LI Feng; LI Yaoming; ZHOU Xuewen; YIN Zun; LIU Tie; XIN Qinchuan
Water shortage is one bottleneck that limits economic and social developments in arid and semi-arid areas. As the impacts of climate change and human disturbance intensify across time, uncertainties in both water resource supplies and demands increase in arid and semi-arid areas. Taking a typical arid region in China, Xinjiang Uygur Autonomous Region, as an example, water yield depth (WYD) and water utilization depth (WUD) from 2002 to 2018 were simulated using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and socioeconomic data. The supply-demand relationships of water resources were analyzed using the ecosystem service indices including water supply-demand difference (WSDD) and water supply rate (WSR). The internal factors in changes of WYD and WUD were explored using the controlled variable method. The results show that the supply- demand relationships of water resources in Xinjiang were in a slight deficit, but the deficit was alleviated due to increased precipitation and decreased WUD of irrigation. WYD generally experienced an increasing trend, and significant increase mainly occurred in the oasis areas surrounding both the Junggar Basin and Tarim Basin. WUD had a downward trend with a decline of 20.70%, especially in oasis areas. Water resources in most areas of Xinjiang were fully utilized and the utilization efficiency of water resources increased. The water yield module in the InVEST model was calibrated and validated using gauging station data in Xinjiang, and the result shows that the use of satellite-based water storage data helped to decrease the bias error of the InVEST model by 0.69×108 m3. This study analyzed water resource supplies and demands from a perspective of ecosystem services, which expanded the scope of the application of ecosystem services and increased the research perspective of water resource evaluation. The results could provide guidance for water resource management such as spatial allocation and structural optimization of water resources in arid and semi-arid areas.
Durdiev KHAYDAR; CHEN Xi; HUANG Yue; Makhmudov ILKHOM; LIU Tie; Ochege FRIDAY; Abdullaev FARKHOD; Gafforov KHUSEN; Omarakunova GULKAIYR
|High water consumption and inefficient irrigation management in the agriculture sector of the middle and lower reaches of the Amu Darya River Basin (ADRB) have significantly influenced the gradual shrinking of the Aral Sea and its ecosystem. In this study, we investigated the crop water consumption in the growing seasons and the irrigation water requirement for different crop types in the lower ADRB during 2004–2017. We applied the FAO Penman–Monteith method to estimate reference evapotranspiration (ET0) based on daily climatic data collected from four meteorological stations. Crop evapotranspiration (ETc) of specific crop types was calculated by the crop coefficient. Then, we analyzed the net irrigation requirement (NIR) based on the effective precipitation with crop water requirements. The results indicated that the lowest monthly ET0 values in the lower ADRB were found in December (18.2 mm) and January (16.0 mm), and the highest monthly ET0 values were found in June and July, with similar values of 211.6 mm. The annual ETc reached to 887.2, 1002.1, and 492.0 mm for cotton, rice, and wheat, respectively. The average regional NIR ranged from 514.9 to 715.0 mm in the 10 Irrigation System Management Organizations (UISs) in the study area, while the total required irrigation volume for the whole region ranged from 4.2×109 to 11.6×109 m3 during 2004–2017. The percentages of NIR in SIW (surface irrigation water) ranged from 46.4% to 65.2% during the study period, with the exceptions of the drought years of 2008 and 2011, in which there was a significantly less runoff in the Amu Darya River. This study provides an overview for local water authorities to achieve optimal regional water allocation in the study area.|
BA Wulong; DU Pengfei; LIU Tie; BAO Anming; LUO Min; Mujtaba HASSAN; QIN Chengxin
|Climate change may affect water resources by altering various processes in natural ecosystems. Dynamic and statistical downscaling methods are commonly used to assess the impacts of climate change on water resources. Objectively, both methods have their own advantages and disadvantages. In the present study, we assessed the impacts of climate change on water resources during the future periods (2020–2029 and 2040–2049) in the upper reaches of the Kaidu River Basin, Xinjiang, China, and discussed the uncertainties in the research processes by integrating dynamic and statistical downscaling methods (regional climate models (RCMs) and general circulation modes (GCMs)) and utilizing these outputs. The reference period for this study is 1990–1999. The climate change trend is represented by three bias-corrected RCMs (i.e., Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA), Regional Climate Model version 4 (RegCM4), and Seoul National University Meso-scale Model version 5 (SUN-MM5)) and an ensemble of GCMs on the basis of delta change method under two future scenarios (RCP4.5 and RCP8.5). We applied the hydrological SWAT (Soil and Water Assessment Tool) model which uses the RCMs/GCMs outputs as input to analyze the impacts of climate change on the stream flow and peak flow of the upper reaches of the Kaidu River Basin. The simulation of climate factors under future scenarios indicates that both temperature and precipitation in the study area will increase in the future compared with the reference period, with the largest increase of annual mean temperature and largest percentage increase of mean annual precipitation being of 2.4°C and 38.4%, respectively. Based on the results from bias correction of climate model outputs, we conclude that the accuracy of RCM (regional climate model) simulation is much better for temperature than for precipitation. The percentage increase in precipitation simulated by the three RCMs is generally higher than that simulated by the ensemble of GCMs. As for the changes in seasonal precipitation, RCMs exhibit a large percentage increase in seasonal precipitation in the wet season, while the ensemble of GCMs shows a large percentage increase in the dry season. Most of the hydrological simulations indicate that the total stream flow will decrease in the future due to the increase of evaporation, and the maximum percentage decrease can reach up to 22.3%. The possibility of peak flow increasing in the future is expected to higher than 99%. These results indicate that less water is likely to be available in the upper reaches of the Kaidu River Basin in the future, and that the temporal distribution of flow may become more concentrated.|