Mapping erosion prone areas in the Bouhamdane watershed (Algeria) using the Revised Universal Soil Loss Equation through GIS

Bouguerra, Hamza; Bouanani, Abderrazak; Khanchoul, Kamel; Derdous, Oussama; Tachi, Salah Eddine

doi:10.1515/jwld-2017-0002

Cited by 43 publications

(11 citation statements)

References 13 publications

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“…Most of the models used the average annual rainfall to calculate the R factor [8], [9], [17], [22]- [26]. Some of the models used the annual average rainfall, the 20 years daily rainfall [27], and the monthly average rainfall [7], [28].…”

Section: ) Rainfall Erosivity Factor (R)mentioning

confidence: 99%

Assessment of Soil Loss Rates in Asreh Watershed (North Jordan Badia) Using RUSLE and GIS

AlAyyash¹

2021

IJESD

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In arid lands, rainwater harvesting can play an important role in making more water available since most of the rainfall runoff evaporates. If rainwater can be collected, it will form a useful resource. Jordan is classified as one of the poorest countries regarding water resources with an arid and semi-arid climate. For these limited and vital sources of water, good estimation of rainfall runoff quantity and quality can enhance the sustainability of water harvesting projects. The hydrologic estimations of runoff quantities and qualities are essential, and several techniques to achieve that exist. Revised Universal Soil Loss Equation (RUSLE) is one of the widely used techniques to assess the soil erosion due to runoff, by assessing other physical factors that affect the soil loss. RUSLE combined five parameters to identify the soil loss rate: rainfall erosivity, topographic, soil erodibility, vegetation cover and management, and land management. Based on RUSLE results, areas are classified as a highly soil loss rate if the annual rates exceeded 20 tons per hectare. The Asreh watershed is a 196 km2 area that is mostly wasted land and receives an annual rainfall between 50 and 300 mm per year. The RUSLE equation inputs parameters for the study area are found and the equation is applied for the watershed. Results of RUSLE application on the Asreh watershed showed that the average annual soil loss rate is about 7.8 tons per hectare, about 73% of the area are classified as low soil loss rate with less than 10 tons per hectare per year, and only 13% of the area is classified as a high soil loss rate of more than 20 tons per hectare per year.

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Section: ) Rainfall Erosivity Factor (R)mentioning

confidence: 99%

Assessment of Soil Loss Rates in Asreh Watershed (North Jordan Badia) Using RUSLE and GIS

AlAyyash¹

2021

IJESD

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“…Low values correspond to pixels with good conservation practice, while the high values denote areas of poor conservation practice [31]. P factor value depends on slope length and steepness, and farming method [102]. Therefore, an increase in the value of P factor is consistent with the rise in the LS factor value (Figures 6A and 8A).…”

Section: The P Factormentioning

confidence: 66%

New Insight on Soil Loss Estimation in the Northwestern Region of the Zagros Fold and Thrust Belt

Othman¹,

Obaid

Ali

et al. 2021

IJGI

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Soil loss is one of the most important causes of land degradation. It is an inevitable environmental and socio-economic problem that exists in many physiographic regions of the world, which, besides other impacts, has a direct bearing on agricultural productivity. A reliable estimate of soil loss is critical for designing and implementing any mitigation measures. We applied the widely used Revised Universal Soil Loss Equation (RUSLE) in the Khabur River Basin (KhRB) within the NW part of the Zagros Fold and Thrust Belt (ZFTB). The areas such as the NW Zagros range, characterized by rugged topography, steep slope, high rainfall, and sparse vegetation, are most susceptible to soil erosion. We used the Digital Elevation Model (DEM) of the Shuttle Radar Topography Mission (SRTM), Tropical Rainfall Measuring Mission (TRMM), Harmonized World Soil Database (HWSD), and Landsat imagery to estimate annual soil loss using the RUSLE model. In addition, we estimated sediment yield (SY) at sub-basin scale, in the KhRB where a number of dams are planned, and where basic studies on soil erosion are lacking. Estimation of SY will be useful in mitigation of excessive sedimentation affecting dam performance and watershed management in this region. We determined the average annual soil loss and the SY in the KhRB to be 11.16 t.ha−1.y−1 and 57.79 t.ha−1.y−1, respectively. The rainfall and runoff erosivity (R factor), slope length (L factor), and slope steepness (S factor), are the three main factors controlling soil loss in the region. This is the first study to determine soil loss at the sub-basin scale along with identifying suitable locations for check dams to trap the sediment before it enters downstream reservoirs. The study provides valuable input data for design of the dams to prevent excessive siltation. This study also aims at offering a new approach in relating potential soil erosion to the actual erosion and hypsometric integrals.

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“…The "flow direction" raster is generated from the DEM, shows the actual direction of water flow. To create a stream network, use the "flow accumulation" tool to calculate the number of upslope cells flowing to a location [BOUGUERRA et al 2017]. "Flow Accumulation" defines a Stream Network by use the "Stream to Feature" tool in ArcGIS to convert the grid to a linear vector file (shapefile).…”

Section: Watershed Delineationmentioning

confidence: 99%

Spatiotemporal evolution of land surface temperature of Lake Oubeira catchment, northeastern Algeria

Bara

Djidel

Medjani

et al. 2019

Journal of Water and Land Development

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The difficulties of access and detailed measurements of land surface temperature (LST) and water surface temperature (WST) especially in wetlands made the use of remote sensing data as one of the sources and techniques to estimate many climate elements including surface temperature and surface emissivity (ɛ). This study aims to estimate the surface temperature of the wetland of Lake Oubeira located in northeastern Algeria and their spatiotemporal evolution in both land and water. Landsat OLI-TIRS images in two dates (April and September 2016) obtained from the USGS have been used in this work, and forms the basis of a series of operations to obtain the final LST: development of the normalized difference vegetation index (NDVI), conversion of the digital number (DN) of the thermal infrared band (TIR) into spectral radiance as well as the calculation of the effective luminosity temperature of the sensor from the spectral radiation and surface emissivity (ɛ).The results show that the LST varies in space and time (from 16 to 31°C in April and from 24 to 41°C in September). This implies that the absorption of the equilibrium temperature at land cover depends on the optical properties of the surface, which are essentially determined by its water content, colour and morphology. At the same time, the water surface is the lowest land cover temperature, which also has a spatial variation (from 19 to 25°C in April and from 26 to 34.5°C in September) induced by atmospheric temperature, wind direction and speed and the depth of the lake.

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Mapping erosion prone areas in the Bouhamdane watershed (Algeria) using the Revised Universal Soil Loss Equation through GIS

Cited by 43 publications

References 13 publications

Assessment of Soil Loss Rates in Asreh Watershed (North Jordan Badia) Using RUSLE and GIS

Assessment of Soil Loss Rates in Asreh Watershed (North Jordan Badia) Using RUSLE and GIS

New Insight on Soil Loss Estimation in the Northwestern Region of the Zagros Fold and Thrust Belt

Spatiotemporal evolution of land surface temperature of Lake Oubeira catchment, northeastern Algeria

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