Assessing NEXRAD P3 Data Effects on Stream-Flow Simulation Using SWAT Model in an Agricultural Watershed

2012 ◽  
Vol 17 (11) ◽  
pp. 1245-1254 ◽  
Author(s):  
R. K. Gali ◽  
K. R. Douglas-Mankin ◽  
X. Li ◽  
T. Xu
Keyword(s):  
Stream Flow ◽  
Swat Model ◽  
Flow Simulation ◽  
Agricultural Watershed

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.

scholarly journals Calibration of SWAT and three data-driven models for monthly stream flow simulation in Maharlu Lake Basin

2021 ◽  
Author(s):  
Fatemeh Moazami Goudarzi ◽  
Amirpouya Sarraf ◽  
Hassan Ahmadi
Keyword(s):  
Machine Learning ◽  
Support Vector Regression ◽  
Computational Intelligence ◽  
Stream Flow ◽  
River Flow ◽  
Swat Model ◽  
Flow Simulation ◽  
Support Vector ◽  
Lake Basin ◽  
Computational Intelligence Methods

Abstract In this study, the performance of SWAT hydrological model and three computational intelligence methods used to simulate river flow are investigated. After collecting the data required for all models used, the calibration and validation stages were performed. Using the SWAT model and three methods of the Extreme Machine Learning (EML), the Support Vector Regression (SVR), and the Least Squares Support Vector Regression (LSSVR), Maharlu Lake Basin stream flow was simulated and the results obtained at Shiraz station were used for this study. A noise reduction filter was employed to improve the results from the computational intelligence methods, and SUFI-2 algorithm was used to analyze the uncertainty of the SWAT model. Finally, in order to evaluate the models developed and the SWAT model, three statistics (RMSE), (R²), and (NS) coefficient were used. The results indicated that the SWAT model and the machine learning models were generally appropriate tools for daily flow modeling, but the LSSVR model showed less errors in both learning and testing, with the coefficients NS = 0.997 and R² = 0.997 in the calibration stage and NS = 0.994 and R² = 0.994 in the validation stage, which prove their better performance compared to the other methods and the SWAT model.

scholarly journals Stream flow simulation and verification in ungauged zones by coupling hydrological and hydrodynamic models: a case study of the Poyang Lake ungauged zone

2017 ◽  
Author(s):  
Ling Zhang ◽  
Jianzhong Lu ◽  
Xiaoling Chen ◽  
Sabine Sauvage ◽  
José-Miguel Sanchez Perez
Keyword(s):  
Water Balance ◽  
Stream Flow ◽  
Poyang Lake ◽  
Swat Model ◽  
Flow Simulation ◽  
Lake Basin ◽  
Observation Data ◽  
Stream Flows ◽  
Covered Area ◽  
The Impact

Abstract. To solve the problem of estimating and verifying stream flows without direct observation data; we extend existing techniques for estimating stream flows in ungauged zones, coupling a hydrological model with a hydrodynamic model, using the Poyang Lake basin as a test case. We simulated stream flows in the land covered area of the ungauged zone by building a SWAT model for the entire catchment area covering gauged stations and the land covered area; then estimated stream flows in the water covered area of the ungauged zone using the simplified water balance equation. To verify the results, we built two scenarios (original and adjusted scenarios) using the Delft3D model. In this study, the original scenario did not take stream flows in the ungauged zone into consideration, unlike the adjusted scenario that accounts for the ungauged zones. Experimental results show there was a narrower discrepancy between the stream flows observed at the outlet of the lake and the simulated stream flows in adjusted scenario. Using our technique, we estimated that the ungauged zone of Poyang Lake produces stream flows of approximately 180 billion m3; representing about 11.4 % of the total inflow from the entire watershed. We also analysed the impact of the stream flows in ungauged zone on the water balance between inflow and outflow of the lake. These results, incorporating the estimated stream flow in ungauged zone, significantly improved the water balance as indicated by R2 with higher value and percent bias with lower value, as compared to the results when the stream flows in the ungauged zone were not taken into account, R2 with lower value and percent bias with higher value. The method can be extended to other lake, river, or ocean basins where observation data is unavailable.

scholarly journals Validation of SWAT model for stream flow simulation and forecasting in Upper Bernam humid tropical river basin, Malaysia

2009 ◽  
Vol 6 (6) ◽  
pp. 7581-7609 ◽  
Author(s):  
A. W. Alansi ◽  
M. S. M. Amin ◽  
G. Abdul Halim ◽  
H. Z. M. Shafri ◽  
W. Aimrun
Keyword(s):  
Land Use ◽  
River Basin ◽  
Irrigation Water ◽  
Stream Flow ◽  
Swat Model ◽  
Land Use Changes ◽  
Land Development ◽  
Flow Simulation ◽  
Low Flow ◽  
Tropical River

Abstract. The study was to evaluate SWAT model for flow simulation and forecasting in the Upper Bernam humid tropical river basin, which is the main source of irrigation water supply for a rice granary. Land use in the study area has rapidly changed from the year of 1984 until today. The study was conducted using 27 years of records (1981–2007). Calibration was performed for the period of 1981 through 2004 while, the period of 2005 through 2007 for the validation of both simulation and forecasting of flow. During calibration, the annual and monthly results were 0.82, 0.65, 0.81 and 0.62 for R2 and ENS, respectively and 0.99, 0.93, 0.98 and 0.92, respectively during validation. As for forecasting validation, were 0.88, 0.78, 0.86 and 0.74 for R2 and ENS, respectively. In general model shows good performance in flow simulating as well as forecasting. Five scenarios were performed to identify the individual effect of mixed land use change on stream flow. The scenarios results demonstrate, land use changes are responsible for an increase in the annual flow depth between 8% to 39% while 16% to 59% during high flow months and decreases between 3% to 32% during low flow months. Flow forecasting for the year 2020 using 30 forecasting cycles which found to be the optimal for the study area was performed. The results show decrease by 50% below the monthly irrigation water demand during low flow months, which emphasize the need to include structured best management practices (BMPs) such as ponds to the study area future land development plan to mitigate the future changes in land use on flow quantity. This study showed that SWAT was able to simulate and forecast flow in humid tropical condition successfully and can be used to study the effects of future land use changes on flow.

scholarly journals Evaluating the accuracy of C- and X-band weather radars and their application for stream flow simulation

2012 ◽  
Vol 15 (4) ◽  
pp. 1121-1136 ◽  
Author(s):  
N. K. Shrestha ◽  
T. Goormans ◽  
P. Willems
Keyword(s):  
Conceptual Model ◽  
Stream Flow ◽  
Flow Simulation ◽  
Winter Storms ◽  
Weather Radars ◽  
X Band ◽  
Rainfall Estimates

This paper investigates the accuracy of rainfall estimates from C- and X-band weather radars and their application for stream flow simulation. Different adjustment procedures are applied to raw radar estimates using gauge readings from a network of 12 raingauges. The stream flow is simulated for the 48.17 km2 Molenbeek/Parkbeek catchment located in the Flemish region of Belgium based on a lumped conceptual model. Results showed that raw radar estimates can be greatly improved using adjustment procedures. The gauge-radar residuals however, remain large even after adjustments. The adjusted X-band radar estimates are observed to be better estimates than corresponding C-band estimates. Their application for stream flow simulation showed that raingauges and radars can simulate spatially more uniform winter storms with almost the same accuracy, whereas differences are more evident on summer events.

Study on nitrogen load reduction efficiency of agricultural conservation management in a small agricultural watershed

2014 ◽  
Vol 69 (8) ◽  
pp. 1689-1696 ◽  
Author(s):  
Xiaoli Liu ◽  
Qiuwen Chen ◽  
Zhaoxia Zeng
Keyword(s):  
Assessment Tool ◽  
Conservation Management ◽  
Swat Model ◽  
Black Soil ◽  
Agricultural Watershed ◽  
Load Reduction ◽  
Agricultural Conservation ◽  
Nitrogen Loads ◽  
Reduction Efficiency ◽  
The Impact

Different crops can generate different non-point source (NPS) loads because of their spatial topography heterogeneity and variable fertilization application rates. The objective of this study was to assess nitrogen NPS load reduction efficiency by spatially adjusting crop plantings as an agricultural conservation management (ACM) measure in a typical small agricultural watershed in the black soil region in northeast China. The assessment was undertaken using the Soil and Water Assessment Tool (SWAT). Results showed that lowland crops produce higher nitrogen NPS loads than those in highlands. It was also found that corn gave a comparatively larger NPS load than soybeans due to its larger fertilization demand. The ACM assessed was the conversion of lowland corn crops into soybean crops and highland soybean crops into corn crops. The verified SWAT model was used to evaluate the impact of the ACM action on nitrogen loads. The results revealed that the ACM could reduce NO3-N and total nitrogen loads by 9.5 and 10.7%, respectively, without changing the area of crops. Spatially optimized regulation of crop planting according to fertilizer demand and geological landscapes can effectively decrease NPS nitrogen exports from agricultural watersheds.

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