Understanding and quantifying changes in hydrological systems due to human interference are critical for the implementation of adaptive management of global water resources in the changing environment. To explore the implications of hydrological variations for water resources management, the Wuding River Basin (WRB) in the Loess Plateau, China, was selected as a case study. Based on the Budyko-type equation with a time-varying parameter n, a human-induced water–energy balance (HWEB) model was proposed to investigate the hydrological variability in the WRB. The investigation showed that runoff continuously reduced by 0.424 mm/a during 1975–2010, with weakly reducing precipitation and increasing groundwater exploitation causing a decrease in groundwater storage at a rate of 1.07 mm/a, and actual evapotranspiration accounting for more than 90% of precipitation having an insignificantly decreasing trend with a rate of 0.53 mm/a under climate change (decrease) and human impact (increase). Attribution analysis indicated that human-induced underlying surface condition change played a dominant role in runoff reduction by driving an increase in actual evapotranspiration, and that mainly impacted the overall decrease in runoff compounded by climate change during the entire period. It is suggested that reducing the watershed evapotranspiration and controlling groundwater exploitation should receive greater attention in future basin management.
The purpose of this study is to illustrate intrinsic correlations and their temporal evolution between hydro-meteorological elements by building three-element-composed system, including precipitation (P), runoff (R), air temperature (T), evaporation (pan evaporation, E), and sunshine duration (SD) in the Wuding River Basin (WRB) in Loess Plateau, China, and to provide regional experience to correlational research of global hydro-meteorological data. In analysis, detrended partial cross-correlation analysis (DPCCA) and temporal evolution of detrended partial-cross-correlation analysis (TDPCCA) were employed to demonstrate the intrinsic correlation, and detrended cross-correlation analysis (DCCA) coefficient was used as comparative method to serve for performance tests of DPCCA. In addition, a novel way was proposed to estimate the contribution of a variable to the change of correlation between other two variables, namely impact assessment of correlation change (IACC). The analysis results in the WRB indicated that (1) DPCCA can analyze the intrinsic correlations between two hydro-meteorological elements by removing potential influences of the relevant third one in a complex system, providing insights on interaction mechanisms among elements under changing environment; (2) the interaction among P, R, and E was most strong in all three-element-composed systems. In elements, there was an intrinsic and stable correlation between P and R, as well as E and T, not depending on time scales, while there were significant correlations on local time scales between other elements, i.e., P-E, R-E, P-T, P-SD, and E-SD, showing the correlation changed with time-scales; (3) TDPCCA drew and highlighted the intrinsic correlations at different time-scales and its dynamics characteristic between any two elements in the P-R-E system. The results of TDPCCA in the P-R-E system also demonstrate the nonstationary correlation and may give some experience for improving the data quality. When establishing a hydrological model, it is suitable to only use P, R, and E time series with significant intrinsic correlation for calibrating model. The IACC results showed that taking pan evaporation as the representation of climate change (barring P), the impacts of climate change on the non-stationary correlation of P and R was estimated quantitatively, illustrating the contribution of climate to the correlation variation was 30.9%, and that of underlying surface and direct human impact accounted for 69.1%. IntroductionComplex hydro-meteorological systems contain various interactions among hydro-meteorological elements [1,2]. Investigating cross-correlations and teleconnections between hydro-meteorological signals benefits to deeply understanding the whole hydrological system and to serve for water resources management [3]. Under the influences of changing climate and anthropogenic disturbance [4], the single hydro-meteorological time series and their interaction relationships tend to exhibit complex [5,6], non-stationary [7], and multi-scale [8] chang...
Under changing environment, the feasibility and potential impact of an inter-basin water transfer project can be evaluated by employing the coincidence probability of runoff in water sources area (WSA), water receiving area (WRA), and the downstream impacted area (DIA). Using the Han River to Wei River Water Transfer Project (HWWTP) in China as an example, this paper computed the coincidence probability and conditional probability of runoff in WSA, WRA and DIA with the copula-based multivariate joint distribution and quantified their acceptable and unfavorable encounter probabilities for evaluating the water supply risk of the water transfer project and exploring its potential impact on DIA. Results demonstrated that the most adverse encounter probability (dry–dry–dry) was 26.09%, illustrating that this adverse situation could appear about every 4 years. The acceptable and unfavorable probabilities in all encounters were 44.83 and 55.17%, respectively, that is the unfavorable situation would be dominant, implying flood and drought risk management should be paid greater attention in project operation. The conditional coincidence probability (dry WRA & dry DIA if dry WSA) was close to 70%, indicating a requirement for an emergency plan and management to deal with potential drought risk.
Natural streamflow reconstruction is highly significant to assess long-term trends, variability, and pattern of streamflow, and is critical for addressing implications of climate change for adaptive water resources management. This study proposed a simple statistical approach named NSR-SVI (natural streamflow reconstruction based on streamflow variation identification). As a hybrid model coupling Pettitt's test method with an iterative algorithm and iterative cumulative sum of squares algorithm, it can determine the reconstructed components and implement the recombination depending only on the information of change points in observed annual streamflow records. Results showed that NSR-SVI is suitable for reconstructing natural series and can provide the stable streamflow processes under different human influences to better serve the hydrologic design of water resource engineering. Also, the proposed approach combining the cumulative streamflow curve provides an innovative way to investigate the attributions of streamflow variation, and the performance has been verified by comparing with the relevant results in nearby basin.
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