a µ0wave scintillometer for 422 determining latent heat fluxes in catchments over 1 km distances; the development of a soil 423 moisture sensor determing soil permittivity and bulk soil conductivity based on the soil 424 dielectric properties (Chavanne and Frangi, 2014); integrative sensors based on DGT 425 (Diffusive Gradient in Thin film) properties to measure U, Sr, Nd and Ni isotopes; the passive 426 “DIAPASON” system deployed in groundwater for isotope tracing (Gal et al., 2017) and the 427 development of a new MRS system for the unsaturated zone (Legchenko et al., 2016). 428 Different platforms were also developped in CRITEX. For example, the hydrosedimentary 429 platform RIPLE is specifically designed for extreme flood monitoring of mountainous rivers 430 measuring every 10 minutes water, fine and coarse sediment fluxes (Michielin et al., 2017). 431 The “River Lab” is a CRITEX prototype set up upon a “lab0in0the0field” concept, measuring 16 50 through Page 17 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 432 the chemical composition (major elements) of the river every 30 minutes (Floury et al., 2017). 433 Finally, the “River Truck” is a mobile laboratory containing instruments for continous 434 measurement of the concentration of dissolved gas (CF0MIMS) and major elements, to be 435 deployed during hot moments in the field. More information on CRITEX is available at 436 http://www.critex.fr. 437 Significant instrumentation efforts have also been achieved by the French cryosphere 438 community. POSSSUM (Profile Of Snow Specific Surface Area Measurement Using SWIR 439 reflectance) is an instrument that measures the specific surface area (SSA, a measure for the 440 grain0size) profile in snow boreholes with a vertical resolution of one centimeter and down to 441 20 m depth (Arnaud et al., 2011). RLS (Rugged Laser Scan ) is an automatic laserscan 442 designed to work in Antarctica that scans an area of 150 m2 every day and allows for 443 monitoring snow accumulation, roughness change, sastrugi dynamics and more (Picard et al., 444 2016a). Solexs is an optical instrument for the measurent of irradiance profiles in snow which 445 can be related to snow microstructure and ice absorption (Picard et al. 2016b). 446 ( 6 4 447 448 In order to comply with the public data policy, a mandatory condition for recurrent funding, 449 most of the OZCAR observatories developed data and/or metadata portals where data can be 450 accessed and sometimes downloaded. All portals in OZCAR provide research data with the 451 exception of the ADES1 portal that provides monitoring information about groundwater level 452 and quality for the whole French territory and was primarily designed for operational use. 453 A critical analysis of the portals reveals a large heterogeneity in practices in OZCAR: i) free 454 access vs. access through login/password, or no access; ii) type of data that are provided: 1 http://www.ades.eaufrance.fr/ConsultationPEBSSLocalisation.aspx 17 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 455 metadata only vs. possible downloading of the data; raw data vs. corrected data or more 456 elaborated products including simulation results; iii) access through information system and 457 GIS interfaces, including sometimes visualization tools, vs. access to files or to ftp files; iv) 458 data formats and storage: relational databases vs. files repositories; v) granularity of a dataset 459 (e.g. one rain gauge or all the data collected within one catchment); vi) level of information 460 provided in the metadata. More specific information on the diversity of current practices in 461 OZCAR is given in Appendix 2 (# 462 In terms of metadata provision, the RBV metadata catalog2 (André et al., 2015) is a common 463 initiative for providing visibility to the data collected within RBV. It follows the INSPIRE3 464 (INfrastructure for SPatial InfoRmation in Europe) norms and can harvest existing sites, when 465 the latter are compliant. For the other portals, a manual system was proposed to feed the 466 metadata. The usefulness of the data portal remains however limited because currently the 467 definition of the granularity of datasets is heterogeneous; metadata which are not 468 automatically harvested are quickly obsolete; metadata documentation is incomplete implying 469 that access to the data portals is not granted. One particular ambition of OZCAR is to improve 470 data accessibility and interoperability, building on the experience of the scientific teams 471 involved in the network. (see section 6.2). 472 5. - $!). 4 473 474 In this section different modeling initiatives developed by the various scientific communities 475 gathered in OZCAR are reviewed. Surprisingly, despite the wide disciplinary spectrum found 476 in OZCAR, common trends can be depicted and observed at the international scale. 2 http://portailrbv.sedoo.fr/#WelcomePlace: 3 http://inspire.ec.europa.eu/ 18 Page 18 of 103 Page 19 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 477 Classically, models in OZCAR can be classified into process understanding, system 478 understanding and management/prediction purposes (Baatz et al., 2018). 479 All scientific communities in OZCAR have developed or used simple models for identifying 480 and 481 in order to interpret the collected data, but data can also question existing representations, in 482 particular when new sensors or increased resolution are available. Process identification is 483 performed by each discipline using mechanistic/physically0based models deployed usually at 484 small scales (plot to small catchment scale) that intend to represent processes complexity 485 using (partial) differential equations and describing the medium heterogeneity. Examples of 486 studies linking data and models conducted in the different OZCAR observatories are shown in 487 Appendix (# 488 experiments are used to test these mechanistic models. For instance in H+, Klepikova et al. 489 (2016) showed how a series of thermal push0pull tests efficiently complement solute tracers to 490 infer fracture aperture and geometry by inverse modeling and better describe aquifer 491 heterogeneity. 492 Once elementary processes are identified, they can be combined in more or less integrated 493 models to provide a representation of 494 compartments of the CZ are involved at larger spatial scales (e.g. small to medium catchment) 495 and are generally addressed. Process representations are often simplified (i.e. process0based 496 models with approaches such as reservoir models) as compared to models deployed for 497 process understanding, because they must cope with a larger degree of heterogeneity. A 498 model calibrated with in0situ data is thus a powerful tool to extend the knowledge acquired at 499 local sites both in space and time (see examples in # 500 help to identify functioning hypotheses that are the most consistent with observations, by 501 varying model parameters or comparing different processes representations. The AMMA0 1 at different scales in their observatories. Models are built $'). In0situ, long0term data as well as experimentation or laboratory 4 19 . Several disciplines and/or $'). Sensitivity analysis can also Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 502 CATCH observatory, in collaboration with African researchers, gives a good example of this 503 effort. In the Ara catchment (10 km2), observations of surface fluxes, soil moisture and 504 groundwater monitoring as well as geochemical, geophysical data and gravimetric 505 measurements ( 506 groundwater discharge in dry season (Richard et al., 2013; Hector et al., 2015). The 507 mechanistic ParFlow0CLM model (Maxwell and Miller, 2005) incorporating the identified 508 processes, was chosen to reproduce the observed functioning (Hector et al., 2018). 509 Finally, a significant number of approaches developed in the OZCAR observatories are 510 motivated by societal challenges such as a better estimation of sea level rise, the prediction of 511 natural risks (floods, droughts, erosion, snow and ice avalanches, contamination, etc..), water 512 resources management, carbon storage, and other ecosystemic functions. The models used for 513 management and prediction purposes are usually inspired from those developed for system 514 understanding and are generally simplified to represent the main active processes and to be 515 used operationally and/or in real0time, due to computational time constraints, and to lower 516 data availability. For instance, Crocus (Brun et al., 1992), a numerical model used to simulate 517 snow cover stratigraphy and the blowing snow scheme SYTRON (Vionnet et al., 2018) were 518 initially tested using field experiments (Col de Porte and Col du Lac Blanc, CRYOBS0CLIM 519 observatory). They are implemented into the French operational chain for avalanche hazard 520 forecasting. Other examples are provided in # 521 Model integration and coupling between compartments of the CZ requires the development of 522 dedicated tools. Modeling platforms allowing for building models from available components, 523 and for managing exchanges of variables and fluxes between components have been 524 successfully developed in OZCAR, mainly by the hydrological community. KARSTMOD4 525 was specifically designed to represent karstic aquifers and provides flexibility to build 7) showed that water uptake by deep rooted trees is the main driver of 4 http://www.sokarst.org/index.asp?menu=karstmod 20 $'. Page 20 of 103 Page 21 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 526 reservoir0based models of various complexity (Mazzili et al., 2017). LIQUID (Branger et al., 527 2010) was designed to represent the heterogeneity of land surfaces using an object0oriented 528 approach (representing explicitly landscape objects). It was used to address different scientific 529 questions related to the impact of urbanization on water flow (Jankowfsky et al., 2014, 530 OTHU/Yzeron observatory) or flash flood understanding (Vannier et al., 2016, OHM0CV 531 observatory). OpenFLUID (Fabre et al., 2013) was developed in OZCAR to improve the 532 spatial modelling of landscapes dynamics and was successfully used to combine the 533 MHYDAS (Moussa et al., 2002) distributed hydrological model, along with an extension to 534 couple runoff and erosion (Gumières et al., 2011). Other initiatives addressed the automation 535 of time0consuming activities such as pre and post0processing (Lagacherie et al., 2010 for 536 agricultural catchments or Sanzana et al., 2017 for periurban catchments) or visualization and 537 analysis of the simulation results (Anquetin et al., 2014). 538 5 6 539 540 OZCAR organizes pre0existing observatories and well0established communities, supported by 541 diverse funding institutions that have their own vocabularies and representations of the CZ 542 and are working at different timescales. This diversity mimics the physical and biological 543 heterogeneity of the CZ inherited from the geological and climatic histories at the local scale. 544 OZCAR was designed in order to allow the defragmentation of the CZ community at the 545 national scale. In this section, ambitious actions promoted by OZCAR, which should enable 546 the CZ community to progress towards a better integration of scientific questions, data, 547 instruments and models are presented. Visions of the internal organization of the network and 548 its involvements in international initiatives are also discussed. 21 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 549 550 Underlying the broad diversity of the disciplines, measured parameters and models 551 encountered throughout OZCAR sites are common, overarching scientific questions that serve 552 to provide fundamental insight into the inner dynamics of the CZ. These grand scientific 553 questions can be separated into three principal topics: 1) the “dynamical architecture” of the 554 CZ; 2) processes and fluxes that shape the CZ; and 3) CZ feedbacks and responses to 555 perturbations ( 556 6.1.1. Dynamical architecture of the Critical Zone. 557 The architecture of the CZ refers to its structural, physical, chemical and biological 558 organization. The spatial extent of the CZ is still poorly defined, which emphasizes the need 559 to better investigate its lateral and vertical organization, 1) to identify the role of the different 560 interfaces; 2) to quantify the impact of spatial heterogeneity and temporal intermittence on 561 fluxes, connectivity, concentrations and micro0organisms; and 3) to determine residence and 562 exposure times of material in the CZ. Here, the architecture of the CZ is defined in a 563 dynamical rather than in a static view. The dynamical architecture of the CZ can be translated 564 into a series of questions detailed in the following. 565 /09 566 The upper limit of the CZ is classically defined as the top of the atmospheric boundary layer. 567 The portion of the atmosphere involved in the CZ as characterized by the location of this 568 upper limit is variable and site specific, depending on local topography and wind patterns. On 569 the catchment scale only the lower portion of the atmosphere is relevant, but when continental 570 scale energy couplings are considered the whole atmosphere plays a role. As an example, a 571 critical question in the assessment of geochemical mass budget studies in CZOs is in 572 determining how to incorporate atmospheric inputs of dust or of Volatile Organic 8). 11 : ; < 22 Page 22 of 103 Page 23 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 573 Compounds. These compounds can be produced locally (in which case they are part of the 574 “soil” system) or can be produced at great distance (like Saharan dust in the Lesser Antilles or 575 the Amazon) in the form of marine aerosols that can serve as significant external input 576 sources to a given CZ site of interest. 577 The lower limit of the CZ is also often poorly defined and this question is complicated by the 578 fact that in many cases the CZ can be composed of multi0layered aquifers in which water 579 infiltrating from the surface can percolate very deeply with very long residence times 580 (Goderniaux et al., 2013; Flipo et al., 2014; Aquilina et al., 2015). 581 Since the CZ is not a 1D system, its lateral extent is equally as important as its vertical extent. 582 Lateral compartments such as floodplains, peatlands, glaciers, or colluvium are important 583 biogeochemical reactors on the continents that should be considered to fully address CZ 584 functions. Describing the dynamical architecture of the CZ is thus a composition exercise, that 585 requires not only the spatial, geomorphologic heterogeneity to be taken into account, but also 586 the connectivity, i.e. the way hydrological patches are connected in space and time. 587 / 09 588 41 ;1 4 4 4 < 589 Determining the duration of time that matter spends in the CZ (residence time), as well as the 590 time that the matter is in favorable biogeochemical conditions to react (exposure time), is a 591 primary step in defining CZ architecture, as it is a direct indicator of its dynamical structure. 592 The residence time concept is typically associated with waters, but it can also be applied to 593 surface (glaciers) or ground (permafrost) ice, sediments and soils. For example, the residence 594 time of soil material results from a subtle balance between weathering and erosion and, 595 therefore, can provide insightful information into the rates at which soil material is formed or 596 transported out of the catchment as part of the CZ architecture characterization. Ecosystem 597 characteristic times are shown to change significantly with spatial scale and thus these diverse 23 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 598 scales must be investigated, taking advantage of the nested structure of observatories (Billings 599 and Sullivan, in press). 600 / 09 601 To overcome the inherent difficulty of describing a “dynamical architecture” of the CZ, one 602 can describe the CZ as a series of critical interfaces. At these interfaces between reservoirs or 603 compartments, energy, water and matter are transformed because of biological, physical and 604 chemical gradients (such as redox gradients). These interfaces may be permanent or transient, 605 depending on the hydrological cycle or on the succession of dry and wet seasons. Examples of 606 CZ interfaces are the topography, the atmosphere/ice0snow interface, the unsaturated0 607 saturated zone interface, hyporheic zones, riparian zones, or more generally the groundwater – 608 river interface, or the topography of the bedrock0saprolite interface (weathering front). 609 / 09 610 Biota plays a crucial role in most of the chemical and physical reactions in the CZ by 611 regulating hydrological and matter budgets through the control of evapotranspiration, the 612 production of physical stresses on the CZ, and through facilitating chemical reactions. Life is 613 not an explicit variable in all OZCAR sites, but a number of biological variables are measured 614 (particularly, through remote sensing). A challenge of CZ science and observatories is to 615 incorporate measurements that assess more explicitly the role of living organisms (and 616 humans) in the CZ. For example, the role of the “microbiome” is particularly unknown in the 617 world and is thought to be a significant contributor to the major geochemical and hydrological 618 processes governing the CZ (Sullivan et al., 2017). 619 6.1.2. Processes and budgets: biogeochemical cycles, sediment and contaminant propagation 620 through the CZ from highlands to sea. 621 The CZ, essentially fueled by solar energy, is controlled by a large number of chemical, = < < 24 Page 24 of 103 Page 25 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 622 physical and biological processes that are tightly coupled at the plot, watershed and 623 continental scales. The concept of 624 adapted to describe the loops in which water, matter, elements and contaminants occur at 625 Earth’s surface. These loops act at different spatial and temporal scales and are not necessarily 626 closed at the size of a CZO. An overarching question is therefore: 627 > 628 1 4 1 is probably the best 4 4 < The search for these coupled processes shaping the CZ and their 629 quantification in terms of kinetics (i.e. of fluxes involved) is therefore central to the OZCAR 630 network. The different processes may be identified and quantified over small spatial scales 631 (grain, plot, hillslope) or may be described over very large scale in the case of large 632 watersheds (Billings and Sullivan, in press). Typical associated timescales may range from 633 seconds to millions of years (Anderson et al., 2004; Robinson et al., 2008; Sullivan et al., 634 2016). Moving up through scales, new processes emerge that are not necessarily the sum of 635 the processes described at a smaller scale. Through a suite of observatories and nested 636 catchments, covering a mountain0to0sea continuum, combined with modeling, OZCAR aims 637 to address the following major questions related to the processes and fluxes through the CZ. 638 /0 639 This includes constraining the different processes at play in the hydrological budget and their 640 spatial and temporal variabilities: precipitation, evapotranspiration or more generally 641 atmosphere0surface exchanges, wind erosion, infiltration or groundwater recharge, and 642 groundwater0river exchanges. These budgets, first applied to water, must also be applied to 643 other components (sediments, nutrients, contaminants or total mass) and thus to any particular 644 element regardless of its phase (gas, solute, particulate), including trace elements and 645 micronutrients, and should be established on timescales relevant to the systems considered. 646 OZCAR aims to combine different techniques, models, and tracers to achieve such a goal > 4 < 25 Page 26 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 647 (e.g. Sullivan et al., 2016). 648 / 0) 649 Solving this question requires time series with sampling frequencies adapted to the different 650 processes and to the scale of investigation. The couplings between processes at the plot or 651 catchment scale can only be disentangled if high frequency measurements (from 1/hr to 652 1/min, depending on the process dynamics) are available. At larger scales, as inter0annual 653 variability is large in the CZ, typically decadal observation series are necessary. Such long0 654 time series have rarely been collected at the global scale so far and require a focused effort by 655 the international CZ community. 656 / 09 657 The role of biological processes and their quantification remains difficult in the CZ, partly 658 because measurable proxies of life0related processes are lacking. So0called “abiotic” and 659 “biotic” processes are so intertwined that deciphering the causalities is a “chicken and egg” 660 problem. An important question, beyond species diversity, is to identify the functions of 661 macro and microorganisms in the CZ. “Biolifting” is a particularly interesting mechanism that 662 consists of nutrient withdrawal at depth by roots and release by organic matter decomposition 663 or throughfall inputs in the top soil. Spatially, the dynamics of organic carbon and nutrients 664 through the mountain to sea continuum also deserves more attention. , > 41 1 1 < < 665 666 6.1.3. Responses and feedbacks to biological, climatic and geological perturbations and global 667 change: Earth’s dynamic surface system. 668 The ultimate scientific question that OZCAR wants to tackle is “what is the response of the 669 CZ to perturbations and forcings that can be either “natural” (such as geologic or 670 meteorological forcing) or anthropogenic (such as climate change, shifts in land use, increase 26 Page 27 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 671 of resources exploitation)? Human activities are now considered as one particular and now 672 prominent forcing factor of Earth’s surface, and most of the OZCAR sites have been strongly 673 impacted by human practices over time. As the CZ holds resources and offers goods and 674 services to humanity, understanding how this dynamical system as a whole responds to events 675 that can be, exceptional, periodic or continuous, is important in terms of better informing 676 society and stakeholders (predicting flood events and associated risks, chemical or radioactive 677 dispersion) and propose a scientific basis for an alternative management of these resources. 678 /0) 679 Humanity faces unprecedented changes in climate, water and food security issues, and 680 population growth, so the main question is, how can we use different CZOs and their design 681 along gradients to quantitatively predict the response of Earth’s surface to changes in global 682 or local forcing parameters, or in short, “Earthcast” (Godderis and Brantley, 2013; Sullivan et 683 al., 2018)? This question is associated with that of the representativeness of observatories. Is 684 heterogeneity the overriding controlling factor or can we, beyond the local diversity in 685 geology, rock texture, climate, soil and vegetation, land use and human practices define 686 general properties (such as state variable) characterizing the systems? Through their large 687 diversity of location, climatic and geological contexts, OZCAR observatories offer an 688 unprecedented opportunity to test the relevance of this hypothesis. Monitoring Earth’s surface 689 through a series of observatories (Banwart et al., 2013, Kulmala et al., 2018) poses the 690 question of how these observatories should be chosen, designed and monitored and also 691 highlights the necessity of defining common metrics for CZOs (Brantley et al., 2016, Sullivan 692 et al., 2017). 693 / 0 ) 694 695 2 1 4 4 < 4 1 4 1 41 < The perturbations induced by human activities on the CZ are a typical case of coupling 27 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 696 between timescales, where human actions may be short0lived, but could have lasting 697 consequences over long timescales. A typical example is that of Laos where a change of land0 698 use from rice crop to teak forest resulted in spectacular and irreversible acceleration of 699 erosion rates (Valentin et al., 2008; Ribolzi et al., 2017). The idea that biota in the CZ 700 responds quickly to climate change and that the structure, function and dynamics of the CZ 701 can change on timescales much faster than currently considered is particularly important 702 (Sullivan et al., 2018). 703 The knowledge acquired from observatories can be incorporated into integrated models, able 704 to model and couple the various components of the CZ at different space and time scales, in 705 order to better quantify fluxes and storages in the CZ and simulate its response to global 706 change. These models should also have a predictive power to address questions raised by 707 societies and stakeholders, such as risk assessment related to floods, droughts, landslides, 708 contamination or water resources shortage. By increasing the common use of models and 709 data, well0instrumented CZOs offer a unique opportunity to understand small0scale processes 710 and to hierarchize their importance according to different environmental and climatic 711 conditions. The development of nested instrumentation, as already done in some OZCAR 712 observatories, provides tools to assess the validity of simplifying assumptions and to address 713 the change of scale problem and how dominant processes may change when moving from 714 small to larger scales. Another challenge, also highlighted in the first scientific question, is the 715 proper integration of the biotic components as well as representations of human 716 infrastructures and activities in CZ integrated models (Billings and Sullivan, in press). 717 / 0 718 All parameters being constant, is the evolution of the CZ at a CZO reproducible? In other 719 words, if the same initial conditions are met, would two similar CZOs follow the same 720 evolutionary trend under the same forcing? Could it also be possible that bifurcations in the 1 ? < 28 Page 28 of 103 Page 29 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 721 evolution of the CZ caused by heterogeneities or sudden changes would result in different 722 evolutionary patterns? Human actions, fires, sudden erosional events, the importance of 723 extreme events on system evolution are factors that could act as tipping events in the 724 evolution of the CZ which clearly need to be better appreciated and incorporated into CZ 725 models. This is why working with socio0ecology is essential. 726 727 728 A main challenge of future CZ instrumentation is to define tools and methods to image how 729 water flows, and how the heterogeneous structure of the geological, soil and biospheric media 730 generates reactivity hotspots at moving interfaces. Adapted spatial and temporal resolution 731 over a wide range of scales is therefore required to capture emerging patterns driven by water 732 flow in the subsurface, with the main challenge being how to define the right scale of 733 heterogeneity and adapt the instrumentation accordingly. A number of techniques currently 734 available for exploring and probing the CZ may not be adapted to the necessary scale of 735 investigation. This is particularly true at the smallest spatial scales (such as the catchment or 736 plot scale) where geophysical imaging is usually at insufficient resolution, where geochemical 737 signals are not recorded at a sufficiently high temporal frequency, and where spatial 738 techniques are still irrelevant. 739 /0 4 4 740 741 First, high time0 and space0frequency of measurements is clearly a frontier in CZ 742 instrumentation. High0frequency acquisition already exists for parts of the CZ like those for 743 atmospheric0ground exchanges of matter and energy (using flux tower or accumulation 744 chambers), or for water levels in piezometers and river gauging stations, but significant 29 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 745 progress still needs to be accomplished particularly for spatialization. Better spatial resolution 746 of ground sensors will improve the link with remote sensing data. Cosmic ray investigation or 747 scintillometry are promising techniques that link local to larger scale observations but still 748 require important technological and theoretical development to be adapted to observatories 749 with marked topography. Compared to water and gas, chemical parameters and solids (in 750 suspension or as bedload) are rarely measured at a high temporal frequency in rivers and 751 aquifers, which should be considered as a priority at the catchment or watershed scale. 752 Commercially0available lab instruments could be beneficially deployed in the field to 753 decrease required manpower and allow for cost0effective sample manipulation, provided that 754 the issue of water filtration can be solved. This concept has been developed in oceanography 755 (“lab on ship”) but is still in its infancy in terms of CZ research. The “River Lab” concept 756 described above (Floury et al. 2017) is an example of such a promising approach. A “snow 757 lab” to probe the surface and the snowpack would also provide a major step forward in the 758 observing capabilities of snow. Industrial solutions exist including in0situ sampling, pumping, 759 filtration and on0line analysis, which should be adapted to field requirements to be sufficiently 760 resistant to extreme field conditions (cyclones, extreme cold events). If, in principle, all lab 761 instruments can be deployed in the field, the “lab0in0the0field” concept would strongly benefit 762 from the development of low0cost sensors, which have the advantage of being miniaturized, 763 less sensitive to fouling than most commercial probes, deployable at a high spatial resolution 764 and eventually able to provide real0time data. The development of low0cost chemical sensors 765 for major solutes, for water in the unsaturated zone and for monitoring solid fluxes in rivers 766 and glaciers is an instrumental challenge that needs a significant investment. Biological data 767 (smart tracers, DNA) acquired at high frequency is also an area of instrumentation requiring 768 considerable development. 769 The second promising direction of instrumental development, requiring a significant 30 Page 30 of 103 Page 31 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 770 experimental and theoretical effort, is the improvement of the time resolution of geophysical 771 imaging of the CZ (“time0lapse” geophysics) in order to move from snapshot views of the 772 inaccessible CZ to the imaging of preferential water pathways. In addition, down0hole 773 exploration and associated experimentation for time0lapse imaging need to be developed as a 774 complement to the ground0based time0lapse exploration. The sensitivity of some geophysical 775 properties 776 “biogeophysics” (Binley et al., 2015), a promising field at the frontier of ecological and earth 777 sciences. 778 Finally, data transmission and synchronization are prerequisites for developing high 779 frequency observation strategies. Autonomy is also particularly important for reducing the 780 costs of human resources as well as for studying inaccessible CZ components (anoxic 781 groundwaters, caves) or moments (extreme events). It is necessary to develop low0cost/low0 782 energy tele0transmission strategies and systems for harsh and remote environments in order to 783 minimize time0series discontinuity and obtain a large spatial coverage. It is also essential to 784 explore new energy sources and to consolidate existing solutions, in particular within cold 785 environments. 786 / 0 ) 787 ;1 to biogeochemical reactions is 1 transforming “hydrogeophysics” into 4 < 788 Given the instrumental challenges listed above, a significant effort in the upstream 789 development of sensors is required, necessitating the collaboration of users (CZ scientists) 790 with sensor developers. Regardless of the need for higher space0 and time0frequency, many 791 variables of interest in CZ science are still challenging to measure (e.g. most snow internal 792 properties, precipitation amount and phase; Grazioli et al., 2017) and require innovative 793 developments. Overall, there is a real challenge in encouraging the CZ community to meet 794 with fundamental chemists, physicists, computer scientists or biologists to develop new 31 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 795 sensors. A good example is the extraordinary development of microfluidic techniques 796 supporting unprecedented miniaturization of sensors as exemplified by numerous medical 797 applications. The role of OZCAR will therefore be to develop a network0level technology 798 survey on emerging technologies and technological forums associating sensor developers and 799 CZ scientists on network0level questions like sensor autonomy, data transmission, and 800 assessment of the ability and reliability of automatic sensors to accurately measure CZ 801 parameters (Trouvilliez et al., 2015, Cucchi et al., 2017). Ocean and atmospheric scientists 802 have also made significant progress over the last decades on the real0time acquisition of 803 chemical and physical data that should be of high impact for CZ communities. Existing 804 structures exist like ENVRIplus (an inter ESFRI initiative addressing instrumental challenges) 805 or SPICE (Snow Precipitation Intercomparison Experiment) that should also help create 806 favorable conditions for sensor development. An assessment of the ability and reliability of 807 automatic sensors to accurately measure CZ parameters is still required. This is even more 808 true when low0cost sensors are considered (Trouvilliez et al., 2015). This can be done through 809 specific campaigns organized in the framework of OZCAR, similar to what has been done 810 globally by WMO during the SPICE project in which CRYOBSCLIM participated. 811 OZCAR finally aims to be a community space for dissemination of sensors and skills and for 812 sharing instruments among the field sites along varying environmental conditions. Sharing 813 instruments within the OZCAR network will follow the model of the CRITEX instrumental 814 facility. Instruments are purchased and managed by individual teams but are accessible to any 815 OZCAR community member. This organization requires training workshops for field0based 816 teams to learn how to use instruments and treat data. 817 32 Page 32 of 103 Page 33 of 103 818 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 ! 819 The large amount and variety of data produced in the OZCAR is expected to increase in the 820 near future due to the increase of high0frequency acquisition systems and the development of 821 new sensors. Simultaneously Open Data is pushed in Europe by the INSPIRE directive for 822 spatial data and the Aarhus agreement 5 for environmental data. This requires data to be 823 permanently and freely accessible on0line, allowing data discovery, visualization and 824 downloading. Open data is expected to enhance new connections between datasets, data 825 mining, and easier use in models. Scientists are aware of these possibilities, but may remain 826 reluctant to openly provide their datasets. Reasons put forward are: lack of technical skills or 827 human resources, legal constraints, data quality and validation, priority for their personal use 828 through embargo on their datasets, lack of traceability of open data and lack of 829 acknowledgement of their work. Open data also raises practical questions about the definition 830 of a dataset, its granularity, its documentation, the juridical status of data (Becard et al., 2016) 831 and technical issues about interoperability between systems often developed independently, 832 the availability of the required expertise for web sites design and maintenance, and of course 833 of associated costs. 834 /0# 835 Identifying, cataloging, and sharing data within OZCAR is a great challenge, starting from a 836 very heterogeneous situation (see section 3), that is common in environmental observation 837 (Horsburgh et al., 2009). Visibility within the scientific community is also a great challenge, 838 pleading for a common metadata/data portal. Given the investment of observatories in data 839 portals and the preference that data remain as close as possible to their producer (Zaslavsky et 840 al., 2011), it seems unrealistic to begin anew and propose the same technical solution for all 841 observatories. The most efficient approach is to work on interoperability between existing 4 5 http://ec.europa.eu/environment/aarhus/ 33 Page 34 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 842 sites, so that metadata first, and data soon after, can be harvested and accessed transparently 843 by users (e.g. Ames et al., 2012). This challenge of data sharing and interoperability is 844 common to the environmental science community and has lead to initiatives such as the 845 Hydrologic Information System by the CUAHSI6 consortium (Horsburgh et al., 2009, 2011) 846 for hydrological observatories, EarthChem system (Lehnert et al., 2010) for geochemical data 847 or CZOData (Zaslavsky et al., 2011) for the CZO Data Management System. All these 848 initiatives had to address semantic and syntactic heterogeneity and proposed shared controlled 849 vocabulary for data and variable indexation (e.g. Horsburgh et al., 2014) and common 850 standards for a data model (e.g. Horsburgh et al., 2008; Zaslavsky et al., 2011). Although 851 individually successful, these initiatives showed limitations in incorporating new data types or 852 sharing data between communities. This led to the development of a second generation of 853 Observation Data Model (Horsburgh et al., 2016; Hsu et al., 2017) handling different kinds of 854 data. Concepts such as the O&M (Observation & Measurement 7 ) and SOS (Sensor 855 Observation Service 8 ) for data harvesting must also be explored and the cost of their 856 deployment evaluated before designing the OZCAR portal. 857 / 0) 858 OZCAR aims at building a common metadata/data portal gathering metadata first, thus 859 ensuring data discovery, and going very soon to data access, taking advantage of the expertise 860 present in the various observatories and of existing international initiatives. First exchanges 861 with the OZCAR community showed that, to be useful, the data portal must provide 862 information down to the level of available variables with their associated location and detailed 863 time windows. This task will require working on the following points: i) agreement on the 864 fields and file format for providing the metadata so that they can be exposed following 1 1 4 4 < 6 Consortium of Universities for the Advancement of Hydrological Sciences, https://www.cuahsi.org/ 7 http://www.opengeospatial.org/standards/om 8 http://www.opengeospatial.org/standards/sos 34 Page 35 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 865 standards (e.g. INSPIRE) and can be used for other purposes such as DOI declaration; ii) 866 agreement on the various entries to find data in the portal (location, dates, variables, climate, 867 geology, observatory, programs, funding institutions (Ames et al., 2012) and iii) definition of 868 a common ontology and controlled vocabulary for naming the variables. Mapping of existing 869 variables towards a commonly shared vocabulary based on the GCMD 9 (Global Change 870 Master Directory) keywords is in progress; iv) define fluxes of information between the 871 OZCAR portal and existing portals so that the information is always up to date; and v) 872 document the data lifecycle and propose archiving solutions for long term preservation 873 (Massol and Rouchon, 2010; Diaconnu et al., 2014). 874 The metadata portal should enable users to download data even if the latter are located in 875 distributed data centers. The downloaded data will be supplied to the users in an identical 876 format. The portal will be considered as a success if researchers use it to retrieve the latest 877 versions of their own data. 878 The recognition of scientists acquiring data is also a major point to which attention must be 879 paid. Initiatives such as DOI (Digital Object Identifier), data papers (e.g. Nord et al., 2017; 880 Guyomarc’h et al., 2018) and licensing of the datasets (e.g. Creative Common licenses10) will 881 be encouraged within OZCAR by providing guidelines on the definition of the corresponding 882 datasets, their granularity, and on filling the associated metadata. It is also planned to propose 883 a minimum Information System kit for observatories that lack the required expertise. 884 "# $ % & 885 OZCAR aims to provide a seamless holistic understanding of the terrestrial compartments of 886 the Earth System and an integrated representation of the coupled water, energy and matter 9 https://earthdata.nasa.gov/about/gcmd/global0change0master0directory0gcmd0keywords 10 https://creativecommons.org/share0your0work/licensing0types0examples/ 35 Page 36 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 887 cycles, including biogeochemical cycles (e.g. Filser et al., 2016), covering various spatial and 888 temporal scales and incorporating the heterogeneity of the critical zone. Such integrated 889 approaches are required to “earthcast”, i.e. assess the effect of future global change or socio0 890 economic scenarios on all the compartments of the CZ (Godderis and Brantley, 2013). To 891 address these scientific challenges, stronger interactions between data science and modeling 892 approaches are necessary (e.g. Kirchner, 2006; Braud et al., 2014; Brantley et al., 2016), 893 raising key cognitive and technical challenges. 894 /0$ 895 A first challenge is related to the process representation at different scales. At small scale, the 896 identification of elementary processes can benefit from instrumental progresses listed in 897 section 6.2. One example is the development of geochemical reactive transport models (i.e. 898 Steefel et al., 2015) at the catchment scale exploiting in particular high frequency datasets of 899 stream chemistry, constraints from new isotopic systems (Sullivan et al. 2016), and the new 900 representation of heterogeneities at the grain0size (Le Borgne et al., 2013). Another challenge 901 is the proper representation of vegetation and biological activity on chemical and physical 902 reactions that determine hydrological and matter budgets. When moving to larger scales, 903 unstructured heterogeneity, non0linearity and thresholds at all scales (Blöschl and Zehe, 904 2005), and the scarcity of integrated data at the scale of interest (Cook, 2015), preclude the 905 use of the same approach. It also becomes necessary to include human interactions within the 906 system (water uses, infrastructures, agricultural and forested land management, etc..), to 907 create socio0hydrological models (Sivapalan et al., 2012). Equations and representations 908 derived at small scales are often used for larger scales, but this approach is questioned as data 909 reveal behaviors such as “emergent properties” (Sivapalan, 2003; McDonnell et al., 2007) that 910 cannot be represented by aggregation of small scale processes to larger scales, calling for new 911 theories (e.g. Kirchner, 2009, Braun et al., 2016) as well as new concepts for non0explicitly 4 36 < Page 37 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 912 resolved processes (i.e. “parameterization” as defined by the atmospheric science 913 community). 914 A second challenge is to progress towards integrated modeling of the CZ, requiring the 915 deployment of coupling strategies. Direct coupling is relevant for exchanges such as water 916 and energy fluxes across the surface that are represented in land – surface models and now 917 incorporate many processes of the continental surface and sub0surface (e.g. SURFEX 918 (Masson et al., 2013) or ORCHIDEE11 (Ducoudre et al.,1993; Krinner et al., 2005). Other 919 examples such as PARFLOW0CLM (Kollet and Maxwell, 2006), DHSVM (Wigmosta et al., 920 2002), PIHM suite (Duffy et al., 2014) as well as the Dhara modeling framework (Le and 921 Kumar, 2017), are built around an initial model that can be enriched with different coupled 922 modules. They all require specific data transfer and the integration of new modules to fit the 923 model requirements (language; mesh and grid resolution; name of variables; etc). Another 924 option is to use couplers such as OPEN0MI12, OpenPALM13 (Piacentini, 2003) that generally 925 preserve model legacies and provides interfaces for their coupling, but also robust coupling 926 methods and complementary tools such as data interpolation. A third option is to design 927 platforms that allow coupling various modules and model representations, keeping the 928 specificity of each component in terms of model mesh, time steps, and that provide interfaces 929 to couple models but also a framework for the runtime environment such as LIQUID (Branger 930 et al., 2010), CSDMS 14 (Peckham et al., 2013), OpenFLUID 15 (Fabre et al., 2013), and 931 JAMS16 (Kralisch and Krause, 2006). Process coupling may also call for the definition of 932 more adapted variables and/or standardized interfaces to favor the coupling between modules 11 http://forge.ipsl.jussieu.fr/Orchidee 12 https://sites.google.com/a/openmi.org/home/dashboard2 13 http://www.cerfacs.fr/globc/PALM_WEB/ 14 http://csdms.colorado.edu/wiki/Main_Page 15 http://www.openfluid0project.org/ 16 http://jams.uni0jena.de/ 37 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 933 describing various processes. Choosing or designing technical solutions adapted to the 934 complexity and heterogeneity of the CZ remains challenging and is an active area of research. 935 In some cases, the dynamics of interfaces should be considered in itself as a research issue 936 requiring adapted characterization and modeling methods. Interactions between vegetation 937 and sediment transport in rivers benefit from the development of accurate topographical 938 devices like LiDAR and require new models for sediment transport and river evolution 939 (Brodu and Lague, 2012; Jourdain et al., 2017). New data can also reveal the spatiotemporal 940 dynamics of exchange variables and fluxes (McDonnell, 2017), questioning current 941 representations. For example, aquifer0river fluxes revealed by fiber0optic temperature data 942 potentially modify the status of the exchange fluxes from boundary conditions to forcing 943 terms (Anderson, 2005; Klepikova et al., 2014). In hydrogeo0eco0logy, coupled nutrient 944 transfer and characterization of microorganisms requires recasting classical residence time 945 concepts in the framework of exposure time concepts where hotspot organization can be 946 integrated (Pinay et al., 2015). 947 Common issues shared at each step of modeling, either when identifying processes or when 948 coupling them, are related to the ability to manage uncertainties coming from observations, 949 process understanding and model parameterizations. This requires the design of calibration 950 and model evaluation criteria and data assimilation systems that are able to account for this 951 uncertainty. Numerical uncertainty must also be quantified when models are used for 952 predictive purposes. 953 From a more technical point of view, important challenges are related to our ability to 954 perform coupling between process modules running at different space and time scales; and to 955 link databases, GIS layers and models (Bhatt et al., 2014). Facilitating data – model 956 interactions to build integrated modeling requires novel technical developments allowing both 957 data interoperability and model sharing (e.g., OLES project; Anquetin et al. (2014); CSMDS 38 Page 38 of 103 Page 39 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 17 958 project, Peckham et al. (2013), CUAHSI community model and web services based on the 959 Basic Model Interface (Jiang et al., 2017)) and needs to be extended to a larger scientific 960 community (Kumar, 2015; Yu et al., 2016). Such platforms may also benefit from distributed 961 computing facilities that help to keep model development closer to the developers. Moreover, 962 improved visualization capacities are also necessary to represent modeling results and provide 963 more accessible pathways to environmental processes for the broader scientific community 964 (Leonard and Duffy, 2014). Implementing such tools (e.g. Paraview 18 ) in the modeling 965 platform will benefit both observational data and modeling data exploration. 966 In addition, the availability of new data, at unprecedented space and time resolutions, related 967 to the rapid development of new sensors, high resolution satellite data and data obtained by 968 experimentations that provide information on more diverse variables, sometimes indirectly 969 related to the variables of interest. Big data challenge current modeling practices that were 970 developed in a data scarce context. This will transform relations between data and models 971 with critical improvements needed in computation, calibration and assimilation capacities 972 (Liu et al., 2012). The availability of a large amount of data also opens new perspectives for 973 the derivation of data0driven models (e.g., Kirchner, 2009), that can benefit from data mining 974 and big data analysis (e.g., Bui, 2016) and allow for reduction in uncertainties. Data mining 975 can also be used to infer the geometry and model parameters for large systems (Bodin et al., 976 2012), and provide complementary calibration strategies for high0dimensional models (Bui, 977 2016; Hsu et al., 1995; Shortridge et al., 2016). 978 / 0) 979 Linking data and models will be one of the pillars of OZCAR. In terms of process 980 representations, the large climatic/ecological/pedological/biological gradients covered by 44 < 17 https://www.cuahsi.org/data0models/community0models/ 18 https://www.paraview.org/ 39 Page 40 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 981 OZCAR, including sites highly impacted by human activity, offer opportunities for providing 982 data at small scales (grain, macropore and catchment scale) and identifying the elementary 983 processes to be implemented into models. Nested instrumented catchments provide data to 984 tackle the change of scale problem and identify and model “emergent” behaviors. 985 To cope with the diversity of models used within the OZCAR community (see # 986 a single CZ model will be considered (Duffy et al., 2014) and coupling between existing 987 models or modular modeling platforms will be used, in order to build dedicated models, 988 adapted to the scientific questions and data availability. Such platforms have already started to 989 be used for integrated land surface 0 aquifer modeling (e.g. the AquiFR project in France; 990 Habets et al., 2015) and other examples were listed in section 5. OZCAR will also explore 991 complementarity approaches that are often opposed in the literature, like in the use of detailed 992 mechanistic models (Godderis and Brantley, 2013) versus simplified models able to capture 993 the main functions within the critical zone (Savenije and Hrachowitz, 2017). With the 994 development of adapted assimilation techniques approaches, the combination of data and 995 models will ultimately lead to CZ reanalysis, providing valuable and novel information about 996 the CZ; as already widely used by the atmospheric science community to produce reanalyses 997 of the state of the atmosphere and of the components of the water cycle at the global scale 998 (e.g. ERA0Interim; Berrisford et al., 2011). Implementing all the tools will require that the 999 OZCAR community expand to applied mathematicians and computing engineers, and train a 1000 1001 $'), not new generation of CZ modelers. ' ( $ ( $) 1002 OZCAR gathers scientists from different disciplines, both from academic and applied 1003 research, and a large number of monitored sites that share a common set of instruments used 1004 for probing the near surface of our planet. Organizing the topology of such a network is 40 Page 41 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1005 important not only for helping this heterogeneous community to identify network0level ideas 1006 and scientific hypotheses to be tested, but also to help promote CZ science and maintain 1007 recurrent funding by institutions, to improve the visibility of CZ science to society, and to 1008 improve collaborations with other Earth surface and environmental science networks. 1009 Several topologic models that optimize the goals pursued by OZCAR are proposed. In all 1010 cases, site0based observatories are the permanent and pivotal structures, recurrently funded by 1011 different environmental research institutions. 1012 A number of existing research infrastructures, developed in particular by climate and 1013 atmospheric science communities, measure one parameter or a limited set of parameters in a 1014 series of instrumented sites along gradients. One successful example of such variable0centered 1015 RI is provided by ICOS, (Integrated Carbon Observation System) a network of flux towers 1016 measuring CO2, as well as other GHG and energy fluxes along climate gradients then directly 1017 connected to climate models. By contrast, OZCAR, and more generally worldwide CZ or 1018 LTER (Long Term Ecological Research) observatories assemble a more complex and diverse 1019 set of instruments measuring parameters determined by local or regional processes (geology, 1020 climatology), that are used to target a systemic approach. 1021 A first possible topology is to define a 1022 network and to organize OZCAR in sub0networks targeting these questions. Several common 1023 questions or scientific themes can be proposed that supersede the heterogeneity of existing 1024 site0based observatories and foster scientists and disciplines to collaborate. One theme could 1025 be reactive transport in porous media. It would associate research teams focusing on 1026 hydrogeological, hydrological and biogeochemical processes to understand and model the 1027 interaction between water, minerals, life and solids in aquifers using the diversity of OZCAR 1028 observatories. Another group could be organized on CZ science in headwater catchments, 1029 targeting the identification of elementary mechanisms or closing mass and energy budgets 44 41 > within the Page 42 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1030 locally. Another transverse theme common to numerous observatories could be a “CZ0 1031 carbon” theme on the topic of carbon storage in the CZ and its relation to functional 1032 biodiversity and the 4‰ initiative 19 . A last thematic cross0site program could address the 1033 upscaling issue by targeting the large spatial scales, including the remote sensing resources 1034 from OZCAR and taking advantage of the regional0to0continental scale observatories (e.g. 1035 Amazon basin). 1036 A second topology model would be a 1037 model, the different site0based observatories of OZCAR, targeting variable compartments of 1038 the CZ (glaciers, peatlands, catchments) would ideally be co0located within a territorial entity 1039 that can be a large river basin or a “geo0climatic” entity. This organizational scheme is not far 1040 from that of the TERENO (Terrestrial Environmental Observatories) terrestrial infrastructure 1041 developed by the German Helmoltz Association (Bogena et al., 2006, Zaccharias et al., 2011). 1042 Each TERENO consists of a series of instrumented atmospheric, hydrological, ecological co0 1043 located sites representing the dominant terrestrial processes, land use, climate and 1044 demographic gradients. The entities could also be socio0ecological systems in which the long0 1045 term observatories of OZCAR are co0located. Socio0ecosystems are typically the setting of 1046 the Long Term Socio0Ecological Research (LTSER) observatories (Haase et al., 2018). This 1047 organization in clusters is also close to the “hub0and0spoke” topology proposed by Brantley et 1048 al. (2017) in the US. A hub is a highly instrumented CZO (essentially river catchments) in 1049 which the broader common metrics of measurements have been defined and which is 1050 connected to “satellite” sites focused on a particular compartment of the CZ and in which 1051 fewer parameters are monitored. 1052 Finally, a last topologic model for OZCAR could be 1053 could be seen as a network of instruments, some of them mobile (e.g. seismology), some . In such a = 19 https://www.4p1000.org/ 42 4 . OZCAR Page 43 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1054 others permanent and site0based (i.e. gauging stations, piezometers). The infrastructure could 1055 then be organized according to the different sub0networks of instruments allowing for 1056 exchange of good practice, data, and models between scientists and centralization of data at 1057 the national scale. The instruments and instrumented sites would then be considered as a 1058 resource community to test hypotheses along gradients or by combining different exploration 1059 techniques. For example, one could imagine a network of mobile hydro0geochemical stations 1060 acquiring high0temporal resolution (Floury et al., 2017) data and covering climate, geological, 1061 and land use gradients. On0site experimentation could also be an added value of such an 1062 infrastructure. This vision of OZCAR as a national equipment facility for the study of the CZ 1063 does not preclude a site0based systemic approach, which is important for the societal 1064 relevance of CZ studies at the local scale (at the scale of “territories”), but it offers structure 1065 for the RI and is fostering collaboration within disciplines. Such a model of organization has 1066 been chosen by other RIs in physics and deep Earth science. A good benchmark is the EPOS 1067 RI monitoring earthquakes, volcanic eruptions, tsunamis and plate tectonics in general with a 1068 common set of integrated data, models and facilities (https://www.epos0ip.org/). 1069 Whatever the structure of OZCAR will be in the future, it is essential that the elementary 1070 components, the long0term observatories, be maintained and funded. Any topology should be 1071 flexible enough to incorporate new sites or instruments and be interoperable with the other RI 1072 dedicated to the study of Earth’s surface. 1073 * ( $ 1074 Born under the leadership of the US0NSF, the CZEN initiative has fostered the development 1075 of CZ networks in various countries either by restructuring existing geoscience0centric 1076 observatories or by launching competitive calls for encouraging multidisciplinary approaches 1077 on existing observatories (Sullivan et al., 2017; Feder, 2018). The Biological and 43 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1078 Environmental Research Subsurface Biogeochemistry Program of the Department of Energy 1079 (DEO) in the USA has developed the “Watershed Function Project”, a instrumented 1080 watershed0based network taking a “system0of0systems” approach (Hubbard et al., 2018) and 1081 utilizes a scale0adaptive simulation approach to quantify how fine0scale processes occurring 1082 in different watershed subsystems contribute to the integrated, time0dependent export of 1083 water, nitrogen, carbon, and metals. In Germany, the TERENO network created in 2008 is 1084 constituted of 4 distributed observatories exploring the long0term ecological, social, and 1085 economic impacts of global change at the regional level by measuring above0 and below0 1086 ground variables and biosphere parameters, and coupling them to remote sensing techniques 1087 (Zaccharias et al., 2011). The EU funded between 2009 and 2014 the SoilTrec program 1088 gathering 4 European CZOs located along a conceptual life cycle of soil. SoilTrec developed 1089 an integrated model quantifying soil processes that support food and fiber production; 1090 filtering, buffering and transformation of water, nutrients and contaminants; storage of 1091 carbon, and biological habitat and gene pool (Banwart et al., 2013). China and UK co0funded 1092 in 2016, 6 CZOs representing different geology, soil and land use types in China. In Australia, 1093 CZOs have been established in synergy with existing LTER and the Terrestrial Ecosystem 1094 Research Network (TERN) (Karan et al., 2016). 1095 In 2014, the EU started to fund different projects aimed at building a pan0European 1096 infrastructure, integrating European LTER, Critical Zone and Socio0Ecological Research 1097 observatories. This led to an ESFRI (European Strategy Forum on Research Infrastructure) 1098 project (eLTER RI) that has been included on the ESFRI road map in 2018 (http://www.lter0 1099 europe.net/elter0esfri). This initiative echoes the need of initiating a dialog between 1100 geoscience, bioscience and social science communities, restructuring the existing 1101 observatories and co0designing Earth Surface models and observation strategies that take into 1102 account socio0economical constrains (Richter and Billings, 2015; Mirtl et al., 2018). Together 44 Page 44 of 103 Page 45 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1103 with the French LTSER network of the “Zones Ateliers” (RZA), OZCAR constitutes the 1104 French mirror of eLTER ESFRI. 1105 Though the scientific approach and the monitoring strategies are different from the US0NSF0 1106 funded program, we hope OZCAR offers a model of integration of pre0existing observatories 1107 of the CZ at the national scale motivated by ambitious scientific and educational goals shared 1108 by the international community (Sullivan et al. 2017). 1109 7 1110 In this paper, we described the ambitions and goals of the newly0created national research 1111 infrastructure OZCAR. OZCAR0RI aims to be the French initiative for the global Critical 1112 Zone Exploration Network (CZEN). OZCAR is gathering a number of pre0existing 1113 instrumented sites grouped in 21 observatories and used for conducting long0term 1114 observations or experimentations and encompassing wide gradients of climate, geology, land 1115 use and land cover. The OZCAR network is assembling sites initially developed for 1116 hydrometeorological, hydrological, hydrogeological, biogeochemical questions, as well as 1117 sites focused on the cryosphere or using remotely sensed observations. The wealth of OZCAR 1118 observatories is inherited not only from the geologic, pedologic and climatic heterogeneity of 1119 the CZ along the mountain0to0sea continuum and along depth, but also from the range of 1120 timescales that characterize its functioning. OZCAR sites and observatories have their own 1121 initial scientific questions, monitoring strategies, databases, and modeling activities, but all 1122 share the main overarching goal: to monitor, understand and simulate CZ adaptation to a 1123 changing planet in the “new climatic regime” (Latour, 2018). 1124 The challenge of OZCAR is thus to build upon the heterogeneity of sites, scientific cultures, 1125 data management practices, to define a strategy at the network level enabling scientists to 1126 share models and data in order to significantly improve our integrated understanding of the 45 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1127 CZ as a system and form a new generation of scientists. 1128 The OZCAR community aims to achieve this goal by defining cross0site activities, through 1129 the construction of a common data base and metadata base environment, by developing and 1130 sharing new instruments for exploring the CZ, by defining a set of parameters in some 1131 representative sites that should be measured at all sites and through facilitating the interaction 1132 between data and Earth sub0surface models, in particular through a better representation of the 1133 coupled water, energy and biogeochemical cycles at all times scales. 1134 To face the unique environmental change that our planet is experiencing in the Anthropocene, 1135 and to achieve the sustainable development goals as defined by the UN, a significant 1136 community effort is needed to better model and predict the response of the Earth system. 1137 Beyond the need to better structure the existing French observatories, OZCAR hopes to serve 1138 as a benchmark for better organizing the environmental research observatories in other 1139 countries and to be part of the European and international CZ network, in particular thanks to 1140 its contribution to the pan0European research infrastructure eLTER. 1141 8 1142 OZCAR0RI is supported by the French Ministry of Education and Research, through the 1143 Allenvi Alliance. OZCAR observatories have benefited from numerous sources of funding 1144 coming from the different research institutions supporting the infrastructure (ANDRA, 1145 BRGM, CEA, CNES, CNRS, Ifsttar, INRA, IPEV, IPGP, IRD, IRSN, Irstea, Météo0France, 1146 LNE, CEA, IRSN), Universities (Avignon Pays de Vaucluse, Bourgogne Franche0Comté, 1147 Bretagne Occidentale, Grenoble0Alpes, La Réunion, Lyon, Montpellier, Orléans, Paris 1148 Diderot, Pierre et Marie Curie, Rennes, Rouen0Normandie, Savoie0Mont Blanc, Strasbourg, 1149 Toulouse, Clermont0Auvergne) and institutes (INP0Toulouse, Mines Telecom, VetAgroSup, 1150 IPGP). In the Southern countries, the following universities: UCAM, TREMA International 46 4 Page 46 of 103 Page 47 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1151 Joint Laboratory, Morocco; lNRGREF, INAT, Tunisia; Univ. Abdou Moumouni, Niger; 1152 Univ. Abomey0Calavi, Bénin; Univ. des Sciences des Techniques et des Technologies de 1153 Bamako, Mali; UFAM in Manaus, Brazil; UFF in Rio de Janeiro, Brazil; UNALM in Lima, 1154 Peru; UMSAin La Paz, Bolivia; UCV in Caracas, Venezuela; UMNG in Brazaville, Republic 1155 of the Congo; as well as the following national hydrological services: ANA, CPRM in Brazil, 1156 SENAMHI in Peru and Bolivia, INAMHI in Ecuador and DEAL in France, are thanked for 1157 making international collaboration possible. The French Ministry of Ecological and Inclusive 1158 Transition (AFB/ONEMA) is supporting the piezometer network (ROSES). 1159 A number of sites were supported by the ANR and PIA (+ 1160 , * ): Equipex CRITEX (ANR0110EQPX00011), LabexOSUG@2020, Labex DRIIHM 0 1161 OHM du Haut Vicdessos. 1162 We also thank the administrative and scientific staff of all institutions contributing to the 1163 collection, analysis and diffusion of the data collected within OZCAR. 1164 Tim White and two anonymous reviewers are thanked for their suggestions that improved the 1165 manuscript. Lin Ma and Nicole Fernadez are thanked in particular for their careful rereadings. 1166 @ 1167 1168 Anderson, M.P. 2005. Heat as a Ground Water Tracer. Groundwater 43: 951-968. doi:doi:10.1111/j.1745-6584.2005.00052.x. 1169 1170 1171 Anderson, S.P., J. Blum, S.L. Brantley, O. Chadwick, J. Chorover, L.A. Derry, et al. 2004. Proposed initiative would study Earth's weathering engine. 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International Journal of Applied Earth Observation and Geoinformation 21: 341355. doi:10.1016/j.jag.2012.07.015. 55 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1468 1469 1470 Massol M. and O. Rouchon. 2010. Quality insurance through business process management in a french archive. 7th International Conference on Preservation of Digital Objects. http://www.ifs.tuwien.ac.at/dp/ipres2010/papers/massol-6.pdf 1471 1472 1473 1474 Masson, V., P. Le Moigne, E. Martin, S. Faroux, A. Alias, R. Alkama, et al. 2013. The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes. Geosci. Model Dev. 6: 929-960. doi:10.5194/gmd-6-929-2013. 1475 1476 1477 Maxwell, R.M. and N.L. Miller. 2005. Development of a Coupled Land Surface and Groundwater Model. Journal of Hydrometeorology 6: 233-247. doi:10.1175/jhm422.1. 1478 1479 1480 1481 Mazzilli, N., M. Boucher, K. Chalikakis, A. Legchenko, H. Jourde and C. 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New Phytologist, 206(3), 900-912. 1553 1554 1555 1556 1557 Robinson, D.A., Binley, A., Crook, N., Day-Lewis, F.D., Ferré, T.P.A., Grauch, V.J.S., Knight, R., Knoll, M., Lakshmi, V., Miller, R. and Nyquist, J., 2008. Advancing process-based watershed hydrological research using near-surface geophysics: A vision for, and review of, electrical and magnetic geophysical methods. Hydrological Processes, 22(18), pp.3604-3635. 1558 1559 1560 1561 Sanzana, P., J. Gironás, I. Braud, F. Branger, F. Rodriguez, X. Vargas, et al. 2017. A GISbased urban and peri-urban landscape representation toolbox for hydrological distributed modeling. Environmental Modelling & Software 91: 168-185. doi:http://dx.doi.org/10.1016/j.envsoft.2017.01.022. 1562 1563 1564 Savenije, H.H.G. and M. Hrachowitz. 2017. HESS Opinions "Catchments as metaorganisms – a new blueprint for hydrological modelling". Hydrol. Earth Syst. Sci. 21: 1107-1116. doi:10.5194/hess-21-1107-2017. 1565 1566 1567 1568 1569 Schuite, J., L. Longuevergne, O. Bour, F. Boudin, S. Durand and N. Lavenant. 2015. Inferring field‐scale properties of a fractured aquifer from ground surface deformation during a well test. Geophysical Research Letters 42. doi:10.1002/2015GL066387. 1570 1571 1572 1573 Shortridge, J.E., S.D. Guikema and B.F. Zaitchik. 2016. Machine learning methods for empirical streamflow simulation: a comparison of model accuracy, interpretability, and uncertainty in seasonal watersheds. Hydrol. Earth Syst. Sci. 20: 2611-2628. doi:10.5194/hess-20-2611-2016. 1574 1575 1576 Sivapalan, M. 2003. Process complexity at hillslope scale, process simplicity at the watershed scale: is there a connection? Hydrological Processes 17: 1037-1041. doi:doi:10.1002/hyp.5109. 58 Page 58 of 103 Page 59 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1577 1578 Sivapalan, M., H.H.G. Savenije and G. Bloeschl. 2012. Socio-hydrology: A new science of people and water. Hydrological Processes 26: 1270-1276. doi:10.1002/hyp.8426. 1579 1580 1581 Steefel, C.I., C.A.J. Appelo, B. Arora, D. Jacques, T. Kalbacher, O. Kolditz, et al. 2015. Reactive transport codes for subsurface environmental simulation. Computational Geosciences 19: 445-478. doi:10.1007/s10596-014-9443-x. 1582 1583 1584 Steffen, W., K. Richardson, J. Rockström, S.E. Cornell, I. Fetzer, E.M. Bennett, et al. 2015. Planetary boundaries: Guiding human development on a changing planet. Science 347. doi:10.1126/science.1259855. 1585 1586 1587 1588 1589 Sullivan, P.L., L. Ma, N. West, L. Jin, D.L. Karwan, J. Noireaux, et al. 2016. CZ-tope at Susquehanna Shale Hills CZO: Synthesizing multiple isotope proxies to elucidate Critical Zone processes across timescales in a temperate forested landscape. Chemical Geology 445: 103-119. doi:https://doi.org/10.1016/j.chemgeo.2016.05.012. 1590 1591 Sullivan, P. L., Wymore, A. S., & McDowell, W. H. (2017). 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Derry, et al. 2015, The role of critical zone observatories in critical zone science, in Principles and Dynamics of the Critical Zone, (eds. R. Giardino and C. Hauser), Elsevier. Chapter 2, Developments in Earth Surface Processes 19: 15–78 1628 1629 1630 1631 Wigmosta, M.S., B. Nijssen, P. Storck, and D.P. Lettenmaier. 2002: The Distributed Hydrology Soil Vegetation Model, In Mathematical Models of Small Watershed Hydrology and Applications, V.P. Singh, D.K. Frevert, eds., Water Resource Publications, Littleton, CO., p. 7-42. 1632 1633 1634 Yu, X., C. Duffy, Y. Gil, L. Leonard, G. Bhatt and E. Thomas. 2016. Cyber-Innovated Watershed Research at the Shale Hills Critical Zone Observatory. Ieee Systems Journal 10: 1239-1250. doi:10.1109/jsyst.2015.2484219. 1635 1636 1637 Zacharias, S., H. Bogena, L. Samaniego, M. Mauder, R. Fuß, T. Pütz, et al. 2011. A Network of Terrestrial Environmental Observatories in Germany. Vadose Zone Journal 10: 955-973. doi:10.2136/vzj2010.0139. 1638 1639 1640 1641 1642 Zaslavsky, I., T. Whitenack, M. Williams, D.G. Tarboton, K. Schreuders and A. Aufdenkampe. 2011. The initial design of data sharing infrastructure for the Critical Zone Observatory. In: Proceedings of the Environmental Information Management Conference, Santa Barbara, CA, 28e29 September, EIM 2011. http://dx.doi.org/10.5060/D2NC5Z4X. 1643 60 Page 60 of 103 Page 61 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1644 - 1645 Fig. 1: The Critical Zone, shown here in particular at the catchment scale, is the thin porous 1646 layer at the surface of the Earth formed by the actions of water and acids on rocks. It is 1647 located between the lower atmosphere and unweathered bedrock, and strongly influenced by 1648 visible and invisible life activities. The integrated study of Critical Zone relies on the 1649 collaboration of different scientific communities, listed non0exhaustively in italic. 1650 1651 Fig. 2: Location of the different OZCAR0RI observatories on a land0to0sea continuum. Each 1652 acronym corresponds to a long0term observatory (primarily defined by a scientific question), 1653 and may be constituted of several instrumented sites. The numbers in parentheses correspond 1654 to the list of different observatories described in # $ . 1655 1656 Fig. 3: River catchment sites (the cubes) from OZCAR plotted according to the climatic and 1657 lithological gradients, noted with land use types. This diagram shows the range of 1658 environmental conditions covered by OZCAR and illustrates the theoretical idea that spatial 1659 gradients can be used to predict the temporal evolution of the Critical Zone (e.g. predicting 1660 the effect of climate change at constant rock type). Heterogeneity and sensitivity to initial 1661 conditions are limitations to this approach. Site names refer to # 1662 ACd: Auzon0Claduène, Aq: karst from Aquitaine, Av: Avène, Ba: Baget, Br: Brusquet, Ca: 1663 Dong Cao, Cp: Capesterre, Cr: Craie, Do: Donga, FN: Fontaine de Nîmes, Fo: Fontaine de 1664 Vaucluse, Ju: Jurassic karst, Ka: Kamech, Ke: Kerien, La: Laval, Lo: Lozère, M: Madiri, Ma: 1665 Huay Ma Nai, Me: Medycyss, Mo: Montoussé, MH: Mule Hole, Na: Naizin, NS: Nsimi, Or: 1666 Orgeval, Pa: Houay Pano, PM: Port Miou, RC: Real0Collobrier, Re: Réunion Island, Ro: 1667 Roujan, St: Strengbach, To: Tourgueille, Va: Valescure, VO: Val d’Orléans, Yz: Yzeron. 61 $ : AC: AmmaCatch, Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1668 1669 Fig. 4: The 320years evolution of the sulfate ion concentration in the stream of the Strengbach 1670 catchment (OHGE observatory) showing the wealth of information provided by long0term 1671 data series. The overall trend shows a decrease of sulfate concentration due to the decrease of 1672 industrial emissions in Western Europe over the period. Superimposed are seasonal variations 1673 and abrupt short0term changes. 1674 1675 Fig. 5: World map of OZCAR instrumented sites. More than 60 instrumented sites (with 1676 scales ranging from the plot to the whole river catchment) are included in 21 observatories or 1677 observation services (not represented) funded and evaluated by diverse research agencies. All 1678 are monitoring parts of the CZ. 1679 1680 Fig. 6: Overview of the CRITEX program (201202020) with the list of the work packages and 1681 associated instrumentation. The red stars correspond to “state0of0the0science” instruments 1682 developed as prototypes in CRITEX. CRITEX instruments are organized for tackling two 1683 scientific objectives: i) high0frequency monitoring in in the CZ (at the interface with the 1684 atmosphere, in the subsurface and at the outlet of catchments) and ii) multi0disciplinary 1685 monitoring of “hot spots” and during “hot moments” of the CZ. 1686 1687 Fig. 7: Simulation of the hydrological cycle components in the Nalohou catchment (AMMA0 1688 CATCH Benin observatory) using the ParFlow0CLM Critical Zone model. The model was set 1689 up based on observations and previous understanding of the processes, and is run without any 1690 calibration. (a) Constructing the model from observations: geophysical exploration using 1691 Electrical Resistivity Tomography (ERT, top) contributes to define the conceptual subsurface 1692 architecture, which is implemented in ParFlow (middle) (adpated from Hector et al., 2015). 62 Page 62 of 103 Page 63 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1693 (Bottom): simulated saturation along profile A shown in part (b). (b) Map of the Nalohou 1694 catchment (0.16 km²) with topographic elevation, instrumentation and ERT profile locations 1695 (adapted from Hector et al., (2015). (c) Simulated and observed Critical Zone variables: 1696 evapotranspiration (ET) at point 1 in (b); surface soil moisture at 5 cm at point 2 in (b); 1697 saturation, permanent and perched water table in the inland valley (“bas0fond”) (red) at point 1698 3 in (b) (adapted from Hector et al., 2018). 1699 1700 Fig. 8: The main scientific questions defined by the OZCAR community and discussed in the 1701 text. 1702 - 1703 1704 Table 1. List of the 24 variables measured in common in the catchments of the RBV network 1705 grouped by the different considered compartments. The frequency of the measurement is not 1706 fixed but depends on the characteristic timescales. 1707 1708 63 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 Table 1. List of the 24 variables measured in common in the catchments of the RBV network grouped by the different considered compartments. The frequency of the measurement is not fixed but depends on the characteristic timescales. n° 1 2 3 4 ATMOSPHERIC Rainfall amount Air temperature Wind velocity Wind direction n° 10 11 12 13 5 6 Air pressure Humidity 14 15 7 8 16 9 Radiation Chemical composition of rain Isotopic composition of rain O and H n° 17 GROUNDWATER Soil moisture content n° 23 18 Groundwater level Electrical conductivity of groundwater Temperature of groundwater Chemical composition of groundwater Isotopic composition of groundwater O and H 24 19 20 21 22 RIVER Discharge Electrical conductivity Water temperature Turbidity Suspended sediment concentration Chemical composition of water Isotopic composition of water O and H SURFACES land use/land cover Chemical composition of agricultural inputs Page 64 of 103 Page 65 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 ! " # $% & ( ! '( $) *+ ! " # $ %% "& &' ) ('%& *+ , %% "& - &' . - + / "0 %% "& 1 + 23345 # &' + 23 6 1 - ,*+ ! " )/ 7 1 5 23 85 Descroix et al. 2012 233 5 # 4837 1 + 2334 + 9 : + 23345 ; < , + 23 25 # + 23 8 + 23 = % 23 25 - + 23 =5 # 1 + 23 8 + 23 5 + , + 23 > ; %% "& ! 1 &' , / Page 66 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 + 23 8 23 ('%& ; & + 233>5 - ? " + - ? , % & & % ? ('%& + @ " ) " + + " + " + , + 23 = A + B $ ('%& ? ! " # * $$ " " -- -" + + ( C %" % $ - - ' - + 2334 $ - + + - - & % & ! - (<$&/ - " ? + 23 6 ('#C + 4435 ; + 46> < 446 / 2 46D Page 67 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 44>+ < + 5 , , - ' + (%C C+ ( %" < + $$+ + (<$&/ " < # + + 23365 : 23 D5 + 23 6 + + 23 E5 % - + 23 E # + + 23 8 + 23365 ( 'F9G $$ %% "& ('%& + 23 = 'G + &' # % + + 23 = % ' "# + 23 E5 + 2334 +( & $$$ + ( C (%C C + + ('%& "& - + 23 = H + %" " (<$&/"' % 0 ; ," 46E , % %" % (<$&/ + 233E + 2332 ; + 2336 / : (%C C - 23345 $ + 23 8 : & + , + ' < %" (<$&/ + - " 46 D 3 % 9? 3 ? 2 9 + 23 8 " Page 68 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 " # $ /0( I ? , + 9 - + ? ? - ? /0( I - + + + + ? - , 0 ( + + $ + + " +? , , . " ) * " - + A ! @ - J. J. , J. 2 ( J /0 , 2332+ , , ! ! 'K ! - " + -+ + ! - + ! - 4 Page 69 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 + + % + -+ 'K + L+ 'K , ! ? - 'K , 'K " ! 1 , ? , ! & 1 , + /'C < , + 1/ + % +< - + ! + ( A 'K + - + + ? + + + + " , 2 , - , ! + ? + + ? , + - - + - ? % 5 Page 70 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 " 3 , ; A , , , + - - A ! - + - + 'K , - E 4 * 5 678 ! @ ? - + ? - ! - ' -- -9 J ' - - -9 ? + J' - - ? J - + . - - " - J ? ' + + - J & G( /"&1$% + - ? -+ C + + " +' + ( 23 8 6 +/ $ " Page 71 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 >3+333 / C ? ? 2333"23 D ' % " , - 43 333 ? M - 2333 - 23 D - " - , = ( '9 ) - ? ! : / ? " C : 7 +- ? - E">N 2336"23 3+ + ;7 - + 23 D + " #'#@ &(2+ &'=+ '2(+ 02( + , ;(&+ <(& - #'#+ ;(& <(& , + #'#+ ;(& <(& + + + - &(2 0 - C - C, &'= @ , / @ 333 2 ! 2 - + + , - - 7 " , Page 72 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 ( & ; + 23 5 ; + 23 > 5 "O > ( ' , - - + 23 85 # + 23 8 ) (/ ! " + + (/ , + + + + - ? E + - " " , + 2 + , + - (/ - - % $ /. : + / - / . + (/ 9+ 23 D5 + 23 85 % 23 E % - < (/ 23 D % % " ! " - + - - " - % 1 < : + 23 8 + 23 2 8 - ! + Page 73 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 D ( 3 ' ! , - ! ) C - ? . ; $ - ! ! + O + 23 2 5 ? + 23 25 C - . + 2336 5 - - ! : 1 + 23 > 5 $ 88 333 + - - 8= 333 - ! ==33 % : - @99--- 8 ( + 93 '6 ,5 " ;C/ - ? , ! ) (<C 3 ! < - ? M A : - (<C - ?+ + - ! + + + + ! - A 33 9 Page 74 of 103 # :% & ! '( ( ! ; & & :) & < ' (%C C (<$&/2 %" < 1 1 9 9 - 23 = ; ," + ( 'F9G & &'> %% "& < ('%& D ('#C8 6 ( (%C C4 / 2 E = > D 8 6 4 @99---D @99 @99--" @99 @99 " @99 @99 " " @99 @99--" 9 " ( ( P P " , 9 9 9; 9 9 9; 9 9 A 9 J 9 9( 9 , 9' , E3 9 J Q - ?R Q 10 + ( 0 : 9 - 9 - ? F F /0( I - / + $0/<$ C ! < / / ('%& ;(' ' %" (<$&/ Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 'G %E ;('= - Page 75 of 103 'K 3 & G( /" &1$% 2 H E (<C 3 2 E & @99 @99--- 1 9 - 0 ? - #&%; $ ( : ;C/ 9 % &' : $0/<$ C ! F " @99 # - 0 " " ; 9 " < " + A 91 @99 1 9 , 11 " - ?; . - Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 (/C/ 9 %% "& " " (/ 1 Page 76 of 103 # -% 3# , Scientific/operational question References Use of data and models for process understanding How to represent snow-pack evolution? Lafaysse et al. (2017) What are the main hydrological controls of dissolved organic carbon in a restored peatland? What are the water and solute pathways in karst and fractured aquifers? Kang et al. (2015) ; Guihéneuf et al., (2017) Dorn et al. (2012); Read et al. (2013); Klepikova et al. (2016) Shakas et al. (2017) Arfib and Charlier (2016) Roques et al. (2014) Ben Maamar et al. (2015) Boisson et al. (2013) Binet et al. (2013); Bernard-Jannin et al. (2017) Maréchal et al. (2004); Le Borgne et al. (2006); Audoin et al. (2008); Binet et al. (2017); Cholet et al. (2017); Charlier et al. (2012); Mazzilli et al. (2017) Labat and Mangin -) Main approach and findings CZ compartment A 18-year time series of climatological variables and snow characterization from the Col de Porte site (CRYOBS-CLIM observatory) was used to compare various snow-pack evolution models, that were included as a modeling toolbox in the SURFEX land surface model (Masson et al., 2013). A combination of convergent and push-pull tracer tests can be effectively used to decipher the role of transit time distribution and velocity correlation for modeling transport processes. Repeated measurements combining electrical, electromagnetic, thermal, hydraulic and geochemical data have provided key in-situ experimental data sets to understand transport processes in fractured media. Cryosphere Fractured aquifers Fractured aquifers Data and models were used to understand salt intrusion in a karstic aquifer. Chemical and microbiological sampling, and field hydraulic and tracer tests were used to infer biogeochemical reaction processes in fractured aquifers Karstic aquifers A hydrological model, calibrated on water table levels, and coupled with a biogeochemical module was shown to correctly reproduced pore water dissolved organic carbon (DOC) concentration time series in a restored peatland. Water table drawdown severity has been identified as the major factor controlling DOC dynamics. Data and models of various complexities helped to identify water and solutes pathways. Peatland Data and models were used to discriminate between rapid flow via conduits networks and slower flow via matrix or fractured systems Karstic aquifers 12 Fractured aquifers Fractured aquifers Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 How does fractured media heterogeneity impact transport processes and biogeochemical reactions in groundwater? '( Page 77 of 103 What is the level of complexity required to model erosion at the hillslope scale? (2015) Labat et al. (2016) Cea et al. (2014); Cea et al. (2016) Gumière et al. (2014) What are the appropriate representations of subsurface water and solute pathways and what are the relevant data and inverse modeling strategies to constrain them? What are the interactions between hydrological and vegetation cycles in SW Niger? Leray et al. (2012) What are the controlling factors of weathering in the Strengbach catchment and the Mule Hole catchment? Godderis et al. (2006); Violette et al. (2010) Can we improve the knowledge of the water balance of the Amazon? Getirana et al. (2010; 2011) Can we predict nitrates and pesticides behavior and transfer in agricultural catchments using agro-hydrological Ferrant et al. (2011) ; Boithias et al. (2011) Velluet et al. (2014); Leauthaud et al, (2017) A process-based model, calibrated using a 40-year time series of discharge and nitrogen concentrations, was used to estimate nitrogen transit times and was able to simulate the constant increase of nitrate linked to the increased of fertilization since the 1960s. The paper demonstrates the interest of combining hydraulic and age information for the prediction of residence time distributions within hydrogeological models, and showed the possibility of identifying global hydrogeological structures from point-like data. A calibrated mechanistic SVAT (Soil Vegetation Atmosphere Transfer) model was first used to retrieve a climatology of water and energy budgets in Niger at the plot scale. Then the model was coupled with the STEP ecological model and the SARAH agronomic model to study interactions between hydrological and vegetation cycles in SW Niger. The WITCH model, coupling kinetics of silicate weathering reactions to the water and carbon cycle in forest ecosystems, initially designed and applied to the granitic Strengbach catchment (OHGE observatory), was coupled with a lumped hydrological model to successfully reproduce the stream chemistry of the Mule Hole catchment. In large catchments where data are scarce, such as the Amazon, satellite altimetry data were combined with in-situ data from gauging stations to assess and strengthen the water balance computed using a distributed hydrological model. Such datasets were also used for the evaluation of large-scale land surface models. A comparison of a distributed (TNT2) and a semi-distributed model (SWAT) allowed the authors to better understand nitrogen transfer dynamics in a small agricultural catchment. Using the SWAT model, 13 Surface water and sediment transport Surface water and sediment transport Surface water and nitrate Fractured aquifer Soil – vegetation – atmosphere interface Catchment hydrology, geochemistry Continental scale catchment hydrology Soil- Water, Catchment scale Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 Use of data and models for system understanding Can we explain long-term trends in nitrate Fovet et al. (2015) concentration in rivers in Britanny? The 2D surface runoff model of Cea et al. (2014) was coupled with an erosion module and plot data from the OHMCV observatory to assess the model complexity required to correctly reproduce the observed sediment yields. Connectivity of sediment transport was taken into account in the modeling of erosion, with evaluation with data from the OMERE Observatory to properly represent erosion yields. Page 78 of 103 modelling? What are the main hydrological controls of bacteria in a tropical mountain watershed? Kim et al. (2017) What is the role played by geology on the hydrological processes during flash-flood events? Vannier et al. (2016) Hydrological and geochemical data (SNO Karst) were used to design a flash flood warning model for the city of Nîmes (SE France) Time series of discharge and glacier mass balance data (CRYOBSCLIM) were used to provide a synthesis of glacier mass balance evolution for the whole Andean region. Once calibrated using local information, remote sensing data combined with a water balance model (SAMIR) provided suitable tools for simulating water needs and irrigation. In-situ and remote sensing data were used to model water resources in the area of Marrakech (Morocco), using a coupling between the WEAP (Water Evaluation And Planning System) hydrological model and the MODFLOW groundwater model. Observations at small scale (Orgeval observatory) were used to calibrate the Riverstrahler model (Ruelland et al., 2007) that was then applied to the whole Seine river basin. What would be the impact of small ponds rehabilitation on nitrate contamination in the Seine catchment? Passy et al. (2012) What is the level of contamination of French aquifers with respect to contaminants from agriculture and emergent pollutants? Can we predict the risk of nitrates and pesticides transfer to surface waters and propose best environmental practices to reduce contaminant fluxes? Lopez et al. (2015) The ROSES data base was used to model transfer time and the behavior of agricultural and emergent contaminants within aquifers of large catchments in France. Macary et al. (2013 a, b) A multi-scale method and a multi-criteria modelling coupled with a GIS was applied to assess pesticide contamination risks in agricultural watersheds. The effect of best environmental practices on reducing pesticide and nitrates pollution towards surface water, was assessed. The long term impact of nitrate mitigation scenarios was simulated in a pilot study basin using an agrohydrological modelling. What is motorists’ exposure to flash floods and what are their behaviors and mobility Ferrant et al. (2013) Shabou et al. (2017) A distributed hydrological model was used to assess exposure of road 14 Surface and ground water Surface water Cryosphere Surface water, aquifers, biosphere Catchment hydrology, river geochemistry, nitrate cycle Groundwater Soil and Catchment scales Surface water ; Human exposure to Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 Use of model and data for management/prediction purposes Can we design a flash flood forecasting Maréchal et al. system in a karstic environment? (2008) What is the sustainability of water Chevallier et al. resources under climate change in the (2010) ; Rabatel et al. Andes region? (2013) What are water and irrigation needs in Battude et al. (2017); different contexts , and what is the impact Le Page et al. (2012) of irrigation on water table levels? the introduction of the partition coefficient Kd to predict pesticides behavior in stream waters improved pesticide transfer modelling.. The SWAT model was improved by implementing in-stream resuspension of sediments and transient storage in the hyporheic zone (Houay Pano catchment) A regional distributed hydrological model was used to perform longterm and flash-flood event simulations at the regional scale. Discharge simulation was improved when the weathered bedrock layer was included into the model. Page 79 of 103 adaptations with respect to roads flooding? users to extreme hydrometeorological events. This model requires the combination of social and hydrometeorological data as well as road flooding impact data. flash flood events Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 15 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 # Abril, G., J.M. Martinez, L.F. Artigas, P. Moreira-Turcq, M.F. Benedetti, L. Vidal, et al. 2014. Amazon River carbon dioxide outgassing fuelled by wetlands. Nature 505: 395-+. doi:10.1038/nature12797. Allemand, P., C. Delacourt, E. Lajeunesse, O. Devauchelle and F. Beauducel. 2014. Erosive effects of the storm Helena (1963) on Basse Terre Island (Guadeloupe — Lesser Antilles Arc). Geomorphology 206: 79-86. doi:10.1016/j.geomorph.2013.09.020. Arfib, B. and J.-B. Charlier. 2016. Insights into saline intrusion and freshwater resources in coastal karstic aquifers using a lumped Rainfall–Discharge–Salinity model (the Port-Miou brackish spring, SE France). 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European aquifer typology: a practical framework for an overview of major groundwater composition at European scale. Environmental Geology 55: 77-85. doi:10.1007/s00254-007-0966-5. 27 Page 92 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 Table  S1. Observarory  (nb   reported  Fig.  2) Catchment/si Climate Lithology te  scales   (km2) Network  RBV  (Réseau  de  Bassins  Versants):  catchment  hydrology,  geochemistry,  erosion,  soil-­‐plant-­‐atmosphere  interactions AMMA-­‐CATCH  (1) Mali Gourma 16°N 1.5°W 1-­‐30000 Semi-­‐arid Sandstone   and  schist OHMCV  (2) Country Name Latitude Longitude Land  use Individual  research  questions Sparse   herbaceaous   vegetation Ecohydrological  monitoring  in  a   Rainfall,  meteo,  water  level  in  ponds,  groundwater  level,   pastoral  environment soil  moisture,  surface  energy  balance,  CO2  flux,  sapflow,   LAI,  PAI,  vegetation  fraction,  phenology,  herbaceous   biomass 1984 http://www.amma-­‐catch.org/   http://www.amma-­‐catch.org/spip.php?rubrique63   idem idem 2013 Idem Idem 1990 Idem Idem 1997 Idem Idem 2005 http://ohmcv.osug.fr/ http://ohmcv.osug.fr/spip.php?article30   2003 Idem Idem Rainfall,  water  level  and  discharge  in  rivers,  physico-­‐ chemical  properties  in  surface  water  (temperature,  pH,   conductivity) Rainfall,  meteo,  water  level  and  discharge,  physico-­‐ chemincal  properties  of  surface  water  and  soil  (pH,   temperature,  conductivity,  anions,  cations),  soil  moisture 2008 Idem Idem 1986 Idem Idem Senegal Ferlo 15.5°N 15.5°W idem idem Sandstone   Niger Niamey  square  degree 13.5ºN 2.5ºE 0.35-­‐16000 Semi-­‐arid Gneiss,  schist   Fallow  savanna,   and  granite tiger  bush  and   pearl  millet Benin Ouémé  9º5N   2ºE 0.16-­‐14000 Soudanian Migmatite France Auzon-­‐Claduègne 44.58°N 4.50E 3.4-­‐116 Mediterranean Basalt,   limestones   and  marls Valescure 44.09N 3.83E 0.3-­‐3.9 Mediterranean Granite Tourgueille 44.13N 3.67°E 1-­‐10 Mediterranean Schist Mont  Lozère 44.7°N 3.82°E 0.19-­‐0.81 Sub-­‐ Granite Mediterranean  -­‐2.83ºW 4,9 Oceanic Mixed  forest  and   Idem grassland Kervidy-­‐Naizin  47.99°N Kerbernez 48.12º  N -­‐4.03ºW Auradé  (4) France Montoussé 43,56  °N 1.06°  E ORACLE  (5) France Orgeval  48.89°N  3.19°E 1  to  1800 Temperate   oceanic OMERE  (6) France Roujan 43.50ºN 3.31  ºE 0.0012-­‐0.91 Mediterranean Limestones   and  marls Mediterranean   agriculture Tunisia Kamech 36.88ºN 10.88ºE 0.013-­‐2.63 Mediterranean Sandstone   and  marls Idem Oceanic hydrology  of  endoric  basins  -­‐   rainfall/vegetation  interaction Idem France 3,2 Temperate   oceanic Rainfall,  soil  moisture,  soil  biogeochemistry Rainfall,  meteo,  water  level  in  ponds,  gullies  and  plots,   groundwater  level  in  piezometers  and  wells,  soil   moisture,  surface  energy  balance,  CO2  flux,    LAI,   vegetation  height,  herbaceous  biomass  and  species woodland,   hydrological  cycle  -­‐  water   Rainfall,  meteo,  water  level  in  rivers  and  gullies,   shrubland,  crops   budget  and  hydrological   groundwater  level  in  piezometers  and  wells,  water   and  herbaceous   processes chemical  analysis,  soil  moisture,  surface  energy  balance,   fallow CO2  flux,  sapflow,  LAI Pasture,  vineyard   Biogeochemical  cycles,  climate   Rainfall,  meteo,  water  level  and  discharge  in  rivers,   and  forest chang,  hydrometeorological   suspended  sediment  and  physico-­‐chemical  properties  of   extremes  in  the  Mediterranean:   surface  water,  soil  moisture,   intense  rain  events  and   subsequent  flash-­‐floods,   erosion Decidious  forest Idem Rainfall,  meteo,  water  level  and  discharge,  physico-­‐ chemincal  properties  of  surface  water  and  soil  (pH,   temperature,  conductivity,  anions,  cations),  soil  moisture AgrHys  (3) 0.095-­‐1.28 Measured  variables  (all  the  variables  are  not  measured   Oldest  measured   Web  site over  the  whole  period) variables Data  portal Schist Intensive   agriculture Response  time  of  hydro-­‐ geochemical  fluxes  to  climate   and  anthropogenic  forcing Rainfall,  meteo,  discharge,  groundwater  level;  physico-­‐ chemical  and  chemical  concentration  in  rainfall,  soil,   surface  water  and  groundwater;  land  use  and   agricultural  practices 1990 https://www6.inra.fr/ore_agrhys/   https://www6.inra.fr/ore_agrhys/Donnees/Le-­‐grapheur-­‐ VIDAE   Granite Intensive   agriculture Crops  (wheat,   sunflower) Idem Idem Marls-­‐ limestone Limestones,   Agriculture gypsum  and   clays 1992 Idem Idem Impact  of  agricultural  activities   Water  level  in  rivers,  nitrates,  pesticides  concentration,   on  water,  matter  (nitrate,   physico-­‐chemical  properties;  13C,  water  isotopes  in  river carbon)  balance  and  fluxes  in   watr,  soils,  ecosystems 1983 http://www.ecolab.omp.eu/bvea/   http://www.ecolab.omp.eu/bvea/donneesdisponibles/don nesdisponibles   Impact  of  climate  variability  on   the  hydrological  cycle  (focus  on   floods  and  drought)  and  of   agriculture  practices  on  hydro-­‐ biogeochemical  fluxes  and   water  quality Impact  of  land  use  change  and   anthropogeneic  practices  on   the  hydrological  and   sedimentological  regime,   impact  of  pesticides  on  water   quality Idem Rainfall,  meteo,  water  level  and  discharge  in  rivers  and   ditches,  groundwater  level,  soil  moisture,  suspended   sediments,  surface  and  groundwater  physico-­‐chemical   properties  (temperature,  pH,  conducitvity,  DOC,  anions),   surface  energy  budget. 1962 https://gisoracle.irstea.fr/ https://bdoh.irstea.fr/ORACLE/ Rainfall,  meteo,  water  level  and  discharge  in  rivers  and   ditches,  suspended  sediment,  groundwater  levels,   pesticides  concentration,  physico-­‐chemical  properties  of   surface  water  (cations,  anions,  isotopes,  metals  ),  surface   energy  budget  and  CO2  fluxes,  soil  moisture 1992 http://www.obs-­‐omere.org/   http://www.obs-­‐ omere.org/index.php?page=geonetwork&lang=fr   Idem 1994 Idem Idem Page 93 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 OTHU  (7) France Yzeron 47.74°N 4.69°E 2.1-­‐129 M-­‐TROPICS  (8) Cameroon Nyong  (Nsimi) 2.9°N 11.4°E India Kabini  (Mule  Hole,   Berambadi) 12.2°N 76.9°E Thailand Huay  Ma  Nai 18°13'20"N 100°23'40"E 0,93 Tropical Laos Houay  Pano 19°51'10"E 102°10'45"E Vietnam Dong  Cao 20°57'40"N 105°29'10"E ObserRA  (9) France 16.18ºN -­‐61.69°E EroRun  (10) France -­‐20.9°N  55.5°E OHGE  (11) France Bras  David  et  Capesterre   (Guadeloupe) Rivière  des  pluies,  la   Réunion Strengbach 48.21°N 7.20°E Real  Collobrier  (12) France Real  Collobrier 43.25°N 6.36°E Draix-­‐Bléone  (13) France Draix-­‐Bléone 44.1°N SNO  Karst  (14) France Baget Medycyss HYBAM  (15) Forest,   Impact  of  urbanization  on   Rainfall,  meteo,  water  level,  temperature  and  discharge   agriculture,  urban hydrology,  geomorphology  and   in  rivers  and  sewers,  physico-­‐chemical  properties  of   water  quality,  ecohydrology water  in  rivers  and  sewers 1997 http://www.graie.org/othu/index.ht https://bdoh.irstea.fr/YZERON/ m 0.6-­‐18500 Continental   Gneiss with   mediterranean   influence Tropical Granite humid  tropical   forest 1994 https://mtropics.obs-­‐mip.fr/ https://mtropics.obs-­‐mip.fr/data-­‐access/ 4.3-­‐590 Tropical Gneiss Dry  forest,   agriculture 2003 idem Idem Sandstone Intensive   agriculture 2001 idem Idem 0,6 Tropical Schist Tree  plantation 2001 Idem Idem 0,5 Tropical Schist Reforested 2002 Idem Idem Andesite Tropical  forest 45 Tropical  (with   basalt cyclones) 0,8 temperate   Granite,   oceanic   gneiss mountainous Tropical  forest 0.08-­‐16.4 Tropical 6.3°E Mediterranean Gneiss  and   schist   0.0013  to  22   Mediterranean Marls Mediterranean   forest   badlands  or   mediterranean   forest 42.95  N 1.03  E 13.25 Forest  and   grasslands 47.9ºN 4.6ºE 1200 Mediterranean Limestone Mediterranean   agriculture Fontaine  de  Vaucluse  -­‐  LSBB 43.92°N 5.13°E 1130 Mediterranean Limestone Forest  and   grasslands Jurassic  Karst 47.1ºN 6.3ºE 1-­‐50 Mountainous   Limestone Forest Karst-­‐Craie 49.43°N 0.19°E 10-­‐230 Oceanic Karst  Val  d'Orléans 47.85°N 1.937°E 3,3122°  S 60,6303°  W Bolivia,  Peru,   Amazon Ecuador,   Brazil 0.7  to  70 Forest Oceanic Limestone Limestone -­‐3.43°W H+  (16) France Poitiers 46.56°N 0.40°E 0,12 Oceanic H+  +  RBV  (SNO   KARST)  (14,  16) France   Fontaine  de  Vaucluse  -­‐  LSBB 43.92°N 5.13°E 1130 Mediterranean Karst 5  to  20   Oceanic Idem Rainfall,  meteo,  water  level,  physico-­‐chemistry   (temperature,  pH,  conductivity,  chlorures,  nitrates,  COT,   COD,  turbidity) 2009 https://zaaj.univ-­‐ fcomte.fr/spip.php?article13&lang= en   agricultural  lands Idem Rainfall,  water  level,  physico-­‐chemistry  (temperature,   pH,  conductivity,  chlorures,  nitrates,  COT,  COD,  turbidity) 1997 http://www.sokarst.org/index.asp?l ang=fr   grasslands mediterranean   forest  +   agriculture Flash  floods   2011  http://www.ipgp.fr/fr/obsera/obser http://webobsera.ipgp.fr/ vatoire-­‐de-­‐leau-­‐de-­‐lerosion-­‐aux-­‐ antilles 2015 http://osur.univ-­‐ reunion.fr/observations/soere/rbv/   1986 http://ohge.unistra.fr/   http://bdd-­‐ohge.u-­‐strasbg.fr/index.php/bdd   1966 https://bdoh.irstea.fr/REAL-­‐ COLLOBRIER/   1983 https://oredraixbleone.irstea.fr/ Micaschists   grasslands  and   and  Granites agriculture Limestones Rainfall,  meteo,  discharge,  groundwater  level,  tensio-­‐ neutronic  soil  monitoring,  hydrochemical  parameters   (anions,  cations,  PH,  DOC,  total  suspended  sediments Impact  of  agriculture  and  forest   idem on  water  and  biogeochemical   cycles Land  use  changes  and   Rainfall,  meteo,  water  level  and  discharge,  suspended   consequence  on  soil  and  water   sediments,  bedload,  land-­‐use,  water  chemistry processes  in  tropical  mountains   environments Idem Rainfall,  meteo,  water  level  and  discharge,  suspended   sediments,  bedload,  land-­‐use Idem Rainfall,  meteo,  water  level  and  discharge,  suspended   sediments,  bedload,  land-­‐use Weathering  and  erosion,   Rainfall,  meteo,  discharge,  suspended  sediment,   sediment  and  organic  carbon   geochemical  species,  physico-­‐chemistry  of  rivers  and  soil   fluxes solution,  dgischarge,   roundwater   level sediment,  geochemical   Water,  sediment  and   Rainfall,   suspended   geochemical  fluxes species Response  of  ecosystems  to   Rainfall,  meteo,  water  level  and  discharge  in  rivers,   climate  and  anthropogenic   groundwater  levels  in  piezometers  and  wells,  suspended   perturbations  (forest   sediments  in  rivers,  physico-­‐chemical  properties  (pH,   exploitation,  atmospheric   temperature,  conductivity,  anions,  cations,  DOC,  trace   pollution)  -­‐  element  and  water   elements)  in  rivers,  springs,  soil  solutions,  rainfall   transfert  at  the   atmosphere/soil/plant  interface Rainfall,  water  level  and  discharge,  suspended  matter   and  bedload  transport Floods  and  erosion  in   Rainfall,  meteo,  discharge,  groundwater  level,  soil   mountainous  catchments,  rock   moisture,  rainfall  stable  isotope  content;  suspended   weathering  and  vegetation   sediment  concentration,  total  solid  transport  during   impact  on  erosion events,  LiDar  DTM,  vegetation  cover,  landslides Hydro-­‐geo-­‐chemistry  of  the   Water  level  and  discharge,  physico-­‐chemical  properties   karst  (quantity  and  quality  of   of  water  (pH,  temperature,  conductivity,  anions,  cations,   the  water  resource,  floods) stable  isotopes,  doc) Idem Rainfall,  meteo,  water  level  and  discharge  in  rivers,   groundwater  levels,  soil  moisture,  physico-­‐chemistry     (temperature,  conductivity,  major  and  trace  elements,   stable  isotopes,  MON,  TOC  ) Idem Rainfall,  meteo,  water  level,  pressure  and  discharge  in   springs,  physico-­‐chemical  properties  of  water  (anions,   cations,  DOC,  stable  isotopes),  gravimetry,  inclinometry 20 Oceanic Limestone Forest  and   grasslands 6400000 Humid  Tropical Mixed   Tropical  forest (sedimentary ,  volcanic  and   metamorphic ) Network  H+:  hydrogeological  observatories  and  sites,  the  deep  CZ. H+  (16) France Ploemeur 47.74°N Chemical  weathering  of   silicated  rocks https://bdoh.irstea.fr/REAL-­‐COLLOBRIER/   https://bdoh.irstea.fr/DRAIX/   1978 http://www.sokarst.org/index.asp?l ang=fr   2005 http://www.medycyss.org/   1995 https://www6.paca.inra.fr/emmah/L es-­‐moyens/Sites-­‐ experimentaux/Fontaine-­‐de-­‐ Vaucluse-­‐LSBB/Fontaine-­‐de-­‐ Vaucluse Idem Water  level,  physico-­‐chemistry  (temperature,  pH,   conductivity,  chlorures,  nitrates,  COT,  COD,  turbidity) Geodynamical,  hydrological  and   Rainfall,  water  level  and  discharge  in  rivers,  suspended   biogeochemical  control  of   sediment  concentration,  physico-­‐chemical  properties  of   erosion/alteration  and  material   rivers  (temperature,  pH,  conductivity),  geochemistry   transport  in  the  Amazon,   (anions,  cations,  organic  carbon) Orinoco  and  Congo  basin 1970 http://www.sokarst.org/index.asp?l ang=fr   2003 http://www.ore-­‐ http://www.ore-­‐hybam.org/index.php/eng/Data   hybam.org/index.php/eng   Groundwater  flow  and   Groundwater  levels  and  discharge,  physico-­‐chemical   transport  modeling  in  a   fluid  properties  (temperature,  conductivity,  chemistry),   fractured  aquifer  used  for   unsaturated  zone,  geophysical    montoring  (GPS,  sismic,   water  supply tiltmeter  ..) Adapated  well  nest  for   Meteo  data,  groundwater  levels,  physico-­‐chemical   groundwater  flow  and   properties  (temperature,  conductivity,  chemistry) transport  experiments  and   models  in  a  karstic  aquifer Hydrogeological  functionning  of   Rainfall,  meteo,  water  level,  pressure  and  discharge  in   a  large  unsaturated  zone  in   springs,  physico-­‐chemical  properties  of  water  (anions,   karst cations,  DOC,  stable  isotopes),  gravimetry,  inclinometry 1991 http://hplus.ore.fr/   http://hplus.ore.fr/base-­‐de-­‐donnees-­‐fr     2002 Idem Idem 1995 Idem  and   Idem http://www.sokarst.org/index.asp?l ang=fr     Page 94 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 H+  (16) France Larzac 43.97°N 3.82°E 100 Mediterranean Karst H+  (16) France AuverWatch 45.74°N 3.21°E 320 Continental H+  (16) India Hyderabad  (Maheswaram   and  Choutuppal) 17.29°N 78.92°E H+  (16) Spain Majorque 39.41°N 2.95°E Network  CRYOBS-­‐CLIM:  glaciers,snow  and  permafrost  studies GlacioClim  (17) France Alpes-­‐Sarennes 45°07’  N Permafrost  (17) Tropical 06°07’  E 0,5 Alpes-­‐Saint  Sorlin 45°09’  N 06°10’  E 3 France Alpes-­‐Mer  de  Glace 45°55’  N 06°57’  E 28 France Alpes-­‐Argentière 45°55’  N 06°57’  E 19 France France Alpes-­‐Gébroulaz Alpes-­‐Col  du  Dome 45°19’  N 06°07’  E 3 France Pyrénées-­‐Ossoue 42°46’  N 00°08’  W 0,45 Svalbard Svalbard-­‐Austre  Loven 77.87497 20.97518 5 Bolivia,  Peru,   Andes-­‐Zongo Ecuador,   Brazil 16°16’  S 68°09’  W 1,8 Ecuador Nepal Andes-­‐Antizana Himalaya-­‐Mera 00°28’  S 27,7°N 78°09’  W 86,9°E 1 5,1 Antarctic Antarctique-­‐Cap   Prud'homme Antarctique-­‐Dome  C -­‐66,69194 139,89667 75°S 123°E Basaltes Cristaline   rocks Gneiss/Migm atites Unknown 8000 France Alpes-­‐Col  de  Porte 45.30°  N 5.77°  E Alpes-­‐  Col  du  Lac  Blanc 6°  6'41.38"E 0,25 Mountainous France Alpes-­‐Laurichard 45°   7'40.38"N 45.018°N 6.40°E 0,08 Mountainous France Alpes-­‐Deux  Alpes 45.0°N 6.19°E France Alpes-­‐Aiguille  du  Midi 45.878°N 6.887°E France Alpes-­‐  Dérochoir 45.866°N 6.809°E 6 High   mountains 0,05 High   mountains 0,05 High   mountains 43.50°N 1.24°E 31.5°N -­‐8°W 42.80°N 1.42°E Morrocco Tensift Network  "Tourbières":  peatland  observatories SNO  Tourbières  (19) France Bernadouze Granites Mica   Schistes,   Gneiss Mica   Schistes,   Gneiss Granite/Gnei ss Granite/Gnei ss Gneiss Granite/Gnei ss Cristaline   rocks Cristaline   rocks Granites France Network  OSR:  Regional  spatial  observatory OSR  (18) France South-­‐West Alluvial  sands Grassland Intensive   agriculture 0,12 Mediterranean Limestones France Antarctic Snow  (17) 04-­‐55 grasslands  and   forests 0,006253 Mountainous 0.001-­‐2500 Oceanic   mountainous Glacier Glacier  mass  balance,  rainfall,  meteo,  raidation  budget,   surface  energy  balance,  glacier  temperature  profile   2006 Idem Idem 2010 Idem  +  http://wwwobs.univ-­‐ Idem bpclermont.fr/SO/auverwatch/index .php     2000 Idem Idem 2003 Idem Idem Glacier Impact  of  climate  change  on   glaciers  and  associated  water   resources Idem Idem 1949 https://cryobsclim.osug.fr/  and   http://devdata.glacioclim.fr/portal/main.jsf http://devdata.glacioclim.fr/portal/ main.jsf   1957 Idem Idem Glacier Idem Idem 1983 Idem Idem Glacier Idem Idem 1975 Idem Idem Glacier Glacier Idem Idem Idem Idem 1983 Idem 1997 Idem Idem Idem Glacier Idem Idem 2001 Idem Idem Glacier Idem Idem 2007 Idem Idem Glacier Idem Idem 1973 Idem Idem Glacier Glacier Idem Idem Idem Idem 1995 Idem 2007 Idem Idem Idem Polar  cap Idem 2004 Idem Idem Polar  cap Idem Air  temperature,  humidity,  wind  speed,  snow   temperature Air  temperature,  humidity,  wind  speed,  snow   temperature Limestones snow  field Interactions  snow  climate  and   Meteo,  snow  depth,  water  equivalent,  temperature impact  of  climate  change Gneiss snow  field Idem Air  temperature,  humidity,  wind,  rainfall  and  snowfall,   transported  snow,  radiation  budget,  sensible  heat  flux Granite/gneis Rocks  permafrost Observation  of  permafrost  in   Drillings  and  monitoring  of  the  evolution  of  the   s mountains  in  relation  with   permafrost climate  change  and   modifications  of  associated   risks   Gneiss Idem Idem Idem 2004 Idem Idem 1959 Idem Idem 1990 Idem Idem 1982 Idem Idem 2007 Idem Idem Granites Idem Idem Idem 2005 Idem Idem  Gneiss   Schistes Idem Idem Idem Idem Idem Marls-­‐ limestone Agriculture  and   moutains Understand,  model  and   Rainfall,  air  temperature,  air  humidity,  soil  temperature,   forecast  the  continental  surface   soil  water  content,  wind  direction  and  speed,  snowfall,   functionning  and  evolution   surface  energy  budget,  water  vapor,  N2O  and  CO2   from  the  ecosystem  to  the   fluxes,  vegetation,  land  use  and  practices regional  scale  using  remote   sensing  data   Idem Idem 2004 http://www.cesbio.ups-­‐ tlse.fr/fr/sud_ouest.html   http://www.cesbio.ups-­‐ tlse.fr/fr/donnees_sudouest.html#sites   2002 http://www.cesbio.ups-­‐ tlse.fr/fr/sud_med.html   http://www.cesbio.ups-­‐ tlse.fr/fr/donnees_cesbio_sudmed.html   Impact  of  global  change  on  the   CO2  fluxes,  groundwater  level,  dissolved  organic  carbon   peatland  carbon  sink,  green   in  the  peatland  and  at  the  output,  physico-­‐chemical   house  gases  (H2O,  CO2,  CH4)   properties  (pH,  conductivity,  temperature),  meteo cyles,  dynamics  of  organic   matter  in  soils 2013 http://www.sno-­‐tourbieres.cnrs.fr/   20000 Mediterranean mixed   Mediterranean   (eruptive  and   agriculture    and   sedimentary) moutains 0,08 Oceanic   mountainous Processes  that  control  the   Rainfall,  groundwater  level,  water  pressure  and   spatio-­‐temporal  variability  of   discharge,  surface  energy  balance,  inclinometry,  gravity,   water  storage  and  fluxes  in  a   GPS,  electric  resistivity karstic  aquifer Hydro-­‐geo-­‐chemistry  of  an   Rainfall,  water  level,  river  discharge,  physico-­‐chemistry   alluvial  system.  Focus  on   (temperature,  pH,  conductivity,major  and  traces  ions,   river/groundwater  interactions,   phytosanitaries,  pharmaceuticals,  stable  isotopes  of  the   transport  of  emergent   water  molecule) pollutants Water  and  matter  fluxes,   Rainfall,  meteo,  groundwater  levels,  physico-­‐chemical   chemical  reactivity,,  residence   properties  (temperature,  conductivity,  chemistry,   times  in  a  fractured  aquifer isotopes) Water  fluxes  in  a  coastal   Groundwater  levels,  ions  concentration aquifer  with  saline  intrusion mixed   Peatland (granite  and   limestone) Page 95 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 France Frasne 46.83°N 6.17°E France La  Guette 47.32°N 2.28°E France Landemarais 48.44°N 1.18°O Perennial  Observatory  of   the  Environnement 48.56°N 5.34°E 240-­‐900 All  France na na na Other  networks  (operational) OPE  (20) France ROSES  (21) France 3 Mountainous limestone Peatland Idem Meteo,  water  level  at  the  outlet,  groundwater  level,   physico-­‐chemical  properties  (pH,  conductivity,   temperature),  soil  temperature,  CO2,  CH4,  H2O  and   energy  fluxes Meteo,  water  level  at  the  outlet,  groundwater  level,   dissolved  organic  carbon  in  the  peatland  and  at  the   output,  physico-­‐chemical  properties  (pH,  conductivity,   temperature),  soil  properties,  CO2,  CH4,  H2O  and  energy   fluxes Meteo,  water  level  at  the  outlet,  groundwater  level,   physico-­‐chemical  properties  (pH,  conductivity,   temperature),  soil  properties,  CO2,  CH4,  H2O  and  energy   fluxes 2008 Idem 0,25 Oceanic sands Peatland Idem 0,16 Oceanic granite Peatland Idem Continental Limestones Agriculture  and   small  forests na na na Environnemental  monitoring  of   Atmospheric  parameters,  Greenhouse  gases  and  aerosol   2007 http://www.andra.fr/ope/index.php http://www.andra.fr/ope/index.php?option=com_datareq a  industrial  territory  in   physico-­‐chemical  properties,  ,  surface  and  groundwater   ?lang=fr   uest&Itemid=331&lang=fr   mutation physico-­‐chemical  properties,  physico-­‐chemistry  of  soils,   biodiversity Groundwater  water  level  and   Groundwater  level  and  quality 1892  :   http://www.ades.eaufrance.fr/Spip. http://www.ades.eaufrance.fr/LienLocalisation.aspx   aspx?page=spip.php?rubrique141   quality  monitoring  over  whole   groundwater   France  and  overseas  territories level,  strenghen   since  2000                         1900:   groundwater   quality 2008 Idem 2014 Idem Page 96 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 Evapotranspiration Ecology Microbiology Pedology Precipitations Vegetation Runoff Meteorology Erosion Hydrometeorology Soil HydroGroundwater geophysics Hydrology Chemical weathering Geomorphology Biogeochemistry Hydrogeology Fig. 1 Geology Page 97 of 103 Fig. 2 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 Page 98 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 Fig. 3 t Re Cp ic at ica og hol im Cl ien ad l gr Lit Ns Pa Ca M Ma MH nt ie ad gr Do AC AC RC l pica Tro clonic cy Va lts sa es sit de es ss s st hi Forested Pristine s am Peri-urban y Ca Agronomical s le ha s ne to -S es lc m d Col le Lo ha -S lc JJuu Li at per Tem ld e co Or Ca Tem Cr Mo Sc Ba VO s ite d Fo ate per M AC an Ka Aq ei n Me ea ann r ter edi PM Gn D Na Gr ical rop ry t St La Ro An Av FN Ke To Ba l pica Tro Br Yz Lo Karst 4Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 Page 99Fig. of 103 SO4 mmol/l 0.12 0.08 0.04 1986 1994 2002 2010 2018 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 Page 100 of 103 Fig. 5 Page 101 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 Fig. 6 High frequency exploration WP1 : soil-atmosphere exchanges 1.1 : microwave scintillometry Hot-spot and hot-moments WP5 : scanning the surface image drone exploration WP6 : geophysical tools of exploration WP2 : pulsation of water in the ZC 2.1 : hydrogravimetry 2.2 : hydrogeodesy 2.3 : water sensors WP3 : temperature monitoring Fiber optic for temperature and gas WP4 : high temporal monitoring 4.1 : extreme event monitoring 4.2 : the River Lab 4.3 : innovative chemical sensors 6.1 : seismic methods 6.2 : MSR 6.3 : electrical methods 6.4 : polarization 6.5 : CS-AMT WP7 : inacessible groundwaters 7.1 : well equipement 7.2 : well monitoring 7.3 : reactive and inert tracer test experiments WP8 : chemical and isotopic fingerprinting 8.1 : gas tracing 8.2 : water isotopes 8.3 : integrative sensors                                                       Profile  A                                                                  Nalohou  catchment                                                              Time  evolu4on   3   2   1 2   ___   Piezometric  level   3   Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 1   Piezometer   Neutron  Probe   Gravimeter   Raingauge   Flux  tower   Discharge   ERT  profile   TDR  moisture   Page 102 of 103 Page 103 of 103 Vadose Zone J. Accepted Paper, posted 08/30/2018. doi:10.2136/vzj2018.04.0067 Fig. 7 Dynamical architecture of the Critical Zone: (i) what are the vertical and horizontal extents of the CZ? (ii) what are the residence and exposure times of water and matter in the different compartments of the CZ? (iii) what are the CZ interfaces? (iv) what is the role of biota in structuring the CZ? Biogeochemical cycles, sediment and-or contaminant propagation through the CZ , from highlands to sea: (i) can we better quantify budgets of mass and energy across our CZ observatories? (ii) how can high frequency sampling help deciphering CZ functionning? (iii) what is the functionnal role of biota at all scales? Responses and feedbacks to biological, climatic and geological perturbations and to global environmental changes: the Earth's surface dynamical system: (i) how can we use our observatories to predict (earthcast) the future of the CZ? (ii) how do processes with short timescales and limited spatial imprint influence the evolution of the CZ on longer timescales? (iii) can we predict CZ trajectories?