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As hydrological systems are pushed outside the envelope of historical experience, the ability of current hydrological models to serve as a basis for credible prediction and decision making is increasingly challenged. Conceptual models are the most common type of surface water hydrological model used for decision support due to reasonable performance in the absence of change, ease of use and computational speed that facilitate scenario, sensitivity and uncertainty analysis. Hence, conceptual models in effect represent the current “shopfront” of hydrological science as seen by practitioners. However, these models have notable limitations in their ability to resolve internal catchment processes and subsequently capture hydrological change. New thinking is needed to confront the challenges faced by the current generation of conceptual models in dealing with a changing environment. We argue the next generation of conceptual models should combine the parsimony of conceptual models with our best available scientific understanding. We propose a strategy to develop such models using multiple hydrological lines of evidence. This strategy includes using appropriately selected physically resolved models as “Virtual Hydrological Laboratories” to test and refine the simpler models' ability to predict future hydrological changes. This approach moves beyond the sole focus on “predictive skill” measured using metrics of historical performance, facilitating the development of the next generation of conceptual models with hydrological fidelity (i.e., models that “get the right answers for the right reasons”). This quest is more than a scientific curiosity; it is expected by policy makers who need to know what to plan for. Key Points New thinking is needed to improve the predictive skill of conceptual hydrological models as they are confronted by multi‐faceted change Next generation conceptual models need to increase their “hydrological fidelity” founded upon multiple hydrological lines of evidence Virtual Hydrological Laboratories accelerate this development through controlled testing for future changes yet to be observed

The economic and human losses caused by drought are increasing, driven by climate change, human activities, and increased exposure of livelihood activities in water‐dependent sectors. Mitigation of these impacts for socio‐ecological securit is necessary to gain a better understanding of how human activities contribute to the propagation of drought as water management further develops. The previous studies investigated the impact of human activities on a macro level, but they overlooked the specific effects caused by human water management measures. In addition, most studies focus on the propagation time (PT, the number of months from meteorological drought propagation to hydrological drought), while other drought propagation characteristics, such as duration, magnitude, and recovery time, are not yet sufficiently understood. To tackle these issues, the PCR‐GLOBWB v2.0 hydrological model simulated hydrological processes in China under natural and human‐influenced scenarios. The study assessed how human activities impact hydrological drought and its propagation. Result shows that human activities have exacerbated hydrological drought in northern China, while it is mitigated in the south. The propagation rate (PR, proportion of meteorological drought propagation to hydrological drought) ranges from 45% to 75%, and the PT is 6–23 months. The PR does not differ substantially between the north and south, while the PT is longer in the north. The PR decreases by 1%–60% due to human activities, and the PT decreases (1–13 months) in the north and increases (1–10 months) in the south. Human activities display significant variations in how they influence the propagation process of drought across different basins. The primary factors driving the spatial pattern of drought disparities are regional variations in irrigation methods and the storage capacity of reservoirs. Plain Language Summary Under the combined impact of climate change and human activities, economic and human losses caused by drought in China have been increasing year by year. To mitigate the impact of disasters, we conducted research using PCR‐GLOBWB v2.0 model to investigate how human activities have altered hydrological drought in China. And the role of human activities in the propagation process of drought was explored. The results indicate that human activities have intensified hydrological drought in northern China, while providing some alleviation in the southern regions. Human activities disrupt the natural processes of drought propagation, resulting in a decrease in propagation rates. Furthermore, human activities have shortened the propagation lag time of drought in the north, while increasing it in the south. Additionally, smaller basins are more sensitive to human activities compared to larger basins. Our study reveals the impact of human activities on hydrological drought and drought propagation, providing valuable insights for the development of more effective drought adaptation strategies. Key Points We used the PCR‐GLOBWB v2.0 model to study the impact of human activities on the process of drought propagation Human activities play a varying role in the propagation process of drought in different river basins Human activities has led to a decrease in drought propagation rates and shortened/prolonging the drought lag time in northern/southern China

Global hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge-which is crucial in flood simulations-has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971-2010) within the ISIMIP2a project. The runoff simulations were used as input for the global river routing model CaMa-Flood. The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about 2/3 of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.

The Bongani River is a primary source of polluted stormwater runof discharging into the shallow Ashmead Channel, a portion of the Knysna Estuary situated on the southern coast of South Africa. One of the ways to improve the quality of stormwater in the Bongani River is to introduce sustainable drainage systems (SuDS) into the catchment area to improve stormwater management. The feasibility of reducing nutrient loads using SuDS was investigated using a continuous hydrological model of the Bongani River and its catchment. Besides the current situation (Current Scenario), various scenarios were developed in PCSWMM (Personal Computer Stormwater Management Model). The total phosphorus reduction objective for SuDS set by the City of Cape Town (used in the absence of Knysna-specific stormwater quality objectives) is 45%. All the scenarios modelled showed pollutant load reductions of between 47% and 78%, exceeding the 45% target, but none approached the pre-development baseline which indicated some 89% and 90% lower concentrations of total nitrogen and total phosphorus, respectively, compared to current conditions. This performance gap highlights the extent of nutrient enrichment in the Bongani River catchment and suggests that, while SuDS can provide improvements, additional watershed-scale interventions are necessary to restore water quality conditions.

Collective memory plays a controlling role in adaptation to potential flood risks, by learning from past disasters. However, with little quantitative empirical data, previous socio‐hydrological models have conceptualized the decaying process of flood memory in an oversimple approach. Here, based on survey data of 683 respondents on Ningxia Floodplain, we confirmed that flood memory decays overtime via two channels: oral communication (communicative memory) and physical recording of information (cultural memory). Using the Universal Decay Model (UDM) proposed by previous researchers provides better fitting of results to the decay of flooding memory (adjusted R2 coefficient are 0.97, 0.90, 0.95 when data of all, rural or urban respondents used, respectively) compared with the original exponential model (adjusted R2 coefficient are 0.91, 0.74, 0.59, corresponding). Then, significantly reduced losses for the same flood sequence predicted by integrating the UDM into a socio‐hydrological model by 16% and the differences between different clusters (urban and rural respondents) can even reach 22.81%. These differences suggest that previous socio‐hydrological models have been too simplistic in their conceptualizations of decaying processes associated with collective memory, which may have limited deeper insights into flood risk management.

Understanding the hydrological processes on the Tibetan Plateau (TP) under climate change is an important scientific question. The frequent multiphase transfer exacerbates the complexity of hydrological processes on the TP, which brings equifinality problem to hydrological models and causes large uncertainties in quantifying the contributions of runoff components. Tracer‐aided hydrological models are helpful for improving model performances and have been adopted in cryospheric regions, but the influence of frozen soil has yet to be considered. This study adopted the Tracer‐aided Tsinghua Representative Elementary Watershed model (THREW‐T) in a typical cold basin with widespread frozen soil on the TP. The model structure was diagnosed with isotope by identifying the influences of frozen soil. A simplified catchment‐scale frozen soil module was incorporated into the model. Results showed that: (a) The THREW‐T model cannot simultaneously simulate baseflow and stream water isotope well. The imbalance of simulations on two objectives could be attributed to the influence of frozen soil, resulting in seasonal variation of soil‐related parameters, which was not considered in the model. (b) Incorporating the frozen soil module significantly improved the balance of baseflow and isotope simulation, simultaneously producing low baseflow and high contribution of subsurface runoff during wet seasons. (c) The frozen soil had little influence on the annual streamflow, but changed the runoff seasonality by reducing baseflow during dry seasons and increasing subsurface runoff during wet seasons. The frozen soil module was still simplified, and further work is needed to improve the physical representation of soil freeze‐thaw process. This study highlights the value of tracer‐aided hydrological modeling method on diagnosing model structure by identifying the influence of specific processes such as frozen soil. Plain Language Summary Soil freeze‐thaw process has important impact on hydrological processes by influencing the hydraulic properties of soil, leading to complex hydrological processes in cold regions and uncertainties in hydrological modeling. Tracer‐aided hydrological models incorporating the simulations of tracers (e.g., stable isotope in water) are helpful for improving model performances, but their values on identifying the impact of frozen soil and reducing related uncertainties are inadequately explored. In this study, we found that the Tracer‐aided Tsinghua Representative Elementary Watershed model (THREW‐T) cannot achieve good simulation of baseflow and stream water isotope simultaneously. We attributed the imbalance of two objectives to the seasonal variation of soil‐related parameters caused by frozen soil, which was not considered in the original model. We developed a simplified frozen soil module to characterize the variations of soil storage and hydraulic conductivity. The model incorporated with this module performed well on the baseflow and isotope simulations, by simulating low baseflow during dry seasons and high contribution of subsurface runoff during wet seasons simultaneously. Given that the streamflow could be simulated well even if not considering frozen soil, this study highlights the value of tracer‐aided modeling on diagnosing model structure by identifying the hydrological impact of frozen soil. Key Points Frozen soil resulted in the imbalanced simulation on baseflow and isotope of THREW‐T model The developed frozen soil module improved the balance of simulations on multiple objectives The tracer‐aided modeling method has significant value on diagnosing model structure and identifying the hydrological impact of frozen soil

This study aims to present a process for hydrological model exploration for selecting an appropriate model compatible with the modeling objectives. The process consists of three stages: (1) initial choice based on the modeling objectives; (2) model selection based on intercomparison among underlying conceptualizations of the models; and (3) final model selection based on influencing criteria such as availability of the model software and documentation, and availability of appropriate data. As an applied example, the process was used to find an appropriate model for a project to evaluate water supply and demand under climate and land use change scenarios in the Gorgan‐rud River Basin, Iran. The criteria affecting the final choice of a hydrological model were classified into three categories: (1) criteria related to the model, (2) criteria related to the model user, and (3) criteria related to the study area. Recommendations for resource managers It is vital to simulate the hydrological conditions on an appropriate temporal and spatial scale useful for management purposes. The simulation resolution should be consistent with the resource management requirements. The simulation resolution depends on modeling objectives. The criteria related to data availability, the model user and those related to the study area are among the main factors affecting the final choice of a hydrological model.

Floods are one of the main natural disaster threats to the safety of people’s lives and property. Flood hazards intensify as the global risk of flooding increases. The control of flood disasters on the basin scale has always been an urgent problem to be solved that is firmly associated with the sustainable development of water resources. As important nonengineering measures for flood simulation and flood control, the hydrological and hydraulic models have been widely applied in recent decades. In our study, on the basis of sufficient remote-sensing and hydrological data, a hydrological (Xin’anjiang (XAJ)) and a two-dimensional hydraulic (2D) model were constructed to simulate flood events and provide support for basin flood management. In the Chengcun basin, the two models were applied, and the model parameters were calibrated by the parameter estimation (PEST) automatic calibration algorithm in combination with the measured data of 10 typical flood events from 1990 to 1996. Results show that the two models performed well in the Chengcun basin. The average Nash–Sutcliffe efficiency (NSE), percentage error of peak discharge (PE), and percentage error of flood volume (RE) were 0.79, 16.55%, and 18.27%, respectively, for the XAJ model, and those values were 0.76, 12.83%, and 11.03% for 2D model. These results indicate that the models had high accuracy, and hydrological and hydraulic models both had good application performance in the Chengcun basin. The study can a provide decision-making basis and theoretical support for flood simulation, and the formulation of flood control and disaster mitigation measures in the basin.

An assessment of climate impacts in the hydrologic system of the Blue Nile basin is useful for enhancing water management planning and basin-wide policymaking. Climate change adaptation activities predominantly require an understanding of the range of impacts on the water resource. In this study, we assessed climate change impacts on the Blue Nile River using 30-year in situ climate data (1981–2010) and five bias-corrected General Circulation Models (GCMs) for future (2026–2045) climate projections of RCP8.5. Both historical and GCM precipitation projections show inter-annual and spatial variability, with the most significant increases in the rainy season and a significant decrease in the dry season. The results suggest the probability of an increase in total precipitation. The intensity and frequency of future extreme rainfall events will also increase. Moreover, the hydrological model simulation results show a likely increase in total river flow, peak discharges, flood inundation, and evapotranspiration that will lead to a higher risk of floods and droughts in the future. These results suggest that the operation of water storage systems (e.g., the Grand Ethiopian Renaissance Dam) should be optimized for Disaster Risk Reduction (DRR) and irrigation management in addition to their intended purposes in the Nile basin.

The Yellow River Basin faces water scarcity and ecological fragility. Changes on the land surface, characterized by large‐scale soil and water conservation measures, have a significant impact on river runoff and ecological environment. However, there are still great uncertainties in the scientific understanding of the mechanisms by which multiple driver impact eco‐hydrological processes due to the diversity of land surfaces and the complexity of the coupling processes. As an international scientific frontier on interdisciplinary studies in climatology, hydrology, ecology, and other related fields, it is significant to study the mechanisms and assess the impacts of land surface change on eco‐hydrological risk to support ecological restoration plan and sustainable water resources utilization in the Yellow River Basin. Taking the Yellow River Basin as the study area, this study proposes several important research initiatives, focusing on addressing the ecological and water resources problems in the Loess Plateau. These initiatives include (1) to quantify the individual effect of land surface elements (e.g., vegetation, terraces, and check dam) and reveal the nonlinear driving mechanisms of multiple drivers on eco‐hydrological processes; (2) to construct a distributed eco‐hydrological model that couples dynamic land surface features, and simulate eco‐hydrological processes in a changing environment; (3) to improve the ecological risk assessment indicator system and methods for assessing the impacts of land surface changes on eco‐hydrological synergistic functions and ecological risk; (4) to establish an ecological regulation model based on multiobjective game theory and adopt an adaptive regulation mode for ecological risk management. The research could enrich the scientific understanding and theory of eco‐hydrology, and prompt disciplinary studies of ecology, hydrology, climatology, and other fields. The expected academic achievements will innovate eco‐hydrological simulation and assessment techniques in a changing environment, and strongly support the implementation of the national strategy for ecological protection and high‐quality development in the Yellow River Basin.