Identification Of Erosion Prone Areas Research Articles

Identification of erosion-prone areas using morphometric, hypsometric, and compound factor approaches in the Ruvu River Basin, Tanzania

Identification of erosion-prone areas using morphometric, hypsometric, and compound factor approaches in the Ruvu River Basin, Tanzania

Study of soil erosion by using remote sensing and GIS techniques in Sone command area in Bihar, India

Soil erosion is caused by various reasons, but the land slope and poor land management are the main reasons. Identification of erosion-prone areas is the most important factor for agricultural planning and effective land management. This study includes an estimation of average annual soil loss in the Sone command area in Bihar and the preparation of spatially distributed soil erosion map for different land-use scenarios. The soil in the study area is generally clay loam. A well-known empirical equation i.e. RUSLE (Revised Universal Soil Loss Equation) has been used to estimate parameters and prepare spatially distributed maps. By using remote sensing and GIS techniques different soil loss parameters like rainfall erosivity (R), soil erodibility (K), slope length and steepness factor (LS), cover management factor (C) and conservation practice factor (P) are estimated and spatially distributed map of all these parameters are prepared. Average soil loss in the study area was found in the range 21 to 40 t.ha−1.yr−1 and the maximum value is found to be around 7000 t.ha−1.yr−1. It was also found that areas with high soil erosion rates are very low. Around 46% variation is observed between the maximum and minimum average soil loss rates.

Identification of erosion-prone areas using modified morphometric prioritization method and sediment production rate: a remote sensing and GIS approach

Watersheds from semiarid zones are sensitive to land degradation processes wherein the morphometric investigation is an important aspect to unwrap the susceptible areas. Hence it is a prerequisite for the assessment of erosional pattern of the watershed. Thus, based on the response to erosional processes, prioritization task has been undertaken for fourteen sub-watersheds from basaltic region of Western Ghats of India. A morphometry-based framework using weighted sum analysis (WSA) coupled with the remote sensing data, field data and topographical maps were generated on geographical information system (GIS) platform to estimate the soil erosion susceptibility. The study also evaluates the performance of this new methodology by considering the sediment production rate (SPR) of these sub-watersheds. The resultant WSA-SPR model has prioritized the study area into high, moderate low and very low categories. The high and moderate priority areas lie in the proximity of outlet, upper elevated and undulating terrain of the watershed. It represents 41.38% of the total area covering SW1, 3, 13 and 14 sub-watersheds. This study proposes a useful tool to define areas for planning the strategies to control soil erosion and promote soil conservation.

Sustainable management of erosion prone areas of upper watershed of Kainji hydropower dam, Nigeria

Reservoir sedimentation has been a major concern to stakeholders around the world in the implementation of sustainable management of hydropower dams. Not only that it reduces the storage capacity of reservoirs, several sediment related problems such as reduction in water quality and acceleration of abrasion of underwater parts can impair the primary purpose of which the reservoir is built. Therefore, sustainable management of watersheds upstream of hydropower dam is necessary to combat the issues of sedimentation and to extend its useful life. In this study, Soil and Water Assessment Tool (SWAT) was interfaced with MapwindowGIS to model and predict sediment yield and concentration into sub-basins of the upper watershed of Kainji hydropower dam in Nigeria which has an area of 30,350 km2. The model was run daily for 30 years and performance evaluation was carried out using Coefficient of Determination (R2) and Nash Sutcliffe Efficiency (NSE). Model calibration and validation as well as identification of erosion prone areas were equally achieved. The results showed that average annual sediment yield and concentration were 35.29 t/ha/year and 11,903.7 mg/l respectively. Application of filter strips on critical erosion prone region showed that sediment yield and concentration could be reduced up to 37% and 34% respectively. Also, construction of stone bunds in the watershed showed a reduction of up to 75% and 84% for sediment yield and concentration respectively. The outcome of this study could allow control effort to be focused effectively on an area identified as extreme cases and could also be used by relevant authorities in prioritizing implementation of Best Management Practices (BMPs) for the area.

Identification of erosion-prone areas using different multi-criteria decision-making techniques and GIS

The awareness of erosion risk in watersheds provides the possibility of identifying critical areas and prioritising protective and management plans. Soil erosion is one of the major natural hazards in the rainy mountainous regions of the Neka Roud Watershed in Mazandaran Province, Iran. This research assesses soil erosion susceptibility through morphometric parameters and the land use/land cover (LU/LC) factor based on multiple-criteria decision-making (MCDM) techniques, remote sensing and GIS. A set of 17 linear, relief and shape morphometric parameters and 5 LU/LC classes are used in the analysis. The aforementioned factors are selected as indicators of soil erosion in the study area. Then, four MCDM models, namely, the new additive ratio assessment (ARAS), complex proportional assessment (COPRAS), multi-objective optimisation by ratio analysis and compromise programming, are applied to the prioritisation of the Neka Roud sub-watersheds. The Spearman’s correlation coefficient test and Kendall’s tau correlation coefficient test indices are used to select the best models. The validation of the models indicates that the ARAS and COPRAS models based on morphometric parameters and LU/LC classes, respectively, achieve the best performance. The results of this research can be used by planners and decision makers in soil conservation and in reducing soil erosion.

Erodibility prioritization of sub-watersheds using morphometric parameters analysis and its mapping: A comparison among TOPSIS, VIKOR, SAW, and CF multi-criteria decision making models

Soil erosion, every year imposes extensive damages to human beings by means of reducing soil productivity and filling reservoirs from sedimentation in Ghaemshahr Basin in Mazandaran Province, (Iran); therefore, identifying prone areas to soil erosion for preventive measures is essential in this basin. In this research, erodibility prioritization of sub-watersheds of Ghaemshahr Basin has done using morphometric parameters analysis and different multi-criteria decision making (MCDM) models such as simple additive weighing (SAW), VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), technique for order preference by similarity to ideal solution (TOPSIS), and compound factor (CF). For this purpose, Advanced Space Thermal Emission Radiometer (ASTER), a Digital Elevation Model (DEM) with spatial resolution of 30m used for extraction and analysis of 23 morphometric parameters including basic, linear, shape, and landscape. For validation of the MCDM methods, the indices of percentage of changes and intensity of changes were used. The results of prioritization of sub-watersheds indicated that in TOPSIS and CF models, sub-watershed 30 with 0 and 13.33 scores are located in first rank, respectively, which is known as the most prone sub-watersheds to erosion. Also, results showed that sub-watersheds in terms of susceptibility to erosion, in CF model has an one category namely Low; meanwhile, in TOPSIS and VIKOR models show four classes including low, moderate, high, and very high. In contrast, for SAW model there are three classes of moderate, high, and very high susceptibility. In general, the results showed that morphometric parameters have high efficiency in identification of erosion-prone areas and also VIKOR method has higher predictive accuracy than TOPSIS, SAW, and CF models.

Soil erosion and transport simulation and critical erosion area identification in a headwater catchment contaminated by the Fukushima nuclear accident

Radiocesium released by the accident at the Fukushima Dai-ichi Nuclear Power Plant in 2011 contaminated a large land surface area. Due to the strong and size-dependent adsorption capability of soil particles to radionuclides, a better understanding of erosion and transport of soil particles and identification of erosion prone areas within watersheds are significant for contaminant management. For this purpose, we simulated soil erosion and transport in a partially forested catchment for multiple particle size classes. Critical erosion areas were identified by the spatial distribution of net soil erosion. Comparisons between simulated and measured suspended solids concentration at multiple locations throughout the catchment demonstrated successful model performance. For the period Mar. 12, 2011 through Dec. 31, 2014, model results indicated that 5500 tonnes of clay, 52000 tonnes of silt, and 22000 tonnes of sand are transported from the catchment. The results showed that soil erosion in the middle part of the catchment is greater mainly because of steep slopes and large fraction of agricultural lands. These simulations suggest that soil decontamination of erosion-prone agricultural lands in the mid- catchment areas would be effective in reducing radiocesium migration with soil particles.

Identification of Erosion Prone Areas by Morphometric Analysis Using GIS

This study was undertaken to determine the priority watersheds for conservation of natural resources of the Haharo sub catchment in the Damodar catchment of upper Damodar valley area having an area of 565 km2 involving four watersheds in Jharkhand State in eastern India by morphometric analysis using topographical maps on a scale of 1:50,000. To define the morphometric features of the watershed, the topographic information of the study area at 1:50,000 scaled are taken for analysis with the help of GIS tools. The topographical information derived from this map is utilized for calculating parameters and fixing of priority of watershed for suggesting conservation measures. The parameters computed include the morphometric parameters like bifurcation ratio, drainage density, stream frequency, texture ratio, and three basin shape parameters i.e., form factor, circularity ratio, and elongation ratio. A rating was done for each of these parameters according to their value. Average of all these parameter for each watershed is calculated to determine the priority. Among the four watersheds 4/4 was the highest priority area where conservation measure has to be taken first then watershed 4/3. Watershed 4/1 was the medium priority area and watershed 4/2 was the low priority area.