Understanding the role of reservoirs in the terrestrial water cycle is critical to support the sustainable management of water resources especially for China where reservoirs have been extensively ...built nationwide. However, this has been a scientific challenge due to the limited availability of continuous, long‐term reservoir operation records at large scales, and a process‐based modeling tool to accurately depict reservoirs as part of the terrestrial water cycle is still lacking. Here, we develop a continental‐scale land surface‐hydrologic model over the mainland China by explicitly representing 3,547 reservoirs in the model with a calibration‐free conceptual operation scheme for ungauged reservoirs and a hydrodynamically based two‐way coupled scheme. The model is spatially calibrated and then extensively validated against streamflow observations, reservoir storage observations and GRACE‐based terrestrial water storage anomalies. A 30‐year simulation is then performed to quantify the seasonal dynamics of China’s reservoir water storage (RWS) and its role in China's terrestrial water storage (TWS) over recent decades. We estimate that, over a seasonal cycle, China's RWS variation is 15%, 16%, and 25% of TWS variation during 1981–1990, 1991–2000, and 2001–2010, respectively, and one‐fifth of China’s reservoir capacity are effectively used annually. In most regions, reservoirs play a growing role in modulating the water cycle over time. Despite that, an estimated 80 million people have faced increasing water resources challenges in the past decades due to the significantly weakened reservoir regulation of the water cycle. Our approaches and findings could help the government better address the water security challenges under environmental changes.
Key Points
A continental‐scale land surface‐hydrologic model is developed for China by fully coupling 3,547 reservoirs and relevant water management
A calibration‐free reservoir operation scheme is developed for simulations of ungauged reservoirs in hydrologic models
The seasonal variation of reservoir water storage is about 19% of China's terrestrial water storage variation averaged over 1981–2010
Urbanization increases regional impervious surface area, which generally reduces hydrologic response time and therefore increases flood risk. The objective of this work is to investigate the ...sensitivities of urban flooding to urban land growth through simulation of flood flows under different urbanization conditions and during different flooding stages. A sub-watershed in Toronto, Canada, with urban land conversion was selected as a test site for this study. In order to investigate the effects of urbanization on changes in urban flood risk, land use maps from six different years (1966, 1971, 1976, 1981, 1986, and 2000) and of six simulated land use scenarios (0%, 20%, 40%, 60, 80%, and 100% impervious surface area percentages) were input into coupled hydrologic and hydraulic models. The results show that urbanization creates higher surface runoff and river discharge rates and shortened times to achieve the peak runoff and discharge. Areas influenced by flash flood and floodplain increases due to urbanization are related not only to overall impervious surface area percentage but also to the spatial distribution of impervious surface coverage. With similar average impervious surface area percentage, land use with spatial variation may aggravate flash flood conditions more intensely compared to spatially uniform land use distribution.
In recent years, wildfires in the western United States have occurred with increasing frequency and scale. Climate change scenarios in California predict prolonged periods of droughts with even ...greater potential for conditions amenable to wildfires. The Sierra Nevada Mountains provide 70% of water resources in California, yet how wildfires will impact watershed‐scale hydrology is highly uncertain. In this work, we assess the impacts of wildfires perturbations on watershed hydrodynamics using a physically based integrated hydrologic model in a high‐performance‐computing framework. A representative Californian watershed, the Cosumnes River, is used to demonstrate how postwildfire conditions impact the water and energy balance. Results from the high‐resolution model show counterintuitive feedbacks that occur following a wildfire and allow us to identify the regions most sensitive to wildfires conditions, as well as the hydrologic processes that are most affected. For example, whereas evapotranspiration generally decreases in the postfire simulations, some regions experience an increase due to changes in surface water run‐off patterns in and near burn scars. Postfire conditions also yield greater winter snowpack and subsequently greater summer run‐off as well as groundwater storage in the postfire simulations. Comparisons between dry and wet water years show that climate is the main factor controlling the timing at which some hydrologic processes occur (such as snow accumulation) whereas postwildfire changes to other metrics (such as streamflow) show seasonally dependent impacts primarily due to the timing of snowmelt, illustrative of the integrative nature of hydrologic processes across the Sierra Nevada‐Central Valley interface.
An integrated hydrologic model is used to simulate watershed hydrodynamics following land cover changes due to a wildfire. Differences between present‐day and postwildfire groundwater pressure show nonlinear increases and decreases that are not spatially limited to burn scar areas.
This study developed a Deep Neural Network (DNN) based distributed hydrologic model for an urban watershed in Republic of Korea. The developed model is composed of multiple Long Short-Term Memory ...(LSTM) hidden units connected by a fully connected layer. To examine the study area using the developed model, time series of 10-minute radar-gauge composite precipitation data and 10-minute temperature data at 239 model grid cells with 1km resolution were used as inputs to simulate 10-minute watershed flow discharge as an output. The model performed well for the calibration period (2013-2016) and validation period (2017-2019), with Nash-Sutcliffe Efficiency coefficient values being 0.99 and 0.67, respectively. Further in-depth analyses were performed to derive the following conclusions: (1) the map of runoff-precipitation ratios produced using the developed DNN model resembled imperviousness ratio map of the study area from the land cover data, revealing that the DNN successfully deep-learned the precipitation partitioning processes only with the input and output data without depending on any priori information about hydrology; (2) the model successfully reproduced the soil moisture dependent runoff process, an essential prerequisite of continuous hydrologic models; (3) each LSTM unit has different temporal sensitivity to the precipitation stimulus, with fast-response LSTM units having greater output weight factors near the watershed outlet, which implies that the developed model has a mechanism to separately consider the hydrological components with distinct response time such as direct runoff and the groundwater-driven baseflow.
Conflicts between increasing irrigated agricultural area, commercial crops, shifting cultivation and ever increasing domestic and industrial demand has already been a cause of tension in the society ...over water in the Ganga River Basin, India. For the development of sustainable water resource strategies, it is essential to establish interaction between landuse changes and local hydrology through proper assessment. Precisely, seeing how change in each LULC affects hydrologic regimes, or conversely evaluating which LULC shall be appropriate for the local hydrological regime can help decision makers to incorporate in the policy instruments. In this study, hydrologic regimes of the Ganga River basin have been assessed with landuse change. Catchment hydrologic responses were simulated using Soil and Water Assessment Tool (SWAT). Meteorological data from IMD of 0.25° × 0.25° spatial resolution were taken as the climate inputs. Simulated stream flow was compared at different gauge stations distributed across the Gang River and its tributaries. Urbanization has been the topmost contributor to the increase in surface runoff and water yield. While increased irrigation demands were the dominant contributor to the water consumption and also added to the increased evapotranspiration. This study can be important tool in quantifying the changes in hydrological components in response to changes made in landuse in especially basins undergoing rapid commercialization. This shall provide substantive information to the decision makers required to develop ameliorative strategies.
Change in Water Yield and evapotranspiration (ET) for the Ganga River basin for the year 2030 with respect to year 2005. Display omitted
•Change in hydrology due to change in landuse for the entire Ganga River basin is modeled using SWAT.•Change in Water balance due to change in landuse for the entire Ganga River basin and its tributaries were investigated.•The model performance for simulations without land use change is assessed and it has been noted that the it gradually decreases with time.
•H1DK2-WS model simulates hydrological fluxes with minimal water balance error.•H1DK2-WS model closely aligns with various reported benchmark simulations.•Dividing watershed into cascades of ...hillslopes enhances spatial representation.•H1DK2-WS model shows superior computational efficiency relative to HYDRUS-2D.
Watershed flow processes consist of partitioning, movement, storage, and redistribution of water fluxes in space and time. However, the integrated modeling of these processes is challenging due to computational burden, extensive data requirements, and/or reliance on simplifying assumptions. This study introduces a novel and computationally efficient modeling framework that leverages two state-of-the-art process-based models: HYDRUS-1D (H1D) for unsaturated flow and KINEROS2 (K2) for overland flow. The framework extends a hillslope-scale coupled H1D-K2 model to simulate watershed-scale processes, where H1D replaces the three-parameter Parlange’s infiltration equation in the event-based K2 model. Boundary condition switching is employed to account for surface ponding and water exchange between the two model domains. The structure of the coupled watershed-scale H1D-K2 model consists of a cascade of connected rectangular planes, channel elements, and 1D soil profiles to simulate 1D overland flow, infiltration, unsaturated zone flow, and recharge. Computational efficiency relative to HYDRUS-2D is achieved through a dynamic time-stepping approach and dimensionality reduction. The watershed scale model improved the computational time by 14.3% and 47% compared to the corresponding Hillslope scale H1D-K2 and HYDRUS-2D, respectively. The performance and efficiency of the new watershed model are demonstrated using benchmark watershed and/or hillslope simulations. Calibrated hydrographs and water balance components using Walnut Gulch Experimental Watershed data, showed excellent agreement with observed data with a Nash-Sutcliffe coefficient (NSC) greator than 0.8 and Pearson correlation coefficient (R2) greater than 0.92.
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.
•Explicit representation of water reservoirs in the VIC hydrologic model.•Simulation and optimization of both rule curves and operating rules.•Powered by state-of-the-art optimization algorithms.•VIC-ResOpt can support regional and global studies on regulated river basins.
The German drought monitor Zink, Matthias; Samaniego, Luis; Kumar, Rohini ...
Environmental research letters,
07/2016, Volume:
11, Issue:
7
Journal Article
Peer reviewed
Open access
The 2003 drought event in Europe had major implications on many societal sectors, including energy production, health, forestry and agriculture. The reduced availability of water accompanied by high ...temperatures led to substantial economic losses on the order of 1.5 Billion Euros, in agriculture alone. Furthermore, soil droughts have considerable impacts on ecosystems, forest fires and water management. Monitoring soil water availability in near real-time and at high-resolution, i.e., 4 × 4 km2, enables water managers to mitigate the impact of these extreme events. The German drought monitor was established in 2014 as an online platform. It uses an operational modeling system that consists of four steps: (1) a daily update of observed meteorological data by the German Weather Service, with consistency checks and interpolation; (2) an estimation of current soil moisture using the mesoscale hydrological model; (3) calculation of a quantile-based soil moisture index (SMI) based on a 60 year data record; and (4) classification of the SMI into five drought classes ranging from abnormally dry to exceptional drought. Finally, an easy to understand map is produced and published on a daily basis on www.ufz.de/droughtmonitor. Analysis of the ongoing 2015 drought event, which garnered broad media attention, shows that 75% of the German territory underwent drought conditions in July 2015. Regions such as Northern Bavaria and Eastern Saxony, however, have been particularly prone to drought conditions since autumn 2014. Comparisons with historical droughts show that the 2015 event is amongst the ten most severe drought events observed in Germany since 1954 in terms of its spatial extent, magnitude and duration.
•Consideration of both regional development patterns and site-scale regulations.•Future urbanization projections generated through ANN machine learning model.•Floodplain increases up to 12.5% ...observed under projected urbanization scenarios.
In the United States, fluvial flood risk is managed by the National Flood Insurance Program (NFIP), which delineates areas that have a 1% chance of flooding each year (i.e. the 100-year floodplain). Development within and adjacent to riverine floodplains exacerbates flood losses by increasing peak discharge and runoff volume, shortening the time to peak, and altering the extent of the floodplain. This paper improves understanding of how future development can alter the 100-year floodplain in a watershed in Houston, TX through land use projection, hydrologic and hydraulic modeling, and implements a novel method for considering the impact of both regional trends in development and site-scale development policies on runoff response. The methodology presented in this paper integrates future development scenarios from a machine learning land use projection model with distributed hydrologic modeling and coupled 1D/2D unsteady hydraulic modeling to produce future floodplain estimates. Current site-scale detention requirements are represented within the hydrologic model to evaluate the regional effectiveness of these policies under future development conditions in 2050. Results indicate that the 100-year floodplain can expand by up to 12.5% across the watershed as a result of projected development in 2050 using current stormwater mitigation policies, and the number of parcels within the floodplain can increase by up to 18.8%. This study demonstrates how incremental land use changes can significantly alter the reality of flood risk in urbanizing watersheds, and how existing land use policies may be insufficient to mitigate impacts from future development.
•Role of hydrological model calibration in climate change impacts assessment in the background of climate model uncertainty.•Hydrological parameter uncertainty in VIC with Monte Carlo ...Simulations.•New finding: hydrological parameter uncertainty negligible compared to climate model uncertainty.•For Indian region, climate models with regional simulations are still immatured to be used for adaptation.•Comparison of statistical and dynamical downscaling with CMIP5 models.
Assessing impacts of climate change on hydrology involves global scale climate projections by General Circulation Models (GCMs), downscaling of global scale projections to regional scale by statistical methods or regional climate models and then use of regional outputs in hydrological simulations. Hydrological simulations considers varying inputs starting with soil characteristics, land cover, vegetation types, control structures to social parameters such as human interventions, irrigation and water use. This makes the model highly parametrized and at the same time highly uncertain due to the non-availability of majority of input parameters. Here, we compare the contributions of uncertainty from hydrological parameterization in the hydrological projections of climate change to that generated from the use of multiple climate models. The Ganga River Basin in India was selected as the study region. For regional climate change projections, we use dynamic downscaling outputs from Coordinated Regional Climate Downscaling Experiment (CORDEX) and statistical downscaling outputs from a transfer function forced with 3 GCMs, Institut Pierre Simon Laplace (IPSL), European Consortium Earth System Model (EC-EARTH) and MPI (Max Plank Institut) ESM (Earth System Model). Monte-Carlo Simulations (MCS) are performed with 1000 generated sets of sensitive model parameters for each of the GCM-regional model combination. We find that the observed time series of river discharge is reproduced well but with bias in low-flow conditions. This is probably associated with human intervention and poor representation of baseflow in VIC due to the neglected groundwater storage which feed the surface water during low flow condition. The future projections show that the major uncertainty lies across climate models for all the four seasons (MAM, JJAS, ON and DJF) and for all the hydrological variables, soil moisture, evapotranspiration (ET), water yield and river discharge. The uncertainty resulting from the MCS is quite small as compared to the climate model uncertainty. We are unable to find any added value in hydrological simulations by rigorous hydrological calibration and parameterization in absence of many required data, when the forcing meteorological data has huge uncertainty. Our findings highlight the need of convergence of climate models before the studies on hydrological impacts assessment and subsequent development of adaptation strategies.
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