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• The counter-demand method effectively simulates water diversion and distribution. • Successfully resolve the simulation of water extraction-conveyance-use in the Karez. • The average annual groundwater overexploitation was 173 million m3 in the ALB. • Excessive extraction of groundwater poses a threat to nature vegetation survival. The long-standing, irrational development and exploitation of water resources in the Aiding Lake Basin (ALB), coupled with excessive groundwater extraction, have led to the gradual depletion of Aiding Lake, the disappearance of Karez wells, the depletion of spring water, and the deterioration of the ecological environment, all of which are serious threats to the economy and survival and welfare of inhabitants. To address the complexities associated with the staggered distribution of natural rivers and artificial canals within the agricultural irrigated region of the ALB, an inverse computation method to gauge canal water requirements was used in building an intelligent simulation of water diversion and conveyance, incorporating different water use methodologies for complex canal systems within the irrigated region. Additionally, this paper characterizes the interaction between the catchment and conveyance section of the Karez wells and the underground aquifer based on the seasonal river module to simulate the entire flow process of the Karez well system, from water extraction and conveyance to groundwater recharge by infiltration. This study presents a coupled simulation model of seasonal river–lake-groundwater interactions in the ALB, where groundwater is simulated under both steady and unsteady flows. The findings indicate that from 2013 to 2022, the annual average groundwater recharge within the ALB was approximately 1.048 billion m3, while the discharge was 1.221 billion m3, with an annual average groundwater overexploitation of 173 million m3. Furthermore, the long-term overexploitation of groundwater has had a direct impact on the ecological environment, resulting in a survival crisis for natural vegetation except in the upper vegetative zone of Aiding Lake, which has good groundwater recharge conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] • The drought pattern in China is closely related to the basin distribution and multiple teleconnection factors. • The intensity and frequency of drought in China exhibited an increasing trend. • The ENSO-AO had important positive effects in the major basins in China. • Multiple wavelet coherence helps identify the processes controlling drought changes. Due to increasing global warming and the frequent occurrence of severe drought risk in recent decades, many studies have investigated drought in China. However, the spatiotemporal heterogeneities of droughts are complicated, and a comprehensive analysis of the driving forces has not been thoroughly explored. In this paper, we studied the temporal and spatial patterns of drought in China from 1960 to 2018 and disclosed its relationship with multiple teleconnection factors on different time scales. The results show that (1) Drought in China has exhibited a fluctuating increasing trend over the past 59 years, with a standardized precipitation–evapotranspiration index (SPEI) rate of change of –0.12/10 a, and the most severe droughts occurred during 2000–2010. (2) There was a significant abrupt change in China's meteorological droughts induced by climate change around 1997. (3) The trend in China was characterized by drought in spring and autumn and humidification in winter, while the trend in the Southwest River Basin was characterized by drought. (4) A combination of factors can best explain the drought variations from basin to basin, and the El Niño-Southern Oscillation (ENSO)-Arctic Oscillation (AO) was most commonly the best predictor. The use of multiple wavelet coherence helps to identify the dominant drought change processes. [ABSTRACT FROM AUTHOR]

• A framework is proposed to analyze compound floods with multiple driving factors. • Local rainfall has a larger impact on the flooding levels of the GBA, China. • Flooding area is about 50 km2 and 1.3 m flooded depth for the worst scenario. • Findings have important implications to GBA's flooding control and management. Low-lying coastal cities are vulnerable to compound floods caused by many factors including river flows, tides and local rainfall. Many previous studies focus on the impacts of rainfall and tidal levels (two driving factors) on estuaries or regions near the main single river, while research about the three influencing factors on the floods for complex urban river networks remain relatively scarce. This paper proposes a framework to simulate the coastal compound flooding process, with a series of scenarios designed to explore the main flooding drivers and their worst possible combination. The approach is used to quantify the induced flooding consequences, in which a two-dimensional model is employed to conduct a case study for a city with complex river networks. The Qianshan River basin in Zhuhai City, located in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China is used as the case study. Application results show that: (i) the occurrence and properties of flooding in this coastal area are jointly affected by upstream river flows, downstream tidal levels and local rainfall intensity with different contribution levels, (ii) compared to tidal levels, local rainfall intensity has a larger impact on the flooding levels of the study region, and (iii) the worst scenario where a 50-year return period upstream river flow co-occurring with high tide and a 100-year return period rainfall can produce a flooding area up to 50 km2 for the study region, with an average of 1.3 m flooded depth. The proposed framework with its findings offers an in-depth understanding and quantification of coastal urban flood characteristics within the GBA of China. [ABSTRACT FROM AUTHOR]

• • Development of a research framework for evaluating streamflow discharge and salinity variation in an estuary with multiple river outlets. • • Investigation of the impacts of freshwater discharge on the vertical and longitudinal distribution and spatial variation of salinity due to anthropogenic impacts. • • Identification of the key factors in determining salinity variation during a rainy season with the different scenarios of freshwater discharge. Estuarine salinity is one of the key factors affecting coastal ecosystems. However, due to impenetrable situation of mixing streamflow from river basins and seawater currents, our capability of evaluating salinity variation is far behind requirement in preventing coastal environment. Thus, this paper presents an integrated study on salinity variation in the Pearl River Estuary (PRE) in South China in the rainy season since the estuary would experience more salinity variation at the time. The PRE has a complicated water body with eight river outlets, four ones in the east and the others in the west. The paper develops a new research framework to evaluate the impacts of streamflow on the salinity variation, including adjusting diversion ratios of freshwater discharges to the estuary and using two numerical models for simulating basin hydrologic processes and estuary salinity variations. With the salinity observation from a field cruise in the PRE in July 2017 and the newly-developed framework, this study validates the numerical simulation results, detects the salinity variation under different scenarios of freshwater discharge, and discloses the environmental factors related to salinity variation. Specifically, the study shows the distinct characteristics of salinity variation in association with freshwater discharge and environmental factors, including seawater current velocity and topography in the east (a funnel-shaped bay consists of four narrow deep channels), and west (a sub-estuary of the Modaomen waterway) part of the estuary. The results indicate that salinity in the east part is more sensitive to streamflow variation with a farther freshwater-saltwater divide (about 25 km) away from the outlets than that in the west part (14 km). The estuary area affected by salinity variation due to different streamflow diversion ratios is more significant in the east (1,266 km2) which is 7.6 times larger than that in the west (166 km2). However, the values of salinity change due to different discharges are greater in the west (more than 2.0 psu in 34% of the affected area) than those in the east (all less than 2.0 psu). Moreover, the study shows that the seawater salinity variation in the east is greatly influenced by the distance to the outlet, freshwater discharge and seawater depth; while in the west, the salinity variation is largely determined by seawater current velocity. [ABSTRACT FROM AUTHOR]

• Geodetector model offers a promising method for downscaling variables selection. • GWR is suitable for downscaling before calibrateing satellite using gauge observations. • Newly proposed GWR_Bi-LSTM framework outperformed the comparative. • Calibrated precipitation demonstrated better accuracy than the original IMERG. Accurate precipitation datasets with a high spatiotemporal resolution are crucial for regional hydrological simulation and water resources management. Although various global satellite precipitation products (SPPs) are available, they cannot be directly applied to small-scale research due to their low spatial resolution and significant bias. To solve these problems, based on the consideration of spatiotemporal relationships, this paper presented a comprehensive downscaling-calibrating framework that consists of spatial downscaling procedures and calibrating processes. Specifically, a geographically weighted regression (GWR) model, coupled with the environmental variables selected by the Geodetector model, was applied to generate uncorrected daily precipitation data with high-spatial resolution (1 km × 1 km). Then, the preliminary downscaled daily precipitation was calibrated using a bidirectional long short-term memory (Bi-LSTM) network. The proposed framework was applied to downscale and calibrate the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) product of the Jiulong River Basin in southeast China from 2010 to 2016. The results indicate that: (1) the spatial downscaling procedures improved the spatial resolution of the SPPs while maintaining its accuracy; (2) the calibrating processes can effectively correct the bias of preliminary downscaled daily precipitation. Meanwhile, the accuracy evaluation showed that the proposed GWR_Bi-LSTM framework outperformed the comparative methods, and the generated precipitation dataset exhibited a better performance under various evaluation conditions. Generally, based on the proposed framework, gridded daily precipitation data with high quality and spatial resolution can be generated for hydrological and meteorological research. [ABSTRACT FROM AUTHOR]

• Calculation unit division induced soil spatial aggregation in SWAT model. • Effect of soil spatial aggregation on simulation was separated and quantified.Soil spatial aggregation caused a significant increase in annual runoff and sediment load. • The effect of soil spatial aggregation on sediment load was greater than on runoff. • Optimal sub-watershed division scheme was discussed. Distributed hydrological model divides watersheds into distinct calculation units to simulate hydrological processes. Within the model, different calculation unit division schemes induce input elements, such as soil and land use, to certain degrees of generalization, thus affecting the simulation result. Analyzing the effect of the calculation unit division on the simulation result is an important methodology to reduce uncertainty and improve the simulation accuracy of the model. Previous researchers have focused on the comprehensive effect of underlying surface generalization (such as soil, land use, and terrain generalization) caused by the calculation unit division on the simulation results, while it did not separate the effect of the generalization of the individual input factor on the simulation result. In this paper, the Dongjiang headwater region in southern China was selected as the study area. The single type of land use and slope were input into the Soil and Water Assessment Tool (SWAT) model to fix the effects of land use and terrain caused by calculation unit division on the simulation results. Eleven calculation unit division schemes were used to analyze the impact of soil spatial aggregation on runoff and sediment load simulations. The calculation unit division schemes included 11 sub-watershed division schemes and their hydrological response unit (HRU) thresholds were set at 8 %. The drainage area thresholds of the 11 sub-watershed division schemes were 30 ha, 60 ha, 120 ha, 240 ha, 480 ha, 1000 ha, 1600 ha, 2200 ha, 2800 ha, 3400 ha and 4000 ha. The results demonstrated that the soil spatial distribution showed an obvious aggregation with an increase in the drainage area threshold in the SWAT model. Of these, the Krasnozem soil type which covers the largest area in the watershed, increased significantly with an increase in the drainage area threshold. However, the areas of all the other soil types decreased significantly. The Lioth soil type covers the smallest area in the watershed decreased and even disappeared when the threshold in the SWAT model was greater than 1000 ha. Furthermore, soil spatial aggregation caused a significant increase in the annual runoff and sediment load (P < 0.05), with the sediment load (Re = 29.78 %) increasing at a greater rate compared to runoff (Re = 1.74 %). Increased soil aggregation significantly increased the sediment loads in the maximum 1-day, the continuous maximum 5-day, the continuous maximum 7-day, and the sediment load in flood processes (P < 0.001). Refining the calculation unit division scheme will cause a significant increase in the number of calculation units. Due to the computer processing power limitations, we cannot further refine the calculation unit division scheme. Based on our current operational calculation unit division scheme, we did not identify the optimal division scheme in the study region. These results can provide reference information for future research into hydrological model uncertainty and can improve the SWAT model simulation accuracy. [ABSTRACT FROM AUTHOR]

• The NPPRI, MCR and SWAT models are superimposed in space to identify the critical source areas. • On the basis of analyzing the influence of BMPs on the landscape characteristics of watershed, the response relationship between NPS and landscape pattern are further revealed. • Based on landscape pattern theory and information entropy method, the best combination management measures for watersheds are proposed and evaluated. The deterioration of ecological environment caused by non-point source pollution (NPS) has seriously threatened human health and socioeconomic development. Effective identification of critical source areas and selecting appropriate best management practices (BMPs) for watersheds are the keys to controlling NPS. This paper, using Hanjiang River basin, the vital water source for the South-to-North Water Division, China, as a case study, presents a method for accurate critical source areas dentification according to the spatial distribution characteristics of underlying surface and pollution load by coupling NPS risk index (NPPRI), Minimum Cumulative Resistance (MCR) Model, and Soil and Water Assessment Tool (SWAT). In this research, ten single and three combined scenarios are set up in the critical source areas, including three non-engineering management practices, two engineering management practices, and five ecological buffer zones. Finally, the effect of BMPs for non-point source pollution is assessed by using landscape pattern theory and information entropy method. Furthermore, the influences of the five ecological buffer zones on the characteristics of landscape in watershed and the response relationship between the landscape pattern and NPS are analyzed. The following findings are obtained: (1) The critical source areas were mainly located in the south-central and southeastern part of the study area, accounting for 35.9 % of the total watershed area, and yielding 54.2 % and 60.7 % of the total nitrogen(TN) and total phosphorus(TP) loads in the watershed; (2) All ecological buffer zones play a positive role in NPS control with an average reduction rate of 32.1 % for TN and 46.7 % for TP, and the control effectiveness for TP are better than that for TN; (3) The deployment of the five ecological buffer zones have a significant impact on the interspersion juxtaposition index (IJI), the connectivity of the "sink" landscape is enhanced, the diversity of the "source" landscape is reduced and the "sink" landscape's ability of interception is boosted; (4) The calculation result of information entropy shows the highest attribute value of practices in the ecological buffer zones is Buffer 200 m. Overall, the findings serve as a reference for NPS control and water environment management in the watershed and strengthen the feasibility of implementing of BMPs in the watershed. [ABSTRACT FROM AUTHOR]

• A new hydrological-water quality model for humid and semi-humid catchments in China is presented. • Both horizontal and vertical heterogeneity are considered in the hydrological process and the water quality process modelling. • Model uncertainty and the sensitivity of model parameters are investigated. Non-point source (NPS) pollutants may cause water quality deterioration and eutrophication, posing a significant threat to aquatic systems. Understanding and modelling surface and sub-surface hydrological processes and nutrient cycles are therefore essential for water resources management and pollution control. This paper presents a new hydrological-water quality model for application in humid and semi-humid catchments in China, considering both hydrological processes, and nutrient transport and transformation. The model divides the soil into three layers, and each layer is implemented with individual computational procedures for soil wetness and nutrient process. Nutrient transport is driven by hydrological processes and follows the same pathways as water flow in the model: surface runoff, infiltration, and outflow from individual soil layers. River channels are described separately with routines to account for the turnover of nutrients. Model parameters are selected according to literature/open-sourced data or estimated from soil texture or land use types. The model is applied to simulate the hydrological processes and phosphorus transport in the Tongyang River Basin in China and the model performance is confirmed by comparing the predicted discharge and total phosphorus concentrations with measured data at the catchment outlets of Tonghe River and Yanghe River over 3 years. Uncertainty analysis has been further carried out using the GLUE method to demonstrate sensitivity of the simulation results to the selection of model parameters. After model calibration, the predicted results are found to compare well with field observations in terms of flow discharge and total phosphorus concentration. From sensitivity analysis, it is found that the recession coefficient of channel system (CS) and the pollutant recession coefficient of surface runoff (p KS) are the most influential hydrological and water quality parameters that control the arrival time and duration of flood peak and nutrient concentration peak, respectively. [ABSTRACT FROM AUTHOR]

• The objectivity verification experiment of the dynamic system response curve (DSRC) method was designed based on multiple hydrological models. • The experiment in Sunshui River and Shiquan catchments presented that the use of DSRC-corrected rainfall series of each hydrological model showed improved simulation accuracy for other hydrological models. • The hypothesis that the DSRC method is objective is not rejected based on the results of the experiment. Error correction methods are widely used to improve the performance of streamflow modeling. The Dynamic system response curve (DSRC) is a newly developed error correction method that utilizes error feedback correction to obtain updated variables and thus enhances model accuracy. While the DSRC method is simple and practical, its objectivity has not been systematically demonstrated. To address this issue, the paper proposes an experiment to verify its objectivity. First, three hydrological models (Xinanjiang (XAJ), Hydrologiska Byråns Vattenavdelning (HBV) and vertically hybrid yielding (VHY)) were calibrated and three corrected areal mean rainfall series were obtained by using the DSRC-based models (XAJ-DSRC, HBV-DSRC and VHY-DSRC). The corrected rainfall series from one hydrological model was then used as input to other hydrological models, and its performance was compared to those of using the original rainfall series by five performance measures (Nash-Sutcliffe efficiency coefficient (NSE), root mean squared error (RMSE), percent bias (PBIAS), mean absolute error (MAE) and correlation coefficient (R)). Finally, this objectivity verification experiment was applied to different model combinations for further demonstration. Case studies of the Sunshui River and Shiquan catchments in China showed that when the DSRC-corrected rainfall series from either hydrological model was applied to the original or other hydrological models, an increase in NSE and R values and a decrease in RMSE and MAE values were observed. The absolute values of PBIAS were within 10%. Accordingly, the hypothesis that the DSRC method is objective is not rejected based on the results of the experiment. [ABSTRACT FROM AUTHOR]

• A theoretical framework for the relationship between WEF and poverty is proposed. • Four development types of YRB are classified. • The Hu Huanyong Line is demonstrated "dividing line between the rich and the poor". • A scheme for the quantification of poverty is provided. Under the double pressure of ecological vulnerability and economic development, natural resources and ecological environment have become the key constraints to the development of the Yellow River Basin (YRB). This paper proposed a theoretical framework for the relationship between water-energy-food (WEF) and poverty. An improved coupling coordination degree model and the geographical detector were used to evaluate the spatio-temporal coupling between WEF and poverty and its influencing factors in YRB. The results suggest that the levels of coupling coordination increase to different degrees in YRB and its provinces from 2000 to 2019, and the coupling types are characterized by pyramidal-shaped distribution. The regions of YRB are divided into four development types: water-driven type, energy-driven type, food-driven type, and economy-driven type. Spatially, a dominant factor zone is formed with a multi-polar core. Furthermore, some practical suggestions are put forward to promote the effective utilization of water resources and high-quality development according to specific regional situations in YRB. This study will promote coupling coordination and high-quality development in YRB, providing a reference for the coordination of the human-land relationship and regional sustainable development. [ABSTRACT FROM AUTHOR]

• An integrated sensitivity analysis (SA) system named GDISCs is proposed. • GDISCs can screen sensitive parameters (SPs) robustly. • The KGE' performs better than NSE and RMSE in parameter SA. • Optimizing SPs greatly accelerates the convergence with satisfied optimized results. Parameter optimization is mandatory in many numerical modeling studies of hydrology sciences. However, optimizing all parameters (APs) is highly inefficient, including the equifinality phenomenon. This paper proposes an integrated sensitivity analysis system consisting of, multiple Global sensitivity analysis methods, Design of experiment algorithms, Indicators, and Sample size design Combinations (GDISCs), for screening the sensitive parameters (SPs) robustly and reducing parameter optimization burden efficaciously. In this study, four design of experiment (DoE) algorithms are applied to collect samples with varying sizes, and the corresponding three indicator values. We evaluate the effectiveness and efficiency of one qualitative and two quantitative global sensitivity analysis (GSA) methods by identifying the appropriate DoE algorithm and the sufficient sample size. To apply the GDISCs, the Block-wise use of the TOPMODEL (BTOP) model is set up for the hydrological simulation in the upper Min River Basin, China. The results show that the GDISCs system robustly screens out three SPs of the BTOP model, and the DoE algorithms significantly impact the effectiveness and efficiency of the GSA methods. The SA performance with applying the modified Kling–Gupta efficiency (KGE') as the indicator is more robust than the root mean squared error (RMSE) and the Nash-Sutcliffe efficiency (NSE). Compared to the traditional APs optimization, the optimal values are identified quickly through almost 1/2 or even fewer model runs and duration for the SPs optimization, with a very close accuracy (the maximum NSE, KGE' and relative bias (RBias) differences are 0.137, 0.037 and 2.70%, and the minimum are 0.002, 0.001 and 0.20%). Optimizing SPs also has a noticeable improvement for the default parameter values, and the maximum differences of NSE, KGE' and RBias reach 0.764, 0.321, and −20.80%. In summary, the GDISCs system is especially applicable for obtaining the robust SA results to considerably improve model calibration efficiency and reduce model computational burden while ensuring satisfactory model simulation performance. [ABSTRACT FROM AUTHOR]

• Optimal GAMLSS models were selected by meteorological and anthropogenic covariates. • A nonstationary SRI was proposed for a coupled human-water system. • NSRI excels in accuracy and recall, showing an advantage in drought recognition. Significant nonstationarity of hydrological sequences, driven by the coupled influence of climate change and anthropogenic activities, has challenged traditional hydrological drought analysis under the stationarity assumption in some regions, and has questioned regional hydrological drought analysis under the changing environment. To evaluate hydrological drought characteristics, the novelty of this paper is the proposition of a GAMLSS (Generalized Additive Models for Location, Scale, and Shape)-based nonstationary standardized runoff index (NSRI), considering climate change and anthropogenic influence, for investigating the hydrological drought regime in the Wuding River basin. To that end, nonstationary test methods were performed on hydrological sequences, and data was segmented into three parts according to the results of the Pettitt test. A nonstationary probability distribution was fitted to runoff data with meteorological covariates (precipitation, temperature) and anthropogenic covariates (water consumption for social development demand, and water consumption triggered by water impounding by check dams). After selecting an optimal combination of covariates, the NSRI was calculated utilizing the GAMLSS model. A newly constructed evaluation threshold was proposed, based on the traditional SRI threshold. The performance of SRI and NSRI were compared at the Dingjiagou station in the Wuding River basin. Results of comparison between index identification and recorded drought events demonstrated that the NSRI better performed in drought event identification. Moreover, the NSRI identified more frequent severe droughts and extreme droughts. Therefore, the proposed NSRI provided a more accurate basis for the identification of drought events, which can offer valuable information for drought planning, preparedness, and mitigation. [ABSTRACT FROM AUTHOR]

• An integrated postprocessing framework for hydrometeorological ensemble is developed. • The canonical event considered observed precipitation improves the forecast accuracy. • The streamflow simulation can benefit from the seamless hydrologic prediction. • The Bayesian method improves the forecast effect than a single hydrological model. Flood forecasting is a challenging task with major concerns that include forecast uncertainty and lead time. This paper aims to comprehensively address the data correction issue for hydrological models by developing an integrated postprocessing framework for hydrometeorological ensemble forecasts based on three types of ensemble precipitation forecasts (ECMWF, GEFS, and CFSv2). This framework mainly comprises the Ensemble Preprocessor (EPP) and the Bayesian model averaging (BMA) scheme: (1) the EPP eliminates various deviations from the ensemble precipitation forecasts, with the canonical event model extracting useful predictive information and extending the lead time by linking the forecasts seamlessly, and (2) the BMA scheme develops more skillful and reliable probabilistic hydrological forecasts from ensemble streamflow forecasts generated by three hydrological models (XAJ, VIC and DTVGM) driven by the postprocessed ensemble precipitation forecasts. The Ganjiang River Basin was selected as a case study to examine the capacity and efficiency of our developed framework. We found that the performance of the integrated postprocessing of hydrometeorological ensemble forecasts benefitted from a reasonable design of canonical events, especially when the observed precipitation was factored into the canonical events. Streamflow forecasts with increased lead times and accuracy were obtained by employing postprocessed precipitation forecasts instead of raw forecasts as the input for the hydrological models. We also found that the BMA scheme further improved the forecast effect by generating more skillful and reliable forecasts than a single hydrological model, which was verified by a series of statistical indices and uncertainty analysis. Our results underscore the importance of considering both input and output for hydrological models in hydrological forecasting. [ABSTRACT FROM AUTHOR]

• There are two different types of knickpoint within the Layue basin. • Damming events usually correspond to a knickpoint and the abrupt change of k sn. • The relief increases by 35.3–214.3% in the process of knickpoint spreading. • The retreat rate of 4 k knickpoint group in the Layue basin is 10.8–51.7 km/Ma. • Natural damming events obviously affect the river profile within 104 year. The longitudinal profile of rivers in active orogenic belts records the competitive process occurring between erosion and uplift, and the knickpoint, as a unique sign, can support this. A series of distinctive knickpoints are distributed at different heights in the basin of the Layue River, which is a tributary located on the northwest side of the Yurlung Tsangpo Basin, China. By combining the stream power erosion model and field investigation, this paper explores the relationship among dams, knickpoints and the normalized steepness index (k sn). In addition to sporadic damming-type knickpoints, a 4 k knickpoint group located in the basin has attracted attention. Using the slope-area analysis method and the integration analysis method, paleo profile reconstruction of 14 tributaries and trunks was carried out to estimate the resulting paleo relief and net uplift. The results show that the topographic relief increases by 35.3–214.3% during the process in which the knickpoint entered into the basin and spread, which is the result of the growth and retreat of the knickpoint. Using the celerity model for the 4 k knickpoint group, 83.3% of the model knickpoints are less than 5 km away from the observed knickpoints, which indicates that the model is suitable for application in the Layue River Basin. And the migration rate of the knickpoint in the Layue Basin is 10.8–51.7 km/Ma at an initial setup time of 1.25–6 Ma. [ABSTRACT FROM AUTHOR]

• An observation-based natural and human-impacted catchment comparison method is proposed. • Human influence are quantified based on gridded socio-economic and land use data. • Climatic and anthropogenic influences on drought propagation are investigated. • Climate change accelerates the response of hydrological drought to meteorological drought. • Human activities delay the propagation from meteorological to hydrological drought. It is crucial to investigate how a precipitation deficit is transformed into hydrological drought and how climate change and human activities affect this transformation process, which is helpful to gain a deep understanding of drought propagation process in this changing environment. This study proposed an observation-based natural and human-impacted catchment comparison method to assess the impacts of climate change and human activities on propagation from meteorological drought to hydrological drought. The method mainly consists of the following three steps: (1) selection of natural catchments through analysis of trends and change points of hydro-meteorological data, as well as statistics analysis of human influence based on land use and socio-economic indicators data sets; (2) calculation of drought propagation characteristics (e.g., drought severity, duration, and propagation time) based on run theory and the Pearson correlation coefficient; and (3) comparison of drought propagation characteristics of natural catchments between undisturbed and disturbed periods to identify the impacts of climate change on drought propagation, and comparison of the propagation characteristics between natural and human-impacted catchments during the disturbed period to investigate human influence on drought propagation. The Laohahe basin (with eleven sub-catchments), located in northern China, was evaluated via the proposed procedure, and standardized precipitation index (SPI) and standardized runoff index (SRI) were used to characterize meteorological and hydrological droughts, respectively. The results demonstrate that the proposed method is suitable tool for distinguishing natural and human-impacted catchments, and separating the impacts of climate change and human activities on drought propagation. Furthermore, the comparison results of different schemes show that climate change accelerates the propagation from meteorological drought to hydrological drought in the Laohahe basin, shortening it by approximately 3 months. Human activities, however, disturb and then delay the natural propagation from meteorological drought to hydrological drought, retarding it by 11–12 months. Although the Laohahe basin was selected as a case study in this paper, the proposed method can be applied in other regions as well to improve drought prediction and water resources management. [ABSTRACT FROM AUTHOR]

[Display omitted] • The Variation Coefficient-Shapley Value Method is proposed. • Several typical allocation methods are compared with the proposed method. • The PTD index is adopted to quantitatively evaluate the stability of the allocation results. Maximizing the benefits of cascade hydropower stations will inevitably reduce the benefits of some upstream hydropower stations. In order to promote the joint operation and mutual cooperation between cascade hydropower stations, the scientific and fair allocation of compensation benefits between cascade hydropower stations is required. In this paper, a Variation Coefficient-Shapley Value Method for the compensation benefits allocation of multi-owner cascade hydropower stations is proposed, by combining individual characteristic weight coefficients with the Shapley value of each hydropower station. The Propensity to Disrupt (PTD) method is adopted to quantitatively evaluate the stability of the allocation results. Then an exemplary cascade of three hydropower stations on the Nanhe River in China is used as a case to calculate the compensation benefits via the proposed Variation Coefficient-Shapley Value Method and compared with other typical allocation methods. The results show that the leading hydropower station can get more compensation benefits as well as the second and third stage hydropower stations get reasonable compensation benefits. The stability of the cascade alliance in the compensation benefits allocation of the proposed method surpasses that of the other methods. This indicates the ability of the proposed method to both consider the individual marginal contribution and individual characteristics of each hydropower station when participating in joint operation. The proposed method proves to achieve a fair and rational compensation benefits allocation among the cascade hydropower stations and can potentially improve the utilization efficiency of water resources in the river basin. [ABSTRACT FROM AUTHOR]