Hydrological response to compounding impacts of climate change and forest management in the upper Kings River basin, CA, USA
Data files
Dec 16, 2025 version files 227.26 KB
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Figure04.Rda
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Figure05.Rda
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Figure06.Rda
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Figure07.Rda
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Figure08.Rda
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Figure09.Rda
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Figure10.Rda
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Figure11.Rda
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README.md
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Abstract
In the western United States, the Sierra Nevada region experienced decades of fire suppression-driven changes in forest structure and composition, resulting in increased vulnerability to drought, water stress, tree mortality, and exposure to severe wildfires. Sierra Nevada’s watersheds and forests are predicted to undergo warmer and drier conditions due to climate change, making them even more vulnerable to disturbances. Restoring forests by reducing forest density and fuel accumulation has the potential to improve forest resilience to droughts and climate change, increase water availability, and provide other ecosystem benefits. In this study, we investigated the individual and compounding effects of forest treatments on evapotranspiration and streamflow in the upper Kings River basin under different warming scenarios using the SWAT+ model. We simulated large-scale forest treatments throughout the landscape to evaluate the hydrological response to warming across a water-energy gradient and the extent to which forest treatments can offset the warming-driven response. Warming increased evapotranspiration in energy-limited forests, while in water-limited forests, evapotranspiration declined due to increased water stress. The water made available through biomass reduction due to forest treatments was directed towards increasing potential runoff or sustaining the remaining trees by providing additional water for evapotranspiration, controlled by water/energy availability. We found that large-scale forest restoration in the upper Kings River basin has the potential to partially mitigate warming impacts on streamflow by a maximum of 48% and 36% under +1.5°C and +3.0°C warming, respectively, thus reducing the severity of warming impacts on streamflow and vegetation water stress. These benefits are most prominent in the first year following forest treatment and gradually decline over time, persisting up to 10 years.
Dataset DOI: 10.5061/dryad.tb2rbp0d9
Description of the data and file structure
These datasets are based on SWAT+ simulations conducted in the Upper Kings River Basin, California, USA. The datasets range from daily to monthly and water year periods, and are spatially aggregated from HRU and LSU components to characteristic hillslopes and the full basin. The datasets are in the R data format ("*.Rda").
Files and variables
File: Figure04.Rda
Description: Simulated monthly snow water equivalent (variable swe, [mm/month]) from 1990 to 2019 for each characteristic hillslope (variable Cluster) and each DT scenario (variable Scenario).
File: Figure05.Rda
Description: Simulated yearly long-term averages (1990-2019) of evergreen forest actual evapotranspiration (aetWYLT [mm/year]), total precipitation (PrecipWYLT [mm/year]), Potential Evapotranspiration (PETWY_LT [mm/year]), for each characteristic hillslope (cluster), and Warming Scenario (DT = 0 °C, DT=+1.5 °C, DT=+3.0 °C). The aridity and evaporative indices are also reported (variables PETP [-], AETP [-]).
File: Figure06.Rda
Description: Simulated monthly actual evapotranspiration (variable aet [mm/month]) from 1990 to 2019 for each characteristic hillslope (variable Cluster) and each DT scenario (variable Scenario).
File: Figure07.Rda
Description: Average monthly simulated streamflow (Q [m^3^/s]) under the control and warming scenarios (variables QDT0 [m^3^/s], QDT15 [m^3^/s], QDT3_0 [m^3^/s]). The variable "Obs" indicates the full natural flow at the outlet of the basin (Pine Flat Dam)
File: Figure08.Rda
Description: Yearly evapotranspiration (aet [mm/year]) for each characteristic hillslope (cluster), Landuse (FRSE = evergreen forest, RNGB = rangeland), warming scenario before and after forest treatment scenarios (variable timing: control = No treatment, dry = June 2000, wet = June 2010). WY indicates the relative year of the simulated forest treatment (0 = year when forest treatment is simulated, negative number, years before the forest treatment and positive number refers to the years after the forest treatments). The difference in ET caused by forest treatments (deltaET [mm/year]) is obtained by subtracting the control scenario (respective year, and warming scenario) to the ET of the respective year, warming scenario and forest management scenario.
File: Figure09.Rda
Description: Climate warming (DQWarming), forest treatments (DQTreatment), and combined (DQ_WarmingAndTreatment) impacts on streamflow [mm/year] for each water year (variable WY), and for each warming (variable ScenarioDT) and forest management scenario (variables Intensity (Leaf Area Index Reduction -25% or -40%), WetDry (dry = June 2000, wet = June 2010), Extent (100%)).
File: Figure10.Rda
Description: Contribution to each characteristic hillslope (cluster) to the outlet streamflow (DQ_Treatment_mmy [mm/year]), for each forest management scenario (variables Intensity, WetDry, Extent) and warming scenario (Scenario_DT). The variable Q_mmy represents the simulated streamflow in mm/year.
File: Figure11.Rda
Description: Simulated averages of actual evapotranspiration (aet [mm/year]), total precipitation (Precip [mm/year]), Potential Evapotranspiration (PET [mm/year]), in the first year after the forest treatments (variables WY=Water Year, Timing = Forest treatment Scenario), for each characteristic hillslope (cluster), Landuse (FRSE = Evergreen Forest, RNGB = Rangeland), and Warming Scenario (DT = 0 °C, DT=+1.5 °C, DT=+3.0 °C). The aridity and evaporative indeces are also reported (variables PETP [-], AETP [-]).