摘 要: |
Water scarcity greatly hinders sustainable development goal agenda and regional agriculture development in dryland regions. As we know, land use and cover changes are strongly responsible for spatial-temporal evolutions of water resource. However, there is little explicit understanding of how spatial patterns of future dryland use will affect the water supply-demand risk. To answer this question, this study took Yulin city of China, a typical dryland region, as a case study area, and firstly estimated its 2020-2050 land use patterns under three different scenarios, covering Natural Increased Scenario (NIS), Food Security Scenario (FSS) and Economic Development Scenario (EDS), with the help of the path-generating land use simulation (PLUS) model as well as Markov-chain model. Furthermore, this study employed InVEST model to explicitly investigate spatial-temporal evolutions of water supply, water demand and water supply-demand risk in all scenarios. The estimated results indicated that the largest expanding/shrinking land use types were grasslands/croplands in NIS, croplands/ grasslands in FSS and built-up lands/croplands in EDS during 2020-2050, respectively. By 2050, all projected land use changes only slightly affected regional water supply (the fluctuation of - 5% compared to that in 2020), but greatly increased by - 57% regional water demand. Particularly, strong land use changes would likely put nearly 90% regions of Yulin city at endangered water supply-demand risk in 2020-2050. Ecological land and built-up land would easier suffer from critically endangered water supply-demand risk. In view of these modeled and analyzed results, some potential mitigation strategies of water resource utilization, such as developing waterefficient eco-agriculture, adjusting agricultural structures and enriching revegetation diversity, were suggested to coordinate future areal human-nature relationships. This study could provide some valuable information for dryland agricultural development, water-environment management and regional policy decision-making. |