Search

In the wake of global and regional climate change and heightened human activities, runoff from some rivers in the world, especially in the arid and semi-arid regions, has significantly decreased. To reveal the varying characteristics leading to the change in runoff, detecting the influencing factors has been important in recent scientific discussions for water resources management in drainage basins. In this paper, an investigation into attributing the runoff response to climate change and human activities were conducted in two catchments (Wushan and Shetang), situated in the upper reaches of Weihe River in China. Prior to the identification of the factors that influenced runoff changes, the Mann-Kendall test was adopted to identify the trends in hydro-climate series. Also, change-points in the annual runoff were detected through Pettitt's test and the precipitation-runoff double cumulative curve method. It is found that both catchments presented significant negative trend in annual runoff and the detected change-point in runoff occurs in 1993. Hence, the pre-change period and post-change period are defined before and after 1993, respectively. Then, runoff response to climate change and human activities was quantitatively evaluated on the basis of hydrologic sensitivity analysis and hydrologic model simulation. They provided similar estimates of the percentage change in mean annual runoff for the post-change period over the considered catchments. It is found that the decline in annual runoff over both catchments can be mainly attributed to the human activities, the reduction percentages due to human activities range from 59 to 77 %. The results of this study can provide a reference for the development, utilization and management of the regional water resources and ecological environment protection. [ABSTRACT FROM AUTHOR]

Abstract: Works of hydrologic model development at the preliminary stage, e.g., determination of flow direction and the order of flow concentration, extraction of drainage network, and spatial interpolation, are very important. In this paper, a preprocessing program is developed with multiple functions for data preparation in hydrologic model. The method in graph theory is used to determine the flow direction, and filling of sink is avoided in this study. A new method, the so-called leaf clipping method, is proposed for watershed division, and the order of runoff concentration is determined according to the flow direction and DEM data. This preprocessing program is developed by using Visual Basic language, detailed algorithms are presented and the program is demonstrated through a case study in the Wei River basin. It shows that this program is useful and helpful for the application of hydrologic models which only needs digital elevation data sets. [Copyright &y& Elsevier]

Irrigation is the greatest human interference with the terrestrial water cycle. Detailed knowledge on irrigation is required to better manage water resources and to increase water use efficiency (WUE). This study applies a framework to quantify net irrigation at monthly timescale at a spatial resolution of 1 km2 providing high spatial and temporal detail for regional water resources management. The study is conducted in the Haihe River Basin (HRB) in China encompassing the North China Plain (NCP), a global hot spot of groundwater depletion. Net irrigation is estimated based on the systematic evapotranspiration (ET) residuals between a remote sensing‐based model and a hydrologic model that does not include an irrigation scheme. The results suggest an average annual net irrigation of 126 mm yr−1 (15.2 km3 yr−1) for NCP and 108 mm yr−1 (18.6 km3 yr−1) for HRB. It is found that net irrigation can be estimated with higher fidelity for winter crops than for summer crops. The simulated water balance for NCP is evaluated with Gravity Recovery and Climate Experiment (GRACE) data, and the net irrigation estimates can close the water balance gap. Annual winter wheat classifications reveal an increasing crop area with a trend of 2,200 km2 yr−1. This trend is not accompanied by a likewise increasing trend in irrigation water use, which suggests an increased WUE in the NCP, which is further supported by net primary productivity data. The proposed framework has potential to be transferred to other regions and support decision makers to support sustainable water management. Plain Language Summary: The irrigation of agricultural fields is taking place at unsustainable rates in many regions of the world. Despite the fact that irrigation is the largest anthropogenic impact on the natural water cycle, there exists limited knowledge of the applied irrigation amounts. This study applies an approach to estimate net irrigation, that is, the evaporative loss of irrigation water. The approach is applied on the Haihe River Basin in North‐Eastern China. For the estimation of net irrigation, two sources of evapotranspiration (ET) are considered. First, baseline ET is obtained from a rainfed hydrologic model without irrigation. Second, ET is obtained from a satellite remote sensing model, which represents rainfed and irrigated ET. We study the ET differences of the two sources to derive net irrigation amounts at monthly timescale at 1 km2 spatial resolution. Our analysis suggest an average annual net irrigation of 108 mm yr−1 (18.6 km3 yr−1). The results are evaluated against annual winter wheat classification maps as well as satellite‐based net primary productivity data and total water storage data (Gravity Recovery and Climate Experiment, GRACE). Our results indicate an increasing water use efficiency as a result of promoting water savings in the agricultural sector. Key Points: Net irrigation can be quantified by evapotranspiration residuals derived from hydrologic models and satellite remote sensingEstimation of winter wheat irrigation has lower uncertainty than estimation of irrigation of summer cropsIrrigation water use efficiency has improved in the North Chin Plain in the period 2002–2016 [ABSTRACT FROM AUTHOR]

The effects of global climate change threaten the availability of water resources worldwide and modify their tempo-spatial pattern. Properly quantifying the possible effects of climate change on water resources under different hydrological models is a great challenge in ungauged alpine regions. By using remote sensing data to support established models, this study aimed to reveal the effects of climate change using two models of hydrological processes including total water resources, peak flows, evapotranspiration, snowmelt and snow accumulation in the ungauged Hotan River Basin under future representative concentration pathway (RCP) scenarios. The results revealed that stream flow was much more sensitive to temperature variation than precipitation change and increased by 0.9-10.0% according to MIKE SHE or 6.5-10.5% according to SWAT. Increased evapotranspiration was similar for both models with a range of 7.6-31.3%. The snow-covered area shrank from 32.5% to 11.9% between the elevations of 4200-6400 m, respectively, and snow accumulation increased when the elevation exceeded 6400 m above sea level (asl). The results also suggested that the fully distributed and semi-distributed structures of these two models strongly influenced the responses to climate change. The study proposes a practical approach to assess the climate change effect in ungauged regions. [ABSTRACT FROM AUTHOR]

The estimation of distribution algorithm(EDA) is a newevolutionary algorithm developed as an alternative to the traditional genetic algorithm (GA). The EDA guides the search by avoiding the crossover and mutation operators of the GA in favor of building and sampling probabilistic distributions of promising candidate solutions. By increasing the probability of generating solutions with better fitness values, the EDA locates the region of the global optimum or its accurate approximation. In this study, EDAwas used to calibrate the parameters of the soil and water assessment tool hydrologic model for the Xunhe River Basin in China. The EDAwas compared with three other algorithms: (1) the Multistart Local Metric Stochastic Radial Basis Function algorithm (a surrogate optimization method), (2) the Shuffled Complex Evolution algorithm, and (3) the GA. Four metrics are presented to assess the performance of the algorithms: (1) efficiency in terms of the average best objective function value in a limited number of function evaluations, (2) variability in terms of standard deviation and the box plot, (3) reliability in terms of the empirical cumulative distribution function, and (4) accuracy in terms of the Nash–Sutcliffe efficiency coefficient and overall volume error. Results indicated that the EDA is more efficient and could provide more accurate solutions with a relatively high probability, at least for this case study. [ABSTRACT FROM AUTHOR]

The Palmer indices (PIs) that have been most widely used for drought monitoring and assessment are criticized for two main drawbacks: coarse hydrological accounting processes with a simplified two-stage bucket soil water balance model and arbitrary rules for defining drought properties and standardizing index values through limited calibration and comparison. In this study, we introduce a new proposal of the VIC hydrologic model-based Palmer drought scheme, where traditional PIs (e.g. PDSI) can readily be calculated on the basis of distributed finescale hydrologic simulations. Moreover, recent variants of PI (i.e., SPDI and SPDI-JDI) also provide a preferable standardization strategy that allows probabilistic invariability and better spatio-temporal comparability of computed drought indices. Using gridded meteorological forcing, soil and vegetation data to drive the three-layer VIC model, both non-VIC and VIC-based PIs are investigated to examine their performances for drought characterization and detection. Results indicate that VIC hydrologic model would allow for adjustments in statistical properties of computed PDSI and VIC-based SPDI is also preferable to PDSI for better statistical robustness and spatio-temporal consistency/comparability. Moreover, the joint SPDI-JDI has the strength of integrating multi-scale probabilistic properties and drought information released by individual SPDI, providing overall drought conditions that take into account the onset, persistence and termination of droughts. At proposed 0.25° grid scale, the VIC-based SPDI-JDI indicates high frequency and long total time of drought condition in the Yellow River basin (YRB), China. Although no significant temporal trends are found in identified drought duration and severity, both the seasonal and annual drought index values demonstrate a downward trend (higher drought intensity) for considerable proportions of the YRB. These findings imply high drought risk and potential drying stress for this region. The new framework of hydrologic model-based PIs can help to strengthen our knowledge and/or practices in regional drought monitoring and assessment. [ABSTRACT FROM AUTHOR]

Much attention has recently been focused on the effects that climate variability and human activities have had on runoff. In this study, these effects are quantified using three methods, namely, multi-regression, hydrologic sensitivity analysis, and hydrologic model simulation. A conceptual framework is defined to separate the effects. As an example, the change in annual runoff from the semiarid Laohahe basin (18 112 km2) in northern China was investigated. Non-parametric Mann-Kendall test, Pettitt test, and precipitation-runoff double cumulative curve method were adopted to identify the trends and change-points in the annual runoff from 1964 to 2008 by first dividing the long-term runoff series into a natural period (1964-1979) and a human-induced period (1980-2008). Then the three quantifying methods were calibrated and calculated, and they provided consistent estimates of the percentage change in mean annual runoff for the human-induced period. In 1980-2008, human activities were the main factors that reduced runoff with contributions of 89-93%, while the reduction percentages due to changes in precipitation and potential evapotranspiration only ranged from 7 to 11%. For the various effects at different durations, human activities were the main reasons runoff decreased during the two drier periods of 1980-1989 and 2000-2008. Increased runoff during the wetter period of 1990-1999 is mainly attributed to climate variability. This study quantitatively separates the effects of climate variability and human activities on runoff, which can serve as a reference for regional water resources assessment and management. [ABSTRACT FROM AUTHOR]

The Laohahe basin is one of the typical semi-arid regions in Northeast China. Quantitatively estimating the contributions of human intervention and climatic variability on runoff changes in this region will help enhance the understanding of local hydrological mechanisms and provide an effective reference for water resources planning and management in other semi-arid regions of the world. The non-parametric Mann–Kendall test was used to analyze the temporal trends of annual precipitation, potential evapotranspiration (PET), and runoff in the whole Laohahe basin and its three sub-basins from 1964 to 2015. The annual runoff showed a decreasing trend in each sub-basin. The change-points of annual runoff detected by Pettitt's test and residual analysis based on double mass curves (RA-DMC) are 1979 and 1998, and the baseline period and change period of each basin are 1964–1979 and 1980–2015. The RA-DMC method and the VIC model were used to quantitatively evaluate the contributions of human intervention and climatic variability to runoff change, which vary in time and space over the past 52 years. The contributions of human intervention to runoff reduction during 1980–2015 was more than 80%. On a multi-decadal temporal scale, human intervention had a stronger impact on runoff during 1980–1989, 2000–2009, and 2010–2015. The influence of human intervention on runoff reduction is gradually increasing in the 21st century. Besides, human intervention has a greater impact in dry years than in wet years. The increase of cropland area leads to a significant increase in irrigation area, which further leads to an increase in the demand for agricultural water, which is also the main reason for the sharp reduction of runoff in the Laohahe basin. [ABSTRACT FROM AUTHOR]

It is reasonable to simulate the hydrologic cycle in regions with drastic land use change using a distributed hydrologic model in the dynamic land use mode (dynamic mode). A new dynamic mode is introduced into an object-oriented modularized model for basin-scale water cycle simulation (MODCYCLE), a distributed hydrologic model based on sub-watersheds, and the hydrological response unit (HRU). The new mode can linearly interpolate data for the years without land use data and consistently transfer HRU water storage between two adjacent years after a land use data update. The hydrologic cycle simulation of the Sanjiang Plain in China was carried out from 2000 to 2014 in the dynamic mode using land use maps of 2000, 2005, 2010, and 2014. Through calibration and validation, the performance of the model reached a satisfactory level. Replacing the land use data of the calibrated model using that of the year 2000, a comparison model in the static land use mode (static mode) was built (i.e., land use unchanged since 2000). The hydrologic effects of land use change were analyzed using the two models. If the land use pattern remained unchanged from 2000, despite the average annual runoff increasing by 4% and the average annual evapotranspiration decreasing by 4% in this region only, the groundwater storage of the plain areas in 2014 would increase by 4.6 bil. m3 compared to that in 2000, rather than the actual decrease of 4.7 bil. m3. The results show that the fluxes associated with groundwater are obviously more disturbed by land use change in the Sanjiang Plain. This study suggests that the dynamic mode should be used to simulate the hydrologic cycle in regions with drastic land use change, and the consistent transfer of HRU water storage may be considered in the dynamic mode. [ABSTRACT FROM AUTHOR]