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Abstract Wildfires have increased in size, frequency, and intensity in arid regions of the western United States because of human activity, changing land use, and rising temperature. Fire can degrade water quality, reshape aquatic habitat, and increase the risk of high discharge and erosion. Drawing from patterns in montane dry forest, chaparral, and desert ecosystems, we developed a conceptual framework describing how interactions and feedbacks among material accumulation, combustion of fuels, and hydrologic transport influence the effects of fire on streams. Accumulation and flammability of fuels shift in opposition along gradients of aridity, influencing the materials available for transport. Hydrologic transport of combustion products and materials accumulated after fire can propagate the effects of fire to unburned stream–riparian corridors, and episodic precipitation characteristic of arid lands can cause lags, spatial heterogeneity, and feedbacks in response. Resolving uncertainty in fire effects on arid catchments will require monitoring across hydroclimatic gradients and episodic precipitation. 

Abstract Atmospheric nitrogen (N) deposition and climate change are transforming the way N moves through dryland watersheds. For example, N deposition is increasing N export to streams, which may be exacerbated by changes in the magnitude, timing, and intensity of precipitation (i.e., the precipitation regime). While deposition can control the amount of N entering a watershed, the precipitation regime influences rates of internal cycling; when and where soil N, plant roots, and microbes are hydrologically coupled via diffusion; how quickly plants and microbes assimilate N; and rates of denitrification, runoff, and leaching. We used the ecohydrological model RHESSys to investigate (a) how N dynamics differ between N‐limited and N‐saturated conditions in a dryland watershed, and (b) how total precipitation and its intra‐annual intermittency (i.e., the time between storms in a year), interannual intermittency (i.e., the duration of dry months across multiple years), and interannual variability (i.e., variance in the amount of precipitation among years) modify N dynamics and export. Streamflow nitrate (NO₃⁻) export was more sensitive to increasing rainfall intermittency (both intra‐annual and interannual) and variability in N‐limited than in N‐saturated model scenarios, particularly when total precipitation was lower—the opposite was true for denitrification which is more sensitive in N‐saturated than N‐limited scenarios. N export and denitrification increased or decreased more with increasing interannual intermittency than with other changes in precipitation amount. This suggests that under future climate change, prolonged droughts that are followed by more intense storms may pose a major threat to water quality in dryland watersheds. 

As wildfires become larger and more severe across western North America, it grows increasingly important to understand how they will affect the biogeochemical processes influencing ecosystem recovery. Soil nitrogen (N) cycling is a key process constraining recovery rates. In addition to its direct responses to fire, N cycling can also respond to other post-fire transformations, including increases or decreases in microbial biomass, soil moisture, and pH. To examine the short-term effects of wildfire on belowground processes in the northern Sierra Nevada, we collected soil samples along a gradient from unburned to high fire severity over 10  months following a wildfire. This included immediate pre- and post-fire sampling for many variables at most sites. While season and soil moisture did not substantially alter pH, microbial biomass, net N mineralisation, and nitrification in unburned locations, they interacted with burn severity in complex ways to constrain N cycling after fire. In areas that burned, pH increased (at least initially) after fire, and there were non-monotonic changes in microbial biomass. Net N mineralisation also had variable responses to wetting in burned locations. These changes suggest burn severity and precipitation patterns can interact to alter N cycling rates following fire. 

Abstract. Mountain pine beetle (MPB) outbreaks in the western United States result inwidespread tree mortality, transforming forest structure within watersheds.While there is evidence that these changes can alter the timing and quantity of streamflow, there is substantial variation in both the magnitude and direction of hydrologic responses, and the climatic and environmental mechanisms driving this variation are not well understood. Herein, we coupled an eco-hydrologic model (RHESSys) with a beetle effects model and applied it to a semiarid watershed, Trail Creek, in the Bigwood River basin in central Idaho, USA, to examine how varying degrees of beetle-caused tree mortality influence water yield. Simulation results show that water yield during the first 15 years after beetle outbreak is controlled by interactions between interannual climate variability, the extent of vegetation mortality, and long-term aridity. During wet years, water yield after a beetle outbreak increased with greater tree mortality; this was driven by mortality-caused decreases in evapotranspiration. During dry years, water yield decreased at low-to-medium mortality but increased at high mortality. The mortality threshold for the direction of change was location specific. The change in water yield also varied spatially along aridity gradients during dry years. In wetter areas of the Trail Creek basin, post-outbreak water yield decreased at low mortality (driven by an increase in ground evaporation) and increased when vegetation mortality was greater than 40 % (driven by a decrease in canopy evaporation and transpiration). In contrast, in more water-limited areas, water yield typically decreased after beetle outbreaks, regardless of mortality level (although the driving mechanisms varied). Our findings highlight the complexity and variability of hydrologic responses and suggest that long-term (i.e., multi-decadal mean) aridity can be a useful indicator for the direction of water yield changes after a disturbance. 

Abstract Extreme wildfires are increasing in frequency globally, prompting new efforts to mitigate risk. The ecological appropriateness of risk mitigation strategies, however, depends on what factors are driving these increases. While regional syntheses attribute increases in fire activity to both climate change and fuel accumulation through fire exclusion, they have not disaggregated causal drivers at scales where land management is implemented. Recent advances in fire regime modeling can help us understand which drivers dominate at management-relevant scales. We conducted fire regime simulations using historical climate and fire exclusion scenarios across two watersheds in the Inland Northwestern U.S., which occur at different positions along an aridity continuum. In one watershed, climate change was the key driver increasing burn probability and the frequency of large fires; in the other, fire exclusion dominated in some locations. We also demonstrate that some areas become more fuel-limited as fire-season aridity increases due to climate change. Thus, even within watersheds, fuel management must be spatially and temporally explicit to optimize effectiveness. To guide management, we show that spatial estimates of soil aridity (or temporally averaged soil moisture) can provide a relatively simple, first-order indicator of where in a watershed fire regime is climate vs. fuel-limited and where fire regimes are most vulnerable to change. 

Abstract Predicting winter flooding is critical to protecting people and securing water resources in California’s Sierra Nevada. Rain-on-snow (ROS) events are a common cause of widespread flooding and are expected to increase in both frequency and magnitude with anthropogenic climate change in this region. ROS flood severity depends on terrestrial water input (TWI), the sum of rain and snowmelt that reaches the land surface. However, an incomplete understanding of the processes that control the flow and refreezing of liquid water in the snowpack limits flood prediction by operational and research models. We examine how antecedent snowpack conditions alter TWI during 71 ROS events between water years 1981 and 2019. Observations across a 500-m elevation gradient from the Independence Creek catchment were input into SNOWPACK, a one-dimensional, physically based snow model, initiated with the Richards equation and calibrated with collocated snow pillow observations. We compare observed “historical” and “scenario” ROS events, where we hold meteorologic conditions constant but vary snowpack conditions. Snowpack variables include cold content, snow density, liquid water content, and snow water equivalent. Results indicate that historical events with TWI > rain are associated with the largest observed streamflows. A multiple linear regression analysis of scenario events suggests that TWI is sensitive to interactions between snow density and cold content, with denser (>0.30 g cm⁻³) and colder (<−0.3 MJ of cold content) snowpacks retaining >50 mm of TWI. These results highlight the importance of hydraulic limitations in dense snowpacks and energy limitations in warm snowpacks for retaining liquid water that would otherwise be available as TWI for flooding. Significance StatementThe purpose of this study is to understand how the snowpack modulates quantities of water that reach the land surface during rain-on-snow (ROS) events. While the amount of near-term storm rainfall is reasonably predicted by meteorologists, major floods associated with ROS are more difficult to predict and are expected to increase in frequency. Our key findings are that liquid water inputs to the land surface vary with snowpack characteristics, and although many hydrologic models incorporate snowpack cold content and density to some degree, the complexity of ROS events justifies the need for additional observations to improve operational forecasting model results. Our findings suggest additional comparisons between existing forecasting models and those that physically represent the snowpack, as well as field-based observations of cold content and density and liquid water content, would be useful follow-up investigations.