Complex River Basin Research Articles

Evaluation of distributed and semi-distributed hydrological models in complex River Basin system, Nepal

Hydrological information is essential for planning water resource projects and for simulating hydrological models to calibrate and generate streamflow data. This study evaluates the performance of distributed and semi-distributed hydrological models in the Tamakoshi River Basin (TRB), Nepal. The models assessed include the Spatial Process in Hydrology (SPHY), Hydrologiska Byråns Vattenbalansavdelning (HBV), and Hydrologic Engineering Centre Hydrologic Modeling System (HEC-HMS). The models were evaluated using metrics such as Nash-Sutcliffe Efficiency (NSE) ranging from 0.62 to 0.77, Coefficient of Determination (R2) from 0.76 to 0.77, and Percentage Bias (P Bias) from 26.16 % to −3.54 % during daily calibration. All three models were successfully calibrated and validated on a daily and monthly basis using observed discharge data at the Busti station in the TRB. The SPHY model performed better during the calibration period compared to the validation period, while the HBV and HEC-HMS models showed better performance during validation than calibration. Among the statistical indicators, the coefficient of determination closely matched, but NSE and P Bias showed some deviations. This comparative analysis of calibrated and validated models is valuable for filling gaps in hydrological data records and for selecting appropriate hydrological models for planning, managing, and developing water resource projects in the TRB.

Flood Simulation in the Complex River Basin Affected by Hydraulic Structures Using a Coupled Hydrological and Hydrodynamic Model

Due to the complexity of terrain and climate in the mountain–plain transition zone, it is difficult to simulate and forecast the flow discharge of river basins accurately. The poor regularity of the river thus leads to uncertain flood control scheduling. Meanwhile, reservoirs and flood detention areas are constructed to store and divert water when severe floods threaten the safety of the basin. In order to improve the accuracy of flood forecasts and the effectiveness of flood control, a hydrological and 1D/2D hydrodynamic coupling model was developed to enable the joint computation of multiple objects, including mountainous streams, plains river networks, hydraulic control structures, and flood detention areas. For the hydrological component, the Xin’anjiang model with the Muskingum module is employed to simulate mountainous flow discharge. For the hydrodynamic component, the Saint–Venant equations and shallow water equations are applied to estimate flood processes in rivers and on land surfaces, respectively. The Dongtiaoxi River Basin in Zhejiang Province, China, serves as the case study, where river flow is influenced by both upstream mountainous floods and downstream backwater effects. Using the integrated model, flood routing and scheduling are simulated and visualized. Both the Xin’anjiang model and the 1D hydrodynamic model demonstrate over 80% acceptability in calibration and validation, confirming their robustness and reliability. Meanwhile, inundation in flood detention areas can be effectively estimated by coupling the 1D and 2D hydrodynamic models with a flood diversion scheduling model. The coupled model proves capable of simulating flood routing in complex river basins that include mountains, plains, and hydraulic control structures, accounting for the interactions between hydrological elements. These findings provide a new perspective on flood simulation in other similarly complex river basins.

Evaluation of Water Resources in a Complex River Basin Using Water Accounting Plus: A Case Study of the Mahi River Basin in India

Evaluation of Water Resources in a Complex River Basin Using Water Accounting Plus: A Case Study of the Mahi River Basin in India

Unraveling spatial patterns and source attribution of nutrient transport: Towards optimal best management practices in complex river basin

A comprehensive understanding of nutrient transport patterns and clarification of pollutant sources' load contributions are critical prerequisites for developing scientific pollution control strategies in complex river basins. Here, we focused on the Minjiang River Basin (MRB) and employed the Soil and Water Assessment Tool (SWAT) model to systematically investigate the nitrogen (N) and phosphorus (P) loads from both point and non-point sources. Results revealed that the key source areas of N and P pollution in the MRB were predominantly located along the riverbanks, influenced by a combination of sediment, precipitation, agricultural activities such as fertilization. Our analysis indicated that soil nutrient loss, fertilization, and livestock farming were the major contributors to N and P inputs, accounting for over 70 % of the total input, followed by rural residential and urban point sources. Based on the identification of non-point source pollution as the primary load source, a multi-objective optimization was conducted using response surface methodology (RSM) coupled with the non-dominated sorting genetic algorithm-II (NSGA-II), resulting in the identification of optimal best management practices (BMPs) that achieve a reduction of 40.04 % in N load, 39.22 % in P load, and a net economic benefit of −1.13 billion yuan per year. Compared to the RSM and automated optimization results, the proposed management measures exhibited significant improvements in N and P load reduction and net benefits. Overall, the findings provide important insights for formulating agricultural management policies in the MRB and offering valuable implications for pollution management in other complex river basins.

Landscape Pollution Source Dynamics Highlight Priority Locations for Basin‐Scale Interventions to Protect Water Quality Under Hydroclimatic Variability

AbstractExtreme weather is associated with a variety of water quality issues that can pose harm to humans and aquatic ecosystems. Under dry conditions, contaminants become concentrated in streams with a greater potential for harmful algal blooms, while wet conditions can cause flooding and broadcast pollution. Developing interventions to improve water quality in a changing climate requires a better understanding of how hydroclimatic variability affects watershed processes, and which places are most vulnerable. We developed a Soil and Water Assessment Tool model of the Cape Fear River Basin (CFRB) in North Carolina, USA, representing contemporary land use, point and non‐point sources, and weather conditions from 1979 to 2019. The CFRB is a large, complex river basin undergoing urbanization and agricultural intensification, with a history of droughts and floods. To identify intervention priorities, we developed a Water Quality Risk Index (WQRI) using the average and variability of contaminant loads across dry, normal and wet conditions. The landscape generally contributed the majority of pollutants (e.g., via erosion, fertilizer and manure applications), including 90.1% of sediment, 83.2% of total nitrogen, and 52.4% of total phosphorus at the City of Wilmington's drinking water intake, yet point sources were influential during dry periods. Approximately 16% of the watershed contributed most of the pollutants across conditions—these represent priority locations for interventions such as restoration, urban, or agricultural best management practices. The WQRI approach considering risks to water quality across conditions can help identify locations where interventions are more likely to improve water quality under climate change.

Extreme streamflow and sediment load changes in the Yellow River Basin: Impacts of climate change and human activities

In recent decades, the increasing frequency and magnitude of extreme hydrological events due to climate change and human activities have caused substantial economic losses and damages to human wellbeing. Here, we investigated the spatiotemporal variations of streamflow extremes (QE) and sediment load extremes (SE) in the Yellow River (YR) during 1956–2019. Furthermore, the effects of main human activities and climate change were identified by establishing quantitative relationships between these factors and changing hydrological extremes. Specifically, the QE and SE have decreased significantly (p < 0.05) since 1956 except the headwater (reach above Tangnaihai). However, the QE increased significantly (p < 0.05) during 2000–2019 due to increased extreme precipitation, while the SE tended to stabilize at most stations. Besides, the contribution of QE to annual streamflow declined distinctly in the upper-middle reaches (Lanzhou-Tongguan reach) but increased significantly in the lower reaches (reach below Huayuankou). Likewise, the contribution of SE to annual sediment load increased remarkably in the middle-lower reaches (Huayuankou-Lijin reach). Furthermore, the timing of QE and SE generally tended to disperse from the flood season to the four seasons. While extreme precipitation fundamentally caused the extreme water and sediment discharge, the magnitude and hazard of QE and SE can be strongly regulated by human activities. Particularly, mainstream dams can artificially regulate QE and SE magnitudes and relationships and reduce their synchronization probability, and intra-basin engineering construction and revegetation measures can substantially reduce their possible peaks in a power function form. In addition, changes in the extreme water–sediment relationships indicated that declining erosive power in the middle reaches and decreasing sediment availability in the lower reaches dominated SE reduction. This study provides a scientific basis for flood risk management and water resources development and utilization in large complex river basins.

Hydrological Impact Assessment of Future Climate Change on a Complex River Basin of Western Ghats, India

Climate change (CC) affects millions of people directly or indirectly. Especially, the effect of CC on the hydrological regime is extensive. Hence, understanding its impact is highly essential. In this study, the Bharathapuzha river basin (BRB) lying in the Western Ghats region of southern India is considered for CC impact assessment, as it is a highly complex and challenging watershed, due to its varying topographical features, such as soil texture, land use/land cover types, slope, and climatology, including rainfall and temperature patterns. To understand the CC impact on the hydrological variables at BRB in the future, five downscaled global circulation models (GCMs) were used, namely BNU-ESM, Can-ESM, CNRM, MPI-ESM MR, and MPI-ESM LR. These GCMs were obtained for two representative concentration pathway (RCP) scenarios: 4.5 representing normal condition and 8.5 representing the worst condition of projected carbon and greenhouse gases concentration on the lower atmosphere. To obtain the continuous simulation of hydrological variables, the SWAT hydrological model was adopted in this study. Results showed that rainfall pattern, evapotranspiration, and soil moisture will increase at moderate to significant levels in the future. This is especially seen during the far future period (i.e., 2071 to 2100). Similar results were obtained for surface runoff. For instance, surface runoff will increase up to 19.2% (RCP 4.5) and 36% (RCP 8.5) during 2100, as compared to the average historical condition (1981–2010). The results from this study will be useful for various water resources management and adaptation measures in the future, and the methodology can be adopted for similar regions.

Assessing Climate Change Impact on Water Resources in Water Demand Scenarios Using SWAT-MODFLOW-WEAP

In this article, we present the use of the coupled land surface model and groundwater flow model SWAT-MODFLOW with the decision support tool WEAP (Water Evaluation and Planning software) to predict future surface-water abstraction scenarios in a complex river basin under conditions of climate change. The modelling framework is applied to the Dee River catchment in Wales, United Kingdom. Regarding hydrology, the coupled model improves overall water balance and low-streamflow conditions compared with a stand-alone SWAT model. The calibrated SWAT-MODFLOW is employed with high-resolution climate model data from the UKCP18 project with the future scenario of RCP85 from 2020 to 2040. Then, water supply results from SWAT-MODFLOW are fed into WEAP as input for the river reach in the downstream region of the river basin. This system is utilized to create various future scenarios of the surface-water abstraction of public water supply in the downstream region—maximum licensed withdraw, 50% authorized abstractions, monthly time series with 1% increases in water use, and maximum water withdraw per year based on historical records repeated every year with 1% increases in water use—to estimate the unmet demands and streamflow requirement. This modelling approach can be used in other river basins to manage scenarios of supply and demand.

Stream Distance-Based Geographically Weighted Regression for Exploring Watershed Characteristics and Water Quality Relationships

We developed a novel spatial stream network geographically weighted regression (SSN-GWR) by incorporating stream-distance metrics into GWR. The model was tested for predicting seasonal total nitrogen (TN) and total suspended solids (TSS) concentrations in relation to watershed characteristics for 108 sites in the Han River Basin, South Korea. The SSN-GWR model was run with the average seasonal water quality parameters from 2012 through 2016 and was validated with the data from 2017 through 2021. The model fit among ordinary least square regression, standard GWR (STD-GWR), and stream distance weighted SSN-GWR were compared based on their ability to explain the variation of seasonal water quality parameters. We also compared residual spatial autocorrelations as well as various error parameters from these models. Compared to the STD-GWR model, the SSN-GWR model generally provided better model fit, reduced residual spatial autocorrelation, and lessened overall modeling errors. Results show that the spatial patterns of model fit, as well as various coefficients from the upstream distance weighted regressions, capture local patterns as a product of upstream–downstream relations. We demonstrate that a successful model could be developed by integrating stream distance into the GWR, which not only improves model fit but also reveals realistic hydrological processes that relate watershed characteristics to water quality along with the stream network. The local variations in model fit derived from this work can be used to devise fine-scale interventions for water quality improvements in a spatially heterogeneous complex river basin.

Using the WEI+ index to evaluate water scarcity at highly regulated river basins with conjunctive uses of surface and groundwater resources.

This paper discusses the role and limitations of using WEI+ as a water resource management tool for highly regulated river basins, with a conjunctive use of surface and groundwater resources. By considering flow regulation by reservoirs and aquifer systems, seasonality of water availability and demand, returns from water uses and environmental flow requirements, WEI+ constitutes an improvement to existing quantitative water scarcity indexes. However, the computation of WEI+ in complex river basins systems requires detailed data on water availability and water allocation to various uses, which are hard to obtain from monitoring records. The paper describes how the combined use of hydrological and water allocation models can help to overcome data gaps in water accounting and contribute to an improved analysis of water scarcity in heterogeneous and intricate river basins. It also examines the information provided by WEI+ and by other widely used water scarcity indexes, such as the Water Stress Index and the Criticality Ratio, as well as discusses the ability of WEI+ to measure the performance of hydraulic systems, usually evaluated by parameters such as reliability, vulnerability, and resilience. The Tagus River transboundary basin was selected as case study due to massive flow regulation by multi-purpose reservoirs and significant seasonality of water availability and demand. Results show the benefits of using WEI+ to define levels of water scarcity, over other indexes. Within the Tagus River systems, high values of WEI+ are reached during the summer months in regions with intensive agriculture, denoting severe water stress conditions in most sub-basins. The analysis also reveals the strong dependence of Portugal, the downstream country, on flows from Spain, the upstream country.

Estimation of Potential Soil Erosion and Sediment Yield: A Case Study of the Transboundary Chenab River Catchment

Near real-time estimation of soil loss from river catchments is crucial for minimizing environmental degradation of complex river basins. The Chenab river is one of the most complex river basins of the world and is facing severe soil loss due to extreme hydrometeorological conditions, unpredictable hydrologic response, and complex orography. Resultantly, huge soil erosion and sediment yield (SY) not only cause irreversible environmental degradation in the Chenab river catchment but also deteriorate the downstream water resources. In this study, potential soil erosion (PSE) is estimated from the transboundary Chenab river catchment using the Revised Universal Soil Loss Equation (RUSLE), coupled with remote sensing (RS) and geographic information system (GIS). Land Use of the European Space Agency (ESA), Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data, and world soil map of Food and Agriculture Organization (FAO)/The United Nations Educational, Scientific and Cultural Organization were incorporated into the study. The SY was estimated on monthly, quarterly, seasonal, and annual time-scales using sediment delivery ratio (SDR) estimated through the area, slope, and curve number (CN)-based approaches. The 30-year average PSE from the Chenab river catchment was estimated as 177.8, 61.5, 310.3, 39.5, 26.9, 47.1, and 99.1 tons/ha for annual, rabi, kharif, fall, winter, spring, and summer time scales, respectively. The 30-year average annual SY from the Chenab river catchment was estimated as 4.086, 6.163, and 7.502 million tons based on area, slope, and CN approaches. The time series trends analysis of SY indicated an increase of 0.0895, 0.1387, and 0.1698 million tons per year for area, slope, and CN-based approaches, respectively. It is recommended that the areas, except for slight erosion intensity, should be focused on framing strategies for control and mitigation of soil erosion in the Chenab river catchment.

Using Isotopic Data to Evaluate Esox lucius (Linnaeus, 1758) Natal Origins in a Hydrologically Complex River Basin

Otolith microchemistry has emerged as a powerful technique with which to identify the natal origins of fishes, but it relies on differences in underlying geology that may occur over large spatial scales. An examination of how small a spatial scale on which this technique can be implemented, especially in water bodies that share a large proportion of their flow, would be useful for guiding aquatic invasive species control efforts. We examined trace isotopic signatures in northern pike (Esox lucius) otoliths to estimate their provenance between two reservoirs in the Upper Yampa River Basin, Colorado, USA. This is a challenging study area as these reservoirs are only 11-rkm apart on the same river and thus share a high proportion of their inflow. We found that three isotopes (86Sr, 137Ba, and 55Mn) were useful in discriminating between these reservoirs, but their signatures varied annually, and the values overlapped. Strontium isotope ratios (87Sr/86Sr) were different between sites and relatively stable across three years, which made them an ideal marker for determining northern pike provenance. Our study demonstrates the usefulness of otolith microchemistry for natal origin determination within the same river over a relatively small spatial scale when there are geologic differences between sites, especially geologic differences underlying tributaries between sites.

Flood Mitigation in the Transboundary Chenab River Basin: A Basin-Wise Approach from Flood Forecasting to Management

Rapid and reliable flood information is crucial for minimizing post-event catastrophes in the complex river basins of the world. The Chenab River basin is one of the complex river basins of the world, facing adverse hydrometeorological conditions with unpredictable hydrologic response. Resultantly, many vicinities along the river undergo destructive inundation, resulting in huge life and economic losses. In this study, Hydrologic Engineering Centre–Hydrologic Modeling System (HEC-HMS) and HEC–River Analysis System (HEC-RAS) models were used for flood forecasting and inundation modeling of the Chenab River basin. The HEC-HMS model was used for peak flow simulation of 2014 flood event using Global Precipitation Mission (GMP) Integrated Multisatellite Retrievals-Final (IMERG-F), Tropical Rainfall Measuring Mission_Real Time (TRMM_3B42RT), and Global Satellite Mapping of Precipitation_Near Real Time (GSMaP_NRT) precipitation products. The calibration and validation of the HEC-RAS model were carried out for flood events of 1992 and 2014, respectively. The comparison of observed and simulated flow at the outlet indicated that IMERG-F has good peak flow simulation results. The simulated inundation extent revealed an overall accuracy of more than 90% when compared with satellite imagery. The HEC-RAS model performed well at Manning’s n of 0.06 for the river and the floodplain. From the results, it can be concluded that remote sensing integrated with HEC-HMS and HEC-RAS models could be one of the workable solutions for flood forecasting, inundation modeling, and early warning. The concept of integrated flood management (IFM) has also been translated into practical implementation for joint Indo-Pak management for flood mitigation in the transboundary Chenab River basin.

Chemical weathering and gully erosion causing land degradation in a complex river basin of Eastern India: an integrated field, analytical and artificial intelligence approach

Chemical weathering and gully erosion causing land degradation in a complex river basin of Eastern India: an integrated field, analytical and artificial intelligence approach

EDNA metabarcoding revealed differential structures of aquatic communities in a dynamic freshwater ecosystem shaped by habitat heterogeneity

Freshwater ecosystems have been threatened by complicated disturbances from both natural and anthropogenic variables, especially in dynamic and complex river basins. The environmental DNA (eDNA)-based approach provides a broader spectrum and higher throughput way of biomonitoring for biodiversity assessment compared with traditional morphological survey. Most eDNA metabarcoding studies have been limited to a few specific taxa/groups and habitat scopes. Here we applied the eDNA metabarcoding to characterize the structures and spatial variations of zooplankton and fish communities among different habitat types in a highly dynamic and complex freshwater ecosystem of the Daqing River basin (DRB). The results showed that varied species spectra of zooplankton and fish communities were identified and unique dominant species occurred across habitats. Additionally, markedly spatial distributions of biotic community structures were observed in areas with different habitat characteristics. Natural variables, including geographic distances and gradient ratio, as well as anthropogenic factors of chemical oxygen demand (COD) and organic chemicals demonstrated significant effects but different outcomes on the structures of zooplankton and fish communities. Moreover, the relative abundances of specific aquatic taxa were associated with the gradient of particular environmental variables. This case study verified the distribution patterns and differentiation mechanisms of biotic communities under habitat heterogeneity could be captured by application of eDNA biomonitoring. And habitat-specific and even species-specific environmental stressors would be diagnosed for improving management of complex river basins.

Potential of hybrid wavelet-coupled data-driven-based algorithms for daily runoff prediction in complex river basins

Potential of hybrid wavelet-coupled data-driven-based algorithms for daily runoff prediction in complex river basins

Multi-geospatial flood hazard modelling for a large and complex river basin with data sparsity: a case study of the Lam River Basin, Vietnam

Mapping flood hazard becomes a basic and crucial requirement to cope with and to mitigate flood risks. However, it is a big challenge to accurately construct a flood hazard map in the large and sparsity data basin. Here, we present a new approach to make a flood hazard map in a large and complex river basin with data sparsity based on a comprehensive analysis of the relationship between previous flood records and hydrometeorological and geographical features coupled with holistic knowledge. The results show that the AHP-GIS approach (an integrated GIS-based Analytic Hierarchy Process method) can produce more accurate and reliable flood hazard map in basins with complex geological and hydrometeorological features such as the Lam River Basin (LRB). The LRB was a high vulnerability to flooding with approximately more than 90% of the total area in this river basin was classified into moderate, high, and very high hazard of flooding. More specifically, high, and very high flood hazard area occupied nearly 30% of the total area and affected nearly 45% of households living in the basin. More noticeable, these high flood hazard areas were in small valleys along the rivers and streams running from high mountains in the southwest to the coastal region. Moreover, the study indicated that rainfall and slope were the main factors that influence mapping flood hazard and assessing flood risk in the steep slope areas.

Coordination and control – limits in standard representations of multi-reservoir operations in hydrological modeling

Abstract. Major multi-reservoir cascades represent a primary mechanism for dealing with hydrologic variability and extremes within institutionally complex river basins worldwide. These coordinated management processes fundamentally reshape water balance dynamics. Yet, multi-reservoir coordination processes have been largely ignored in the increasingly sophisticated representations of reservoir operations within large-scale hydrological models. The aim of this paper is twofold, namely (i) to provide evidence that the common modeling practice of parameterizing each reservoir in a cascade independently from the others is a significant approximation and (ii) to demonstrate potential unintended consequences of this independence approximation when simulating the dynamics of hydrological extremes in complex reservoir cascades. We explore these questions using the Water Balance Model, which features detailed representations of the human infrastructure coupled to the natural processes that shape water balance dynamics. It is applied to the Upper Snake River basin in the western US and its heavily regulated multi-reservoir cascade. We employ a time-varying sensitivity analysis that utilizes the method of Morris factor screening to explicitly track how the dominant release rule parameters evolve both along the cascade and in time according to seasonal high- and low-flow events. This enables us to address aim (i) by demonstrating how the progressive and cumulative dominance of upstream releases significantly dampens the ability of downstream reservoir rules' parameters to influence flow conditions. We address aim (ii) by comparing simulation results with observed reservoir operations during critical low-flow and high-flow events in the basin. Our time-varying parameter sensitivity analysis with the method of Morris clarifies how independent single-reservoir parameterizations and their tacit assumption of independence leads to reservoir release behaviors that generate artificial water shortages and flooding, whereas the observed coordinated cascade operations avoided these outcomes for the same events. To further explore the role of (non-)coordination in the large deviations from the observed operations, we use an offline multi-reservoir water balance model in which adding basic coordination mechanisms drawn from the observed emergency operations is sufficient to correct the deficiencies of the independently parameterized reservoir rules from the hydrological model. These results demonstrate the importance of understanding the state–space context in which reservoir releases occur and where operational coordination plays a crucial role in avoiding or mitigating water-related extremes. Understanding how major infrastructure is coordinated and controlled in major river basins is essential for properly assessing future flood and drought hazards in a changing world.

Is there enough water? How bearish and bullish outlooks are linked to decision maker perspectives on environmental flows

Policies that mandate environmental flows (e-flows) can be powerful tools for freshwater conservation, but implementation of these policies faces many hurdles. To better understand these challenges, we explored two key questions: (1) What additional data are needed to implement e-flows? and (2) What are the major socio-political barriers to implementing e-flows? We surveyed water and natural resource decision makers in the semi-arid Red River basin, Texas-Oklahoma, USA, and used social network analysis to analyze their communication patterns. Most respondents agreed that e-flows can provide important benefits and identified the same data needs. However, respondents sharply in their beliefs on other issues, and a clustering analysis revealed two distinct groups of decision makers. One cluster of decision makers tended to be bearish, or pessimistic, and believed that: current flow conditions are not adequate, there are many serious socio-political barriers to implementation, water conflicts will likely increase in the future, and climate change is likely to exacerbate these issues. The other cluster of respondents was bullish, or optimistic: they foresaw fewer future water conflicts and fewer socio-political barriers to implementation. Despite these differences, both clusters largely identified the same data needs and barriers to e-flows implementation. Our social network analysis revealed that the frequency of communication between clusters was not significantly different than the frequency of communication within clusters. Overall, our results suggest that the different perspectives of decision-makers could complicate efforts to implement e-flows and proactively plan for climate change. However, there are opportunities for collaboration on addressing common data needs and barriers to implementation. Overall, our study provides a key socio-environmental perspective on e-flows implementation from a semi-arid and socio-politically complex river basin and contextualizes the many challenges facing e-flows implementation in river basins globally.

Advancing Diagnostic Model Evaluation to Better Understand Water Shortage Mechanisms in Institutionally Complex River Basins

AbstractWater resources systems models enable valuable inferences on consequential system stressors by representing both the geophysical processes determining the movement of water and the human elements distributing it to its various competing uses. This study contributes a diagnostic evaluation framework that pairs exploratory modeling with global sensitivity analysis to enhance our ability to make inferences on water scarcity vulnerabilities in institutionally complex river basins. Diagnostic evaluation of models representing institutionally complex river basins with many stakeholders poses significant challenges. First, it needs to exploit a large and diverse suite of simulations to capture important human‐natural system interactions as well as institutionally aware behavioral mechanisms. Second, it needs to have performance metrics that are consequential and draw on decision‐relevant model outputs that adequately capture the multisector concerns that emerge from diverse basin stakeholders. We demonstrate the proposed model diagnostic framework by evaluating how potential interactions between changing hydrologic conditions and human demands influence the frequencies and durations of water shortages of varying magnitudes experienced by hundreds of users in a subbasin of the Colorado River. We show that the dominant factors shaping these effects vary both across users and, for an individual user, across percentiles of shortage magnitude. These differences hold even for users sharing diversion locations, demand levels or water right seniority. Our findings underline the importance of detailed institutional representation for such basins, as institutions strongly shape how dominant factors of stakeholder vulnerabilities propagate through the complex network of users.