期刊
FRONTIERS IN EARTH SCIENCE
卷 9, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/feart.2021.677191
关键词
water resources; blue water; green water; climate change; parallel parameter calibration method; prediction uncertainty; SWAT
This study analyzes the spatiotemporal variations in blue and green water resources in the Xiangjiang River Basin under historical and future climate change scenarios. By using an improved model calibration method, it is found that blue water resources and green water storage will decrease, while green water flow will increase in the future. Incorporating green water into future water resource management in the region is deemed essential.
Green water resources, which are fundamental for plant growth and terrestrial ecosystem services, reflect precipitation that infiltrates into the unsaturated soil layer and returns to the atmosphere by plant transpiration and soil evaporation through the hydrological cycle. However, green water is usually ignored in water resource assessments, especially when considering future climate impacts, and green water modeling generally ignores the calibration of evapotranspiration (ET), which might have a considerable impact on green water resources. This study analyzes the spatiotemporal variations in blue and green water resources under historical and future climate change scenarios by applying a distributed hydrological model in the Xiangjiang River Basin (XRB) of the Yangtze River. An improved model calibration method based on remotely sensed MODIS ET data and observed discharge data is used, and the results show that the parallel parameter calibration method can increase the simulation accuracy of blue and green water while decreasing the output uncertainties. The coefficients (p-factor, r-factor, KGE, NSE, R ( 2 ), and PBIAS) indicate that the blue and green water projections in the calibration and validation periods exhibit good performance. Blue and green water account for 51.9 and 48.1%, respectively, of all water resources in the historical climate scenario, while future blue and green water projections fluctuate to varying degrees under different future climate scenarios because of uncertainties. Blue water resources and green water storage in the XRB will decrease (5.3-21.8% and 8.8-19.7%, respectively), while green water flow will increase (5.9-14.7%). Even taking the 95% parameter prediction uncertainty (95 PPU) range into consideration, the future increasing trend of the predicted green water flow is deemed satisfactory. Therefore, incorporating green water into future water resource management is indispensable for the XRB. In general, this study provides a basis for future blue and green water assessments, and the general modeling framework can be applied to other regions with similar challenges.
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