Modelling Surface Water Potential of Somodo Watershed Using SWAT Model
Issue:
Volume 9, Issue 4, December 2021
Pages:
74-78
Received:
30 August 2021
Accepted:
26 September 2021
Published:
15 October 2021
Abstract: Despite increased worldwide water demand, freshwater availability is decreasing as a result of population expansion, industrialization, land use, and climate change. As a result, in order to provide strategic information for long-term water security planning, it is required to quantify the water resources potential. The objective of this study was to determine the surface water potential of the Somodo watershed. GPS, GIS, Arc SWAT, and SWAT-CUP software were all utilized to collect data. Secondary data, such as DEM, land use/land cover maps, soil maps, stream flow, and meteorological data, were collected from appropriate institutions. We investigated the model's sensitivity, calibration, and validation. According to the findings, surface runoff and base flow were the most sensitive parameters of stream flow in the Somodo watershed. The statistical results for model performance revealed a very good agreement (R2 of 0.795 and NSE of 0.68) between the simulated and observed flow for calibration, and a very good agreement (R2 of 0.821 and NSE of 0.7) between the observed and simulated stream flow for validation. The catchment, with a total watershed area of 19860 hectares, generated 56.75 million cubic meter (MCM) surface runoff per year, according to the model. The watershed's surface water potential of 56.75 MCM is sufficient to meet a variety of water demands.
Abstract: Despite increased worldwide water demand, freshwater availability is decreasing as a result of population expansion, industrialization, land use, and climate change. As a result, in order to provide strategic information for long-term water security planning, it is required to quantify the water resources potential. The objective of this study was ...
Show More
Comparison and Applicability of Selected Soil Erosion Estimation Models
Dawit Kanito,
Samuel Feyissa
Issue:
Volume 9, Issue 4, December 2021
Pages:
79-87
Received:
20 November 2021
Accepted:
8 December 2021
Published:
24 December 2021
Abstract: Soil erosion is a globally challenging issue that hinders agricultural productivity by enhancing land degradation and loss to the top fertile soil. Although it is a global issue, its effect is adverse on farmers dwell in developing countries. Hence, providing information on soil loss is crucial to plan and implement appropriate soil and water conservation measures. Accordingly, erosion estimation models were developed and grouped as empirical, conceptual, and physical-based broad umbrella. This review paper primarily is intended to compare the opportunities and limitations of widely implemented soil erosion estimation models and review their applicability by selecting widely used models such as: USLE, RUSLE, SLEMSA, and WEPP. The result of this review revealed that the so reviewed erosion models have been designed to predict soil loss from sheet and rill erosion. Evidence from studies indicated that R/USLE models can be universally used by calibrating to the local environmental conditions. They are simple, requires less data and computational time, however; they are not event responsive and measure soil loss from gully and stream-bank erosion. But, RUSLE model has different parameter calculation procedure than the USLE. This study also depicts the SLEMSA model treats soil erosion factors as a separate entities and is highly influenced by LS factors. The WEPP model has capability to estimate soil loss in a short time scale and out-of-place erosion rates, but; it only works for individual hillslope. Thus, based on the result of this review the following recommendations are forwarded for further study to fill the gaps; upgrading of R/USLE parameters, modification of topographic sub-model of SLEMSA, and revision of essential parameters in WEPP model to estimate erosion from large catchments.
Abstract: Soil erosion is a globally challenging issue that hinders agricultural productivity by enhancing land degradation and loss to the top fertile soil. Although it is a global issue, its effect is adverse on farmers dwell in developing countries. Hence, providing information on soil loss is crucial to plan and implement appropriate soil and water conse...
Show More
