Hongjuan Zhang

Water resources are the foundation of human survival and development. Thus, it is essential to quantify the relationship between water supply and demand and assess water security to ensure sustainable use of water resources. In this study, we quantified the relationship between water supply and demand in the Yiluo River Basin (YRB) using the InVEST model, constructed a spatial flow model of water provision service at the sub-watershed scale, and analyzed the water security index (WSI) under static and dynamic conditions. Subsequently, we used geographic detectors to identify the explanatory power of the main influencing factors of the WSI. The results showed that (1) from 2005 to 2018, the water supply decreased continuously and the water demand first increased and then decreased in the YRB; (2) the spatial pattern of WSI showed that it was high in the southwest and low in the northeast, wherein the highest and lowest WSI values occurred in 2005 and 2018, respectively. From 2005 to 2018, the mean values of the static and dynamic WSI decreased from 0.77 to 0.60 and 1.56 to 1.20, respectively. (3) The precipitation factor from the supply dimension and the gross domestic product (GDP) factor from the demand dimension had the strongest explanatory power for the static WSI. For the dynamic WSI, the flow quantity of the water provision service flow had the strongest explanatory power. This study provided a reference for governments to formulate sustainable water resource management.

Using the Google Earth Engine (GEE) platform, Moderate-resolution image spectroradiometer (MODIS) data of the Weihe River Basin from 2001 to 2021 were acquired, four ecological indicators, namely, greenness, wetness, heat, and dryness, were extracted, and the remote sensing ecological index (RSEI) was constructed through principal component analysis. In addition, the geographic detectors and a multi-scale geographic weighted regression model (MGWR) were used to identify the main driving factors of RSEI changes and capture the differences in spatial changes from different perspectives using multiple indicators. The results show that (1) the quality of the eco-environment in the Weihe River basin improved as a whole from 2001 to 2021, and the RSEI increased from 0.376 to 0.414. In terms of the RSEI grade, the medium RSEI and high RSEI areas increased significantly and the growth rate increased significantly, reaching 26.42% and 27.70%, respectively. (2) Spatially, the quality of the eco-environment in the Weihe River Basin exhibited a spatial distribution pattern that was high in the south and low in the north, among which the quality of the eco-environment in the Weihe River Basin in northern Shaanxi and northwestern Ningxia and Gansu was relatively low. In addition, during the study period, the RSEI of the Qinling Mountains in the southern part of the Weihe River Basin and the Jinghe River and Luohe River areas improved significantly. The urban area on the Guanzhong Plain in the Weihe River Basin experienced rapid economic growth, and urban expansion led to a significant decrease in the quality of the eco-environment. (3) The eco-environment quality in the Weihe River Basin is the result of the interaction of natural, anthropogenic, and landscape pattern factors. All of the interactions between the influencing factors had a stronger influence than those of the individual factors. There were significant differences between the individual drivers and the spatial variation in RSEI, suggesting that different factors dominate the variation in RSEI in different regions, and zonal management is crucial to achieving sustainable management of RSEI. The study shows that to improve the eco-environment quality of the Weihe River Basin, it is necessary to further strengthen ecological protection projects, reasonably allocate landscape elements, and strengthen the resistance and resilience of the ecosystem.

Urban riverfront space has diversified ecosystem services, but due to excessive changes in the geographical environment, such as drastic changes in land use, people gain social value at a great ecological cost. Obtaining benefits from the ecosystem in this way is not sustainable. Therefore, this paper uses the SolVES model to evaluate the social value of ecosystem services on the east bank of the Fenghe River, while also studying the contribution of different environmental variables to social value. The main results are as follows. (1) Environmental variables affect the spatial distribution characteristics of social value. The distance to water (DTW) means the social value was distributed in strips, and the distance to road (DTR) concentrated the social value along the road. The landscape type (LT) means the social value was concentrated in the landscape space. (2) When DTW, DTR, and LT were collectively used as environmental variables, the distribution characteristics of various social values were similar to when LT was used as the only environmental variable. (3) The results of MaxEnt show that LT made a greater contribution to the aesthetic, recreation, therapeutic, and historic values, and was the largest contribution factor to the aesthetic, therapeutic, and historic values, with contribution rates of 47.6, 50.5, and 80.0%, respectively. DTW is the factor that contributed the most to recreation, with a contribution rate of 43.1%. Improving social value based on the influence and contribution of environmental variables can reduce the damage to the ecological environment caused by changes in geographic factors. This is sustainable for both the ecosystem and the services it provides to mankind.