The water conservation function (WCF), as one of the most critical ecosystem services, has an important impact on the ecological sustainability of a region. Accurately characterizing the spatiotemporal heterogeneity of WCF and further exploring its driving factors are of great significance for river basin management. Here, the WCF of the upper Yangtze River basin (UYRB) from 1991 to 2020 was calculated using the water yield module in the Integrated Valuation of Ecosystem Service and Tradeoffs (InVEST) model. Also, we innovatively applied emerging hot spot analysis (EHSA), which could describe the location and pattern of historical changes more accurately, to investigate the spatiotemporal heterogeneity and evolution of WCF. Based on the Geographical Detector Model (GDM), the main driving factors of WCF and their interactions were revealed. The results showed the following: (1) the WCF in the UYRB experienced a temporal increase at a growth rate of 1.48 mm/a, while remarkable differences were observed across the change rates of sub-watersheds. (2) The spatial variation of the WCF showed a gradual increase from northwest to southeast. Interestingly, the Jinshajing River upstream (JSJU) source area with a low WCF showed an increasing trend (with diminishing cold spots). On the contrary, the downstream regions of the JSJU watershed (with intensifying cold spots) underwent a weakening WCF. (3) Among all driving factors, precipitation (q = 0.701) exhibited the most remarkable prominent impact on the spatial heterogeneity of the WCF. Additionally, the interaction of factors exhibited more explanatory power than each factor alone, such as precipitation and saturated soil hydraulic conductivity (q = 0.840). This research study is beneficial to water resource management and provides a theoretical basis for ecological restoration.

Improving the agricultural water resources allocation efficiency (AWRAE) and promoting the efficient and intensive utilization of agricultural water resources and high-quality development is an effective path to alleviate the water scarcity in one basin. In this study, the AWRAE and its influencing factors were measured and evaluated by constructing the evaluation system of the AWRAE in nine provinces (autonomous regions) of the Yellow River Basin, which consists of the super-efficiency slacks-based model (SBM), standard deviation ellipse (SDE), spatial autocorrelation analysis, Malmquist index and Tobit regression model. The results show that the value of AWRAE is 0.768 and it is at the medium level in the whole Yellow River Basin. The AWRAE values in the nine provinces (autonomous regions) ranking from large to small are Sichuan > Shaanxi > Ningxia > Henan > Inner Mongolia > Shanxi > Qinghai > Shandong > Gansu, and the AWRAE values show a significant increasing trend in Shanxi, Henan, Inner Mongolia and Shandong. The gravity center of the AWRAE keeps wandering along the provincial boundaries of Gansu and Shaanxi, which presents a counterclockwise rotation trend; the AWRAE of Shaanxi exhibits significant H-H aggregation in 2000, 2005, 2010, and 2015 (p < 0.05) while the agglomeration is not significant in 2020. The AWRAE has been continuously improved in which the technological progress change (Techch) and technical efficiency change (Effch) play an important positive role while the pure technical efficiency change (Pech) acts as the negative role in the Yellow River Basin. Moreover, the key influencing factors on the AWRAE in different provinces and autonomous regions are significantly different; for example, the total power of agricultural machinery (AMTP) has a significant positive effect on AWRAE in most provinces, but the annual average precipitation (AAP), agricultural water (AW), water saving irrigated area (WIA) and water saving irrigation machinery (WIM) have significant negative effects on the efficiency of AWRAE in Qinghai. The research results can provide quantitative support for agricultural water-saving and stable grain yield increase in the Yellow River Basin.