RUSLE

The purpose of this study is to estimate soil losses at the Mikkes watershed upstream of the Sidi Chahed dam in the Meknes region (Morocco), using the revised universal equation of losses in soil of (Walter H Wischmeier et Smith, 1978). The spatial empiric model was based on the integration of the five factors in the Geographical Information System (GIS), namely, the erosivity of rains "R", the erodibility of soils "K", the vegetation cover "C", topography "LS" and anti-erosion practices "P", the superposition of which allowed the development of a quantitative map of soil losses at the scale of the watershed. The catchment area of Oued Mikkes covers an area of 1444 km2; it is of elongated shape with an altitude ranging from 2090 meters to 184 meters from the South to the North, and a slope which varies from 0 to 189%. The rainfall survey of the eleven climatic stations located at the catchment level has shown the irregularity of precipitation in time and space. The erosivity factor R showed values ranging from 60 to 119, with an average of 85 Mj.mm/ha.h.a ". Erodibility factor K showed values from 0 to 0.6 and showed that poor soils and vertisols are the most vulnerable to erosion. The LS topography factor varies between 0 and 2562, the upstream of which is more rugged and more sensitive. The C factor differs according to the land use, from which the soils of the rangelands, the uncultivated and the cultivated soils are the most fragile. Water erosion affects all parts of the watershed, but with varying degrees depending on the factors of erosion. Land below the tolerance level of 7 t / ha / year represents only 11% of the catchment area, those with losses varying between 7 and 20 t / ha / year occupy 53%, the erosion factor in 24% of the area has values between 20 and 40 t / ha / year and those exceeding 40 t / ha / year affect about 12% of the territory.

Bu çalışmanın amacı, Coğrafi Bilgi Sistemleri (CBS) tabanlı Düzenlenmiş
Evrensel Toprak Kaybı Denklemi (RUSLE) kullanılarak Gelibolu Yarımadası’nda
erozyon risk sahalarının ve yıllık ortalama toprak kayıp miktarının belirlenmesi ve
haritalanmasıdır. Bu amaç kapsamında önce sahanın genel coğrafi özellikleri ve
erozyon risk potansiyeli açıklanmıştır. Daha sonra çeşitli kaynaklardan elde edilen
veriler, erozyona etkileri ölçüsünde sınıflandırılmış ardından CBS ortamına
aktarılmış ve 10x10 metre çözünürlüğünde raster haritalara dönüştürülmüştür.
Daha sonra Raster Calculator kullanılarak RUSLE denklemi uygulanmış ve
Gelibolu Yarımadası’nın erozyon risk sınıfları haritası ve yıllık ortalama toprak
kayıp miktarı elde edilmiştir. Çalışmada ulaşılan bulgu ve sonuçlar, arazi
çalışmaları ile yerinde kontrol edilmiştir.
Altı risk sınıfının belirlendiği Gelibolu Yarımadası’nın büyük bir kısmının
(%75,8’i) çok hafif erozyon riski altında olduğu tespit edilmiştir. Sahanın % 86,2
sinde toprak kayıp miktarı 0 - 12 ton/ha/yıl arasında ve % 13,8 inde toprak kayıp
miktarı ise 12 - > ton/ha/yıl arasında olduğu görülmüştür. Gelibolu Yarımadası’nda
yaşanan yıllık ortalama toprak kaybı ise 4.79 ton/ha/yıl olarak hesaplanmıştır. Bu
değer, Türkiye ortalaması (6.14 ton/ha/yıl) ve farklı bölgelere ait çalışmaların
sonuçları ile karşılaştırılmıştır.
Erozyon riskinin yüksek olduğu lokasyonlarda eğimin kısmen yüksek, bitki
örtüsünün zayıf, vadi yoğunluğunun fazla ve toprağın hızlı aşınabilir özellikte
(ince karakterde) olduğu tespit edilmiştir. Erozyon riskinin düşük olduğu yerlerin
ise ormanlık sahalar ve ova tabanları olduğu görülmüştür. Ayrıca 34 yıllık süreçte
(1981-2015) yarımadada çok hafif, hafif ve orta erozyon risk sınıflarında artış;
güçlü, şiddetli ve çok şiddetli erozyon risk sınıflarında ise azalış şeklinde bir
değişim yaşandığı tespit edilmiştir. Bununla birlikte sahada meydana gelen
erozyonu azaltmak için bazı tedbirler alınması gerektiği belirtilmiştir.

Soil erosion due to running water has dramatic consequences because it removes nutrients and organic matter from the soil and besides it loads with high amounts of sediments the hydrographic network. The last one affects directly downstream communities that use this recourse. According to FAO (1993), almost 19% of the territory of Chubut Province is currently affected by severe water and wind erosion.
In this study the RUSLE model was applied to assess the soil erosion due to rain and runoff. Predictions were compared against measurements carried on in a small endorheic basin placed in Northeast Chubut Province. Detailed measurements were available comprising runoff, precipitation, soil loss in 18 land units (6 m2 each one). The record period extended 3 years (Rostagno et al. 1999). Erosion rate was acceptably predicted by the model, i.e., it was of the same magnitude. The rain-runoff factor (R) underestimated measurements when the 30 min maximum rain intensity was used. Instead, better predictions were found when the 10min maximum rain intensity was used. William’s (1975) parameter, that considers erosion due to runoff exclusively, produced good results too.

A comprehensive methodology that integrates Revised Universal Soil Loss Equation (RUSLE) model and Geographic Information System (GIS) techniques were adopted to determine the soil erosion vulnerability of a forested mountainous sub-watershed in Kerala, India. The spatial pattern of annual soil erosion rate was obtained by integrating geo-environmental variables in a raster-based GIS method. GIS data layers including, rainfall erosivity (R), soil erodability (K), slope length and steepness (LS), cover management (C) and conservation practice (P) factors were computed to determine their effects on average annual soil loss in the area. The resultant map of annual soil erosion shows a maximum soil loss of 282.2 t/h/yr with a close relation to grassland areas, degraded forests and deciduous forests on the steep side-slopes. The spatial erosion maps generated with RUSLE method and GIS can serve as effective inputs in deriving strategies for land planning and management in the environmentally sensitive mountainous areas.

Soil erosion is a serious environmental problem in Kothagiri Taluk. Many studies have been carried out to map shifting
cultivation and areas susceptible to soil erosion. Mostly, estimated soil loss is taken as the basis to classify the level of soil loss susceptibility of area.

Revised Universal Soil Loss Equation (RUSLE) to predict the annual average soil loss rate from the Kottangudi watershed and to use the output data to the SDR model for sediment yield calculation. To achieve the goals of the thesis, the RUSLE factors were calculated. The soil survey data were used to develop the soil erodibility factor (K), and a digital elevation model of the catchment was used to generate the topographic factor (LS). The values of cover-management (C) factor and support practice (P) factor were collected from literature due to lack of satellite image and soil map. Usually C and P factors determine from land cover and land use classes respectively. The rainfall-runoff erosivity (R) was derived from monthly rainfall data and yearly rainfall along with the drainage data.

In this paper, we attempted to review the soil erosion studies conducted throughout the globe using Revised Universal Soil Loss Equation (RUSLE). We searched the SCI, Scopus, Web of Science, Google Scholar database and various theses for this study. Though RUSLE is the most widely used model for estimation of soil erosion, the factors, namely rainfall erosivity, soil erodibility, slope length and steepness, cover management and conservation practice; vary greatly over different climatic zones, soil properties, slope, land cover and crop phase, respectively. Depending upon those variations, researchers have developed various sets of equation for different factors of RUSLE. These equations can be useful to map soil loss for many places on this planet.

Occurrence of soil erosion will lead to sedimentation and siltation of reservoirs in case of major rivers. Remote sensing data provide compact information to evaluate the sedimentation yield in the reservoirs by deriving several surface parameters. SAGA (System for Automated Geo-Scientific Analysis) GIS software with version 6.3.2 used and was used for preparation of maps and to verify the spatial extent of the area. The value of soil loss can be determined by using predictive model known as RUSLE (Revised Universal Soil Loss Equation) model approaches. The study area selected for present study is watershed no-63 of Narmada river lying in Narmada river watershed situated in two different districts , one of them is Narmada district located in Gujarat and Nan durbar district located in Maharashtra. Integration of results obtained from satellite data show Watershed no: 63 comes under very high soil erosion class i.e.33.12 Ton/ha/year (By RUSLE approach) indicating a moderate to steep slope exist in such area and sustainable moderate land use practices in that particular catchment.

The greatest obstacle to soil erosion modelling at larger spatial scales is the lack of data on soil characteristics.
One key parameter for modelling soil erosion is the soil erodibility, expressed as the K-factor in the widely
used soil erosion model, the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). The K-factor,
which expresses the susceptibility of a soil to erode, is related to soil properties such as organic matter content,
soil texture, soil structure and permeability. With the Land Use/Cover Area frame Survey (LUCAS) soil survey
in 2009 a pan-European soil dataset is available for the first time, consisting of around 20,000 points across 25
Member States of the European Union. The aim of this study is the generation of a harmonised high-resolution
soil erodibility map (with a grid cell size of 500 m) for the 25 EU Member States. Soil erodibility was calculated
for the LUCAS survey points using the nomograph of Wischmeier and Smith (1978). A Cubist regression
model was applied to correlate spatial data such as latitude, longitude, remotely sensed and terrain features
in order to develop a high-resolution soil erodibility map. The mean K-factor for Europe was estimated
at 0.032 t ha h ha−1 MJ−1 mm−1 with a standard deviation of 0.009 t ha h ha−1 MJ−1 mm−1. The yielded soil
erodibility dataset compared well with the published local and regional soil erodibility data. However, the incorporation
of the protective effect of surface stone cover, which is usually not considered for the soil erodibility
calculations, resulted in an average 15% decrease of the K-factor. The exclusion of this effect in K-factor calculations
is likely to result in an overestimation of soil erosion, particularly for the Mediterranean countries, where
highest percentages of surface stone cover were observed.

Soil erosion in caused by five factors: rainfall erosivity, soil erodibility, slope and slope length, crop management, and land conservation practices. In theory, vegetation as one of the affecting factors has inversed correlation with soil erosion. This research is aimed to: (1) model RUSLE using pixel-based GIS, and (2) prove whether or not vegetation really has the said correlation with the soil erosion that occurs in Gesing Watershed. The method used in this research is divided into two: the use of RUSLE to estimate the soil erosion rate; and the use of fractional vegetation cover (FVC) formula to estimate the vegetation density in the area. Both methods used Landsat-8 OLI imagery, which is used to extract the RUSLE parameters as well as to derive the vegetation density through NDVI, and pixel-based GIS. The mapping of soil erosion rate distribution done in this research demonstrated that pixel-based modeling is able to represent a much more detailed and logical distribution of a phenomenon. The distribution of soil erosion rate in Gesing Watershed showed that the erosion rate in this area is relatively minor. About 1425.99 hectares and 1587.57 hectares of the total area have erosion rate of 0 –15 tons/ha/yr (very mild) and 15 – 60 tons/ha/yr (mild) respectively.

Al-Sen watershed with a surface area of 98.8 km2 is forming an important vital spatial sector for Syrian Coast Basin in the western part of Syria. Soil loss in Al-Sen basin is one of the major growing eco-environmental risks that need to be assessed geographically. Statistical-Spatial evaluation of soil erosion risks is a useful and urgent step for creating soil erosion management plans along with spatial implementation. At present study, a quantitative
assessment of soil erosion on grid basis is carried out using GIS and SPSS technologies. The outcomes illustrate that 43.01% of the study area affected by low erosion of soil, 29.05% moderate erosion, 16.33% high erosion, and 11.85% very high erosion, respectively. Moreover, the major factor accelerating soil loss in the study basin was LS factor of RUSLE (r2=0.74). This study, however, has also suggested two statistical models of the soil erosion case in an Al-Sen basin. The results of this study are very important for local decision-makers in establishing spatial conservation strategies.

Con el propósito de generar información que contribuya a resolver incertidumbres que se plantean durante procesos de gestión ambiental orientados al desarrollo agropecuario, nos propusimos estimar la erosión hídrica potencial o de referencia (Er) para establecer niveles de riesgo de pérdida de suelo y generar un sistema de información geográfica (SIG). Se considera que la información generada y el modo de consulta propuesto, son requerimientos que auxiliarán la elaboración y ejecución de programas para la preservación y conservación del medio ambiente.
La Er se calculó resolviendo la ecuación universal de pérdida de suelo revisada (RUSLE), para lo cual, en el contexto de la metodología SIG, se empleó la técnica procedimental “Sediment Assessment Tool for Effective Erosion Control” (SATEEC). Los niveles de riesgo de pérdida de suelo fueron definidos relacionando tasas de Er con tasas de tolerancia de pérdida de suelo; y entre otros resultados se cuantificó que en el 79,58% de la superficie del territorio cabe esperar que las pérdidas de suelo por Er sean de menor cuantía que estándares considerados admisibles. El riesgo de pérdida de suelo por Er es bajo o moderadamente bajo en el 14,37% de la superficie evaluada, y tan sólo en el 3,00% del área la Er se asocia con niveles de riesgo de pérdida de suelo que califican como alto, muy alto o crítico. También puede enunciarse que la erosión hídrica en la mayoría de los paisajes en el territorio relevado no es una variable relevante de valorar cuando se evalúa el riesgo de ocasionar daño al medio ambiente debido a la actividad agropecuaria; sin embargo existen tierras ubicadas en paisajes distribuidos en los partidos de Tandil, Balcarce, General Pueyrredón, Lobería, Benito Juárez, General Alvarado, Necochea y Olavarría, donde las tasas de Er se asocian con niveles de pérdida de suelo muy superiores a los considerados admisibles. Sobre la base de la información que genera el procedimiento SATEEC puede afirmarse que el grado de inclinación de las pendientes y la escasa tolerancia de los suelos a pérdidas de material por erosión hídrica, son factores determinantes para que unidades con niveles de riesgo de pérdida de suelo alto, muy alto o crítico se emplacen en sectores serranos y periserranos; característica que distingue a dichos sitios geográficos a pesar que los índices de erodibilidad en las capas superficiales de sus tierras están entre los de menor cuantía de la región.

"A soil erosion risk map was developed for Yulin, North Shaanxi province, China, using the revised universal soil loss equation (RUSLE) and geoinformation technolog, i. e. remote sensing (RS) , geographical information system (GIS) and global positioning system (GPS). Spatially modeling soil erosion in the GIS required generating representative raster layers based on secondary data for the following pararneters; rainfall erosivity, slope length,/gradient, soil erodibility and conservation practices. Landsat TM imagery for the year 1999 was utilized to produce land use/cover maps of the study area based on the maximum likelihood classification method. These maps were then used to generate the conservation practice factor in the RUSLE.
The analysis was performed using IDRISI32, a raster based GIS software, which is used to interactively calculate soil loss and map erosion risk. Results showed that 2 202.7 km'? has very slight soil erosion, and I 004.4 km' has slight soil erosion. This study demonstrates the effectiveness of geoinformation technology
for generating soil risk maps. "

Resumo: Processos erosivos são eventos naturais, porém podem ser acelerados pelo uso incorreto do solo na produção agrícola. Nessa perspectiva, a utilização de modelos preditivos e georreferenciados para quantificar e classificar a suscetibilidade erosiva vem se tornando uma importante ferramenta na compreensão dos processos e, consequentemente, no planejamento do uso adequado dos solos. A região norte paranaense é caracterizada pela grande predisposição ao cultivo de lavouras temporárias, destacando-se o município de Bela Vista do Paraíso que apresenta como substratos geológicos predominantes rochas eruptivas basálticas, pertencentes à Formação Serra Geral (JKsg) e rochas areníticas da Formação Adamantina (Ka), sendo estas a gênese de material para os solos encontrados no município. Desta forma a presente tese demonstra em três estudos, onde a erosividade dos solos de diferentes litologias é avaliada, a utilização do NDVI (Índice de Vegetação por Diferença Normalizada) mensal e posterior conversão para o fator Cr e a utilização do modelo preditivo da Equação Universal de Perda de Solos Revisada (RUSLE – Revised Universal Soil Loss Equation), em análises mensais, para a estimativa de perda e degradação dos solos na área de estudo. No primeiro estudo estimou-se o fator de erodibilidade dos solos (fator K) a partir da metodologia de Boyoucos (1935), identificando que solos formados em rochas areníticas se encontram em classes alta a muito alta de erodibilidade, enquanto os formados em rochas basálticas têm valores menores devido ao incremento substancial de argila nos horizontes superficiais. Também se constatou que a metodologia poderia apresentar uma subestimação dos valores, acarretando uma análise inconsistente das classes de erodibilidade. No segundo estudo objetivou-se estabelecer as classes de uso e manejo dos solos e práticas conservacionistas de caráter mensal, utilizando-se o cálculo NDVI, proposto por Rouse et al. (1973), com imagens do satélite Sentinel-2. Posteriormente, houve uma conversão para o fator Cr, proposto por Durigon et al. (2014), para que não apresentassem valores negativos e apontassem valores mais próximos da realidade da cobertura vegetal da região dos trópicos. Foram identificadas três fases distintas quanto aos seus usos: sendo uma fase de pousio, em que o solo se encontra com baixo índice de cobertura vegetal ou até mesmo nula; uma fase intermediária, com propriedades já em cultivo e outras ainda em pousio; e uma fase de cultivo intensivo das lavouras temporárias, demonstrando, assim, que a técnica responde positivamente para a análise do calendário agrícola. Como última etapa da presente tese, para consecução da RUSLE mensal para o município, empregou-se o plugin GISus-M, no software ArcGIS. Nesta etapa, o fator Cr foi utilizado para ponderar os fatores C e P, contribuindo assim para a compreensão do modelo com as três fases distintas de usos, além de indicar a associação do fator LS com a erodibilidade dos solos. Sendo que no mês de janeiro de 2018 apresentou a maior perda de solos com 194,201 ton/ha/mês, porém em uma área de somente 0,022 km² e o menor valor de perda ocorreu no mês de agosto de 2018 com o valor de 36,081 ton/ha/mês. Com isso, o trabalho demonstrou-se relevante para a compreensão da dinâmica das lavouras temporárias para a modelagem preditiva da RUSLE, além de que a utilização do NDVI auxiliou no mapeamento de forma ágil com respostas precisas em um período mais curto de análise.

Abstract: Erosive processes are natural events, but they can be accelerated by incorrect use of the soil in agricultural production. From this perspective, the use of predictive and georeferenced models to quantify and classify erosive susceptibility has become an important tool in understanding the processes and, consequently, in planning the proper use of land. The northern region of Paraná is characterized by the great predisposition to the cultivation of temporary crops, highlighting the municipality of Bela Vista do Paraíso, which presents as predominant geological substrates basaltic eruptive rocks, belonging to the Serra Geral Formation (JKsg) and sandstone rocks from the Adamantina Formation (Ka), these being the genesis of material for the soils found in the municipality. Thus, this thesis demonstrates in three studies, where the erosivity of soils from different lithologies is evaluated, the use of the monthly NDVI (Normalized Difference Vegetation Index) and subsequent conversion to the Cr factor and the use of the predictive model of the Universal Equation of Revised Universal Soil Loss Equation (RUSLE), in monthly analyses, to estimate the loss and degradation of soils in the study area. In the first study, the soil erodibility factor (K factor) was estimated using the methodology of Boyoucos (1935), identifying that soils formed in sandstone rocks are in high to very high erodibility classes, while those formed in basaltic rocks have lower values due to the substantial increment of clay in the superficial horizons. It was also found that the methodology could present an underestimation of values, leading to an inconsistent analysis of the erodibility classes. The second study aimed to establish the classes of use and management of soils and monthly conservation practices, using the NDVI calculation, proposed by Rouse et al. (1973), with images from the Sentinel-2 satellite. Subsequently, there was a conversion to the Cr factor, proposed by Durigon et al. (2014), so that they did not present negative values and pointed out values closer to the reality of vegetation cover in the region of the tropics. Three distinct phases were identified regarding their uses: being a fallow phase, in which the soil has a low level of vegetation cover or even zero; an intermediate phase, with properties already under cultivation and others still fallow; and a phase of intensive cultivation of temporary crops, thus demonstrating that the technique responds positively to the analysis of the agricultural calendar. As the last step of this thesis, to achieve the monthly RUSLE for the city, the GISus-M plugin was used, in ArcGIS software. At this stage, the Cr factor was used to weight the C and P factors, thus contributing to the understanding of the model with the three distinct phases of uses, in addition to indicating the association of the LS factor with soil erodibility. In January 2018 it had the greatest loss of soil with 194,201 ton/ha/month, but in an area of only 0.022 km² and the lowest loss value occurred in August 2018 with the value of 36.081 ton/ ha/month. Thus, the work proved to be relevant for understanding the dynamics of temporary crops for predictive modeling of RUSLE, in addition to the use of NDVI assisted in mapping quickly with accurate responses in a shorter period of analysis.

Erosi merupakan suatu fenomena alam yang kejadiannya dapat memberikan dampak negatif terhadap kemampuan lahan, khususnya apabila prosesnya dipercepat. Berbagai faktor mampu memberikan kontribusi terhadap laju erosi yang terjadi di dalam suatu wilayah, dan salah satunya adalah vegetasi. Di antara berbagai faktor yang dipertimbangkan dalam model estimasi erosi atau kehilangan tanah, penutupan vegetasi dapat dikalkulasi dari atribut jenis penutupan lahan melalui tabel konversi. Penelitian ini mencoba mengkaji hubungan antara nilai laju erosi dengan kerapatan vegetasi yang tidak diperoleh melalui pendekatan jenis penutup lahan, melainkan diperoleh dari hasil korelasi antara indeks vegetasi dengan pengukuran kerapatan di lapangan di Sub-DAS Gesing, Kabupaten Purworejo. Untuk memperoleh gambaran yang lebih rinci, model estimasi berbasis RUSLE (Revised Universal Soil Loss Equation) dan model estimasi kerapatan vegetasi dijalankan dengan model berbasis raster. Pada model RUSLE ini: (a) faktor erosivitas diperoleh melalui interpolasi spasial data hujan per bulan yang dikumpulkan dari 10 statisun hujan, (b) faktor panjang dan kemiringan lereng diekstrak dengan bantuan model flow accumulation, (c) faktor erodibilitas tanah diperoleh dari 35 sampel di lapangan yang kemudian diinterpolasi spasial dengan metode Kriging, dan (d) faktor pengelolaan tanaman (C) diperoleh melalui analisis regresi antara NDVI dengan C asumtif. Di sisi lain, untuk pemetaan kerapatan vegetasi, digunakan FVC (Fractional Vegetation cover), yang rumusnya adalah (NDVI – NDVI min)/(NDVI max – NDVI min). Hasil akhir dari penelitian ini memperkuat teori bahwa laju erosi di daerah penelitian bervariasi tidak hanya tergantung pada kerapatan vegetasi. KATA KUNCI: RUSLE, FVC, erosi, kerapatan vegetasi 1. PENDAHULUAN Erosi merupakan salah satu permasalahan lingkungan yang harus ditanggulangi. Fenomena alam ini menjadi penyebab utama terbentuknya lahan kritis, terutama jika didukung oleh tingginya intensitas dan jumlah curah hujan (Abdurachman dan Sutono, 2002, dalam Sulistyo, 2011). Erosi yang terjadi di dalam DAS pada dasarnya dipengaruhi oleh empat faktor: iklim, sifat tanah, topografi, dan vegetasi penutup lahan (Blanco dan Lal, 2008). Berkaitan dengan pengaruh vegetasi terhadap laju erosi, Morrow et al (2014) menjabarkan secara singkat pengaruh vegetasi terhadap erosi. Faktor kanopi berhubungan dengan kemampuan vegetasi dalam mengintersepsi air hujan yang mampu mengurangi energi penyebab terjadinya erosi percik (raindrop erosion atau splash erosion). Limpasan permukaan dapat menyebabkan erosi lembar (sheet erosion) dan dapat dihambat dengan adanya tutupan permukaan tanah seperti vegetasi rerumputan, sersah dedaunan, dan residu vegetasi lain. Faktor akar tanaman memberikan pengaruh pada tingkat infiltrasi air hujan, dimana air hujan yang jatuh akan masuk ke dalam pori-pori tanah yang disediakan oleh akar tanaman. Akar tanaman saling terjalin (interweave) dengan tanah sehingga membentuk massa yang lebih solid dan lebih tahan terhadap erosi (Styczen dan Morgan, 1995). Oleh karena inilah tutupan vegetasi sangat berpengaruh besar terhadap laju erosi yang terjadi di dalam suatu DAS. Penelitian ini bertujuan untuk melihat hubungan antara laju erosi, yang diperoleh dari kalkukasi RUSLE, dengan kerapatan vegetasi yang diekstraksi dari FVC. 2. DAERAH KAJIAN Penelitian ini dilakukan di Sub-DAS Gesing, yang terletak di Kabupaten Purworejo bagian timur. DAS Gesing memiliki luas sebesar 47,09 km 2 , dan sebagian besar areanya terletak di Perbukitan Menoreh

Soil erosion by water is considered as one of the most significant forms of land degradation that affects sustained productivity of agricultural land use and water quality. It is influenced by a considerable number of factors (including climate, soil, topography, land use and types of land management), so that the information on the spatial distribution of soil erosion rate and its related effects can be effectively employed as a baseline data for land use development and water protection. The principal aim of this study is three-fold: (i) to map existing land use; (ii) to assess and map the spatial distribution of average annual rate of soil losses in the study area; (iii) to evaluate spatial matching between existing and proposed land use including a distance analysis from the water body (the Bili-Bili Dam). An analytical procedures used, respectively, include supervised classification of satellite imagery, application of RUSLE (Revised USLE), and overlay analysis in a raster GIS environment, utilising available information in the region covering some parts of Jeneberang catchment, South Sulawesi, Indonesia. The results suggest that the outputs of this study can be used for the identification of land units on a cell-basis with different land use types, rate of soil loss, inconsistency between proposed and planned land use, as well as the threat of land degradation to the main river and the dam. The analytical procedures developed in this research may be useful in other areas, particularly in the studies related to the assessment and mapping of land use and erosion for the importance of sustainable land use at a relatively large area.

Một mô hình có thể giải quyết bài toán xói mòn bồi tụ phục vụ cho các chính sách quản lý tổng hợp tài nguyên lưu vực sông là yêu cầu thực tiễn cho các nghiên cứu xói mòn đất hiện nay. Bài báo nghiên cứu và áp dụng mô hình RUSLE2 (USDA, 2008) vào lưu vực Suối Rạt, tỉnh Bình Phước. Kết quả bài báo đã đánh giá được khả năng áp dụng của mô hìnhđể tính toán cân bằng vật chất quy mô lưu vực, yêu cầu dữ liệu đầu vào, định lượng xói mòn và bồi tụ cho 56 mặt cắt sườn dốc điển hình trong lưu vực, từ đó tính được tổng lượng xói mòn bồi tụ của cả lưu vực. Kết quả phân cấp xói mòn theo quy định của TCVN 5299:2009 cho thấy cấp độ IV chiếm tới 75.24% diện tích lưu vực, tiếp đến là cấp V (24,16%), trong khi đó, xói mòn ở cấp I, II, III trong lưu vực là không đánh kể. Kết quả bài báo là căn cứ rất quan trọng cho việc hoạch định chính sách sử dụng đất hợp lý đối với các địa phương trong phạm vi lưu vực.

Purpose: This study gives a critical assessment of the rainfall erosivity factor (R) for selected sites in the Majha region, representing different locations use of mean monthly rainfall data.
Methodology: By applying empirical methods, the rainfall intensity for all the locations was obtained and was further determined at three different intervals of 30-minutes, 45-minutes, and 60-minutes, respectively. The rainfall erosivity factor (R) was calculated by the revised universal soil loss equation (RUSLE).
Main Findings: Using RUSLE, the rainfall erosivity factor (R) for each of the locations was measured as follows; EI = 3878.49 (MJmmha-1hr-1), EI = 4013.71 (MJmmha-1hr-1), EI = 4302.24 (MJmmha-1hr-1) for Majha region of Amritsar, Tarntaran and Pathankot respectively. A close observation of the data obtained revealed that as rainfall intensity increased with the duration, the rainfall erosivity index reduced or decreased.
Implications of study: Nevertheless, it is expected that if proper cover crop and management practices are applied despite the region, the study area falls within, rainfall erosivity can be cushioned, thus reducing further erosion tendencies and enhancing food production chances from productive lands within the area.
The novelty of the study: The rainfall erosivity factor (R) was calculated by the revised universal soil loss equation (RUSLE).

The study integrated the Revised Universal Soil Loss Equation (RUSLE) with Geographic Information System (GIS) to quantify the potential soil erosion risk in the Fincha'a watershed. Rainfall, soil, digital elevation model (DEM) and satellite image data sets were used as inputs in order to generate RUSLE factor values. The potential annual soil loss of the study area ranged from nil at plain surfaces to 223.12 t ha yr at steep 1 1 slopes of the farmland. The mean annual soil loss rate of the study area was 33.66 t ha yr. We obtained 1 1 the highest mean annual soil loss of 38.8 t ha yr for farmland. However, the smallest annual soil loss of 1 1 4.3 t ha yr was obtained from the forestland. Nearly 36.2% of the total farmland was classified under high 1 1 soil erosion risk while only 2.4 and 11.7% were categorized under high soil erosion risk for the forestland and grassland, respectively. The study revealed that the farmland was highly vulnerable to erosion than other land use and land cover types. In conclusion, information on average annual soil loss is important for selecting appropriate conservation measures to reduce on-site soil loss and their off-site effects.

With this study, it is aimed to draw a potential erosion risk map needed to be used for planning the precautions against erosion, which is one of the biggest problems of our country, by using advanced techniques. An area of 1126 km 2 including Çeşme Karaburun peninsula, which is located on the west coast of Turkey, has been selected as study area. RUSLE soil loss factors have been used in the study. Each factor used for detecting the soil loss has been determined geographically from different sources and recorded as layer in database according to Geographic information system. In the study, for determining C factor 15-m spatial resolution ASTER image, for determining "L" and "S" factors numerical counter lines, for determining "R" factor weather observation results, for determining "K" factor soil order maps have been used. Afterwards, layers are united by using spatial intersection and new polygons containing all attributes have been created. After the database was created, Rusle model has been applied and as a result soil loss has been determined for each polygon. At the end of the study, it has been determined that Çeşme Karaburun peninsula, selected as study area, has 1.279.548 ton/ha/year.

Aquí se estima la pérdida natural de suelos por erosión hídrica en la Alta Cuenca del río Escoipe- Chicoana, que resulta ser un tipo de erosión lenta. En vistas de que parte del área actualmente está sujeta a un proyecto de Declaración de Paisaje Protegido, es que surge este trabajo porque, posiblemente, los suelos de la zona se vean afectados si, una vez concretada la iniciativa, se verifica un incremento (no planificado) de la actual tasa de visitas. Para la estimación de A (A ACTUAL) se recurrió a la Ecuación Universal de Pérdida de Suelo (RUSLE) mediante la creación y ejecución de un Sistema de Información Geográfica (SIG). Se trabajó sobre una superficie de 31424,00 hectáreas, obteniéndose que aproximadamente el 85 % de la zona presenta serios problemas de pérdida de suelo y que, de mantenerse en el tiempo, alcanzaría los 5 centímetros de espesor de suelo al cabo de 100 años, cuando para la formación de igual altura de suelo son necesarios aproximadamente 400 años. Ello, es preocupante y nos indica que algo muy serio está sucediendo. Después de analizar varias posibilidades y sin descartarlas, se concluye que se ha de buscar respuestas en el pastoreo a campo abierto de los animales domesticados. Se recomienda establecer pautas sustentables de manejo pecuario en toda la zona.
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Laterites of Birbhum district are indentified as the ‘low-level laterites’ of ‘Rarh Plain’ of West Bengal and these are very much prone to severe soil erosion (mainly surface and sub-surface water erosion) in the monsoonal season (June - September.) Laterites and lateritic soils (locally named ‘Kankara’) of Caniozoic upland (adjoining areas of Rampurhat I block, Birbhum and Shikaripara block, Dumka- the study area), are the direct result of monsoonal wet-dry type of morpho-climatic processes and further laterisation of fluvial deposited materials (formation of surface duricrust) which was coming from Rajmahal Hills of eastern Chotanagpur Plateau (Jharkhand) in late Pleistocene. Such type of vermiform laterites is shaped and dissected by numerous gullies and ravines, giving birth of badland topography (locally named ‘Khoai’) of both degradation and aggradation processes. Before the soil conservation practices it is helpful if the assessment of soil erosion can be transformed into a statement of how fast soil is being eroded. The estimation of rate of annual soil loss is required in that case, because we must have to predict soil loss through effective models under a wide range of conditions. In this study the entire assessment is focused on the application Universal Soil Loss Equation (USLE) and Morgan, Morgan and Finney (MMF) methods in the soil loss estimation of sample slope segments, and relative comparison and suitability of both methods in the precise estimation of predicting soil loss.

Agriculture is the backbone of Kenya’s economy. Agriculture in Kenya is characterized by low productivity due to low external inputs, lack of good farming practices, soil erosion, and other losses. In most farming regions of the country, agriculture depends entirely on rainfall which sometimes is scarce. The problem of selecting the correct land for the cultivation of certain crops is a long-standing and mainly empirical issue. The objective of this study is to extrapolate and generate a crop suitability map showing areas suitable for agricultural activities in Taita Hills in Kenya. It utilizes the information on environmental condition, altitude, rainfall and other relevant parameters of the case study where the variability of rainfall and recurrent droughts have a great impact on the lives of people whose livelihood is mainly dependent on subsistence agriculture. The methods used include development of elevation models, watershed mapping, climate variability mapping, soil erosion ...

La présente étude a pour but d’estimer les pertes en sol dans le bassin versant de l’Oued Mikkès en amont du barrage Sidi Chahed situé dans la région de Meknès (Maroc), par l’utilisation de l’équation universelle révisée des pertes en sol de (Wischmeier et Smith, 1978). La spatialisation du modèle empirique s’est basée sur l’intégration des cinq facteurs dans le Système d’Information Géographique (SIG), à savoir, l’érosivité des pluies « R », l’érodibilité des sols « K », le couvert végétal « C », la topographie « LS » et les pratiques antiérosives « P », et dont la superposition a permis d’élaborer la carte quantitative des pertes en sols à l’échelle du bassin versant. Le bassin versant de l’Oued Mikkès s’étale sur une superficie de 1444 km2 ; il est de forme allongée avec une altitude allant de 2090 m à 184 m du Sud vers le Nord et une pente qui varie de 0 à 189 %. L’étude pluviométrique des onze stations climatiques qui se trouvent au niveau du bassin versant a démontré l’irrégul...

Assessment of soil erosion risk, especially in hilly areas, is a challenging task mainly due tovariability in topography and non-availability or insufficiency of relevant data. The Revised Universal Soil Loss Equation (RUSLE) model is applied worldwide for prediction of soil loss. Although it is an empirical model, it not only predicts erosion rates of ungauged watersheds but also presents the spatial heterogeneity of soil erosion that is too feasible with reasonable costs and better accuracy in larger areas. Remote sensing (RS) technology plays an important role in mapping of soil erosion risk in agriculture, forest and degraded land. Its application in the soil erosion risk mapping introduces new opportunities for conservation planning and management. With the incorporation of Geographical Information System (GIS), it is possible to analyze satellite data, which gives required information like land use and cover, slope, distribution of rainfall, flow direction etc. of study watershed. The capabilities of these technologies even increase when they are integrated with empirical erosion prediction models like RUSLE. RS and GIS integrated erosion prediction models do not only estimate soil loss but also provide the spatial distributions of the erosion. Generating accurate erosion risk maps in GIS environment is very important to locate the areas with high erosion risks for prioritization and to develop adequate conservation techniques. Micro-watershed prioritization within a large watershed is considered as one of the most important aspects of planning and development for natural resources for soil and water conservation measures. This review article highlights the application of RUSLE, RS and GIS technology in the study of soil erosion and gives an insight of their valuable application in soil erosion risk mapping

Conservation-oriented land practices have long been a strategy for mediating the environmental issues resulting from conventional agriculture. However, there is limited economic support and incentive for landowners to transition the sensitive marginal lands that need mitigation the most. To improve this approach, information tools built out of landowner preferences may help facilitate successful long-term adoption of diverse systems that achieve production and conservation goals, such as Multifunctional Perennial Cropping Systems (MPCs). Previous work has recognized MPCs to have the potential for providing both ecosystem services and perennial crops such as fruits, nuts, and grasses on land that landowners would otherwise consider marginal. To prioritize efforts for implementation of MPCs and provide tailored information to landowners, this study introduces a suitability model that identifies marginal land based on soil erosion, crop productivity, and other land traits that are important to landowners. Information provided by this tool can inform land management decisions. The land traits were spatially analyzed using a geographic information system (GIS) and parameterized to encode the magnitude of each variable's effect on MPCs suitability. Applied in the Upper Sangamon River watershed, central Illinois, we identified 18,685 ha of highly suitable cropland for MPCs. An 8.5 m spatial resolution allowed identification of subfield suitability areas, in addition to locating target regions of extensive occurrences of high suitability. The distribution of target areas was often located where crop productivity was low and topographic potential for erosion was high. For 26,743 ha of cropland, potential erosion was estimated to be greater than the soil loss standard, particularly in the northeastern section of the watershed where there was higher relief and peri-urban or riparian areas surrounding cropland. In a scenario in which landowners would implement MPCs on identified target regions, simulated soil erosion was reduced by 56% across the watershed. The model provides a simple and effective management tool for identifying priority areas for MPCs implementation, giving landowners and researchers actionable information to improve upon conservation strategies for marginal cropland.

En este trabajo se estimó la pérdida de suelos actual de campos de cultivos establecidos en un territorio serrano ubicado en el centro de la provincia de Salta, Argentina, en la Alta Cuenca del río Escoipe- Chicoana, de jurisdicción del municipio de Chicoana. Los cálculos que intervienen en la Ecuación Universal de Pérdida de Suelo Revisada (RUSLE) se llevaron a cabo a través de la creación y calibración de un Sistema de Información Geográfica (SIG) para la superficie agrícola de 697,85 has del área. Se obtuvo que el 65,69 % de los campos agrícolas (458,40 has) presentan pérdidas de suelo superiores a 10 Mg/ha/año, lo cual, era de esperar, pues, en la zona no se realizan otras prácticas agronómicas más que las tendientes a mantener la mayor cantidad de la superficie cultivada cubierta durante el año, especialmente, en la época estival. Se recomienda tomar medidas correctivas, pues ya no hay lugar para realizar mitigaciones. Éstas, consistentes en planificar y ejecutar actividades en el terreno tendientes a disminuir el valor final de los factores Largo y Porcentaje de la Pendiente (LS) y, se advierte, que modificar los valores actuales de los factores Prácticas de Cultivo (P) y Cobertura (C), ciertamente representará una ardua tarea.
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The open source Geographic Information System (GIS) and Revised Universal Soil Loss Equation (RUSLE) were used to predict the soil erosion hazard for Langkawi Island, Malaysia. Secondary raster data for the following parameters; rainfall erosivity (R), slope length-steepness (LS), soil erodibility (K), cover management (C), and conservation practices (P) were used to generate soil erosion map. The results predicted that about 58 percent of the Langkawi has very low to moderate erosion risk and about 32 percent of the study area is of high to extreme erosion risk. This study demonstrates the effectiveness of open source GIS in generating quantitative information on soil erosion studies.

Background and Objectives: Preservation of soil and prevention of occurrence and intensification of erosion are the most important functions of natural ecosystems. This issue is especially important in steep and mountainous areas. Soil conservation function, like many other ecosystem services, lacks a market to determine value. Natural ecosystems are one of the important economic resource for many developing countries that contribute to the development of regions and communities by producing goods and services. This study was conducted in 2019 with the aim of investigating the role of natural ecosystem in Kechik area in controlling soil erosion and determining the economic value of soil protection based on soil fertility maintenance function.
Materials and methods: In order to estimate soil erosion quantitatively , the RUSLE model, which inputs include rain erosion factor, soil erodibility factor, length and degree of slope factor, vegetation factor and protective operations factor, was used in GIS environment. To calculate the economic value of soil fertility maintenance function, soil retention and soil nutrient content including nitrogen, phosphorus and potassium in the area were estimated and its economic value was calculated using the alternative cost approach.
Results: The results of soil erosion by RUSLE method showed that the range of soil erosion in the region varied between 0 to 239.2 tons per hectare per year and its average was estimated at 7.94 tons per hectare per year. The value of the main elements preserved in the soil of the whole basin was equal to 9.21 billion Rials per year and the value of each hectare of the region's ecosystem was estimated at 2.55 million Rials per year. Also, the analysis of erosion data in IDRISI Selva software showed that the factor of length and degree of slope with a correlation coefficient of 93% and a coefficient of determination (R2) of 0.87 had the greatest effect on estimating annual soil erosion.
Conclusion: The result of this study states that the value obtained per hectare of forest is 3.39, rangeland 2.84 and dry land 2.16 million rials per year, which shows the more value of rangeland ecosystem than dry lands. Due to the positive effects of vegetation, the need for special attention to rangeland and forest vegetation to reduce soil erosion is felt and it is recommended that biological and soil protection programs to reduce soil erosion damage in areas with high erosion sensitivity in the region.

In this study, quantitative assessment of soil erosion and sediment was done using the famous RUSLE model in the framework of GIS and remote sensing technology. The results showed the erosion values ​​of the basin vary from 0.001 to 257 (t ha-1y-1) at the pixel level and the average erosion in the study basin is 17.62 (t ha-1y-1). Medium rangelands have high average erosion values for two reasons; One is due to the steep slope and consequently the runoff speed in the destruction and transport of particles, which intensifies the role of LS factor and weakens the vegetation factor and the other is the high values of precipitation, which shows the role of rain erosion factor (R). Classification of erosion values showed that about 42% of the study basin with value higher than 16 (t ha-1y-1) is in a severe situation in terms of soil loss. Therefore, due to the erosion situation in the study basin, the role of watershed management, soil protection, and watershed management operations with a focus on the upstream basin and in areas with high slopes is more necessary.

Accelerated soil erosion is a worldwide problem because of its economic and environmental impacts. Enfraz watershed is one of the most erosion-prone watersheds in the highlands of Ethiopia, which received little attention. This study was, therefore, carried out to spatially predict the soil loss rate of the watershed with a Geographic Information System (GIS) and Remote Sensing (RS). Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions was used to estimate potential soil losses by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using soil map, vegetation cover (C) using satellite images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P ) using satellite images. Based on the analysis, about 92.31% (5914.34 ha) of the watershed was categorized none to slight class which under soil loss tolerance (SLT) values ranging from 5 to 11 tons ha-1 year-1. The remaining 7.68% (492...

Climate change poses an imminent physical risk to cultural heritage sites and their surrounding landscape through intensifying environmental processes such as damaging wetting and drying cycles that disrupt archaeological preservation conditions, and soil erosion which threatens to expose deposits and alter the archaeological context of sites. In the face of such threats, geospatial techniques such as GIS, remote sensing, and spatial modelling have proved invaluable tools for archaeological research and cultural heritage monitoring. This paper presents the application of secondary multi-source and multi-temporal geospatial data within a processing framework to provide a comprehensive assessment of geophysical risk to the Roman fort of Magna, Carvoran, UK. An investigation into the ancient hydraulic system at Magna was carried out with analysis of vegetation change over time, and spatio-temporal analysis of soil erosion risk at the site. Due to COVID-19 restrictions in place at the t...

The study integrated the Revised Universal Soil Loss Equation (RUSLE) with Geographic Information System (GIS) to quantify the potential soil erosion risk in the Fincha’a watershed. Rainfall, soil, digital elevation model (DEM) and satellite image data sets were used as inputs in order to generate RUSLE factor values. The potential annual soil loss of the study area ranged from nil at plain surfaces to 223.12 t ha yr at steep 1 1 slopes of the farmland. The mean annual soil loss rate of the study area was 33.66 t ha yr . We obtained 1 1 the highest mean annual soil loss of 38.8 t ha yr for farmland. However, the smallest annual soil loss of 1 1 4.3 t ha yr was obtained from the forestland. Nearly 36.2% of the total farmland was classified under high 1 1 soil erosion risk while only 2.4 and 11.7% were categorized under high soil erosion risk for the forestland and grassland, respectively. The study revealed that the farmland was highly vulnerable to erosion than other land use and la...

Identification of soil loss is a global concern as it increases the pollution and sedimentation in the concerned river or reservoir. Due to sedimentation not only the water storage capacity of the waterbody reduces but also the aqua life gets hampered. Several studies have been done on estimation of soil erosion using the revised universal soil loss equation (RUSLE). The RUSLE model shows the influence of impact of rain drop energy on top soil that causes erosion. The vegetation cover present on the top soil reduces the impact of raindrop energy and thus reduces the soil erosion. This factor is termed as cover management factor (C). From the detailed observation of satellite imageries of Bakreshwar watershed and Bakreshwar dam, lots of sedimentation has been observed in the Bakreshwar dam. In this study we have tried to identify the relationship (if any) between land surface temperature changes with the cover management factor of upper Bakreshwar river basin over a time of 30 years. The study area is located in Humid Subtropical climatic zone where the summer is hot and humid and winter is mild. So a change in temperature may cause a change in rainfall amount and in turn it may affect the cover management factor. From the study it has been observed that negative relationship prevails with temperature and cover management factor in the study area. As we are studying on winter data it prevails that the vegetation cover present in high surface temperature region than cold regions that can reduce the soil loss. This observation may help to future modification of cover management factor in RUSLE model by incorporating the land surface temperature in it.

Soil erodability that correlated with barren or void vegetation cover land has an outlandish result in the lower part of the study area. This study aim to analysis the soil erosion risk of G Madugula Mandal, Visakhapatnam district. The study combines both remote sensing and GIS techniques to obtain severe erosion risk zones in the study area by taking into consideration of ancillary data such as Soil, DEM and LandSat satellite data. The method verified and cross checked by ground truth data. The results show that, Very Low and Low classes are scattered in all over the study area due to the randomization of the Land units and represent almost 76.14% of the study area. The Very Low class is occupying 50.67% of the study area in correspondence to valley fills or foot slopes, where the low slope gradient allows the accumulation of materials transported by water or
Ch. Vasudeva Rao, G. Ashenafi Tolessa, E. Aminnedu- Erosion risk identification
study using RUSLE model in G. Madugula Mandal, Visakhapatnam District,
A.P., India
EUROPEAN ACADEMIC RESEARCH - Vol. II, Issue 9 / December 2014
12247
gravity. The High class is mainly concentrated in the Kumbidisingi Panchiteat at Solamulu and in a small unit in Solabham Panchiteat Mallipadu village representing 17.36% of the study area. Therefore, appropriate soil conservation measure should be taking place in order to further prevent soil loss.

Soil erosion is a major factor in losses of soil. Different models are used for prediction of the amount of soil loss by erosion. In the present study, modelling using Revised Universal Soil Loss equation (RUSLE) is integrated with Remote Sensing (RS) and Geographical Information Systems (GIS) techniques and employed to estimate soil erosion and prioritization of watersheds of Udham Singh Nagar district of Uttarakhand, India. The results showed that Udham Singh Nagar district's major portion (38.66%) is covered with agriculture land and only 17.57% area is covered with forest. Water-bodies have occupied 2.18% area of US Nagar district. A large variation has been noticed in case of built-up land which has been recorded as 5.71%. US Nagar has more agricultural land. Udham Singh Nagar is having plane topography hence the range of soil erosion is from 0 to 40 ton/ha/year. However, most region of Udham Singh Nagar district falls under the category of 0-2 ton/ha/year soil erosion. The value of soil losses in most of cases is less than 1 t/ha/yr except in case of 11 watersheds, where it is slightly higher than 1 t/ha/yr. Moreover, it has been concluded that major portion of Udham Singh Nagar district were slight prone category of soil erosion, and therefore, no major plan/activity is required for reducing soil losses. Only checking large amount of runoff and enhancing organic matter build up in the soil will suffice the purpose.

Soil erosion is a serious environmental problem in Kothagiri Taluk. Many studies have been carried out to map shifting cultivation and areas susceptible to soil erosion. Mostly, estimated soil loss is taken as the basis to classify the level of soil loss susceptibility of area. The Revised Universal Soil Loss Equation (RUSLE) function is a commonly used erosion model for this purpose in Kothagiri Taluk. This research integrates the RUSLE within a Geographic Information System (GIS) environment to investigate the spatial distribution of annual soil loss potential in the Kothagiri Taluk. Both magnitude and spatial distribution of potential soil erosion in the catchment is determined GIS data layers including, rainfall erosivity (R), soil erodability (K), slope length and steepness (LS), cover management (C) and conservation practice (P) factors were computed to determine their effects on average annual soil loss. The rainfall erosive factor was developed from local annual precipitatio...

In the context of Nepal, there are few gauged stations and long term data are not available which makes difficult to estimate the river flow. There are different approaches to estimate the flow of ungauged rivers and it is up to the individual to choose a suitable method among those available methods. However it is essential to know the parameters of selected method (e.g., rainfall, surface characteristics of the catchment, steepness of the basin etc.). On the other hand all these methods use various assumptions. The selected method might leads to unreliable results if the parameters and assumptions are not considered well. Therefore it is a challenge to calculate design discharge for a hydropower project in Nepal where most of the rivers are ungauged. Furthermore there are limited investigations on the comparison of design discharge calculation approaches till the date. Detailed hydrological study was conducted at the ungauged river, Padhu Khola in Sikles, Madi Gaupalika, Kaski, Nepal. Rational method, NRCS-CN method, MIP method and Catchment Area Ratio methods were used in this study to estimate the mean monthly discharge of Padhu Khola. Catchment Area Ratio method found to be suitable one for estimating the design discharge of Padhu Khola. The methodology developed in this study can be used to estimate the design flow of other ungauged rivers in Nepal.