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Bahaa Khalil

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Papers by Bahaa Khalil

A comparison of conventional and wavelet transform based methods for streamflow record extension

Journal of Hydrology, 2019

This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

A review: dew water collection from radiative passive collectors to recent developments of active collectors

Sustainable Water Resources Management, 2015

Dew water is water droplets formed due to condensation of atmospheric water vapor on surfaces of ... more Dew water is water droplets formed due to condensation of atmospheric water vapor on surfaces of temperature below its dew point temperature. Dew water can be seen as a nonconventional source of water and may be exploited in regions where weather conditions favor dew formation and inadequate supply and quality of water is a prevalent problem. There are two main types of dew condenser, the apparatus used to collect dew water, namely radiative (also called passive) and active condensers. Radiative passive collectors rely on exploiting the physical processes responsible for dew formation to collect dew water without any additional energy input. Previous studies indicate that a 1 m 2 radiative condenser yields between 0.3 and 0.6 L/day of dew water in arid and semi-arid regions. Active condensers have been designed as an alternative method of collection that produces higher yields by using additional energy inputs. Several designs of active condensers have been patented for which the yield can reach 20 L/day for portable devices, and up to 200,000 L/day for larger agricultural water devices. Active condensers are also known as atmospheric water generators, dehumidifiers, and air to water devices. Most of the active condensers are based on a regenerative desiccant that attracts and holds large volumes of water from the air or on a means of cooling the condensing surface below the dew point temperature (refrigeration circuit). The larger yields and wider range of environmental conditions in which dew can be collected make active condensers a promising option as an alternative or supplemental source of water in water scarce regions. The aim of this paper was to provide a comprehensive review of radiative and active condensers, including dew formation processes, methods of dew collection, and parameters that influence the dew collection. Subsequently, patents of active condensers were reviewed to ascertain how they can be integrated with different types of renewable energy and to assess the potential use of such integrated systems as a sustainable source of water in regions that suffer water scarcity and/or as a sustainable source of water for agriculture.

Controlled drainage system: desk study for surveying of sub-collectors in the Nile Delta

Development of a wavelet neural network hybrid model for Total Dissolved Solids short-term forecasting in the Nile Delta drainage system

ABSTRACT

Using the Discrete Wavelet Transform in Trend Analysis of Streamflow in Quebec and Ontario from 1954 to 2008

This paper aims to analyze trends in the average flow in Ontario and Quebec. Specifically, we aim... more This paper aims to analyze trends in the average flow in Ontario and Quebec. Specifically, we aim to discover the main periodicities in flow time series responsible for trends. To achieve this, we applied a new method of trend detection, which combines the use of the discrete wavelet transform (DWT), the Mann-Kendall (MK) trend test and sequential Mann-Kendall analysis. The DWT decomposes a time series and separates its high-frequency and lowfrequency components. The MK test/sequential MK analysis are then applied to these components in order to determine the most influential periodicities for trends. To date, co-utilizing the DWT and the MK test/sequential MK analysis in detecting trends in the hydrological field has not been done. Two criteria were used to d t i (i) th b f d iti l l (ii) th

Long-term Drought Forecasting Using Wavelet-Neural Networks and Wavelet-Support Vector Regression

Long term drought forecasts can be an effective tool for mitigating some of the more adverse cons... more Long term drought forecasts can be an effective tool for mitigating some of the more adverse consequences of drought. Data based models are suitable forecast tools due to their minimal information requirements and rapid development times. This study compares the effectiveness of five data based models for forecasting long term drought conditions in the Awash River Basin of Ethiopia. The Standard Precipitation Index (SPI) is forecast using a traditional stochastic model (ARIMA) and compared to machine learning techniques such as artificial neural networks (ANNs) and support vector regression (SVR). In addition, wavelet analysis is used since wavelet transforms have recently shown great ability in modeling and forecasting nonlinear and non-stationary time series in hydrologic forecasting studies. Wavelet transforms are used to pre-process the inputs for the ANNs and SVR models. The performances of all models were compared using RMSE, MAE, R2 and a measure of persistence. The forecast results indicate that the coupled wavelet neural network (WA-ANN) models were the best models for forecasting SPI values over long lead times in the Awash River Basin.

Statistical assessment of a water quality monitoring system using principal components and cluster analyses

JOURNAL OF ENGINEERING AND APPLIED SCIENCE-CAIRO-, 2005

Reconstruction of Information for Short-gauged Water Quality Parameters Using a Robust Version of the Line of Organic Correlation Technique

2012 Dallas, Texas, July 29 - August 1, 2012, 2012

ABSTRACT Missing data are a common problem in water quality management and operational hydrology.... more ABSTRACT Missing data are a common problem in water quality management and operational hydrology. In such situations, filling in missing observations is warranted. However, sometimes the extension of hydrological or water quality time series at short-gauged stations is required. Records can be extended in time at short-gauged stations by exploiting the correlation between the station of interest and a nearby long-gauged station. Ordinary least squares regression (OLS) is a traditional and commonly used record extension technique. However, its purpose is to generate optimal estimates of each record rather than of the population characteristics, for which OLS tends to underestimate the variance in the extended records. This leads to underestimation of high percentiles and overestimation of low percentiles, given that the data is normally distributed. The development of the line of organic correlation (LOC) technique, also known as the maintenance of variance extension technique (MOVE), is aimed at correcting this bias. The LOC is preferable when the probability distribution of the estimates, and not just an individual estimate, is of interest. Given that water resources data in general, and water quality data in particular, are characterized by the presence of outliers, positive skewness and non-normal distribution of data, a robust record extension technique is more appropriate. In this study, three record extension techniques were investigated, and their properties were explored: OLS, LOC and a new technique proposed in this paper, the robust line of organic correlation technique (RLOC). RLOC includes the advantage of the LOC in reducing the bias in estimating the variance, but at the same time it is also robust to the presence of outliers. An empirical examination of the preservation of the characteristics of the water quality parameters was carried out using water quality records from the Nile Delta drainage system monitoring network in Egypt. Ten years of monthly records of Electric Conductivity and Chloride measured at eleven locations were used in this study. A comparison between the three record extension techniques was performed to examine the extended records for bias and standard error of the estimate of statistical moments and over the full range of percentiles. The results of this study show that the proposed RLOC technique outperforms the OLS and LOC techniques by producing extended records that preserve variability as well as high and low percentiles. As such, it is recommended that the newly proposed RLOC technique be further investigated using simulated records with specific characteristics and data sets from other geographical areas.

An Evaluation of À Trous-Based Record Extension Techniques for Water Quality Record Extension

by Samah Anwar, A El Saadi, and Bahaa Khalil

Water

Hydrological data in general and water quality (WQ) data in particular frequently suffer from mis... more Hydrological data in general and water quality (WQ) data in particular frequently suffer from missing records and/or short-gauged monitoring/sampling sites. Many statistical regression techniques are employed to substitute missing values or to extend records at short-gauged sites, such as the Kendall-Theil robust line (KTRL), its modified version (KTRL2), ordinary least squares regression (OLS), four MOVE techniques, and the robust line of organic correlation (RLOC). In this study, in aspiring to achieve better accuracy and precision, the À Trous-Haar wavelet transform (WT) was adopted as a data denoising preprocessing step prior to applying record extension techniques. An empirical study was performed using real WQ data, from the National WQ monitoring network in the Nile Delta in Egypt, to evaluate the performance of these eight record-extension techniques with and without the WT data preprocessing step. Evaluations included the accuracy and precision of the techniques when used f...

An Evaluation of À Trous-Based Record Extension Techniques for Water Quality Record Extension

Water

Hydrological data in general and water quality (WQ) data in particular frequently suffer from mis... more Hydrological data in general and water quality (WQ) data in particular frequently suffer from missing records and/or short-gauged monitoring/sampling sites. Many statistical regression techniques are employed to substitute missing values or to extend records at short-gauged sites, such as the Kendall-Theil robust line (KTRL), its modified version (KTRL2), ordinary least squares regression (OLS), four MOVE techniques, and the robust line of organic correlation (RLOC). In this study, in aspiring to achieve better accuracy and precision, the À Trous-Haar wavelet transform (WT) was adopted as a data denoising preprocessing step prior to applying record extension techniques. An empirical study was performed using real WQ data, from the National WQ monitoring network in the Nile Delta in Egypt, to evaluate the performance of these eight record-extension techniques with and without the WT data preprocessing step. Evaluations included the accuracy and precision of the techniques when used f...

A nonparametric statistical approach for the estimation of water quality characteristics in ungauged streams/watersheds

Journal of Hydrology

Interactive comment on “Record extension for short-gauged water quality parameters using a newly proposed robust version of the line of organic correlation technique” by B. Khalil and J. Adamowski

I enjoyed reading this manuscript. The Authors suggest a modified version of the LOC regression (... more I enjoyed reading this manuscript. The Authors suggest a modified version of the LOC regression (I am more familiar with the acronym MOVE) as a simple analytical tool to perform data record extension preserving the variance of the extended records. I like such a type of simple but effective engineering solutions, especially when they are supported by well designed Monte Carlo experiments. As the editing details have been already recognized by the other Reviewer, I would like to add some remarks about the

Information-theoretic-based input variable selection for hydrology and water resources

The existence of useful varying parameter space for river flow forecasting

Like any time series generated by complex systems, river flows can be represented by a timevaryin... more Like any time series generated by complex systems, river flows can be represented by a timevarying parameter (TVP) model. TVP modeling frameworks often assume that the system evolution exhibits superstatistical random walks. Also, the TVPs should hone a predefined model ability to capture system&#39;s recurrence. In this work, we develop a computationally efficient method that extracts useful cyclic-type TVPs which are strongly coupled over extended, but more continuous and less aggregated, time horizons. A multi-level modeling framework is suggested to facilitate the creation and direct use of updated parameters. The modeling framework produce stable results of parameter variations at different time strings. The proposed framework can incorporate exogenous descriptors at different levels without loss of generality, and can be used in forecasting applications.

A statistical approach for the estimation of water quality characteristics of ungauged streams/watersheds under stationary conditions

Journal of Hydrology, 2018

Water quality and quantity data are essential for water resources management, but historical reco... more Water quality and quantity data are essential for water resources management, but historical records are not always available at sites where information is required, especially for water quality (WQ) data because of the high costs of implementing and operating water quality monitoring networks. This leads to the impossibility/impracticality of monitoring all water streams in a region under monitoring. A novel statistical approach is proposed for the estimation of WQ characteristics (25 th , 50 th , and 75 th percentiles) at ungauged streams. The proposed approach is based on developing a WQ causes-effects functional relationship, which has not been done before. The WQ causes are represented by the watershed physiographic (natural and anthropogenic) attributes and the effects are represented by the WQ characteristics. For a target ungauged stream: (i) a canonical correlation analysis-based-neighborhood approach was applied to identify homogeneous gauged watersheds; and (ii) nonlinear regression models were then calibrated using data available at the selected gauged watersheds to develop the causes-effects functional relationship between the physiographic attributes as predictors, and WQ characteristics as dependent variables. Once the regression models were validated, the physiographic characteristics of the target ungauged stream were used to estimate its WQ characteristics. The jack-knife validation method was applied to evaluate the proposed statistical approach using 50 gauged streams from the Nile-Delta of Egypt. Results showed accurate and precise estimation of the Electric Conductivity and Sodium percentiles. For Iron, relatively less precision was obtained due to the absence of attributes that can describe the Iron concentrations.

Sincere thanks are extended to the following colleagues for reviewing one or more manuscripts for the Journal during the period from January 1, 2012 to December 31, 2012

Canadian Water Resources Journal, 2013

Towards an independent dew water irrigation system for arid or insular areas

2014 ASABE Annual International Meeting, 2014

Abstract. Dew water refers to the atmospheric vapor that condenses during the evening or early mo... more Abstract. Dew water refers to the atmospheric vapor that condenses during the evening or early morning on exposed surfaces. In arid or insular areas, dew water collection systems have been explored as a means of providing water for human and agricultural consumption. In order to utilize dew water for irrigation, there are two possible options: using a small passive condenser that allows for the irrigation of a small number of trees, or using a large dew water irrigation system that allows for the irrigation of large areas. The main goal of this paper is to highlight the possibility of using dew water for irrigation in arid and semi-arid regions through a review of various factors that affect dew water collection, and of the possibilities in terms of the condenser type and the system design.

A Novel Record-Extension Technique for Water Quality Variables Based on L-Moments

by Bahaa Khalil and Ayman Georges

Water, Air, & Soil Pollution, 2016

Extension of hydrological or water quality records at short-gauged stations using information fro... more Extension of hydrological or water quality records at short-gauged stations using information from another long-gauged station is termed record extension. The ordinary least squares regression (OLS) is a traditional and commonly used record-extension technique. However, OLS is more appropriate for the substitution of scattered missing values than for record-extension as the OLS provides extended records with underestimated variance. Underestimation of the variance of the extended records leads to underestimation of high percentiles and overestimation of low percentiles given that the data is normally distributed. The Maintenance of Variance Extension techniques (MOVE) have the advantage of maintaining the variance in the extended records. However, the OLS and MOVE techniques are sensitive to the presence of outliers. Two new record-extension techniques with the advantage of being robust in the presence of outliers were recently proposed by the authors: the robust line of organic correlation (RLOC) and modified version of the Kendall-Theil Robust line (KTRL2). In this study a new robust technique is proposed. The new regression technique based on L-moments (LMOM) is a modified version of the RLOC and uses the same intercept as that of RLOC and KTRL2 while the estimated slope is based on the second L-moment. An empirical examination of the preservation of the water quality variable characteristics was carried out using water quality records from the Nile Delta water quality monitoring network in Egypt. A comparison between nine recordextension techniques (OLS, MOVE1 to MOVE4, KTRL, KTRL2, RLOC and LMOM) was performed to examine the extended records for bias and standard error in their statistical moment estimates and over the full range of percentiles. Results showed that the proposed LMOM technique outperforms other techniques by producing extended records that preserve variance as well as extreme percentiles.

Bootstrap rank‐ordered conditional mutual information (broCMI): A nonlinear input variable selection method for water resources modeling

Water Resources Research, 2016

The input variable selection problem has recently garnered much interest in the time series model... more The input variable selection problem has recently garnered much interest in the time series modeling community, especially within water resources applications, demonstrating that information theoretic (nonlinear)-based input variable selection algorithms such as partial mutual information (PMI) selection (PMIS) provide an improved representation of the modeled process when compared to linear alternatives such as partial correlation input selection (PCIS). PMIS is a popular algorithm for water resources modeling problems considering nonlinear input variable selection; however, this method requires the specification of two nonlinear regression models, each with parametric settings that greatly influence the selected input variables. Other attempts to develop input variable selection methods using conditional mutual information (CMI) (an analog to PMI) have been formulated under different parametric pretenses such as k nearestneighbor (KNN) statistics or kernel density estimates (KDE). In this paper, we introduce a new input variable selection method based on CMI that uses a nonparametric multivariate continuous probability estimator based on Edgeworth approximations (EA). We improve the EA method by considering the uncertainty in the input variable selection procedure by introducing a bootstrap resampling procedure that uses rank statistics to order the selected input sets; we name our proposed method bootstrap rank-ordered CMI (broCMI). We demonstrate the superior performance of broCMI when compared to CMI-based alternatives (EA, KDE, and KNN), PMIS, and PCIS input variable selection algorithms on a set of seven synthetic test problems and a real-world urban water demand (UWD) forecasting experiment in Ottawa, Canada.

Analyzing the Relationship between El-Niño Southern Oscillation and Streamflow in Ontario and Quebec Using Wavelet Transforms

2014 ASABE Annual International Meeting, 2014

ABSTRACT The impacts of El Nino Southern Oscillation (ENSO) on streamflow variability have been s... more ABSTRACT The impacts of El Nino Southern Oscillation (ENSO) on streamflow variability have been studied extensively in many different parts of the world. Due to the non-stationary nature of streamflow data, wavelet transform approaches are useful for analyzing these types of data. In the Canadian context, applying the wavelet transform approaches, especially those that involve the use of continuous wavelet transform (CWT) and wavelet coherence (WTC) to analyze the influence of ENSO on streamflow variability, is still rare. This present study assessed the influence of ENSO activity on streamflow in Ontario and Quebec. Monthly data from a total of 8 stations were used. Spearman correlation was used to determine the amount of time taken by streamflow to respond to ENSO activity. The wavelet spectra of streamflow CWT revealed significant periodicities at the 6-month and 12-month wavebands throughout the period covered by the data - this observation is consistent from one station to another. The CWT spectra of the SST data showed significant regions of up to 8 years, most of which occur after 1960. the influence of ENSO on streamflow as seen in the WTC spectra occur both up to and over 8 years. Areas of significant regions observed for periodicities of over 8 years mostly occur after 1960. Spearman correlation analyses indicate that the influence of ENSO is significant for all stations except for Sydenham River. Correlations between SST and reconstructed streamflow data also indicate that the influence of ENSO occurs both at low and high time scales.

A comparison of conventional and wavelet transform based methods for streamflow record extension

Journal of Hydrology, 2019

This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

A review: dew water collection from radiative passive collectors to recent developments of active collectors

Sustainable Water Resources Management, 2015

Dew water is water droplets formed due to condensation of atmospheric water vapor on surfaces of ... more Dew water is water droplets formed due to condensation of atmospheric water vapor on surfaces of temperature below its dew point temperature. Dew water can be seen as a nonconventional source of water and may be exploited in regions where weather conditions favor dew formation and inadequate supply and quality of water is a prevalent problem. There are two main types of dew condenser, the apparatus used to collect dew water, namely radiative (also called passive) and active condensers. Radiative passive collectors rely on exploiting the physical processes responsible for dew formation to collect dew water without any additional energy input. Previous studies indicate that a 1 m 2 radiative condenser yields between 0.3 and 0.6 L/day of dew water in arid and semi-arid regions. Active condensers have been designed as an alternative method of collection that produces higher yields by using additional energy inputs. Several designs of active condensers have been patented for which the yield can reach 20 L/day for portable devices, and up to 200,000 L/day for larger agricultural water devices. Active condensers are also known as atmospheric water generators, dehumidifiers, and air to water devices. Most of the active condensers are based on a regenerative desiccant that attracts and holds large volumes of water from the air or on a means of cooling the condensing surface below the dew point temperature (refrigeration circuit). The larger yields and wider range of environmental conditions in which dew can be collected make active condensers a promising option as an alternative or supplemental source of water in water scarce regions. The aim of this paper was to provide a comprehensive review of radiative and active condensers, including dew formation processes, methods of dew collection, and parameters that influence the dew collection. Subsequently, patents of active condensers were reviewed to ascertain how they can be integrated with different types of renewable energy and to assess the potential use of such integrated systems as a sustainable source of water in regions that suffer water scarcity and/or as a sustainable source of water for agriculture.

Controlled drainage system: desk study for surveying of sub-collectors in the Nile Delta

Development of a wavelet neural network hybrid model for Total Dissolved Solids short-term forecasting in the Nile Delta drainage system

ABSTRACT

Using the Discrete Wavelet Transform in Trend Analysis of Streamflow in Quebec and Ontario from 1954 to 2008

This paper aims to analyze trends in the average flow in Ontario and Quebec. Specifically, we aim... more This paper aims to analyze trends in the average flow in Ontario and Quebec. Specifically, we aim to discover the main periodicities in flow time series responsible for trends. To achieve this, we applied a new method of trend detection, which combines the use of the discrete wavelet transform (DWT), the Mann-Kendall (MK) trend test and sequential Mann-Kendall analysis. The DWT decomposes a time series and separates its high-frequency and lowfrequency components. The MK test/sequential MK analysis are then applied to these components in order to determine the most influential periodicities for trends. To date, co-utilizing the DWT and the MK test/sequential MK analysis in detecting trends in the hydrological field has not been done. Two criteria were used to d t i (i) th b f d iti l l (ii) th

Long-term Drought Forecasting Using Wavelet-Neural Networks and Wavelet-Support Vector Regression

Long term drought forecasts can be an effective tool for mitigating some of the more adverse cons... more Long term drought forecasts can be an effective tool for mitigating some of the more adverse consequences of drought. Data based models are suitable forecast tools due to their minimal information requirements and rapid development times. This study compares the effectiveness of five data based models for forecasting long term drought conditions in the Awash River Basin of Ethiopia. The Standard Precipitation Index (SPI) is forecast using a traditional stochastic model (ARIMA) and compared to machine learning techniques such as artificial neural networks (ANNs) and support vector regression (SVR). In addition, wavelet analysis is used since wavelet transforms have recently shown great ability in modeling and forecasting nonlinear and non-stationary time series in hydrologic forecasting studies. Wavelet transforms are used to pre-process the inputs for the ANNs and SVR models. The performances of all models were compared using RMSE, MAE, R2 and a measure of persistence. The forecast results indicate that the coupled wavelet neural network (WA-ANN) models were the best models for forecasting SPI values over long lead times in the Awash River Basin.

Statistical assessment of a water quality monitoring system using principal components and cluster analyses

JOURNAL OF ENGINEERING AND APPLIED SCIENCE-CAIRO-, 2005

Reconstruction of Information for Short-gauged Water Quality Parameters Using a Robust Version of the Line of Organic Correlation Technique

2012 Dallas, Texas, July 29 - August 1, 2012, 2012

ABSTRACT Missing data are a common problem in water quality management and operational hydrology.... more ABSTRACT Missing data are a common problem in water quality management and operational hydrology. In such situations, filling in missing observations is warranted. However, sometimes the extension of hydrological or water quality time series at short-gauged stations is required. Records can be extended in time at short-gauged stations by exploiting the correlation between the station of interest and a nearby long-gauged station. Ordinary least squares regression (OLS) is a traditional and commonly used record extension technique. However, its purpose is to generate optimal estimates of each record rather than of the population characteristics, for which OLS tends to underestimate the variance in the extended records. This leads to underestimation of high percentiles and overestimation of low percentiles, given that the data is normally distributed. The development of the line of organic correlation (LOC) technique, also known as the maintenance of variance extension technique (MOVE), is aimed at correcting this bias. The LOC is preferable when the probability distribution of the estimates, and not just an individual estimate, is of interest. Given that water resources data in general, and water quality data in particular, are characterized by the presence of outliers, positive skewness and non-normal distribution of data, a robust record extension technique is more appropriate. In this study, three record extension techniques were investigated, and their properties were explored: OLS, LOC and a new technique proposed in this paper, the robust line of organic correlation technique (RLOC). RLOC includes the advantage of the LOC in reducing the bias in estimating the variance, but at the same time it is also robust to the presence of outliers. An empirical examination of the preservation of the characteristics of the water quality parameters was carried out using water quality records from the Nile Delta drainage system monitoring network in Egypt. Ten years of monthly records of Electric Conductivity and Chloride measured at eleven locations were used in this study. A comparison between the three record extension techniques was performed to examine the extended records for bias and standard error of the estimate of statistical moments and over the full range of percentiles. The results of this study show that the proposed RLOC technique outperforms the OLS and LOC techniques by producing extended records that preserve variability as well as high and low percentiles. As such, it is recommended that the newly proposed RLOC technique be further investigated using simulated records with specific characteristics and data sets from other geographical areas.

An Evaluation of À Trous-Based Record Extension Techniques for Water Quality Record Extension

by Samah Anwar, A El Saadi, and Bahaa Khalil

Water

Hydrological data in general and water quality (WQ) data in particular frequently suffer from mis... more Hydrological data in general and water quality (WQ) data in particular frequently suffer from missing records and/or short-gauged monitoring/sampling sites. Many statistical regression techniques are employed to substitute missing values or to extend records at short-gauged sites, such as the Kendall-Theil robust line (KTRL), its modified version (KTRL2), ordinary least squares regression (OLS), four MOVE techniques, and the robust line of organic correlation (RLOC). In this study, in aspiring to achieve better accuracy and precision, the À Trous-Haar wavelet transform (WT) was adopted as a data denoising preprocessing step prior to applying record extension techniques. An empirical study was performed using real WQ data, from the National WQ monitoring network in the Nile Delta in Egypt, to evaluate the performance of these eight record-extension techniques with and without the WT data preprocessing step. Evaluations included the accuracy and precision of the techniques when used f...

An Evaluation of À Trous-Based Record Extension Techniques for Water Quality Record Extension

Water

Hydrological data in general and water quality (WQ) data in particular frequently suffer from mis... more Hydrological data in general and water quality (WQ) data in particular frequently suffer from missing records and/or short-gauged monitoring/sampling sites. Many statistical regression techniques are employed to substitute missing values or to extend records at short-gauged sites, such as the Kendall-Theil robust line (KTRL), its modified version (KTRL2), ordinary least squares regression (OLS), four MOVE techniques, and the robust line of organic correlation (RLOC). In this study, in aspiring to achieve better accuracy and precision, the À Trous-Haar wavelet transform (WT) was adopted as a data denoising preprocessing step prior to applying record extension techniques. An empirical study was performed using real WQ data, from the National WQ monitoring network in the Nile Delta in Egypt, to evaluate the performance of these eight record-extension techniques with and without the WT data preprocessing step. Evaluations included the accuracy and precision of the techniques when used f...

A nonparametric statistical approach for the estimation of water quality characteristics in ungauged streams/watersheds

Journal of Hydrology

Interactive comment on “Record extension for short-gauged water quality parameters using a newly proposed robust version of the line of organic correlation technique” by B. Khalil and J. Adamowski

I enjoyed reading this manuscript. The Authors suggest a modified version of the LOC regression (... more I enjoyed reading this manuscript. The Authors suggest a modified version of the LOC regression (I am more familiar with the acronym MOVE) as a simple analytical tool to perform data record extension preserving the variance of the extended records. I like such a type of simple but effective engineering solutions, especially when they are supported by well designed Monte Carlo experiments. As the editing details have been already recognized by the other Reviewer, I would like to add some remarks about the

Information-theoretic-based input variable selection for hydrology and water resources

The existence of useful varying parameter space for river flow forecasting

Like any time series generated by complex systems, river flows can be represented by a timevaryin... more Like any time series generated by complex systems, river flows can be represented by a timevarying parameter (TVP) model. TVP modeling frameworks often assume that the system evolution exhibits superstatistical random walks. Also, the TVPs should hone a predefined model ability to capture system&#39;s recurrence. In this work, we develop a computationally efficient method that extracts useful cyclic-type TVPs which are strongly coupled over extended, but more continuous and less aggregated, time horizons. A multi-level modeling framework is suggested to facilitate the creation and direct use of updated parameters. The modeling framework produce stable results of parameter variations at different time strings. The proposed framework can incorporate exogenous descriptors at different levels without loss of generality, and can be used in forecasting applications.

A statistical approach for the estimation of water quality characteristics of ungauged streams/watersheds under stationary conditions

Journal of Hydrology, 2018

Water quality and quantity data are essential for water resources management, but historical reco... more Water quality and quantity data are essential for water resources management, but historical records are not always available at sites where information is required, especially for water quality (WQ) data because of the high costs of implementing and operating water quality monitoring networks. This leads to the impossibility/impracticality of monitoring all water streams in a region under monitoring. A novel statistical approach is proposed for the estimation of WQ characteristics (25 th , 50 th , and 75 th percentiles) at ungauged streams. The proposed approach is based on developing a WQ causes-effects functional relationship, which has not been done before. The WQ causes are represented by the watershed physiographic (natural and anthropogenic) attributes and the effects are represented by the WQ characteristics. For a target ungauged stream: (i) a canonical correlation analysis-based-neighborhood approach was applied to identify homogeneous gauged watersheds; and (ii) nonlinear regression models were then calibrated using data available at the selected gauged watersheds to develop the causes-effects functional relationship between the physiographic attributes as predictors, and WQ characteristics as dependent variables. Once the regression models were validated, the physiographic characteristics of the target ungauged stream were used to estimate its WQ characteristics. The jack-knife validation method was applied to evaluate the proposed statistical approach using 50 gauged streams from the Nile-Delta of Egypt. Results showed accurate and precise estimation of the Electric Conductivity and Sodium percentiles. For Iron, relatively less precision was obtained due to the absence of attributes that can describe the Iron concentrations.

Sincere thanks are extended to the following colleagues for reviewing one or more manuscripts for the Journal during the period from January 1, 2012 to December 31, 2012

Canadian Water Resources Journal, 2013

Towards an independent dew water irrigation system for arid or insular areas

2014 ASABE Annual International Meeting, 2014

Abstract. Dew water refers to the atmospheric vapor that condenses during the evening or early mo... more Abstract. Dew water refers to the atmospheric vapor that condenses during the evening or early morning on exposed surfaces. In arid or insular areas, dew water collection systems have been explored as a means of providing water for human and agricultural consumption. In order to utilize dew water for irrigation, there are two possible options: using a small passive condenser that allows for the irrigation of a small number of trees, or using a large dew water irrigation system that allows for the irrigation of large areas. The main goal of this paper is to highlight the possibility of using dew water for irrigation in arid and semi-arid regions through a review of various factors that affect dew water collection, and of the possibilities in terms of the condenser type and the system design.

A Novel Record-Extension Technique for Water Quality Variables Based on L-Moments

by Bahaa Khalil and Ayman Georges

Water, Air, & Soil Pollution, 2016

Extension of hydrological or water quality records at short-gauged stations using information fro... more Extension of hydrological or water quality records at short-gauged stations using information from another long-gauged station is termed record extension. The ordinary least squares regression (OLS) is a traditional and commonly used record-extension technique. However, OLS is more appropriate for the substitution of scattered missing values than for record-extension as the OLS provides extended records with underestimated variance. Underestimation of the variance of the extended records leads to underestimation of high percentiles and overestimation of low percentiles given that the data is normally distributed. The Maintenance of Variance Extension techniques (MOVE) have the advantage of maintaining the variance in the extended records. However, the OLS and MOVE techniques are sensitive to the presence of outliers. Two new record-extension techniques with the advantage of being robust in the presence of outliers were recently proposed by the authors: the robust line of organic correlation (RLOC) and modified version of the Kendall-Theil Robust line (KTRL2). In this study a new robust technique is proposed. The new regression technique based on L-moments (LMOM) is a modified version of the RLOC and uses the same intercept as that of RLOC and KTRL2 while the estimated slope is based on the second L-moment. An empirical examination of the preservation of the water quality variable characteristics was carried out using water quality records from the Nile Delta water quality monitoring network in Egypt. A comparison between nine recordextension techniques (OLS, MOVE1 to MOVE4, KTRL, KTRL2, RLOC and LMOM) was performed to examine the extended records for bias and standard error in their statistical moment estimates and over the full range of percentiles. Results showed that the proposed LMOM technique outperforms other techniques by producing extended records that preserve variance as well as extreme percentiles.

Bootstrap rank‐ordered conditional mutual information (broCMI): A nonlinear input variable selection method for water resources modeling

Water Resources Research, 2016

The input variable selection problem has recently garnered much interest in the time series model... more The input variable selection problem has recently garnered much interest in the time series modeling community, especially within water resources applications, demonstrating that information theoretic (nonlinear)-based input variable selection algorithms such as partial mutual information (PMI) selection (PMIS) provide an improved representation of the modeled process when compared to linear alternatives such as partial correlation input selection (PCIS). PMIS is a popular algorithm for water resources modeling problems considering nonlinear input variable selection; however, this method requires the specification of two nonlinear regression models, each with parametric settings that greatly influence the selected input variables. Other attempts to develop input variable selection methods using conditional mutual information (CMI) (an analog to PMI) have been formulated under different parametric pretenses such as k nearestneighbor (KNN) statistics or kernel density estimates (KDE). In this paper, we introduce a new input variable selection method based on CMI that uses a nonparametric multivariate continuous probability estimator based on Edgeworth approximations (EA). We improve the EA method by considering the uncertainty in the input variable selection procedure by introducing a bootstrap resampling procedure that uses rank statistics to order the selected input sets; we name our proposed method bootstrap rank-ordered CMI (broCMI). We demonstrate the superior performance of broCMI when compared to CMI-based alternatives (EA, KDE, and KNN), PMIS, and PCIS input variable selection algorithms on a set of seven synthetic test problems and a real-world urban water demand (UWD) forecasting experiment in Ottawa, Canada.

Analyzing the Relationship between El-Niño Southern Oscillation and Streamflow in Ontario and Quebec Using Wavelet Transforms

2014 ASABE Annual International Meeting, 2014

ABSTRACT The impacts of El Nino Southern Oscillation (ENSO) on streamflow variability have been s... more ABSTRACT The impacts of El Nino Southern Oscillation (ENSO) on streamflow variability have been studied extensively in many different parts of the world. Due to the non-stationary nature of streamflow data, wavelet transform approaches are useful for analyzing these types of data. In the Canadian context, applying the wavelet transform approaches, especially those that involve the use of continuous wavelet transform (CWT) and wavelet coherence (WTC) to analyze the influence of ENSO on streamflow variability, is still rare. This present study assessed the influence of ENSO activity on streamflow in Ontario and Quebec. Monthly data from a total of 8 stations were used. Spearman correlation was used to determine the amount of time taken by streamflow to respond to ENSO activity. The wavelet spectra of streamflow CWT revealed significant periodicities at the 6-month and 12-month wavebands throughout the period covered by the data - this observation is consistent from one station to another. The CWT spectra of the SST data showed significant regions of up to 8 years, most of which occur after 1960. the influence of ENSO on streamflow as seen in the WTC spectra occur both up to and over 8 years. Areas of significant regions observed for periodicities of over 8 years mostly occur after 1960. Spearman correlation analyses indicate that the influence of ENSO is significant for all stations except for Sydenham River. Correlations between SST and reconstructed streamflow data also indicate that the influence of ENSO occurs both at low and high time scales.