Fire suppression in western U.S. mountains has caused dense forests with high water demands to grow. Restoring natural wildfire regimes to these forests could affect hydrology by changing vegetation ...composition and structure, but the specific effects on water balance are unknown. Mountain watersheds supply water to much of the western United States, so understanding the relationship between fire regime and water yield is essential to inform management. We used a distributed hydrological model to quantify hydrologic response to a restored fire regime in the Illilouette Creek Basin (ICB) within Yosemite National Park, California. Over the past 45 years, as successive fires reduced the ICB's forest cover approximately 25%, model results show that annual streamflow, subsurface water storage, and peak snowpack increased relative to a fire‐suppressed control, while evapotranspiration and climatic water deficit decreased. A second model experiment compared the water balance in the ICB under two vegetation cover scenarios: 2012 vegetation, representing a frequent‐fire landscape, and 1969 vegetation, representing fire suppression. These two model landscapes were run with observed weather data from 1972 to 2017 in order to capture natural variations in precipitation and temperature. This experiment showed that wet years experienced greater fire‐related reductions in evapotranspiration and increases in streamflow, while reductions in climatic water deficit were greater in dry years. Spring snowmelt runoff was higher under burned conditions, while summer baseflow was relatively unaffected. Restoring wildfire to the fire‐suppressed ICB likely increased downstream water availability, shifted streamflows slightly earlier, and reduced water stress to forests.
Key Points
Fire suppression has altered vegetation cover in Sierra Nevada watersheds, affecting water balance
Models show that mixed‐severity fires lead to increased snowpack, annual streamflow, and water storage
Most changes in the water balance due to fire were more pronounced in wet years compared to dry years
Understanding the severity and extent of near surface critical zone (CZ) disturbances and their ecosystem response is a pressing concern in the face of increasing human and natural disturbances. ...Predicting disturbance severity and recovery in a changing climate requires comprehensive understanding of ecosystem feedbacks among vegetation and the surrounding environment, including climate, hydrology, geomorphology, and biogeochemistry. Field surveys and satellite remote sensing have limited ability to effectively capture the spatial and temporal variability of disturbance and CZ properties. Technological advances in remote sensing using new sensors and new platforms have improved observations of changes in vegetation canopy structure and productivity; however, integrating measures of forest disturbance from various sensing platforms is complex. By connecting the potential for remote sensing technologies to observe different CZ disturbance vectors, we show that lower severity disturbance and slower vegetation recovery are more difficult to quantify. Case studies in montane forests from the western United States highlight new opportunities, including evaluating post‐disturbance forest recovery at multiple scales, shedding light on understory vegetation regrowth, detecting specific physiological responses, and refining ecohydrological modeling. Learning from regional CZ disturbance case studies, we propose future directions to synthesize fragmented findings with (a) new data analysis using new or existing sensors, (b) data fusion across multiple sensors and platforms, (c) increasing the value of ground‐based observations, (d) disturbance modeling, and (e) synthesis to improve understanding of disturbance.
Key Points
Increasing remote sensing capabilities improve observations of disturbance severity and recovery in varying critical zone settings
Case studies present how new approaches from multiple platforms and sensors better quantify post‐disturbance recovery of montane forests
We suggest integrating the new approaches to refine remote sensing capabilities and resolve critical zone processes at multiple scales
Background
Recent increases in wildfire activity in the Western USA are commonly attributed to a confluence of factors including climate change, human activity, and the accumulation of fuels due to ...fire suppression. However, a shortage of long-term forestry measurements makes it difficult to quantify regional changes in fuel loads over the past century. A better understanding of fuel accumulation is vital for managing forests to increase wildfire resistance and resilience. Numerical models provide one means of estimating changes in fuel loads, but validating these models over long timescales and large geographic extents is made difficult by the scarcity of sufficient data. One such model, MC2, provides estimates of multiple types of fuel loads and simulates fire activity according to fuel and climate conditions. We used the Forest Inventory and Analysis Database (FIADB) observed data to validate MC2 estimates of fuel load change over time where possible.
Results
We found that the MC2 model’s accuracy varied geographically, but at a regional scale the distributions of changes in fuel loads were similar to distributions of FIADB values. While FIADB data provided consistent measurement types across a wide geographic area, usable data only spanned approximately 30 years. We therefore supplemented this quantitative validation with a qualitative comparison to data that covered less area, but for much longer time spans: long-term forestry plots outside of the FIA plot network and repeat photography studies. Both model results and long-term studies show increases in fuel loads over the past century across much of the western USA, with exceptions in the Pacific Northwest and other areas. Model results also suggest that not all of the increases are due to fire suppression.
Conclusions
This model validation and aggregation of information from long-term studies not only demonstrate that there have been extensive fuel increases in the western USA but also provide insights into the level of uncertainty regarding fire suppression’s impact on fuel loads. A fuller understanding of changing fuel loads and their impact on fire behavior will require an increase in the number of long-term observational forestry studies.
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•Groundwater-surface water fluxes impact agricultural water shortage in Walker Basin.•Machine learning estimated groundwater fluxes faster than a physically-based model.•Machine ...learning was less accurate when conditions were far from training data.•Current infrastructure limits impacts of snowmelt timing on agricultural water use.•Current infrastructure cannot buffer water losses in a no-snow future.
Water allocation models (WAM) can capture complex feedbacks between water infrastructure, water supply, water demand, and water rights structure. They are an important tool for water managers to reduce conflict and aid in future water resource planning. Future streamflow reductions and shifts in timing are anticipated in snow-dominated watersheds of the western United States due to projected reductions in snow water storage. These basins tend to be water-limited and rely on groundwater to support agricultural demand. Water managers in the snow-fed, agricultural Walker River Basin (WRB) in California and Nevada use a dynamically coupled WAM and physically based groundwater flow model as a decision support tool. Large computation time is required to simulate groundwater dynamics, limiting the number of model scenarios that can feasibly be run to test alternative management scenarios under climate change. Machine learning (ML) techniques have been used to capture complex nonlinear hydrologic dynamics in other contexts, but to our knowledge there have not been efforts to use ML to increase computational efficiency in modeling groundwater responses to agricultural water use. We use extreme gradient boosting to replace the groundwater sub-model for the WRB decision support tool, resulting in accurate estimates of reservoir storage (monthly error almost always < 5% of reservoir capacity), streamflow (total outflow errors from −3% to 20% depending on scenario) and agricultural water shortages (-12% to 18% error in total shortage depending on scenario). For comparison, we found that omitting groundwater modeling from the WAM results in a larger overprediction of outflows (2 to 58%) and underprediction in agricultural water shortages (0 to 41%) across a range of scenarios. We use this validated ML method to explore the sensitivity of agricultural water availability to a range of streamflow volumes and streamflow timings. Results indicate that agricultural water shortages are more sensitive to annual streamflow volume in comparison to shifts in streamflow timing. Our model shows that reservoirs can buffer the impact of altered flow timing on agricultural production, except under extreme conditions in which all precipitation falls as rain (no snow storage) and streamflow peaks in the winter. Future work will explore these thresholds in more detail. While the results here are site-specific, the methodology for coupling a WAM with a ML representation of surface–groundwater interactions can be applied to a wide variety of water resource modeling applications. These results also provide a stark example of the importance of snowpack storage and groundwater management to western US water infrastructure.
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•A calibrated hydro-economic model is developed to assess the impact of reservoir capacity upgrade on irrigated agriculture.•Counterfactual policy intervention scenarios are evaluated ...relative to baseline conditions.•Diminishing returns on investment in reservoir capacity for agriculture.•Meeting instream flow requirements increases costs for agriculture due to declining snowpack.•Agricultural income protection in the face of climate-induced snowpack declines, hydrologic, and environmental constraints.
Climate-induced declines in snowpack storage have profound consequences for snowmelt-dependent river basins globally, including those in the western United States. These basins face the risk of economic losses in agriculture and environmental damage due to disrupted instream flows. To mitigate these potential losses, two strategies are commonly employed: enhancing built reservoir storage capacity and increasing groundwater use during the irrigation season. However, implementing these strategies carries the risk of exacerbating instream flow disruptions and compromising the sustainability of aquifers. This article develops a hydro-economic optimization model of Nevada's Walker River Basin (WRB) and uses it to examine the impact of storage capacity and groundwater management on mitigating economic losses in agriculture caused by altered snowmelt-driven inflows. The model accounts for environmental constraints on instream flows that limit water availability for agricultural use. Results show that the WRB is projected to experience a decline in irrigated farm acreage and agricultural output due to reduced snowpack storage. The findings also indicate diminishing returns on reservoir capacity investments, while highlighting the increased value of these investments when groundwater pumping is constrained due to aquifer sustainability concerns. Results show that upgrading existing reservoir capacity by not more than 1.5% in a free water leasing market could protect upwards of 94% and 83% of baseline agricultural income when the basin faces future climate-induced early season snowmelt-driven flow timing, and reduced streamflow, respectively, while managing the basin for hydrologic and environmental constraints.
Managed wildfire is an increasingly relevant management option to restore variability in vegetation structure within fire-suppressed montane forests in western North America. Managed wildfire often ...reduces tree cover and density, potentially leading to increases in soil moisture availability, water storage in soils and groundwater, and streamflow. However, the potential hydrologic impacts of managed wildfire in montane watersheds remain uncertain and are likely context dependent. Here, we characterize the response of vegetation and soil moisture to 47 years (1971–2018) of managed wildfire in Sugarloaf Creek Basin (SCB) in Sequoia-Kings Canyon National Park in the Sierra Nevada, California, USA, using repeat plot measurements, remote sensing of vegetation, and a combination of continuous in situ and episodic spatially distributed soil moisture measurements. We find that, by comparison to a nearby watershed with higher vegetation productivity and greater fire frequency, the managed wildfire regime at SCB caused relatively little change in dominant vegetation over the 47 year period and relatively little response of soil moisture. Fire occurrence was limited to drier mixed-conifer sites; fire-caused overstory tree mortality patches were generally less than 10 ha, and fires had little effect on removing mid-and lower strata trees. Few dense meadow areas were created by fire, with most forest conversion leading to sparse meadow and shrub areas, which had similar soil moisture profiles to nearby mixedconifer vegetation. Future fires in SCB could be managed to encourage greater tree mortality adjacent to wetlands to increase soil moisture, although the potential hydrologic benefits of the program in drier basins such as this one may be limited.
Fire suppression in many dry forest types has left a legacy of dense, homogeneous forests. Such landscapes have high water demands and fuel loads, and when burned can result in catastrophically large ...fires. These characteristics are undesirable in the face of projected warming and drying in the western US. Alternative forest and fire treatments based on managed wildfire—a regime in which fires are allowed to burn naturally and only suppressed under defined management conditions—offer a potential strategy to ameliorate the effects of fire suppression. Understanding the long-term effects of this strategy on vegetation, water, and forest resilience is increasingly important as the use of managed wildfire becomes more widely accepted. The Illilouette Creek Basin in Yosemite National Park has experienced 40 years of managed wildfire, reducing forest cover by 22%, and increasing meadow areas by 200% and shrublands by 24%. Statistical upscaling of 3300 soil moisture observations made since 2013 suggests that large increases in wetness occurred in sites where fire caused transitions from forests to dense meadows. The runoff ratio (ratio of annual runoff to precipitation) from the basin appears to be increasing or stable since 1973, compared to declines in runoff ratio for nearby, unburned watersheds. Managed wildfire appears to increase landscape heterogeneity, and likely improves resilience to disturbances, such as fire and drought, although more detailed analysis of fire effects on basin-scale hydrology is needed.
Water temperatures in mountain streams are likely to rise under future climate change, with negative impacts on ecosystems and water quality. However, it is difficult to predict which streams are ...most vulnerable due to sparse historical records of mountain stream temperatures as well as complex interactions between snowpack, groundwater, streamflow and water temperature. Minimum flow volumes are a potentially useful proxy for stream temperature, since daily streamflow records are much more common. We confirmed that there is a strong inverse relationship between annual low flows and peak water temperature using observed data from unimpaired streams throughout the montane regions of the United States' west coast. We then used linear models to explore the relationships between snowpack, potential evapotranspiration and other climate‐related variables with annual low flow volumes and peak water temperatures. We also incorporated previous years' flow volumes into these models to account for groundwater carryover from year to year. We found that annual peak snowpack water storage is a strong predictor of summer low flows in the more arid watersheds studied. This relationship is mediated by atmospheric water demand and carryover subsurface water storage from previous years, such that multi‐year droughts with high evapotranspiration lead to especially low flow volumes. We conclude that watershed management to help retain snow and increase baseflows may help counteract some of the streamflow temperature rises expected from a warming climate, especially in arid watersheds.
Minimum streamflows each summer are determined by a combination of factors, including the previous winter's snow water equivalent (SWE), carryover storage water from the previous year and evapotranspiration. This figure shows an example watershed in which the lowest summer streamflows occur when peak SWE and the previous year's low flow (a proxy for subsurface storage) are both low, with important climate change implications. This relationship is strongest in arid watersheds.
Water budgets integrate and summarize the water inputs and outputs that are essential for effective water resources management. Using water data collected from different sources, we constructed three ...water budgets (a 12-year annual average, a wet year, and a critically dry year) for the Sacramento–San Joaquin Delta (Delta), the Sacramento River (SR) watershed, and the San Joaquin River (SJR) watershed. Although multiple water budgets for the Delta exist, the water budgets presented here are the first to provide all three of the following: (1) water budgets for the entire Delta watershed, divided into management-relevant components, (2) comparisons between wet and dry years and between different regions of the watershed, and (3) discussion of major gaps and uncertainties in the available water data to guide and inform future data collection and water management. Results show that, from 1998 to 2009, the Delta received 24.2 million acre feet (maf) of water each year on average, which primarily exited the Delta as river outflow (71%), water exports (22%), and evapotranspiration (ET; 6%). The SR watershed received 56.9 maf of water (95% as precipitation). The major outputs from the SR watershed were ET (63%) and flows to the Delta (34%). In the SJR watershed, total water input was 28.7 maf composed of precipitation (74%), water imported from the Delta (18%), and storage depletion (7%). The major outputs from the SJR watershed were ET (65%), water exports (19%), and flows to the Delta (14%). Most values varied greatly from year to year. Although streamflows, water exports, and valley precipitation are relatively well measured and estimated, uncertainties are higher for groundwater storage change as well as for ET and precipitation in montane regions. Improvement in data collection and synthesis in these components is necessary to build a more detailed and accurate water budget.