Macroscale Hydrologic Model Research Articles

Global Evaluation of Simulated High and Low Flows from 23 Macroscale Models

Abstract Macroscale hydrological/land surface models are important tools for assessing historical and predicting future characteristics of extreme hydrological events, yet quantitative understandings of how these large-scale models perform in simulating extreme hydrological characteristics remain limited. Here we evaluate simulated high and low flows from 23 macroscale models within three modeling experiments (i.e., 14 climate models from CMIP6, 6 global hydrological models from ISIMIP2a, and 3 land surface models from GLDAS) against observation in 633 unimpaired catchments globally over 1971–2010. Our findings reveal limitations in simulating extreme flow characteristics by these models. Specifically, we find that (i) most models overestimate high-flow magnitudes (bias range: from +15% to +70%) and underestimate low-flow magnitudes (bias range: from −80% to −20%); (ii) interannual variability in high and low flows is reasonably reproduced by ISIMIP2a and GLDAS models but poorly reproduced by CMIP6 models; (iii) no model consistently replicates the observed trend direction in high and low flows in over two-thirds of the catchments, and most models overestimate high-flow trends and underestimate low-flow trends; and (iv) CMIP6 and GLDAS models show timing biases, with early high flows and late low flows, while ISIMIP2a models exhibit the opposite pattern. Furthermore, all models performed better in more humid environments and noncold regions, with model structure and parameterization contributing more to uncertainties than climatic forcings. Overall, our results demonstrate that extreme flow characteristics simulated from current state-of-the-art macroscale models still contain large uncertainties and provide important guidance regarding the robustness of assessing extreme hydrometeorological events based on these modeling outputs. Significance Statement Macroscale hydrological and land surface models represent crucial tools for assessing historical trends and making predictions about future hydrological changes. Nevertheless, our current understanding of the quantitative performance of these large-scale models in simulating extreme hydrological characteristics remains limited. Here, we evaluate simulated high and low flows from 23 state-of-the-art macroscale models against observation in 633 unimpaired catchments globally over 1971–2010. Our results reveal important limitations in the extreme flow characteristics simulated from these models and provide important guidance regarding the robustness of assessing extreme hydrometeorological events based on these modeling outputs. The model evaluation performed herein serves as a pivotal, offering valuable insights to inform the development of the next generation of macroscale hydrological and land surface models.

Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins

Abstract. The calibration of macroscale hydrological models is often challenged by the lack of adequate observations of river discharge and infrastructure operations. This modeling backdrop creates a number of potential pitfalls for model calibration, potentially affecting the reliability of hydrological models. Here, we introduce a novel numerical framework conceived to explore and overcome these pitfalls. Our framework consists of VIC-Res (a macroscale model setup for the Upper Mekong Basin), which is a novel variant of the Variable Infiltration Capacity (VIC) model that includes a module for representing reservoir operations, and a hydraulic model used to infer discharge time series from satellite data. Using these two models and global sensitivity analysis, we show the existence of a strong relationship between the parameterization of the hydraulic model and the performance of VIC-Res – a codependence that emerges for a variety of performance metrics that we considered. Using the results provided by the sensitivity analysis, we propose an approach for breaking this codependence and informing the hydrological model calibration, which we finally carry out with the aid of a multi-objective optimization algorithm. The approach used in this study could integrate multiple remotely sensed observations and is transferable to other poorly gauged and heavily regulated river basins.

Evaluation of two new-generation global soil databases for macro-scale hydrological modelling in Norway

Lack of national soil property maps limits the studies of soil moisture (SM) dynamics in Norway. One alternative is to apply the global soil data as input for macro-scale hydrological modelling, but the quality of these data is still unknown. The objectives of this study are 1) to evaluate two recent global soil databases (Wise30sec and SoilGrids) in comparison with data from local soil profiles; 2) to evaluate which database supports better model performance in terms of river discharge and SM for three macro-scale catchments in Norway and 3) to suggest criteria for the selection of soil data for models with different complexity. The global soil databases were evaluated in three steps: 1) the global soil data are compared directly with the Norwegian forest soil profiles; 2) the simulated discharge based on the two global soil databases is compared with observations and 3) the simulated SM is compared with three global SM products. Two hydrological models were applied to simulate discharge and SM: the Soil and Water Integrated Model (SWIM) and the Variable Infiltration Capacity (VIC) model. The comparison with data from local soil profiles shows that SoilGrids has smaller mean errors than Wise30sec, especially for upper soil layers, but both soil databases have large root mean squared errors and poor correlations. SWIM generally performs better in terms of discharge using SoilGrids than using Wise30sec and the simulated SM has higher correlations with the SM products. In contrast, the VIC model is less sensitive to soil input data and the simulated SM using Wise30sec is higher correlated with the SM products than using SoilGrids. Based on the results, we conclude that the global soil databases can provide reasonable soil property information at coarse resolutions and large areas. The selection of soil input data should depend on the characteristics of both models and study areas.

Calibration of a Distributed Hydrological Model (VIC-3L) Based on Global Water Resources Reanalysis Datasets

The lack of observed streamflow datasets for calibration of rainfall-runoff models imposes substantial problems for their applicability, especially in poorly gauged or ungauged river basins. Developing satellite technologies and increasing computational powers over the past decades, have provided an environment for researchers to simulate several water balance components globally using these datasets and assimilation techniques. Due to importance of accurate hydrologic modeling, this study aims to investigate the applicability of global water resources reanalysis (GWRR) datasets including surface soil moisture (SSM), evapotranspiration (ET), and surface runoff (SR) components for calibration of the macro-scale hydrological model (VIC-3L) over the SefidRood basin (SRB) in Iran at different calibration scenarios. Results show that in the case of using SSM datasets, the model’s performance in the simulation of streamflow hydrograph, with the NSE value higher than 0.65, is better than using other datasets. Among different datasets, the SSM based on LISFLOOD and HBV are the best ones for calibration of VIC-3L model over SRB. In contrast, using ET datasets aren’t so reliable for hydrological calibration in the study area. Furthermore, in the cases of using SSM and surface runoff datasets, the model tends to overestimation of low-flows, while, ET datasets are more reliable for simulation of such these flows. Also, findings displayed that the combination of ET and SSM datasets for hydrological calibration performed better than using only one dataset. In conclusion, this research gives useful and applied insights in the applicability of GWRR data sources for hydrological modeling and water resources studies, especially in data limited regions.

Atmospheric Rivers and Snow Accumulation in the Upper Colorado River Basin

AbstractWe utilized a macroscale hydrology model in conjunction with an atmospheric river (AR) catalog to evaluate AR‐affected snow accumulation in the Upper Colorado River basin (UCRB) headwaters for water years 1951–2015. We find that there are on average 11.4 days during which AR‐originating snow accumulates in the UCRB each year, yielding 5.75 km3 of snow water equivalent (SWE). This AR‐originating SWE accounts for 30.8% of average annual peak SWE in the basin. Most of the ARs that reach the UCRB first intercept the Sierra Nevada region of California; 84% of days affected by ARs in the UCRB are also AR‐affected days in the Sierra Nevada. The pathways of the ARs reaching the UCRB do not have a great effect on snow accumulation, however ARs that first pass through the Sierra Nevada generally produce greater snow accumulations there than in the UCRB.

Interplay of changing irrigation technologies and water reuse: example from the upper Snake River basin, Idaho, USA

Abstract. Careful allotment of water resources for irrigation is critical for ensuring the resiliency of agriculture in semiarid regions, and modernizing irrigation technology to minimize inefficient water losses is an important tool for farmers and agricultural economies. While modernizing irrigation technology can achieve reductions in the nonbeneficial use of water, such as bare soil evaporation and nonconsumptive losses, water returned to the landscape is also reduced, often eliminating flow paths that other users rely on. In basins using a combination of surface and groundwater, replenishing aquifer storage by the managed aquifer recharge (MAR) of seasonally available water can mitigate the aquifer drawdown that results from reduced recharge when irrigation efficiency is improved. We examine the effects of MAR on the system-scale efficiency of modernizing irrigation technology and the resulting changes in the reuse of nonconsumptive losses, using a macroscale hydrologic model applied to the semiarid upper Snake River basin (USRB) of western Wyoming and southern Idaho, USA. Irrigation technologies were represented explicitly in the model, and available data informed baseline parameterizations of the irrigation technology. A suite of parameterizations were simulated that updated the existing technologies to be more efficient, both with and without sufficient MAR to cause a stabilization of the aquifer at the present-day head. As expected, simulated changes in irrigation technology resulted in greater downstream export of pristine water and a higher rate of aquifer drawdown when MAR was not simulated. Under current water use and cropping patterns, we were not able to simulate aquifer stabilization and maintain discharge downstream at any level of irrigation efficiency. We found support for the hypothesis that, as efficiency improves, less MAR is required to maintain a stable aquifer than when return flows are reduced due to increased efficiency. To evaluate the hypothesis, we defined the management benefit as a metric that compared the difference between the change in irrigation's net recharge and the change in MAR required as irrigation technology became more efficient. The metric generally indicated that less MAR was needed than net recharge was lost, but only for the most efficient case did the management benefit exceed the MAR needed at the baseline to stabilize the aquifer. Increasing efficiency of irrigation technology reduced the reuse of the gross irrigation derived from prior nonconsumptive losses, but simulating MAR increased reuse for a given parameterization, leading to higher effective irrigation efficiency. We find that local groundwater storage that users depend on is generally more sensitive to management decisions than downstream flows, and the drawdown of the aquifer without MAR always exceeded any decrease in discharge induced by MAR. Improving resource sufficiency in semiarid systems like the USRB will require an array of solutions that will need to balance benefits to local and downstream users.

Simulating human impacts on global water resources using VIC-5

Abstract. Questions related to historical and future water resources and scarcity have been addressed by several macroscale hydrological models. One of these models is the Variable Infiltration Capacity (VIC) model. However, further model developments were needed to holistically assess anthropogenic impacts on global water resources using VIC. Our study developed VIC-WUR, which extends the VIC model using (1) integrated routing, (2) surface and groundwater use for various sectors (irrigation, domestic, industrial, energy, and livestock), (3) environmental flow requirements for both surface and groundwater systems, and (4) dam operation. Global gridded datasets on sectoral demands were developed separately and used as an input for the VIC-WUR model. Simulated national water withdrawals were in line with reported Food and Agriculture Organization (FAO) national annual withdrawals (adjusted R2 > 0.8), both per sector and per source. However, trends in time for domestic and industrial water withdrawal were mixed compared with previous studies. Gravity Recovery and Climate Experiment (GRACE) monthly terrestrial water storage anomalies were well represented (global mean root-mean-squared error, RMSE, values of 1.9 and 3.5 mm for annual and interannual anomalies respectively), whereas groundwater depletion trends were overestimated. The implemented anthropogenic impact modules increased simulated streamflow performance for 370 of the 462 anthropogenically impacted Global Runoff Data Centre (GRDC) monitoring stations, mostly due to the effects of reservoir operation. An assessment of environmental flow requirements indicates that global water withdrawals have to be severely limited (by 39 %) to protect aquatic ecosystems, especially with respect to groundwater withdrawals. VIC-WUR has potential for studying the impacts of climate change and anthropogenic developments on current and future water resources and sector-specific water scarcity. The additions presented here make the VIC model more suited for fully integrated worldwide water resource assessments.

Socioeconomic Drought Under Growing Population and Changing Climate: A New Index Considering the Resilience of a Regional Water Resources System

AbstractSocioeconomic drought occurs when water supply from a regional water resources system cannot meet the water demands. Even if a socioeconomic drought ends, the antecedent water deficit may continue to have impacts for some time, thus influencing the resilience of a regional water resources system. To take this into account, especially under growing population and changing climate, this study develops a new method through integrating a new index, Water Resources System Resilience Index (WRSRI), into socioeconomic drought event identification. The new index represents the percentage of the antecedent water deficit for a socioeconomic drought that can be recovered from the excess water during subsequent periods through analyzing records of a historical drought event. The methodology, implemented on the East River Basin in South China, involves three major steps: (1) calculation of WRSRI value; (2) analysis of key features of identified future socioeconomic drought events, that is, total number, longest duration (LD), and percentage on different drought levels; and (3) sensitivity analysis of WRSRI based on a total of 52 streamflow data sets generated from General Circulation Model outputs and using a macroscale hydrologic model. The results indicate that, for each data set, the total number decreases with an increase in WRSRI but the LD increases; moreover, for most data sets, the LD is less sensitive within the WRSRI range of [0, 0.6]. The outcomes of this study can enhance our capability in more effectively assessing the resilience of a regional water resources system, especially under changing future socioeconomic and environmental conditions.

Integrated sensitivity analysis of a macroscale hydrologic model in the north of the Iberian Peninsula

Process-based hydrologic models allow to identify the behavior of a basin providing a mathematical description of the hydrologic processes underlying the runoff mechanisms that govern the streamflow generation. This study focuses on a macroscale application of the Variable Infiltration Capacity (VIC) model over 31 headwater subwatersheds belonging to the Duero River Basin, located in the Iberian Peninsula, through a three-part approach: (1) the calibration and evaluation of the VIC model performance for all the subwatersheds; (2) an integrated sensitivity analysis concerning the soil parameters chosen for the calibration, and (3) an assessment of equifinality and the efficiency of the calibration algorithm. The temporal evaluation of the model was done for the calibration and the subsequent validation periods, and showed good results for most of the subwatersheds that largely improved the benchmark performance. The spatial performance reflected a high transferability for most parameter combinations, and the least transferable were related to subwatersheds located in the northern mountains. An additional evaluation of the simulated actual evapotranspiration produced satisfactory adjustments to two selected data products. The sensitivity measures were obtained with the Standardized Regression Coefficients method through a post-process of the outputs of a Monte Carlo simulation carried out for 10,000 parameter samples for each subwatershed. This allowed to quantify the sensitivity of the water balance components to the selected parameters for the calibration and understanding the strong dependencies between them. The final assessment of the equifinality hypothesis manifested that there are many parameter samples with performances as good as the optimum, calculated using the Shuffled-Complex-Evolution Algorithm. For almost all the analyzed subwatersheds the calibration algorithm resulted efficient, reaching the optimal fit. Both the Monte Carlo simulation and the use of a calibration algorithm will be of interest for other feasible applications of the VIC model in other river basins.

Identification of uncertainty sources in quasi-global discharge and inundation simulations using satellite-based precipitation products

Predicting river discharge and inundation is crucial for water resources management and flood hazard reduction; however, it is still unclear to what extent their variabilities can be captured on global scale. This study evaluates uncertainty sources in the quasi-global river discharge and inundation simulations using the Variable Infiltration Capacity (VIC) macroscale hydrologic model and the Catchment-based Macroscale Floodplain (CaMa-Flood) hydrodynamic model, forced with five high-resolution satellite precipitation datasets. The simulated discharge is first evaluated against more than 2852 sites selected from the Global Streamflow Indices and Metadata Archive (GSIM) dataset, and then the simulated inundation is compared with complementary multiple satellite observations. Globally, about 38% – 43% of the stations produce reasonable discharge simulations with positive Kling-Gupta Efficiency (KGE) on monthly time scale. The simulations show good agreement for flood fractions with mean correlations ranging from 0.47 to 0.62 for satellite detected events. The potential uncertainties sources of discharge and inundation simulation related to physics setting and forcing datasets, such as precipitation, land surface model, routing model, and observation from site and satellite are discussed, as well as future directions for improving large-scale model applications. By using default model settings, we hope our study can offer valuable insights into the applicability of flood simulations and provide guides for model development.

Aridity Trends in Central America: A Spatial Correlation Analysis

Trend analyses are common in several types of climate change studies. In many cases, finding evidence that the trends are different from zero in hydroclimate variables is of particular interest. However, when estimating the confidence interval of a set of hydroclimate stations or gridded data the spatial correlation between can affect the significance assessment using for example traditional non-parametric and parametric methods. For this reason, Monte Carlo simulations are needed in order to generate maps of corrected trend significance. In this article, we determined the significance of trends in aridity, modeled runoff using the Variable Infiltration Capacity Macroscale Hydrological model, Hagreaves potential evapotranspiration (PET) and near-surface temperature in Central America. Linear-regression models were fitted considering that the predictor variable is the time variable (years from 1970 to 1999) and predictand variable corresponds to each of the previously mentioned hydroclimate variables. In order to establish if the temporal trends were significantly different from zero, a Mann Kendall and a Monte Carlo test were used. The spatial correlation was calculated first to correct the variance of each trend. It was assumed in this case that the trends form a spatial stochastic process that can be modeled as such. Results show that the analysis considering the spatial correlation proposed here can be used for identifying those extreme trends. However, a set of variables with strong spatial correlation such as temperature can have robust and widespread significant trends assuming independence, but the vast majority of the stations can still fail the Monte Carlo test. We must be vigilant of the statistically robust changes in key primary parameters such as temperature and precipitation, which are the driving sources of hydrological alterations that may affect social and environmental systems in the future.

A software package for the representation and optimization of water reservoir operations in the VIC hydrologic model

Macroscale hydrological and land surface models increasingly rely on novel streamflow routing algorithms that explicitly account for the presence of engineered water storages, which largely affect river basin dynamics. In this short communication, we contribute to this growing field by presenting VIC-ResOpt, a software package for the representation and optimization of water reservoirs in the routing model commonly used as a post-processor with the Variable Infiltration Capacity (VIC) hydrologic model. VIC-ResOpt comprises tools for simulating different reservoir operating approaches, optimizing operations, and exploring the sensitivity of the model output with respect to the parameterization of the operating rules. The package relies on automated scripts and optimization engines, thereby requiring minimal user effort. We demonstrate some of its functionalities in the upper portion of the Chao Phraya river basin (Thailand), which is regulated by two large dams.

Understanding Reservoir Operating Rules in the Transboundary Nile River Basin Using Macroscale Hydrologic Modeling with Satellite Measurements

Abstract Challenges to manage and secure a sustainable water supply are expected to become more acute in Egypt as the lowermost riparian country of the Nile basin with the construction of new transboundary water infrastructures in Ethiopia and Sudan. To understand the impact of such transboundary water projects on Egypt, it is first necessary to develop a modeling tool that can simulate potential flow and reservoir scenarios inside Egypt without requiring in situ hydrologic or transboundary dam data that are typically unavailable. This study presents the water management value of a modeling framework to predict the current and future reservoir operating rules in the lower Nile basin using satellite Earth observations and hydrologic models. The platform comprises the Variable Infiltration Capacity (VIC) hydrologic model driven by high spatial and temporal resolution of satellite observations. Reservoir storage change is estimated using altimeter and visible imagery of lake area for Lake Nasser and then applied to infer reservoir operation for High Aswan Dam (HAD). The modeling framework based on satellite observations yielded a simulated streamflow at the outlet for Blue Nile basin (BNB) with a Nash–Sutcliffe efficiency of 0.68 with a correlation and RMSE of 0.94 and 1095 m3 s−1, respectively. Storage and outflow discharge of HAD were estimated for the period of 1998–2002 within 1.4% accuracy (0.076 km3 month−1) when compared with published reports. Because BNB controls the lion’s share of the variability to HAD inflow inside Egypt, the proposed modeling framework is appropriate for policy-makers to understand the implications of transboundary projects on the future water security of Egypt.

Future Carbon Emission From Boreal and Permafrost Lakes Are Sensitive to Catchment Organic Carbon Loads

AbstractCarbon storage, processing, and transport in freshwater systems are important components of the global carbon cycle and sensitive to global change. However, in large‐scale modeling this part of the boundless carbon cycle is often lacking or represented in a very simplified way. A new process‐oriented lake biogeochemical model is used for investigating impacts of changes in atmospheric CO2 concentrations and organic carbon loading from the catchment on future greenhouse gas emissions from lakes across two boreal to subarctic regions (Northern Sweden and Alaska). Aquatic processes represented include carbon, oxygen, phytoplankton, and nutrient dynamics leading to CO2 and CH4 exchanges with the atmosphere. The model is running inside a macroscale hydrological model and may be easily implemented into a land surface scheme. Model evaluation demonstrates the validity in terms of average concentration of nutrients, algal biomass, and organic and inorganic carbon. Cumulative annual emissions of CH4 and CO2, as well as pathways of CH4 emissions, also compare well to observations. Model calculations imply that lake emissions of CH4 may increase by up to 45% under the Representative Concentration Pathway 8.5 scenario until 2100, and CO2 emissions may increase by up to 80% in Alaska. Increasing organic carbon loading to the lakes resulted in a linear response in CO2 and CH4 emissions across both regions, but increases in CO2 emissions from subarctic lakes in Sweden were lower than for southern boreal lakes, probably due to the higher importance of imported vegetation‐“generated” inorganic carbon for CO2 emission from subarctic lakes.

Projecting climate change impacts on hydrological processes on the Tibetan Plateau with model calibration against the glacier inventory data and observed streamflow

Analyzing the impacts of climate change on hydrology and future projections of water supplies is fundamental for the efficient management and planning of water resources in large river systems on the Tibetan Plateau (TP), which is known as the “water tower of Asia.” However, large uncertainties remain in the projections of streamflow and glaciers in these cryospheric catchments due to great uncertainties in climate change projection and modeling processes. In this work, we developed an extended Variable Infiltration Capacity (VIC) macroscale hydrological model (named VIC-CAS), which was coupled with glacier melting and glacier evolution schemes. A two-stage calibration procedure that used glacier inventory data and the observed streamflow was adopted to derive the model parameters. The calibrated VIC-CAS model was then used to assess the future change in glaciers and runoff using downscaled climate model data in the upstream regimes of the Yellow, Yangtze, Mekong, Salween, and Brahmaputra rivers on the TP. The results indicated that both temperature and precipitation were projected to increase, resulting in a greater than 50% decline of the glacier area by the end of the 21st century in the five catchments. Glacier runoff was already beyond its tipping point at the beginning of the 21st century with a greater than 20% loss of the glacier area except in the upstream of the Yangtze River, where glacier runoff was projected to decrease after the 2030 s. Annual streamflow was projected to increase significantly as a result of increased rainfall-induced runoff, compensating for the reduced glacier/snow melt water in the five major upstream river basins. The increasing rate of warm season streamflow was clearly less than that of annual runoff. A negative trend in warm season streamflow was expected if precipitation did not sufficiently increase. The annual hydrograph remained largely unchanged, except in the upstream of the Yellow River, where peak streamflow was predicted to occur 1 month earlier because of the earlier snowmelt and greater rainfall/precipitation ratio from May to June.

An improved operation-based reservoir scheme integrated with Variable Infiltration Capacity model for multiyear and multipurpose reservoirs

Multiyear and multipurpose reservoirs generally need to adjust operational functions for different storage levels; most existing reservoir schemes lack the pertinence to model the complex behaviors of such reservoirs. This paper proposes an improved operation-based reservoir scheme to simulate the storage and outflow variations for multiyear and multipurpose reservoirs at a daily time step. In this improved reservoir scheme, the new parametric functions to represent the weights of the outflow through considering various operation purposes (e.g., hydropower generation, flood control, and water supply) are introduced. Then, the improved reservoir scheme is integrated into a macroscale hydrological model, i.e., Variable Infiltration Capacity (VIC) model. In this study, the performance of the proposed reservoir scheme is evaluated with the observed storage and outflow of a multiyear and multipurpose reservoir (Xinfengjiang Reservoir) in South China and compared to two other reservoir schemes (i.e., a multilinear regression reservoir scheme and an operation-based reservoir scheme). In addition, through uncertainty analysis, this study shows that the time-varying operation-based parameters can reflect the changes of reservoir storage but not reservoir outflow, indicating that the parameters for establishing functional relationships need further exploration. Results reveal that the proposed reservoir scheme has a wide applicability for reservoir storage and outflow simulation, especially for the reservoirs with limited reservoir management data.

Projected glacier meltwater and river run‐off changes in the Upper Reach of the Shule River Basin, north‐eastern edge of the Tibetan Plateau

AbstractGlacier meltwater change in the north‐eastern edge of the Tibetan Plateau is greatly important for the projection of the impact of future climate change on local water resource management. Although the glaciated area is only approximately 4% of the Upper Reach of the Shule River Basin (URSRB), the average glacier meltwater contribution to river run‐off was approximately 23.6% during the periods 1971/1972 to 2012/2013. A new glacier melting module coupled with the macroscale hydrologic Variable Infiltration Capacity model (VIC‐CAS) was adopted to simulate and project changes in the glacier meltwater and river run‐off of the URSRB forced by downscaled output of the BCC‐CSM1.1(m), CANESM2, GFDL‐CM3, and IPSL‐CM5A‐MR models. Comparisons between the observed and simulated river run‐offs and glacier area changes during the periods 2000/2001, 2004/2006, 2008/2009, and 2012/2013 suggest that the simulation is reasonable. Due to increases in precipitation, the annual total run‐off is projected to increase by approximately 2.58–2.73 × 108 m3 in the 2050s and 0.28–1.87 × 108 m3 in the 2100s compared with run‐off in the 2010s based on the RCP2.6 (low greenhouse gas emission) and RCP4.5 (moderate greenhouse gas emission) scenarios, respectively. The contribution of glacier meltwater to river run‐off will more likely decrease to approximately 10% and less than 5% during the 2050s and 2100s, respectively.

Extended Dependence of the Hydrological Regime on the Land Cover Change in the Three-North Region of China: An Evaluation under Future Climate Conditions

The hydrological regime in arid and semi-arid regions is quite sensitive to climate and land cover changes (LCC). The Three-North region (TNR) in China experiences diverse climate conditions, from arid to humid zones. In this region, substantial LCC has occurred over the past decades due to ecological restoration programs and urban expansion. At a regional scale, the hydrological effects of LCC have been demonstrated to be less observable than the effects of climate change, but it is unclear whether or not the effects of LCC may be intensified by future climate conditions. In this study, we employed remote sensing datasets and a macro-scale hydrological modeling to identify the dependence of the future hydrological regime of the TNR on past LCC. The hydrological effects over the period from 2020–2099 were evaluated based on a Representative Concentration Pathway climate scenario. The results indicated that the forest area increased in the northwest (11,691 km2) and the north (69 km2) of China but declined in the northeast (30,042 km2) over the past three decades. Moreover, the urban area has expanded by 1.3% in the TNR. Under the future climate condition, the hydrological regime will be influenced significantly by LCC. Those changes from 1986 to 2015 may alter the future hydrological cycle mainly by promoting runoff (3.24 mm/year) and decreasing evapotranspiration (3.23 mm/year) over the whole region. The spatial distribution of the effects may be extremely uneven: the effects in humid areas would be stronger than those in other areas. Besides, with rising temperatures and precipitation from 2020 to 2099, the LCC may heighten the risk of dryland expansion and flooding more than climate change alone. Despite uncertainties in the datasets and methods, the regional-scale hydrological model provides new insights into the extended impacts of ecological restoration and urbanization on the hydrological regime of the TNR.

Hydrologic Impacts of Ensemble-RCM-Projected Climate Changes in the Athabasca River Basin, Canada

Abstract In this study, the Providing Regional Climates for Impacts Studies (PRECIS) and the Regional Climate Model (RegCM) system as well as the Variable Infiltration Capacity (VIC) macroscale hydrologic model were integrated into a general framework to investigate impacts of future climates on the hydrologic regime of the Athabasca River basin. Regional climate models (RCMs) including PRECIS and RegCM were used to develop ensemble high-resolution climate projections for 1979–2099. RCMs were driven by the boundary conditions from the Hadley Centre Global Environment Model, version 2 with Earth system configurations (HadGEM2-ES); the Second Generation Canadian Earth System Model (CanESM2); and the Geophysical Fluid Dynamics Laboratory Earth System Model with MOM (GFDL-ESM2M) under the representative concentration pathways (RCPs). The ensemble climate simulations were validated through comparison with observations for 1984–2003. The RCMs project increases in temperature, precipitation, and wind speed under RCPs across most of the Athabasca River basin. Meanwhile, VIC was calibrated using the University of Arizona Shuffled Complex Evolution method (SCE-UA). The performance of the VIC model in replicating the characteristics of the observed streamflow was validated for 1994–2003. Changes in runoff and streamflow under RCPs were then simulated by the validated VIC model. The validation results demonstrate that the ensemble-RCM-driven VIC model can effectively reproduce historical climatological and hydrological patterns in the Athabasca River basin. The ensemble-RCM-driven VIC model shows that monthly streamflow is projected to increase in the 2050s and 2080s under RCPs, with notably higher flows expected in the spring for the 2080s. This will have substantial impacts on water balance on the Athabasca River basin, thus affecting the surrounding industry and ecosystems. The developed framework can be applied to other regions for exploration of hydrologic impacts under climate change.

A model-aided satellite-altimetry-based flood forecasting system for the Mekong River

A freely accessible model-aided satellite altimeter-based daily water level forecasting system using simple regression analysis is proposed for the Mekong River with feasibility study being performed. In the Mekong Delta (MD), where Regional Flood Management and Mitigation Center (RFMMC) does not provide forecasting, ocean tides strongly impact river levels and were specifically addressed by the sum of 5-term sinusoidal function. Forecasting skills of our system are quite promising in the MD, although RFMMC's forecasting system has better skills than ours in the Mekong mainstem upstream of MD. In contrast to current operational system, our system circumvents the need of frequent altimeter samplings in the upstream by using the Variable Infiltration Capacity (VIC) macroscale hydrologic model with 0.1° resolution. The proposed forecasting system is computationally efficient without the need of complex hydrodynamic modeling, making such approach globally applicable for river basins and deltas with comparable forecasting skill and minimal computational cost.