In the context of climate change, the problem of water scarcity is becoming increasingly serious, and improving the efficiency of water resources use is an important measure to alleviate this problem. The evaluation of water resources utilization efficiency has become the basis of water resource management. Data envelopment analysis (DEA) and analytic hierarchy process (AHP) are widely used in the evaluation of water resources utilization efficiency. However, one of these methods is mostly used for evaluation, which cannot reflect the influence of both objective and subjective factors. Therefore, in this study, we propose a water resources utilization efficiency index (WEI) to evaluate the water resources utilization efficiency of each region in the Tumen River Basin (TRB), combining both DEA and AHP methods. Firstly, the DEA-CCR model was used to quantify domestic, agricultural and industrial water use efficiency in the TRB. The DEA-BCC model was used to analyze the main influences on water use efficiency in each sector. Secondly, the WEI was constructed by assigning weights using the AHP model based on the importance of each water use sector. The results show that the WEI values for most areas within the TRB trended upwards between 2014 and 2019. In particular, domestic water use efficiency ranged from 0.294 to 0.775, while agricultural and industrial water use efficiency ranged from 0.039 to 0.054 and 0.031 to 0.375, respectively. Technical efficiency is the main factor influencing water use efficiency in TRB. This study could provide a basis for water resource management and mitigation of water scarcity in the context of climate change.

The Daqinghe River Basin is located in the North China Plain. In recent years, however, climate warming, drying, and intense human activities have led to declining ecosystem functions and shrinking wetlands in the region. Understanding streamflow changes in the upstream mountainous areas of the Daqinghe River Basin in this changing environment and identifying the driving factors can provide a scientific basis for water resources management and optimization in these areas. This study focuses on the Beihedian River watershed, the Xidayang Reservoir watershed, and the Wangkuai Reservoir watershed in the upstream mountainous areas of the Daqinghe River. It is based on hydro-meteorological data collected between 1963 and 2019. The methods used in the study include the linear tendency estimation method, the non-parametric Mann-Kendall trend test, the elasticity coefficient method, and hydrological simulation methods. The results of this study suggest that the streamflow, precipitation, and potential evapotranspiration (PET) in the three watersheds showed an overall decreasing trend. The minimum precipitation decrease rate ranged from −1.09 to −0.55 mm/a, and the minimum streamflow decreasing rate at the Beihedian Hydrological Station was −1.32 mm/a, with a minimum range of 0–176.03 mm. Change-point analysis revealed that the streamflow in the Beihedian River and Xidayang Reservoir watersheds experienced a significant change point around 1999, with a significant level of α=0.05. As for the Wangkuai Reservoir watershed, a significant change point was observed around 1980, which is likely attributable to land system reforms and protective forest projects. The attribution analysis which combined both climate change and human activities using the elasticity coefficient method and hydrological simulation methods indicated that climate change contributed an average of 32.93%, 34.50%, and 35.12% to the reduction in streamflow in the three watersheds, respectively. Human activities accounted for an average contribution of 67.07%, 65.50%, and 64.88%, respectively. Water conservancy projects, afforestation, and other human activities were identified as the primary factors contributing to streamflow decreases.