scholarly journals Runoff Simulation in the Upper Reaches of Heihe River Basin Based on the RIEMS–SWAT Model

Water ◽  
2016 ◽  
Vol 8 (10) ◽  
pp. 455 ◽  
Author(s):  
Songbing Zou ◽  
Hongwei Ruan ◽  
Zhixiang Lu ◽  
Dawen Yang ◽  
Zhe Xiong ◽  
...  
Keyword(s):  
River Basin ◽  
Swat Model ◽  
Heihe River Basin ◽  
Heihe River ◽  
Runoff Simulation

scholarly journals Runoff Simulation by SWAT Model Using High-Resolution Gridded Precipitation in the Upper Heihe River Basin, Northeastern Tibetan Plateau

Water ◽  
2017 ◽  
Vol 9 (11) ◽  
pp. 866 ◽  
Author(s):  
Hongwei Ruan ◽  
Songbing Zou ◽  
Dawen Yang ◽  
Yuhan Wang ◽  
Zhenliang Yin ◽  
...  
Keyword(s):  
High Resolution ◽  
Tibetan Plateau ◽  
River Basin ◽  
Swat Model ◽  
Heihe River Basin ◽  
Heihe River ◽  
Runoff Simulation ◽  
Northeastern Tibetan Plateau

Integrated numerical model for irrigated area water resources management

2019 ◽  
Vol 11 (4) ◽  
pp. 980-991 ◽  
Author(s):  
Aidi Huo ◽  
Xiaofan Wang ◽  
Yan Liang ◽  
Cheng Jiang ◽  
Xiaolu Zheng
Keyword(s):  
River Basin ◽  
Water Resource Management ◽  
Assessment Tool ◽  
Swat Model ◽  
Hydrologic Model ◽  
Heihe River Basin ◽  
Irrigation District ◽  
Heihe River ◽  
Model Parameters ◽  
Long Term Effects

Abstract The likelihood of future global water shortages is increasing and further development of existing operational hydrologic models is needed to maintain sustainable development of the ecological environment and human health. In order to quantitatively describe the water balance factors and transformation relations, the objective of this article is to develop a distributed hydrologic model that is capable of simulating the surface water (SW) and groundwater (GW) in irrigation areas. The model can be used as a tool for evaluating the long-term effects of water resource management. By coupling the Soil and Water Assessment Tool (SWAT) and MODFLOW models, a comprehensive hydrological model integrating SW and GW is constructed. The hydrologic response units for the SWAT model are exchanged with cells in the MODFLOW model. Taking the Heihe River Basin as the study area, 10 years of historical data are used to conduct an extensive sensitivity analysis on model parameters. The developed model is run for a 40-year prediction period. The application of the developed coupling model shows that since the construction of the Heihe reservoir, the average GW level in the study area has declined by 6.05 m. The model can accurately simulate and predict the dynamic changes in SW and GW in the downstream irrigation area of Heihe River Basin and provide a scientific basis for water management in an irrigation district.

scholarly journals The China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) Application in China: A Case Study in Heihe River Basin

2017 ◽  
Author(s):  
Xian-yong Meng ◽  
Hao Wang ◽  
Si-yu Cai ◽  
Xue-song Zhang ◽  
Guo-yong Leng ◽  
...  
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Hydrologic Modeling ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Heihe River Basin ◽  
Heihe River ◽  
Climate Data ◽  
Weather Stations

Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluatedtheir applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.

Distributed SWAT Model for Ecological Remediation Project Assessment

2014 ◽  
Vol 915-916 ◽  
pp. 1460-1463
Author(s):  
Yu Hang Wei ◽  
De Shan Tang ◽  
Yi Fan Ding
Keyword(s):  
River Basin ◽  
River Runoff ◽  
Swat Model ◽  
Heihe River Basin ◽  
Natural State ◽  
Heihe River ◽  
Effect Assessment ◽  
Project Assessment ◽  
Improved Model ◽  
Ecological Remediation

In arid area, ecological remediation aims at decreasing soil erosion by foresting. Distributed SWAT model is further improved model of integrated model, capable of analyzing the relation between river runoff, sediment and land use change by human activities. In this study, distributed SWAT model is built in the Heihe River Basin to simulate watershed water and sand conditions, and natural state of river runoff and sediment without ecological remediation project is estimated. Significant differences are observed between the estimated natural state runoff and sediment and conditions after the remediation projects. This provides valuable reference for effect assessment of Heihe River Basin ecological remediation project.

scholarly journals The China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) and it's Application in the Heihe River Basin in China

2016 ◽  
Author(s):  
Hao Wang ◽  
Xian-yong Meng ◽  
Si-yu Cai ◽  
Xue-song Zhang ◽  
Xiao-hui Lei ◽  
...  
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Hydrologic Modeling ◽  
Hydrological Modeling ◽  
Swat Model ◽  
Heihe River Basin ◽  
Heihe River ◽  
Climate Data ◽  
Weather Stations ◽  
The Heihe River Basin

Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data. Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluated their applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.

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