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Abstract 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. 

This dataset is part of a project studying the effects of wildfire on the Illilouette Creek Basin, a watershed within Yosemite National Park. Three temporary weather stations were installed under distinct types of vegetation cover. Each station measures air temperature, relative humidity, rainfall (the rain gage is not heated, so only the portion of snowfall that melts within the gage is measured), wind speed and direction, solar radiation, and both soil moisture and temperature at three depths. These measurements are recorded every 10 minutes, beginning in the summer of 2015 through June 2021. Snow depths and percent cover were estimated from time lapse imagery up to four times per day, and field measurements of snow depth and density were conducted up to two times each winter. The west-facing hillside where these stations are located most recently burned in 2004 and 2017 (Empire Fire). Photos are included of the stations both before and after the Empire Fire. For descriptions of the data format and units, see the included WeatherStnMetadata.xlsx file. 

The impact of wildfire on soil properties is difficult to predict, partially due to a shortage of field observations. To help address this need, we have assembled a unique dataset of soil properties (moisture, infiltration rate, and water drop penetration time) at over 100 individual locations within Yosemite National Park. These locations cover a wide range of fire history, soil texture, vegetation cover, and topography. Measurements span May 2022 through July 2023, capturing both a dry year and a wet year. A subset of sites burned in late summer 2022, allowing for pre- and post-fire measurements. Each individual site was measured 1-3 separate times. Water drop penetration time was measured at the soil surface, 1cm, and 3cm depths. Infiltration rate was measured at the soil surface and at 3cm depth using a mini disk infiltrometer. 

These files contain air temperature and relative humidity in Illilouette Creek Basin, within different post-fire vegetation patches including a wetland, shrub field, and forest. Onset's HOBO U23 Pro V2 temperature and relatively humidity sensors were attached to trees and protected using white plastic radiation shields. Temperatures measured may be impacted by temperature of the tree trunks. These time series can be used to compare air temperature and humidity at different heights above the ground, different canopy covers, and different sides of trees. These data can also be compared to temperature and relative humidity at nearby meteorological stations. Most of these sensors were temporarily removed in order to protect them from the 2017 Empire Fire, but sensor #315 remained in place and shows elevated temperatures on October 16, 2017 due to the fire. See Metadata file for details of sensor locations. 

Montane snowpack in the Sierra Nevada provides critical water resources for ecological functions and downstream communities. Forest removal allows us to manage the snowpack in montane forests and mitigate the effect of climate on water resources. Little is known about the mid- to long-term effects that changing snowpack following forest disturbance has on tree re-growth, and how tree re-growth might in turn affect snowpack accumulation and melt. We use a 1-m resolution process-based snow model (SnowPALM) coupled with a stand-scale ecohydrological model (RHESSys) that resolves water, energy and carbon cycling to represent tree growth, and to quantify how trees and snowpack co-evolve following two disturbance scenarios (thinning and clearcutting) over a period of 40 years in a small 100 m x 234 m mid-elevation forested area in the Sierra Nevada, California. We first calculate the impact of forest disturbance on the snowpack assuming no tree regrowth and then we compare it with scenarios that include the feedback of trees regrowth on the snowpack. Without tree regrowth, snow accumulation and melt volume increase on average by roughly 5 % and 13 % following thinning and clearcutting, respectively. With tree regrowth, a regrowth rate of 0.75 and 1.15 m/decade are found for thinning and clearcutting, respectively, along with a decrease of melt volumes of 2.5 to 0.9 mm/decade, respectively. About 50 % of the snowmelt volume gains from forest thinning are lost after 40 years of regrowth, whereas only about 7 % is lost from clearcutting after the same period, which are largely explained by changes to canopy interception and sublimation. This proof-of-concept study is expected to shed light into the coevolution of montane forests and snowpack response to forest disturbance. 

Snowmelt is a critical water resource in the Sierra Nevada impactingpopulations in California and Nevada. In this region, forest managersuse treatments like selective thinning to encourage resilient ecosystemsbut rarely prioritize snowpack retention due to a lack of simplerecommendations and the importance of other management objectives likewildfire mitigation and wildlife habitat. We use light detection andranging (lidar) data collected over multiple snow accumulation seasonsin the Sagehen Creek Basin, central Sierra Nevada in California, USA, toinvestigate how snowpack accumulation and ablation are affected byforest structure metrics at coarse, stand-scales (e.g., fraction ofvegetation, or fVEG) and fine, tree-scales (e.g., a modified leaf areaindex, and the ratio of gap-width to average tree height). Using a newlydeveloped lidar point cloud filtering method and an “open-areareference” approach, we show that for each 10% decrease in fVEG thereis a ~30% increase in snow accumulation and a~15% decrease in ablation rate at the Sagehen fieldsite. To understand variability around these relationships, we use arandom forest analysis to demonstrate that areas with fVEG greater than~30% have the greatest potential increased accumulationresponse after forest removal. This spatial information allows us toassess the utility of completed and planned forest restorationstrategies in targeting areas with the highest potential snowpackresponse. Our new lidar processing methods and reference-based approachare easily transferrable to other areas where they could improvedecision support and increase water availability from landscape-scaleforest restoration projects. 

Abstract Reducing the risk of large, severe wildfires while also increasing the security of mountain water supplies and enhancing biodiversity are urgent priorities in western US forests. After a century of fire suppression, Yosemite and Sequoia-Kings Canyon National Parks located in California’s Sierra Nevada initiated programs to manage wildfires and these areas present a rare opportunity to study the effects of restored fire regimes. Forest cover decreased during the managed wildfire period and meadow and shrubland cover increased, especially in Yosemite’s Illilouette Creek basin that experienced a 20% reduction in forest area. These areas now support greater pyrodiversity and consequently greater landscape and species diversity. Soil moisture increased and drought-induced tree mortality decreased, especially in Illilouette where wildfires have been allowed to burn more freely resulting in a 30% increase in summer soil moisture. Modeling suggests that the ecohydrological co-benefits of restoring fire regimes are robust to the projected climatic warming. Support will be needed from the highest levels of government and the public to maintain existing programs and expand them to other forested areas.