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Modelling hydrological process in the critical zone not only contributes to a better understanding of interactions across different Earth surface spheres but also holds significant practical implications for water resource management and disaster prevention. Rainfall‐runoff simulation in critical zones is particularly challenging due to the amalgamation of temporal and spatial complexity, rainfall variability, and data limitations. As a pivotal input variable of hydrological models, accurate estimation of areal rainfall is critical to successful runoff simulation. However, most estimation methods ignore temporal information, thereby increasing uncertainty in rainfall estimation and constraining the precision of rainfall‐runoff simulation. In this study, the matrix decomposition‐based estimation method (F‐SVD), which considers the spatial and temporal correlation of the rainfall process is employed to estimate areal rainfall. The superiority of the method in producing two‐dimensional rainfall information is evaluated through its application in runoff simulation with the Xin'anjiang model. The simulation results of selected flood events in the Jianxi basin in southeast China, spanning from 2009 to 2019, are compared with those of two widely used rainfall estimation methods, namely Arithmetical Mean (AM) and Thiessen Polygons (TP). The results show that (1) F‐SVD not only produces the highest Pearson correlation coefficient between rainfall and runoff series but also reduces the number of flood events with abnormal rainfall‐runoff relationships; (2) the Xin'anjiang model based on F‐SVD achieves the highest Nash‐Sutcliffe efficiency and lowest Relative Error, and performs best in simulating peak flow and its occurrence time as compared to AM and TP. This study contributes to a finer characterization of watershed rainfall distribution, enhancing the accuracy and sharpness of runoff simulation. It provides reliable data support for critical zone research and offers a scientific foundation for rationally allocating and managing water resources. [ABSTRACT FROM AUTHOR]

Glaciers are important freshwater storage systems in the Tianshan Mountains. Under the context of climate change, quantifying changes in glacier mass balance, the melt-season (June–September) runoff and its key runoff component (glacier runoff) is of importance for understanding the discharge composition and ensuring adequate management of water resources. In this study, the modified HBV-D (Hydrologiska Byrans Vattenbalansavdelning-D) hydrological model was used to simulate hydrological processes for a data-sparse glacierized watershed, the headwater catchment of Manas River basin (MRB) in the Tianshan Mountains. Meanwhile, the roles of three modified elements of HBV-D in simulating glacier dynamics are identified. Sequently, the glacier mass balance and runoff during 1984–2006 are reconstructed and their responses to climate change are investigated. The analysis showed (1) the snow/glacier melt method makes more contribution to improving the performance of HBV-D model in simulating historical change of glacier volume, followed by the glacier dynamic method. (2) The reconstructed mass balance follows a decreased trend in the MRB. The maximum accumulation of glacier mass balance occurs in June. Snowmelt over the surface of glacier and glacier melt reach peak in June and August, respectively. Furthermore, sensitivity experiments showed increased mass balance induced by a 10% increase in precipitation cannot compensate for the decreased mass balance due to a 1 °C temperature rise. (3) Significant contribution (about 41.5%) of runoff in glacierized area to the melt-season total runoff of the catchment is identified. Both the glacier runoff and its contribution to melt-season total runoff show increased trends during the simulation period. Compared with the melt-season mean temperature and annual precipitation over glaciers, the melt-season positive accumulated temperature over glaciers played the most important role in influencing changes in glacier runoff in MRB. The findings in this study are beneficial for implementing adaptive countermeasures for water resources management in the data-scarce glaciated high-mountainous region. [ABSTRACT FROM AUTHOR]

• Parameter uncertainty varies over time scales due to land use change (LUC). • The calibrated daily runoff model is deficient for the extreme flow changes. • Model structure impacts the extreme runoff direction change for moderate LUC. Hydrological modeling has provided key insights into the mechanisms of land-use change impacts on runoff. However, the uncertainty of this impact is poorly understood. This paper examines the uncertainty originated from hydrological models' parameters and structure in simulating hydrological responses to land use change on daily, monthly and annual time scales. Two hydrological models, SWAT and HSPF, were applied to simulate the runoff response in the Xitiaoxi basin of eastern China. The effects of three land use scenarios (in 1985, 2002 and 2014) were analyzed with respect to the expansion of urban areas and reduction of cropland and forests. The changes in streamflow with multi-timescales between two models were compared at the whole basin and the sub-basin scales. The parameter uncertainty was estimated based on a sequential uncertainty analysis method (SUFI-2). The results indicate that the two models (SWAT and HSPF) could reproduce the observed daily and seasonal flows well, but they cannot accurately reconstruct the extreme flows (such as annual 7-day minimum discharge, R_7dMIN). The effect of parameter uncertainty on streamflow varies over time scales. The simulated annual and monthly runoff change values show large discrepancies but with same trends. The simulated changes for annual maximum discharge (R_1dMAX) and R_7dMIN often show different signs. The average width of the predictive interval in the relative change of different flow characteristics exceeded 100% of the average relative changes for both models. HSPF tends to present larger relative changes for the annual and monthly runoffs compared to SWAT. Moreover, the model choice could affect the direction change in R_1dMAX and R_7dMIN. However, when land use change was significant to a certain degree, both models simulated increased R_1dMAX and decreased R_7dMIN, but with different significance levels. The study suggests that the model structure represents an additional uncertainty, which should be accounted for in the land-use change impact assessment. [ABSTRACT FROM AUTHOR]

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For sake of improving our current understanding on soil erosion processes in the hilly-gully loess regions of the middle Yellow River basin in China, a digital elevation model (DEM)-based runoff and sediment processes simulating model was developed. Infiltration excess runoff theory was used to describe the runoff generation process while a kinematic wave equation was solved using the finite-difference technique to simulate concentration processes on hillslopes. The soil erosion processes were modelled using the particular characteristics of loess slope, gully slope, and groove to characterize the unique features of steep hillslopes and a large variety of gullies based on a number of experiments. The constructed model was calibrated and verified in the Chabagou catchment, located in the middle Yellow River of China and dominated by an extreme soil-erosion rate. Moreover, spatio-temporal characterization of the soil erosion processes in small catchments and in-depth analysis between discharge and sediment concentration for the hyper-concentrated flows were addressed in detail. Thereafter, the calibrated model was applied to the Xingzihe catchment, which is dominated by similar soil erosion processes in the Yellow River basin. Results indicate that the model is capable of simulating runoff and soil erosion processes in such hilly-gully loess regions. The developed model are expected to contribute to further understanding of runoff generation and soil erosion processes in small catchments characterized by steep hillslopes, a large variety of gullies, and hyper-concentrated flow, and will be beneficial to water and soil conservation planning and management for catchments dealing with serious water and soil loss in the Loess Plateau. [ABSTRACT FROM AUTHOR]

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: Predicting hydrological variables in ungauged catchments has been singled out as one of the major issues in the hydrological sciences. In this study, the conceptual rainfall-runoff model, HBV, was applied to Dongjiang basin and its 13 sub-basins for the purposes of examining the applicability of this well-known model in south China and exploring the possibility of transferring the calibrated parameter values to ungauged basins. For testing the applicability of the model in gauged basins, the model was calibrated for a period of 1978–1983 and validated for a period of 1984–1988. For testing the transferability of parameter values to ungauged basins, two parameter regionalization methods – proxy-basins and global mean – were investigated. The results showed that: 1) the HBV model worked well in the Dongjiang basin with the average indexes of agreement (D) and coefficient of efficiency (ME), respectively, equal to 0.79 and 0.82 in the calibration period, and 0.76 and 0.78 in the validation period; 2) transferring the parameter values from basins that passed the cross-basin test with higher ME values to the hypothetical ungauged catchments produced acceptable results with an average ME value equals to 0.72; 3) compared with the proxy-basin method of parameter estimation, the model produced equally good results for the global mean method with an average ME value equals to 0.74 when using simple arithmetic mean values. Neither the area weighted mean method nor the Thiessen polygon method produced regional parameter values could markedly improve the accuracy of modeling results. It was concluded that both regionalization methods could effectively estimate parameters for ungauged catchments in the Dongjiang basin, and similar model performances were obtained. [Copyright &y& Elsevier]

• A framework was provided for analyzing change causes of runoff and sediment load. • Runoff change attribution analysis was incorporated in quantifying sediment change. • Dam construction obviously disturbed the evolution characteristics of sediment load. Under the background of climate variability and anthropogenic stresses, changes of the runoff and sediment processes have drawn increasing concerns during the past decades. Analyzing the evolution characteristics and causes of runoff and sediment load is critical for the sustainable development of water resource and terrestrial ecosystems of river basins. This study presents an integrated approach for analyzing the evolution characteristics of the annual runoff and sediment load, including the trend, periodicity, change point and their correlations in the Wujiang River basin (WRB) –a typical mountainous river system in southwest China, based on the observed data during the period 1970–2016. On this basis, the contributions of climate variability and human activities on runoff change were first distinguished by using a widely applied Budyko-based hydrological sensitivity method, and then the quantified result was further applied in the attribution analysis of river sediment load change. Research results revealed that the change patterns of runoff and sediment processes, such as the trend, periodicity and potential change point, as well as the relationships of precipitation-runoff and runoff-sediment load are quite different in the WRB. Quantitative assessment revealed that climate variability contributes to 71.5%–85.6% changes of mean annual runoff in 1985–1994, 1995–2004 and 2005–2016 with reference to the baseline period of 1970–1984. In contrary, human activities dominate the reduction of sediment load in the river, and the contribution rate ranged in 67.2%–107.5%. Variations of annual runoff in the WRB was the direct result of climate variability, while land use change played a secondary role. The construction of cascade hydropower reservoirs, particularly in the upper and middle reaches of the Wujiang River is fundamentally responsible for the significant decreasing and the weakened periodicity of sediment load as well as the changed runoff-sediment load correlation at Wulong station in recent years. However, this influence was not big enough to modify the regime of annual runoff. [ABSTRACT FROM AUTHOR]

Characterized by increasing surface air temperature, global warming has altered the hydrological cycle at global and regional scales. In order to adapt water resources management under the context of global warming, attribution analysis on regional differentiation of water resources in the Yangtze River basin (YRB) was conducted in this study. Meteoro-hydrological variations across the basin were examined for the period 1960–2013, and then a statistic-based method was applied in quantifying the contributions of climate variability and human activities on annual runoff variations in different tributary sub-basins in the YRB. Our observation indicates that both the annual increasing rate and the inter-annual fluctuations of temperature in China and in the YRB were higher than that of the global average since the turn of the century. Climate change analysis indicates that the YRB experienced a hot-wet period during 1994–2002 and a hot-dry period during 2003–2013, since the step change of temperature in 1993. Contributions of climate change and human activities on runoff variations varied spatially in the basin. With reference to the baseline period of 1960–1993, the contribution of climate change played a dominant role in most regions of the basin, especially in those upstream sub-basins. The effect of human activities in the basin was quite complicated, not only its regional differentiation, but also its contribution were opposite during the hot-wet period and the hot-dry period in some sub-basins. The result of this study is helpful in understanding the impacts of climate change and human activities on water resources variation in both temporal and spatial scales. [ABSTRACT FROM AUTHOR]

The impacts of climate change on water resources in snow- and glacier-dominated basins are of great importance for water resource management. The Snowmelt Runoff Model (SRM) was developed to simulate and predict daily streamflow for high mountain basins where snowmelt runoff is a major contributor. However, there are many sources of uncertainty when using an SRM for hydrological simulations, such as low-quality input data, imperfect model structure and model parameters, and uncertainty from climate scenarios. Among these, the identification of model parameters is considered to be one of the major sources of uncertainty. This study evaluates the parameter uncertainty for SRM simulation based on different calibration strategies, as well as its impact on future hydrological projections in a data-scarce deglaciating river basin. The generalized likelihood uncertainty estimation (GLUE) method implemented by Monte Carlo sampling was used to estimate the model uncertainty arising from parameters calibrated by means of different strategies. Future snowmelt runoff projections under climate change impacts in the middle of the century and their uncertainty were assessed using average annual hydrographs, annual discharge and flow duration curves as the evaluation criteria. The results show that: (1) the strategy with a division of one or two sub-period(s) in a hydrological year is more appropriate for SRM calibration, and is also more rational for hydrological climate change impact assessment; (2) the multi-year calibration strategy is also more stable; and (3) the future runoff projection contains a large amount of uncertainty, among which parameter uncertainty plays a significant role. The projections also indicate that the onset of snowmelt runoff is likely to shift earlier in the year, and the discharge over the snowmelt season is projected to increase. Overall, this study emphasizes the importance of considering the parameter uncertainty of time-varying hydrological processes in hydrological modelling and climate change impact assessment. [ABSTRACT FROM AUTHOR]

Highlights • The study shows the transferability of regionalization methods with changing climate. • The study compares the uncertainty from climate models and regionalization methods. • The difference between the regionalization methods tends to increase in the future. • In larger precipitation regions, climate models dominate the uncertainty. • Physical similarity method with parameter option produced the most robust result. Abstract Regionalization methods have been extensively discussed as the solution for runoff predictions in ungauged basins (PUB), especially during the PUB decade (2003–2012). At the same time, research topics relevant to climate change appear to be an essential and attractive field for hydrologists in recent decades, because the availability and quality of water resources are strongly affected by climate change. However, it is still unknown whether regionalization methods can be used to predict hydrological impacts of climate change for ungauged catchments or how much uncertainty of future predictions may result from the use of regionalization methods. Therefore, in this study, we investigate the transferability of regionalization methods (i.e. spatial proximity and physical similarity methods, regression method) under changing climate conditions and compare the uncertainty resulting from regionalization methods with that from using climate models. The investigation is based on 108 catchments in Norway, with large variability in climate conditions and geographic characteristics. The study applies a lumped conceptual rainfall-runoff model (WASMOD) with simple structure and six model parameters. Our result shows that (a) the differences in the predictions by the regionalization methods tend to increase in the future, (b) the physical similarity method with parameter option (i.e. the model parameters from the physically-similar donor catchments are first averaged and then used to run the model for the target catchment) shows higher transferability than other methods, (c) the uncertainty contributions from climate models and regionalization methods to future runoff prediction are basin dependent, and (d) the uncertainty of future runoff prediction due to regionalization methods can be higher than that from climate models in low precipitation areas. This study provides insight to the choice of regionalization methods under changing climate conditions and the role of regionalization methods to the uncertainty contributions in future runoff predictions. [ABSTRACT FROM AUTHOR]

Highlights • A progressive segmented optimization algorithm (PSOA) for calibration was proposed. • The PSOA calibrated time-variant parameters of Snowmelt Runoff Model effectively. • The PSOA outperformed the segmented optimization algorithm (SOA) Abstract To capture the temporal variability of parameters of hydrological models, the segmented optimization algorithm (SOA) is usually used which subdivides the calibration period into a number of sub-periods and seeks optimal parameters for each sub-period by optimizing the objective function based on the measured and estimated data in the same sub-period. In this paper, we developed a new method that is called a progressive segmented optimization algorithm (PSOA), which seeks optimal parameters by optimizing the objective function based on both the current and all the prior sub-periods. We applied and compared the SOA and PSOA algorithms to the Snowmelt Runoff Model (SRM) in simulating snow-melt streamflow for the Manasi River basin, northwest of China, during snowmelt seasons of 2001–2012. The study showed: (1) PSOA can effectively calibrate the time-variant model parameters while avoiding too much computational time caused by a significant increase of parameter dimensionality. (2) PSOA outperforms SOA for both single-snowmelt-season and multi-snowmelt-season simulations. (3) For single-snowmelt-season simulation, the length of the sub-period has an apparent effect on model performance, the shorter the sub-period is, the better the model performance will be, when the model is calibrated using the PSOA method. (4) For multi-snowmelt-season simulation, an over-short sub-period may cause overfitting problems in some cases such as the situation of taking Nash-Sutcliffe efficiency (NSE) as the objective function. A compromised length of sub-period and objective function may have to be chosen as a trade-off among evaluation criteria and between the importance of calibration and validation. [ABSTRACT FROM AUTHOR]

Summary: In this study, a GIS based simple and easily performed runoff routing approach based on travel time was developed to simulate storm runoff response process with consideration of spatial and temporal variability of runoff generation and flow routing through hillslope and river network. The watershed was discretized into grid cells, which were then classified into overland cells and channel cells through river network delineation from the DEM by use of GIS. The overland flow travel time of each overland cell was estimated by combining a steady state kinematic wave approximation with Manning’s equation, the channel flow travel time of each channel cell was estimated using Manning’s equation and the steady state continuity equation. The travel time from each grid cell to the watershed outlet is the sum of travel times of cells along the flow path. The direct runoff flow was determined by the sum of the volumetric flow rates from all contributing cells at each respective travel time for all time intervals. The approach was calibrated and verified to simulate eight storm runoff processes of Jiaokou Reservoir watershed, a sub-catchment of the Yongjiang River basin in southeast China using available topography, soil and land use data for the catchment. An average efficiency of 0.88 was obtained for the verification storms. Sensitivity analysis was conducted to investigate the effect of the area threshold of delineating river networks and parameter K relating channel velocity calculation on the predicted hydrograph at the basin outlet. The effects of different levels of grid size on the results were also studied, which showed that good results could be attained with a grid size of less than 200m in this study. [Copyright &y& Elsevier]