scholarly journals Sediment Analysis using Soil and Water Assessment Tool (Swat) - A Case Study of Kabini River Basin

2020 ◽  
Vol 8 (8) ◽  
pp. 1251-1255
Author(s):  
Prajnya V Hosapeti
Keyword(s):  
River Basin ◽  
Assessment Tool ◽  
Sediment Analysis ◽  
Water Assessment ◽  
Soil And Water

Simulation of Non-Point Source Pollution Based on SWAT Model - A Case Study of Ashi River Basin

2014 ◽  
Vol 1073-1076 ◽  
pp. 1751-1755
Author(s):  
Fang Ma ◽  
Xiao Feng Jiang ◽  
Li Wang ◽  
Dan Shan ◽  
Xiong Wei Liang ◽  
...  
Keyword(s):  
River Basin ◽  
Stream Flow ◽  
Assessment Tool ◽  
Swat Model ◽  
Validation Period ◽  
Point Source Pollution ◽  
Water Assessment ◽  
Non Point Source Pollution ◽  
Soil And Water

The Soil and Water Assessment Tool (SWAT) model was examined for its applicability in modeling stream-flow and nutrients (total nitrogen, TN and total phosphorus, TP) in Ashi River Basin, China covering an area of 3545 km2. This model was calibrated by using the observed data of monthly flow during 1996-2005 and nutrients (TN and TP) during 2006-2008, and validated by using the observed data of monthly flow during 2006-2010 and water quality during 2009-2010. For stream-flow, the monthly results of RE, R2 and ENS values reached 6.42%, 0.61 and 0.59 respectively for calibration period, whereas these were-12.83%, 0.69 and 0.67, respectively for validation period; for TN calibration, values of RE, R2 and ENS were-18.33%, 0.64 and 0.55 respectively, and for validation period they were-17.34%, 0.68 and 0.57 respectively; for TP calibration, values of RE, R2 and ENS were-4.32%, 0.61 and 0.56 respectively, and for validation period they were-18.02%, 0.67 and 0.58 respectively. Results show that SWAT has applicability in modeling stream-flow and nutrients (TN and TP) in cold and flat area.

scholarly journals Using the Soil and Water Assessment Tool to Simulate the Pesticide Dynamics in the Data Scarce Guayas River Basin, Ecuador

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 696 ◽  
Author(s):  
Naomi Cambien ◽  
Sacha Gobeyn ◽  
Indira Nolivos ◽  
Marie Anne Eurie Forio ◽  
Mijail Arias-Hidalgo ◽  
...  
Keyword(s):  
River Basin ◽  
Assessment Tool ◽  
Model Development ◽  
Model Performance ◽  
Water Quality Monitoring ◽  
Freshwater Ecosystem ◽  
Set Up ◽  
The Impact ◽  
Water Assessment ◽  
Soil And Water

Agricultural intensification has stimulated the economy in the Guayas River basin in Ecuador, but also affected several ecosystems. The increased use of pesticides poses a serious threat to the freshwater ecosystem, which urgently calls for an improved knowledge about the impact of pesticide practices in this study area. Several studies have shown that models can be appropriate tools to simulate pesticide dynamics in order to obtain this knowledge. This study tested the suitability of the Soil and Water Assessment Tool (SWAT) to simulate the dynamics of two different pesticides in the data scarce Guayas River basin. First, we set up, calibrated and validated the model using the streamflow data. Subsequently, we set up the model for the simulation of the selected pesticides (i.e., pendimethalin and fenpropimorph). While the hydrology was represented soundly by the model considering the data scare conditions, the simulation of the pesticides should be taken with care due to uncertainties behind essential drivers, e.g., application rates. Among the insights obtained from the pesticide simulations are the identification of critical zones for prioritisation, the dominant areas of pesticide sources and the impact of the different land uses. SWAT has been evaluated to be a suitable tool to investigate the impact of pesticide use under data scarcity in the Guayas River basin. The strengths of SWAT are its semi-distributed structure, availability of extensive online documentation, internal pesticide databases and user support while the limitations are high data requirements, time-intensive model development and challenging streamflow calibration. The results can also be helpful to design future water quality monitoring strategies. However, for future studies, we highly recommend extended monitoring of pesticide concentrations and sediment loads. Moreover, to substantially improve the model performance, the availability of better input data is needed such as higher resolution soil maps, more accurate pesticide application rate and actual land management programs. Provided that key suggestions for further improvement are considered, the model is valuable for applications in river ecosystem management of the Guayas River basin.

scholarly journals Application of SWAT (Soil and Water Assessment Tool) to the Abay River Basin of Ethiopia: The Case of Didessa Sub Basin

2018 ◽  
Author(s):  
Timketa Adula Duguma
Keyword(s):  
River Basin ◽  
Time Scale ◽  
Assessment Tool ◽  
Peak Flow ◽  
Swat Model ◽  
Distributed Model ◽  
Statistical Measures ◽  
Sensitive Parameters ◽  
Water Assessment ◽  
Soil And Water

Abstract: In this study the semi-distributed model SWAT (Soil and Water Assessment Tool), were applied to evaluate stream flow of Didessa sub basin, which is one of the major sub basins in Abay river basin of Ethiopia. The study evaluated the quality of observed meteorological and hydrological data, established SWAT hydrological model, identified the most sensitive parameters, evaluated the best distribution for flow and developed peak flow for major tributary in the sub basin. The result indicated that the SWAT model developed for the sub basin evaluated at multi hydro-gauging stations and its performance certain with the statistical measures, coefficient about determination (R2) and also Nash coefficient (NS) with values ranging 0.62 to 0.8 and 0.6 to 0.8 respectively at daily time scale. The values of R2 and NS increases at monthly time scale and found ranging 0.75 to 0.92 and 0.71 to 0.91 respectively. Sensitivity analysis is performed to identify parameters those were most sensitive for the sub basin. CN2, GWQMN, CH_K, ALPHA_BNK and LAT_TIME are the most sensitive parameters in the sub basin. Finally, the peak flow for 2-10000 returns periods were determined after the best probability distribution is identified in EasyFit computer program.

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