Effects of soil data resolution on SWAT model stream flow and water quality predictions

2008 ◽  
Vol 88 (3) ◽  
pp. 393-406 ◽  
Author(s):  
Mengistu Geza ◽  
John E. McCray
Keyword(s):  
Water Quality ◽  
Stream Flow ◽  
Swat Model ◽  
Data Resolution

A Review on SWAT Model for Stream Flow Simulation

2013 ◽  
Vol 726-731 ◽  
pp. 3792-3798
Author(s):  
Wen Ju Zhao ◽  
Wei Sun ◽  
Zong Li Li ◽  
Yan Wei Fan ◽  
Jian Shu Song ◽  
...  
Keyword(s):  
Spatial Data ◽  
Stream Flow ◽  
Assessment Tool ◽  
Swat Model ◽  
Flow Simulation ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Rs And Gis ◽  
Model Research ◽  
Gis And Rs

SWAT (Soil and Water Assessment Tool) model is one of distributed hydrological model, based on spatial data offered by GIS and RS. This article mainly introduces the SWAT model principle, structure, and it is the application of stream flow simulation in China and other countries, then points out the deficiency existing in the process of model research. In order to service in water resources management work better, experts and scholars further research the rate constant and uncertainty of the simplification of the model parameters, and the combination of RS and GIS to use, and hydrological scale problems.

Impact of climate change on streamflow and water quality in the upper Dong Nai river basin, Vietnam

2018 ◽  
pp. 70-79 ◽  
Author(s):  
Le Viet Thang ◽  
Dao Nguyen Khoi ◽  
Ho Long Phi
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
River Basin ◽  
Sediment Load ◽  
Swat Model ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Nutrient Load ◽  
Impact Of Climate Change ◽  
The Impact

In this study, we investigated the impact of climate change on streamflow and water quality (TSS, T-N, and T-P loads) in the upper Dong Nai River Basin using the Soil and Water Assessment Tool (SWAT) hydrological model. The calibration and validation results indicated that the SWAT model is a reasonable tool for simulating streamflow and water quality for this basin. Based on the well-calibrated SWAT model, the responses of streamflow, sediment load, and nutrient load to climate change were simulated. Climate change scenarios (RCP 4.5 and RCP 8.5) were developed from five GCM simulations (CanESM2, CNRM-CM5, HadGEM2-AO, IPSL-CM5A-LR, and MPI-ESM-MR) using the delta change method. The results indicated that climate in the study area would become warmer and wetter in the future. Climate change leads to increases in streamflow, sediment load, T-N load, and T-P load. Besides that, the impacts of climate change would exacerbate serious problems related to water shortage in the dry season and soil erosion and degradation in the wet season. In addition, it is indicated that changes in sediment yield and nutrient load due to climate change are larger than the corresponding changes in streamflow.

scholarly journals Modelling the hydrology and water quality of 3S river system (Sekong, Sesan and Srepok)

2016 ◽  
Vol 19 (2) ◽  
pp. 107-117
Author(s):  
Trang Thi Thuy Nguyen ◽  
Khoi Nguyen Dao
Keyword(s):  
Water Quality ◽  
Swat Model ◽  
Model Performance ◽  
River System ◽  
Water Quality Assessment ◽  
River Basin Management ◽  
Analysis Tool ◽  
Nitrogen And Phosphorus ◽  
Model Soil

The objective of this study was to simulate the hydrologic characteristic and water quality of 3S rivers system (Sekong, Sesan and Srepok) using SWAT model (Soil and Water Analysis Tool). Agriculture and forest are the main land use types in this basin accounting for more than 80 % of the total area. Therfore, nitrogen and phosphorus were selected to be parameters for water quality assessment. SWAT-CUP model was applied to calibrate the model for stream flow and water quality based on SUFI-2 (Sequential Uncertainty Fitting version 2) method. The model performance has been assessed by three statistical indices, including coefficient corellation (R2), Nash-Sutcliffe efficient coefficience (NSE) and percentage Bias (PBIAS). The results showed that SWAT model was well calibrated for simulating the streamflow and water quality with the values of R2 greater than 0.5 except for the Attapeu and Kontum stations, and of PBIAS less than 10 % and 35 % for streamflow and water quality, respectively. The well-calibrated SWAT model can be applied in predicting the hydrology and water quality for other application. Furthermore, it is a tool supporting the policy makers to offer a suitable decisions regarding the sustainable river basin management.

scholarly journals Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 115 ◽  
Author(s):  
Roxelane Cakir ◽  
Mélanie Raimonet ◽  
Sabine Sauvage ◽  
Javier Paredes-Arquiola ◽  
Youen Grusson ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Water Resources ◽  
Stream Water ◽  
Swat Model ◽  
Water Yield ◽  
Observation Data ◽  
Hydrological Alteration ◽  
Water Quality And Quantity ◽  
The Impact

Modeling is a useful way to understand human and climate change impacts on the water resources of agricultural watersheds. Calibration and validation methodologies are crucial in forecasting assessments. This study explores the best calibration methodology depending on the level of hydrological alteration due to human-derived stressors. The Soil and Water Assessment Tool (SWAT) model is used to evaluate hydrology in South-West Europe in a context of intensive agriculture and water scarcity. The Index of Hydrological Alteration (IHA) is calculated using discharge observation data. A comparison of two SWAT calibration methodologies are done; a conventional calibration (CC) based on recorded in-stream water quality and quantity and an additional calibration (AC) adding crop managements practices. Even if the water quality and quantity trends are similar between CC and AC, water balance, irrigation and crop yields are different. In the context of rainfall decrease, water yield decreases in both CC and AC, while crop productions present opposite trends (+33% in CC and −31% in AC). Hydrological performance between CC and AC is correlated to IHA: When the level of IHA is under 80%, AC methodology is necessary. The combination of both calibrations appears essential to better constrain the model and to forecast the impact of climate change or anthropogenic influences on water resources.

scholarly journals Comparative Analysis of Bioenergy Crop Impacts on Water Quality Using Static and Dynamic Land Use Change Modeling Approach

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 410 ◽  
Author(s):  
Eeshan Kumar ◽  
Dharmendra Saraswat ◽  
Gurdeep Singh
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Land Use Change ◽  
Assessment Tool ◽  
Swat Model ◽  
State Agency ◽  
Bioenergy Crops ◽  
Marginal Land ◽  
Cache River ◽  
Land Area

Researchers and federal and state agency officials have long been interested in evaluating location-specific impact of bioenergy energy crops on water quality for developing policy interventions. This modeling study examines long-term impact of giant miscanthus and switchgrass on water quality in the Cache River Watershed (CRW) in Arkansas, United States. The bioenergy crops were simulated on marginal lands using two variants of a Soil and Watershed Assessment Tool (SWAT) model. The first SWAT variant was developed using a static (single) land-use layer (regular-SWAT) and for the second, a dynamic land-use change feature was used with multiple land use layers (location-SWAT). Results indicated that the regular-SWAT predicted larger losses for sediment, total phosphorus and total nitrogen when compared to location-SWAT at the watershed outlet. The lower predicted losses from location-SWAT were attributed to its ability to vary marginal land area between 3% and 11% during the 20-year modeling period as opposed to the regular-SWAT that used a fixed percentage of marginal land area (8%) throughout the same period. Overall, this study demonstrates that environmental impacts of bioenergy crops were better assessed using the dynamic land-use representation approach, which would eliminate any unintended prediction bias in the model due to the use of a single land use layer.

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