Previous studies that quantified variations in runoff have mainly focused on the combined impacts of climate and human activities or climate and land cover change. Few have separated land cover change from human activities, which is critical for effective management of water resources. This study aims to investigate the impact of changing environmental conditions on runoff using the Soil and Water Assessment Tool (SWAT) model; we examined three categories: climate, land cover change and direct human activities. The study area was the Wei River Basin, a typical arid to semi-arid basin that was divided into five sub-zones (UZ, MZ, DZ, JZ and BZ). Our results showed the following: (1) the calibrated SWAT model produced satisfactory monthly flow processes over the baseline period from 1978 to 1986; (2) compared to the baseline period, the impact of climatic variations decreased and the impact of direct human activities increased from the 1990s to the 2000s, while the impact of land cover change was generally stable; and (3) climatic variations were the main cause of runoff declines over the entire basin during the 1990s and in the UZ, MZ and JZ areas during the 2000s, while direct human activities were most important in the DZ and BZ areas during the 2000s.

Pumped water storage (PWS) is an advanced component of interbasin water transfer (IBWT) projects that plays a critical role in addressing streamflow variability. However, improper operating rules result in a large amount of unnecessary pumping and spills, wasting water resources and energy. Here, multiobjective optimization (MO) was applied to develop effective operating rules for PWS with the objectives of minimizing the water shortage index and maximizing the net revenues of consumed and produced energy. A metaheuristic algorithm named cuckoo search was used to optimize the decision variables in the framework of parameterization–simulation–optimization. Additionally, the water diversion performance of PWS and parallel reservoirs (without pumped storage) were compared. The Han to Wei IBWT project in northwest China was selected for a case study. The results indicate that (1) the proposed MO model and adopted methods are effective for derivation of PWS operating rules, improving water use benefits and decreasing operational costs significantly; (2) the two optimization goals established in the MO model conflict (increasing water supply reliability will decrease the net revenue of energy); and (3) when the water diversion target is relatively small, parallel reservoirs outperform PWS; however, PWS is superior to parallel reservoirs when the water diversion target increases.

This study investigates the runoff-sediment relationship (RSR) of the Weihe River, a sandy waterway originating from the Loess Plateau, and considers the potential variations in RSR under an evolving environment. The double mass curve method was used to investigate RSR inflection points at six hydrologic stations located in the Weihe River basin (WRB) spanning the period from 1956 to 2010. Because of its ability to accurately define nonlinear and asymmetric correlations between variables, the Copula function provided the joint probability distributions and revealed the joint probabilities of annual runoff and sediment yield through different periods. The results indicated: (1) The sediment yield and runoff exhibit decreasing trends, which was principally related to human activity such as soil and water conservation measures, water projects and industrial and domestic water use, (2) the RSR inflection points principally occurred around 1983 at the Weijiabu, Xianyang, Huaxian and Zhuangtou stations, whereas they were non-significant at the Linjiacun and Zhangjiashan stations. Changes in RSR are attributed to the irregular effect of human activity reducing the runoff and sediment output; and (3) the joint probability distributions of annual runoff and sediment yield varied under an evolving environment and were characterized by spatial variability, which is more evident in the mainstream areas of the Weihe River than in the tributary regions.

Copula functions have been extensively used to describe the joint behaviors of extreme hydrological events and to analyze hydrological risk. Advanced marginal distribution inference, for example, the maximum entropy theory, is particularly beneficial for improving the performance of the copulas. The goal of this paper, therefore, is twofold; first, to develop a coupled maximum entropy-copula method for hydrological risk analysis through deriving the bivariate return periods, risk, reliability and bivariate design events; and second, to reveal the impact of marginal distribution selection uncertainty and sampling uncertainty on bivariate design event identification. Particularly, the uncertainties involved in the second goal have not yet received significant consideration. The designed framework for hydrological risk analysis related to flood and extreme precipitation events is exemplarily applied in two catchments of the Loess plateau, China. Results show that (1) distribution derived by the maximum entropy principle outperforms the conventional distributions for the probabilistic modeling of flood and extreme precipitation events; (2) the bivariate return periods, risk, reliability and bivariate design events are able to be derived using the coupled entropy-copula method; (3) uncertainty analysis highlights the fact that appropriate performance of marginal distribution is closely related to bivariate design event identification. Most importantly, sampling uncertainty causes the confidence regions of bivariate design events with return periods of 30 years to be very large, overlapping with the values of flood and extreme precipitation, which have return periods of 10 and 50 years, respectively. The large confidence regions of bivariate design events greatly challenge its application in practical engineering design.