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1. Transferring Hydrologic Data Across Continents – Leveraging Data‐Rich Regions to Improve Hydrologic Prediction in Data‐Sparse Regions

   https://doi.org/10.1029/2020WR028600  

   Ma, Kai ; Feng, Dapeng ; Lawson, Kathryn ; Tsai, Wen‐Ping ; Liang, Chuan ; Huang, Xiaorong ; Sharma, Ashutosh ; Shen, Chaopeng ( May 2021 , Water Resources Research)

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2. Hydrologic Characteristics of Streamflow in the Southeast Atlantic and Gulf Coast Hydrologic Region during 1939–2016 and Conceptual Map of Potential Impacts

   https://doi.org/10.3390/hydrology5030042  

   Anandhi, Aavudai ; Crandall, Christy ; Bentley, Chance ( September 2018 , Hydrology)

   Streamflow is one the most important variables controlling and maintaining aquatic ecosystem integrity, diversity, and sustainability. This study identified and quantified changes in 34 hydrologic characteristics and parameters at 30 long term (1939–2016) discharge stations in the Southeast Atlantic and Gulf Coast Hydrologic Region (Region 3) using Indicators of Hydrologic Alteration (IHA) variables. The southeastern United States (SEUS) is a biodiversity hotspot, and the region has experienced a number of rapid land use/land cover changes with multiple primary drivers. Studies in the SEUS have been mostly localized on specific rivers, reservoir catchments and/or species, but the overall region has not been assessed for the long-term period of 1939–2016 for multiple hydrologic characteristic parameters. The objectives of the study were to provide an overview of multiple river basins and 31 hydrologic characteristic parameters of streamflow in Region 3 for a longer period and to develop a conceptual map of impacts of selected stressors and changes in hydrology and climate in the SEUS. A seven step procedure was used to accomplish these objectively: Step 1: Download data from the 30 USGS gauging stations. Steps 2 and 3: Select and analyze the 31 IHA parameters using boxplots, scatter plots, and PDFs. Steps 4 and 5: Synthesize the drivers of changes and alterations and the various change points in streamflow in the literature. Step 6: Synthesize the climate of the SEUS in terms of temperature and precipitation changes. Step 7: Develop a conceptual map of impacts of selected stressors on hydrology using Driver–Pressure–State-Impact–Response (DPSIR) framework and IHA parameters. The 31 IHA parameters were analyzed. The meta-analysis of literature in the SEUS revealed the precipitation changes observed ranged from −30% to +35% and temperature changes from −2 °C to 6 °C by 2099. The fiftieth percentile of the Global Climate Models (GCM) predict no precipitation change and an increase in the temperature of 2.5 °C in the region by 2099. Among the GCMs, the 5th and 95th percentile of precipitation changes range between −40% and 110% and temperature changes between −2 °C and 6 °C by 2099. Meta-analysis of land use/land cover show the region has experienced changes. A number of rapid land use/land cover changes in 1957, 1970, and 1998 are some of the change points documented in the literature for precipitation and streamflow in the region. A conceptual map was developed to represent the impacts of selected drivers and the changes in hydrology and climate in the study region for three land use/land cover categories in three different periods. 

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3. Continental Hydrologic Intercomparison Project, Phase 1: A Large‐Scale Hydrologic Model Comparison Over the Continental United States

   https://doi.org/10.1029/2020WR028931  

   Tijerina, Danielle ; Condon, Laura ; FitzGerald, Katelyn ; Dugger, Aubrey ; O’Neill, Mary Michael ; Sampson, Kevin ; Gochis, David ; Maxwell, Reed ( July 2021 , Water Resources Research)

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4. Flash flooding in small urban watersheds: Storm event hydrologic response: STORM EVENT HYDROLOGIC RESPONSE OVER SMALL URBAN WATERSHEDS

   https://doi.org/10.1002/2015WR018326  

   Yang, Long ; Smith, James A. ; Baeck, Mary Lynn ; Zhang, Yan ( June 2016 , Water Resources Research)
5. Identifying uncertainties in hydrologic fluxes and seasonality from hydrologic model components for climate change impact assessments

   https://doi.org/10.5194/hess-24-2253-2020  

   Feng, Dongmei ; Beighley, Edward ( January 2020 , Hydrology and Earth System Sciences)

   Abstract. Assessing impacts of climate change on hydrologic systemsis critical for developing adaptation and mitigation strategies for waterresource management, risk control, and ecosystem conservation practices. Suchassessments are commonly accomplished using outputs from a hydrologic modelforced with future precipitation and temperature projections. The algorithmsused for the hydrologic model components (e.g., runoff generation) canintroduce significant uncertainties into the simulated hydrologic variables.Here, a modeling framework was developed that integrates multiple runoffgeneration algorithms with a routing model and associated parameteroptimizations. This framework is able to identify uncertainties from bothhydrologic model components and climate forcings as well as associatedparameterization. Three fundamentally different runoff generationapproaches, runoff coefficient method (RCM, conceptual), variableinfiltration capacity (VIC, physically based, infiltration excess), andsimple-TOPMODEL (STP, physically based, saturation excess), were coupledwith the Hillslope River Routing model to simulate surface/subsurface runoffand streamflow. A case study conducted in Santa Barbara County, California,reveals increased surface runoff in February and March but decreasedrunoff in other months, a delayed (3 d, median) and shortened (6 d,median) wet season, and increased daily discharge especially for theextremes (e.g., 100-year flood discharge, Q100). The Bayesian modelaveraging analysis indicates that the probability of such an increase can be up to85 %. For projected changes in runoff and discharge, general circulationmodels (GCMs) and emission scenarios are two major uncertainty sources,accounting for about half of the total uncertainty. For the changes inseasonality, GCMs and hydrologic models are two major uncertaintycontributors (∼35 %). In contrast, the contribution ofhydrologic model parameters to the total uncertainty of changes in thesehydrologic variables is relatively small (<6 %), limiting theimpacts of hydrologic model parameter equifinality in climate change impactanalysis. This study provides useful information for practices associatedwith water resources, risk control, and ecosystem conservation and forstudies related to hydrologic model evaluation and climate change impactanalysis for the study region as well as other Mediterranean regions. 

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