scholarly journals Application and Evaluation of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) in Poorly Gauged Regions in Western China

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2171 ◽  
Author(s):  
Xianyong Meng ◽  
Xuesong Zhang ◽  
Mingxiang Yang ◽  
Hao Wang ◽  
Ji Chen ◽  
...  

The temporal and spatial differentiation of the underlying surface in East Asia is complex. Due to a lack of meteorological observation data, human cognition and understanding of the surface processes (runoff, snowmelt, soil moisture, water production, etc.) in the area have been greatly limited. With the Heihe River Basin, a poorly gauged region in the cold region of Western China, selected as the study area, three meteorological datasets are evaluated for their suitability to drive the Soil and Water Assessment Tool (SWAT): China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS), Climate Forecast System Reanalysis (CFSR), and Traditional Weather Station (TWS). Resultingly, (1) the runoff output of CMADS + SWAT mode is generally better than that of the other two modes (CFSR + SWAT and TWS + SWAT) and the monthly and daily Nash–Sutcliffe efficiency ranges of the CMADS + SWAT mode are 0.75–0.95 and 0.58–0.77, respectively; (2) the CMADS + SWAT and TWS + SWAT results were fairly similar to the actual data (especially for precipitation and evaporation), with the results produced by CMADS + SWAT lower than those produced by TWS + SWAT; (3) the CMADS + SWAT mode has a greater ability to reproduce water balance than the other two modes. Overestimation of CFSR precipitation results in greater error impact on the uncertainty output of the model, whereas the performances of CMADS and TWS are more similar. This study addresses the gap in the study of surface processes by CMADS users in Western China and provides an important scientific basis for analyzing poorly gauged regions in East Asia.

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1305 ◽  
Author(s):  
Xin Han ◽  
Zheng Wei ◽  
Baozhong Zhang ◽  
Congying Han ◽  
Jianzheng Song

The adjustment of crop planting structure can change the process of water and material circulation, and thus affect the total amount of water and evapotranspiration in the irrigation district. To guide the allocation of water resources in the region, it is beneficial to ascertain the effects of changing the crop planting structure on water saving and farmland water productivity in the irrigation district. This paper takes Yingke Irrigation District as the background. According to the continuous observation data from 2012 to 2013, Based on the modified Soil and Water Assessment Tool (SWAT) model and taking advantage of monthly scale remote sensing EvapoTranspiration (ET) and crop growth parameters (leaf area index and shoot dry matter), we tested the simulation accuracy of the model, proposed irrigation efficiency calculation methods considering water drainage, and established the scenario analysis method for the spatial distribution of crop planting structure. Finally, we evaluated the changes in water savings in irrigation district projects and resources, the irrigation water productivity and the net income water productivity under different planting structure scenarios. The results indicate that the efficiency of irrigation has increased by 15~20%, while considering drainage, as compared with conventional irrigation efficiency. Additionally, the adjustment of crop planting structure can reduce regional evapotranspiration by 14.9%, reduce the regional irrigation volume by 30%, and increase the net income of each regional water area by 16%.


2019 ◽  
Vol 11 (4) ◽  
pp. 980-991 ◽  
Author(s):  
Aidi Huo ◽  
Xiaofan Wang ◽  
Yan Liang ◽  
Cheng Jiang ◽  
Xiaolu Zheng

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.


Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1177 ◽  
Author(s):  
Lufang Zhang ◽  
Baolin Xue ◽  
Yuhui Yan ◽  
Guoqiang Wang ◽  
Wenchao Sun ◽  
...  

Distributed hydrological models play a vital role in water resources management. With the rapid development of distributed hydrological models, research into model uncertainty has become a very important field. When studying traditional hydrological model uncertainty, it is very common to use multisite observation data to evaluate the performance of the model in the same watershed, but there are few studies on uncertainty in watersheds with different characteristics. This study is based on the Soil and Water Assessment Tool (SWAT) model, and uses two common methods: Sequential Uncertainty Fitting Version 2 (SUFI-2) and Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis. We compared these methods in terms of parameter uncertainty, model prediction uncertainty, and simulation effects. The Xiaoqing River basin and the Xinxue River basin, which have different characteristics, including watershed geography and scale, were used for the study areas. The results show that the GLUE method had better applicability in the Xiaoqing River basin, and that the SUFI-2 method provided more reasonable and accurate analysis results in the Xinxue River basin; thus, the applicability was higher. The uncertainty analysis method is affected to some extent by the characteristics of the watershed.


2020 ◽  
Author(s):  
Yu Deng ◽  
Zhifeng Guo ◽  
Fuquan Ni ◽  
Lianqing Xue ◽  
Yiping Wu ◽  
...  

Abstract Drought research under climate change is of great scientific significance. For Land Use and Land Cover Change (LUCC), temperature and rainfall in climate change, which factor has a greater impact on runoff change in alpine mountainous areas? Can the increase of rainfall in the alpine mountainous area completely eliminate the drought driven by temperature rise? This study takes the upper reaches of Heihe River basin (URHRB) as an example, the URHRB's Soil and Water Assessment Tool (SWAT) model is constructed. Based on 58 scenarios and The Budyko Framework, here we show that a)climate change has a greater contribution to runoff than LUCC, effect of increased rainfall greater than temperature rising on runoff in alpine mountainous area; b)the drought of 57.14% of UHRRB’s sub-basins have eased, 42.86% of the sub-basins is more serious, the increase in rainfall can't completely eliminate the drought driven by temperature rise. This study coupling SWAT simulation with Budyko Framework and other methods solves the problem of lack of data in alpine mountainous areas, and more accurately quantifies the impact of climate change, LUCC on runoff changes, realizing theoretical and method innovation. The results of this study provide a scientific paradigm for solving scientific problems in similar regions in China and other countries, and have important promotion value.


Author(s):  
Yuejian Wang ◽  
Guang Yang ◽  
Xinchen Gu ◽  
Xinlin He ◽  
Yongli Gao ◽  
...  

Abstract Precise simulations of hydrological processes under the influence of climate change and human activities have special significance in arid basins. During the past 60 years, the annual average temperature and precipitation at the northern foothills of the Tianshan Mountains have increased at the rates of 0.035 °C/year and 0.881 mm/year, respectively. Rising temperatures will change the temporal and spatial distributions and forms of precipitation, accelerate glacier retreat, melt snow on high mountains, cause the degeneration of frozen soil, and change the runoff composition in the Tianshan area. In this work, the CMADS (China Meteorological Assimilation Driving Dataset for the SWAT model) was combined with the SWAT (Soil and Water Assessment Tool) model to simulate runoff in the upper reaches of the Jing River and Bo River Basins in the Tianshan area. The results were as follows. (1) On the monthly scale, the average Nash–Sutcliffe efficiency (NSE) coefficients of the calibration period in the Wenquan and Jinghe–Shankou hydrological stations were 0.79 and 0.87, respectively, and the NSE coefficients of validation period were 0.71 and 0.82, respectively. On the daily scale, the NSE coefficients of the two hydrological stations were between 0.69 and 0.77. The simulation results were considered to be ideal on the monthly and daily scales. (2) Under different climate scenarios and land-use patterns, the cultivated land in the basin leads to the reduction of runoff, and the grassland and woodland stabilise the river flood season. Lakes and wetlands, which can reduce the flow in the flood season and provide water for rivers in the dry season, are very important for runoff regulation. Compared with the traditional meteorological stations, CMADS demonstrates good representativeness and reliability in the Jinghe River and Bohe River Basins under different climate and land-use scenarios, greatly improving the runoff simulation ability.


2017 ◽  
Vol 21 (11) ◽  
pp. 5847-5861 ◽  
Author(s):  
Ling Zhang ◽  
Jianzhong Lu ◽  
Xiaoling Chen ◽  
Dong Liang ◽  
Xiaokang Fu ◽  
...  

Abstract. To solve the problem of estimating and verifying stream flow without direct observation data, we estimated stream flow in ungauged zones by coupling a hydrological model with a hydrodynamic model, using the Poyang Lake basin as a test case. To simulate the stream flow of the ungauged zone, we built a soil and water assessment tool (SWAT) model for the entire catchment area covering the upstream gauged area and ungauged zone, and then calibrated the SWAT model using the data in the gauged area. To verify the results, we built two hydrodynamic scenarios (the original and adjusted scenarios) for Poyang Lake using the Delft3D model. In the original scenario, the upstream boundary condition is the observed stream flow from the upstream gauged area, while, in the adjusted scenario, it is the sum of the observed stream flow from the gauged area and the simulated stream flow from the ungauged zone. The experimental results showed that there is a stronger correlation and lower bias (R2 = 0.81, PBIAS  =  10.00 %) between the observed and simulated stream flow in the adjusted scenario compared to that (R2 = 0.77, PBIAS  =  20.10 %) in the original scenario, suggesting the simulated stream flow of the ungauged zone is reasonable. Using this method, we estimated the stream flow of the Poyang Lake ungauged zone as 16.4 ± 6.2 billion m3 a−1, representing ∼ 11.24 % of the annual total water yield of the entire watershed. Of the annual water yield, 70 % (11.48 billion m3 a−1) is concentrated in the wet season, while 30 % (4.92 billion m3 a−1) comes from the dry season. The ungauged stream flow significantly improves the water balance with the closing error decreased by 13.48 billion m3 a−1 (10.10 % of the total annual water resource) from 30.20 ± 9.1 billion m3 a−1 (20.10 % of the total annual water resource) to 16.72 ± 8.53 billion m3 a−1 (10.00 % of the total annual water resource). The method can be extended to other lake, river, or ocean basins where observation data is unavailable.


Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 897 ◽  
Author(s):  
Xin Jin ◽  
Yanxiang Jin

The calibration of hydrological models is often complex in regions with scarce data, and generally only uses site-based streamflow data. However, this approach will yield highly generalised values for all model parameters and hydrological processes. It is therefore necessary to obtain more spatially heterogeneous observation data (e.g., satellite-based evapotranspiration (ET)) to calibrate such hydrological models. Here, soil and water assessment tool (SWAT) models were built to evaluate the advantages of using ET data derived from the Global Land surface Evaporation Amsterdam Methodology (GLEAM) to calibrate the models for the Bayinhe River basin in northwest China, which is a typical data-scarce basin. The result revealed the following: (1) A great effort was required to calibrate the SWAT models for the study area to obtain an improved model performance. (2) The SWAT model performance for simulating the streamflow and water balance was reliable when calibrated with streamflow only, but this method of calibration grouped the hydrological processes together and caused an equifinality issue. (3) The combination of the streamflow and GLEAM-based ET data for calibrating the SWAT model improved the model performance for simulating the streamflow and water balance. However, the equifinality issue remained at the hydrologic response unit (HRU) level.


2020 ◽  
Vol 12 (15) ◽  
pp. 6177
Author(s):  
Xiaoyu Song ◽  
Yuqing Liu ◽  
Fanglei Zhong ◽  
Xiaohong Deng ◽  
Yuan Qi ◽  
...  

Quantitative evaluation of the relationship between payment criteria and the amount of additional ecosystem services can improve the cost-effectiveness of payment for ecosystem services (PES) projects. This paper simulated additional water conservation (AWC) using the Soil and Water Assessment Tool (SWAT) model, examined appropriate payment criteria, and matched different payment modes with local herders’ preferences in Northwest China. The results showed that if all the low-coverage grass areas were to be closed through PES projects, the actual payment criteria, 37 yuan/ha, would need to be increased eight times, which would be 302 yuan/ha. Along with that, annual AWC could reach 1.69 × 106 m3. If PES projects were implemented in all the low- and medium-coverage grass areas, payment criteria would need to be increased to 365 yuan/ha, and the annual AWC would reach 2.59 × 106 m3. There were scale economy effects in this range, because a 21% increase in the payment criteria would result in a 66% increase in the total AWC. The appropriate mode for herders above 40 years old is “cash + in-kind compensation” and “cash + capacity” for those below 40, due to the preferences varying in age.


Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 97 ◽  
Author(s):  
Chuanfu Zang ◽  
Ganquan Mao

Research on relationship between green and blue water flow and ecosystem service functions has great significance for improving water resources management and for ecological protection. In this study, the distribution patterns and service functions of green and blue water flow in different ecosystems were analysed by Soil and Water Assessment Tool (SWAT) model simulation and Correlational Analysis. In the entire basin, the amount of green and blue water flow in the grassland was greater than that in the cropland, and that in the cropland was larger than that in the forest. The corn yield per hectare of cropland was highest in the Heihe River Basin, followed by wheat, and the lowest yield was the oil yield from 2000 to 2010. The mutton yield in the grassland ecosystem was greater than the beef yield from 2000 to 2010, which shows that the beef production would consume more water flow. Results show an obvious positive correlation between green or blue water flow and wheat and corn yields. Beef and mutton had a significant correlation with blue water flow, whereas mutton had a stronger correlation with green water flow.


Author(s):  
Xian-yong Meng ◽  
Hao Wang ◽  
Si-yu Cai ◽  
Xue-song Zhang ◽  
Guo-yong Leng ◽  
...  

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.


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