Effects of climate change on streamflow extremes and implications for reservoir inflow in the United States

Naz, Bibi S.; Kao, Shih‐Chieh; Ashfaq, Moetasim; Gao, Huilin; Rastogi, Deeksha; Gangrade, Sudershan

doi:10.1016/j.jhydrol.2017.11.027

Cited by 81 publications

(49 citation statements)

References 62 publications

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“…It shows a tendency for VIC to perform worse for catchment with a lower runoff ratio than catchments with higher runoff ratios. Possible reasons for poor performance in the dry region included errors in forcing data (Beck et al, ; Lohmann et al, ; Mizukami et al, ; Naz et al, ; Oubeidillah et al, ; Troy et al, ; Xia et al, ), anthropogenic effects on streamflow (Maurer et al, ; Troy et al, ; Xia, Mitchell, Ek, Cosgrove, et al, ) as well as limitations in model physics (Demaria et al, ; Naz et al, ; Newman et al, ; Oubeidillah et al, ). Issues in dry regions are being addressed in newer versions of VIC model.…”

Section: Resultsmentioning

confidence: 99%

In Quest of Calibration Density and Consistency in Hydrologic Modeling: Distributed Parameter Calibration against Streamflow Characteristics

Yang

Pan

Beck

et al. 2019

Water Resources Research

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Conventional basin‐by‐basin approaches to calibrate hydrologic models are limited to gauged basins and typically result in spatially discontinuous parameter fields. Moreover, the consequent low calibration density in space falls seriously behind the need from present‐day applications like high resolution river hydrodynamic modeling. In this study we calibrated three key parameters of the Variable Infiltration Capacity (VIC) model at every 1/8° grid‐cell using machine learning‐based maps of four streamflow characteristics for the conterminous United States (CONUS), with a total of 52,663 grid‐cells. This new calibration approach, as an alternative to parameter regionalization, applied to ungauged regions too. A key difference made here is that we tried to regionalize physical variables (streamflow characteristics) instead of model parameters whose behavior may often be less well understood. The resulting parameter fields no longer presented any spatial discontinuities and the patterns corresponded well with climate characteristics, such as aridity and runoff ratio. The calibrated parameters were evaluated against observed streamflow from 704/648 (calibration/validation period) small‐to‐medium‐sized catchments used to derive the streamflow characteristics, 3941/3809 (calibration/validation period) small‐to‐medium‐sized catchments not used to derive the streamflow characteristics as well as five large basins. Comparisons indicated marked improvements in bias and Nash‐Sutcliffe efficiency. Model performance was still poor in arid and semiarid regions, which is mostly due to both model structural and forcing deficiencies. Although the performance gain was limited by the relative small number of parameters to calibrate, the study and results here served as a proof‐of‐concept for a new promising approach for fine‐scale hydrologic model calibrations.

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Section: Resultsmentioning

confidence: 99%

In Quest of Calibration Density and Consistency in Hydrologic Modeling: Distributed Parameter Calibration against Streamflow Characteristics

Yang

Pan

Beck

et al. 2019

Water Resources Research

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“…This study used three distinct hydrologic models of varying complexity and spatiotemporal resolution, including the Precipitation Runoff Modeling System (PRMS, ~7.5 km spatial resolution at daily timestep), Variable Infiltration Capacity model (VIC, ~4 km at three-hourly timestep 27 ), and Distributed Hydrology Soil Vegetation Model (DHSVM, 90 m at three-hourly timestep 39 ). These models were selected due to their wide range of applications in climate change studies 26,27,[40][41][42] . In addition, these models can simulate hydrologic processes at a fine spatial resolution using distributed process-based equations allowing them to better capture meteorological and basin heterogeneity.…”

Section: Methodsmentioning

confidence: 99%

“…Similarly, Chegwidden et al (2019) demonstrated that choices of GCM and greenhouse emission pathways are the dominant contributors to annual streamflow volume, and the choices of hydrologic model and parameters are prominent in capturing low-flow uncertainties over the US Pacific Northwest 23 . While multiple climate models and greenhouse gas emission scenarios have been used to capture the ensemble of climate scenarios in the past two decades, such studies are often limited to the choice of a single hydrologic model 17,20,22,[25][26][27] . Despite studies indicating that choice of hydrologic model can produce substantial differences in hydrologic projections, at times exceeding the mean signal from climate scenarios 11 , the use of multiple hydrological models has only begun to gain traction 21,28,29 .The selection of appropriate hydrologic model(s) in the modeling framework remains a challenge, as decisions so subjective in nature require careful consideration of several factors, including model applicability, suitable spatiotemporal scale of implementation, availability of computational resources, quality of meteorological forcings and land surface parameters, and the overall technical feasibility 30 .…”

mentioning

confidence: 99%

Multi-model Hydroclimate Projections for the Alabama-Coosa-Tallapoosa River Basin in the Southeastern United States

Gangrade

Kao

McManamay

2020

Sci Rep

Self Cite

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This study uses a high-resolution, process-based modeling framework to assess the impacts of changing climate on water resources for the Alabama-Coosa-Tallapoosa River Basin in the southeastern United States. A 33-member ensemble of hydrologic projections was generated using 3 distributed hydrologic models (Precipitation-Runoff Modeling System, Variable Infiltration Capacity, and Distributed Hydrology Soil Vegetation Model) of different complexity. These hydrologic models were driven by dynamically downscaled and bias-corrected future climate simulations from 11 Coupled Model Intercomparison Project Phase 5 global climate models under Representative Concentration Pathway 8.5 emission scenario, with 40 years each in baseline and future (2011-2050) periods. The hydroclimate response, in general, projects an increase in mean seasonal precipitation, runoff, and streamflow. The high and low flows are projected to increase and decrease, respectively, in general, suggesting increased likelihood of extreme rainfall events and intensification of the hydrologic cycle. The uncertainty associated with the ensemble hydroclimate response, analyzed through an analysis of variance technique, suggests that the choice of climate model is more critical than the choice of hydrologic model for the studied region. this study provides in-depth insights of hydroclimate response and associated uncertainties to support informed decisions by water resource managers.A changing climate is projected to intensify regional and global hydrologic cycles 1,2 . These alterations in hydrologic cycles will potentially increase the frequency and magnitudes of hydroclimate extremes such as floods and droughts, and potentially impact water resource availability due to changes in the seasonality of streamflow and runoff 3-5 . The future hydrologic projections are, therefore, important to inform mitigation and adaptation strategies aimed at addressing impacts of climate change in addition to increasing water demands. Moreover, reliable estimates of hydroclimate extreme trends can ensure better preparedness of society and infrastructure from threats arising from extreme events and their socioeconomic impacts 6 .Studies assessing climate change impacts on future hydrology at regional or catchment scales often adapt a standard procedure involving the use of a hierarchical hydro-meteorological framework (hereinafter "modeling framework"), including selection of the following key elements: (a) greenhouse gas emission scenario, (b) global climate model (GCM), (c) downscaling method (statistical or dynamical), (d) bias correction of downscaled data (if required), and (e) hydrologic model 7-10 . These hydrologic projections are inevitably associated with uncertainties introduced at each stage of the modeling framework. In addition to external factors such as natural variability and the choice of emission scenarios, many uncertainties are model-related, such as model assumptions, structures, accuracy, initial conditions, calibration procedures, training datasets,...

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“…An important contribution of our study is the inclusion of a seasonal timing a. The timing at which precipitation takes place in a given location has implications for how P will be partitioned (Naz et al 2018). Regionally, the contrasting changes in the northern and southern part of the region have been previously identified (Sagarika et al 2014).…”

Section: May 2019mentioning

confidence: 99%

Seasonal Changes in Water and Energy Balances over the Appalachian Region and Beyond throughout the Twenty-First Century

Fernández

Zégre

2019

Journal of Applied Meteorology and Climatology

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The Appalachian Mountains serve as a water source for important population centers in the eastern and midwestern United States. Despite this, the effects of climate change on the hydroclimatology of the region have not been thoroughly assessed, and its effects for water resources remain uncertain. In this study, we analyze the effects of climate change in a holistic approach to consider differential changes between atmospheric water supply (precipitation) and atmospheric water demand (potential evapotranspiration). We analyze the absolute and relative changes in both variables, as well as their relation (aridity index) and future projected shifts in their seasonality. Our findings show that precipitation is projected to increase in the northeastern part of the region and decrease in the southwest with a transition zone in the central Appalachians. Potential evapotranspiration increases consistently throughout the twenty-first century at a higher rate than precipitation, increasing the aridity of the region except for some small localized pockets at high elevations. The seasonality of precipitation indicates different shifts across the region related to changes in the dominant synoptic drivers of the region and changes in the seasonal characteristics of the land surface. All changes are exacerbated in the most extreme future climate scenario, highlighting the importance of local to global policies toward a more sustainable water resources development. In addition, we perform a basin-scale assessment on 20 major rivers with headwaters within the “Appalachian Region.” Our basin-scale results enforce the gridded regional results and indicate that, as temperatures continue to increase, lowland areas will rely more heavily on higher-elevation forested headwater catchments for water supply.

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Effects of climate change on streamflow extremes and implications for reservoir inflow in the United States

Cited by 81 publications

References 62 publications

In Quest of Calibration Density and Consistency in Hydrologic Modeling: Distributed Parameter Calibration against Streamflow Characteristics

In Quest of Calibration Density and Consistency in Hydrologic Modeling: Distributed Parameter Calibration against Streamflow Characteristics

Multi-model Hydroclimate Projections for the Alabama-Coosa-Tallapoosa River Basin in the Southeastern United States

Seasonal Changes in Water and Energy Balances over the Appalachian Region and Beyond throughout the Twenty-First Century

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