The predictions of flood hazard over the design life of a hydrological project are of great importance for hydrological engineering design under the changing environment. The concept of a nonstationary flood hazard has been formulated by extending the geometric distribution to account for time-varying exceedance probabilities over the design life of a project. However, to our knowledge, only time covariate is used to estimate the nonstationary flood hazard over the lifespan of a project, which lacks physical meaning and may lead to unreasonable results. In this study, we aim to strengthen the physical meaning of nonstationary flood hazard analysis by investigating the impacts of climate change and population growth. For this purpose, two physical covariates, i.e., rainfall and population, are introduced to improve the characterization of nonstationary frequency over a given design lifespan. The annual maximum flood series of Xijiang River (increasing trend) and Weihe River (decreasing trend) are chosen as illustrations, respectively. The results indicated that: (1) the explanatory power of population and rainfall is better than time covariate in the study areas; (2) the nonstationary models with physical covariates possess more appropriate statistical parameters and thus are able to provide more reasonable estimates of a nonstationary flood hazard; and (3) the confidences intervals of nonstationary design flood can be greatly reduced by employing physical covariates. Therefore, nonstationary flood design and hazard analysis with physical covariates are recommended in changing environments.

Desert terminal lakes are important signals to discern ecological degradation crises, particularly in arid areas where an artificial project of ecological water diversion has designated a quota of river water to prevent lake body shrinkage and protect the ecosystem. Knowledge of the minimum ecological water demand (EWD) is thus necessary to ensure the basic health of lake ecosystems. This study analyzed the spatiotemporal evolution of water boundaries using Landsat satellites data via remote sensing technology from 2002 to 2017 in East Juyan Lake, an inland desert terminal lake of the Heihe River in northwest China. The minimum lake water demand was determined using two estimation methods: the lake-evaporation-oriented EWD method and the minimum water level method. In the latter method, both lake topography (using water-level area curves) and biological survival demands (using bighead carps as indicators) were considered to derive the minimum lake EWD. Water diversion to the lake over the past 15 years has increased the lake’s area, but there are still marked intra-annual seasonal variations. The annual minimum lake water demand was suggested to be 54 × 10⁶ m³/year by comparing the different methods; however, it was not satisfied, and the lake survival was endangered when the occurrence frequency of the annual runoff in the Zhengyixia hydrological station exceeded 65%. This study offered promising directions for inland lake water resource management.

Water resources, energy, and food are essential for the development of society, and they are strongly interdependent. The coupling and coordination relationships of the water–energy–food (WEF) system are important for regional resource security and high-quality development. The Yellow River Irrigation Area in Shandong Province, China, is a grain production base and has a substantial impact on national food security. To examine the water, energy, and food subsystem dynamics in this area, an evaluation system for the WEF system was established. A comprehensive weighting method based on game theory was employed to determine index weights. TOPSIS was used to assess the development level of the WEF system. A coupling coordination degree model was used to analyze the evolution of the coupling coordination degree of the WEF system from 2000 to 2020, and a GWR model was constructed to explore the spatial heterogeneity of its driving factors. The findings indicated that the development level of the WEF system in the study area was moderate, with a gradual upward trend. The coupling coordination degree fluctuated between 0.62 and 0.739. The GWR model revealed that temperature had an overall negative effect on the coupling coordination degree, with the greatest impact on the central irrigation area; the slope and NDVI had a negative effect, with increasing intensity from the southwest to the northeast; and rainfall had an overall positive effect, with the greatest impact on the irrigation area near the estuary in the northeast. Overall, the building area ratio had a negative effect on the coupling coordination degree, with exceptions in some areas. These research outcomes provide theoretical support for sustainable agricultural development in the Yellow River irrigation areas of Shandong Province and methodological reference data for studying collaborative resource utilization in irrigation regions.