Sierra Nevada Watersheds Research Articles

Dynamic, downstream‐propagating thermal vulnerability in a mountain stream network: Implications for biodiversity in the face of climate change

AbstractAs climate change continues to increase air temperature in high‐altitude ecosystems, it has become critical to understand the controls and scales of aquatic habitat vulnerability to warming. Here, we used a nested array of high‐frequency sensors, and advances in time‐series models, to examine spatiotemporal variation in thermal vulnerability in a model Sierra Nevada watershed. Stream thermal sensitivity to atmospheric warming fluctuated strongly over the year and peaked in spring and summer—when hot days threaten invertebrate communities most. The reach scale (~ 50 m) best captured variation in summer thermal regimes. Elevation, discharge, and conductivity were important correlates of summer water temperature across reaches, but upstream water temperature was the paramount driver—supporting that cascading warming occurs downstream in the network. Finally, we used our estimated summer thermal sensitivity and downscaled projections of summer air temperature to forecast end‐of‐the‐century stream warming, when extreme drought years like 2020–2021 become the norm. We found that 25.5% of cold‐water habitat may be lost under high‐emissions scenario representative concentration pathway (RCP) 8.5 (or 7.9% under mitigated RCP 4.5). This estimated reduction suggests that 27.2% of stream macroinvertebrate biodiversity (11.9% under the mitigated scenario) will be stressed or threatened in what was previously cold‐water habitat. Our quantitative approach is transferrable to other watersheds with spatially replicated time series and illustrates the importance of considering variation in the vulnerability of mountain streams to warming over both space and time. This approach may inform watershed conservation efforts by helping identify, and potentially mitigate, sites and time windows of peak vulnerability.

Dynamical downscaling of global reanalysis data for high-resolution spatial modeling of snow accumulation/melting at the central/southern Sierra Nevada watersheds

Data scarcity is one of the major constraints for hydrological modeling at a mountainous region with complex terrains. In this study, WRF (Weather Research and Forecasting model) model was configured to produce high-resolution atmospheric data for spatial modeling of snow at seven watersheds in central/southern Sierra Nevada.The configured WRF model downscaled a global reanalysis dataset into hourly time intervals and 3-km spatial grid resolution. Performance of the configured WRF model was validated by comparing basin averages of daily precipitation and daily mean temperature between the WRF simulation and data from Parameter-elevation Relationships on Independent Slopes Model (PRISM). The WRF model demonstrated satisfactory performance in simulating peaks and variations of daily precipitation and daily mean temperature. The atmospheric data which were obtained by the dynamical downscaling of Climate Forecast System Reanalysis dataset (CFSR) were then used for calibration and validation of the snow model for the seven watersheds. The dynamical downscaling and the subsequent simulation of snow were performed through the application of The Watershed Environmental Hydrology Hydro-Climate Model (WEHY-HCM) into the central/southern Sierra Nevada. The daily scale validation of the calibrated snow model showed that the simulated snow water equivalent (SWE) was mostly in agreement with observed SWE, however, tended to somewhat underestimate SWE. The snow model simulation with the precipitation input from PRISM indicated that the results using the dynamical downscaling had comparable performance with the results using PRISM precipitation, while some observation points showed improvements of the simulated SWE by using PRISM precipitation. Spatial comparison of the snow cover between the snow model simulations and Moderate Resolution Imaging Spectroradiometer (MODIS) observations showed that the snow model was capable of detecting the snow cover at high elevation bands while the snow cover detection at low elevation bands, which correspond to the boundary between snow cover and no snow cover area, was less accurate.

Skill of Rain–Snow Level Forecasts for Landfalling Atmospheric Rivers: A Multimodel Assessment Using California’s Network of Vertically Profiling Radars

AbstractThe partitioning of rain and snow during atmospheric river (AR) storms is a critical factor in flood forecasting, water resources planning, and reservoir operations. Forecasts of atmospheric rain–snow levels from December 2016 to March 2017, a period of active AR landfalls, are evaluated using 19 profiling radars in California. Three forecast model products are assessed: a global forecast model downscaled to 3-km grid spacing, 4-km river forecast center operational forecasts, and 50-km global ensemble reforecasts. Model forecasts of the rain–snow level are compared with observations of rain–snow melting-level brightband heights. Models produce mean bias magnitudes of less than 200 m across a range of forecast lead times. Error magnitudes increase with lead time and are similar between models, averaging 342 m for lead times of 24 h or less and growing to 700–800 m for lead times of greater than 144 h. Observed extremes in the rain–snow level are underestimated, particularly for warmer events, and the magnitude of errors increases with rain–snow level. Storms with high rain–snow levels are correlated with larger observed precipitation rates in Sierra Nevada watersheds. Flood risk increases with rain–snow levels, not only because a greater fraction of the watershed receives rain, but also because warmer storms carry greater water vapor and thus can produce heavier precipitation. The uncertainty of flood forecasts grows nonlinearly with the rain–snow level for these reasons as well. High rain–snow level ARs are a major flood hazard in California and are projected to be more prevalent with climate warming.

Hydrologic responses to climate warming for a snow‐dominated watershed and a transient snow watershed in the California Sierra

AbstractClimate warming will have substantial impacts on hydrological fluxes in the California Sierra. A commonly used approach for assessing these impacts, particularly in mountain watersheds, is to substitute space for time. This conceptual model assumes that with warming, the hydrologic behaviour of higher elevation snow dominated watersheds (SDWs) will converge to the hydrologic behaviour of lower elevation transient snow watersheds (TSWs). To investigate the efficacy of this conceptual model, a process‐based model (RHESSys) was applied to a TSW and a SDW with a mean annual temperature 2 °C lower than the TSW in the Sierra National forest, California. This study investigated the effect of climate warming (2 and 4 °C) on the model estimates of snow water equivalent (SWE), streamflow, evapotranspiration (ET), and moisture deficit in the two watersheds. Modelling results show that SDW under 2 °C warming scenarios generates monthly SWE similar in magnitude and timing as TSW under historic conditions. However, SDW under 2 °C warming scenarios generates higher annual and summer streamflow due to shallower groundwater storage and experiences less water limitation due to lower ET, compared with TSW under historical climate conditions. In both watersheds, leaf area index and wetness index are primary factors controlling spatial patterns of seasonal ET under both historical climate conditions and warming scenarios. Climate warming increases the spatial variability in monthly ET, especially in the summer period. These modelling results suggest that vegetation structure and subsurface properties may be as important as climate in explaining hydrologic response to climate warming in small Sierra Nevada watersheds.

Sensitivity of Streamflow Response in the Snow-Dominated Sierra Nevada Watershed Using Projected CMIP5 Data

AbstractThe American River basin, a snow-dominated alpine watershed in Northern California, was simulated using the Soil and Water Assessment Tool (SWAT) model to evaluate change in future streamfl...

Prioritizing forest fuels treatments based on the probability of high-severity fire restores adaptive capacity in Sierran forests.

In frequent fire forests of the western United States, a legacy of fire suppression coupled with increases in fire weather severity have altered fire regimes and vegetation dynamics. When coupled with projected climate change, these conditions have the potential to lead to vegetation type change and altered carbon (C) dynamics. In the Sierra Nevada, fuels reduction approaches that include mechanical thinning followed by regular prescribed fire are one approach to restore the ability of the ecosystem to tolerate episodic fire and still sequester C. Yet, the spatial extent of the area requiring treatment makes widespread treatment implementation unlikely. We sought to determine if a priori knowledge of where uncharacteristic wildfire is most probable could be used to optimize the placement of fuels treatments in a Sierra Nevada watershed. We developed two treatment placement strategies: the naive strategy, based on treating all operationally available area and the optimized strategy, which only treated areas where crown-killing fires were most probable. We ran forecast simulations using projected climate data through 2,100 to determine how the treatments differed in terms of C sequestration, fire severity, and C emissions relative to a no-management scenario. We found that in both the short (20years) and long (100years) term, both management scenarios increased C stability, reduced burn severity, and consequently emitted less C as a result of wildfires than no-management. Across all metrics, both scenarios performed the same, but the optimized treatment required significantly less C removal (naive=0.42 Tg C, optimized=0.25 Tg C) to achieve the same treatment efficacy. Given the extent of western forests in need of fire restoration, efficiently allocating treatments is a critical task if we are going to restore adaptive capacity in frequent-fire forests.

Recent Patterns in Climate, Vegetation, and Forest Water Use in California Montane Watersheds

California has recently experienced one of the worst droughts on record, negatively impacting forest ecosystems across the state. As a major source of the region’s water supply, it is important to evaluate the vegetation and water balance response of these montane forested watersheds to climate variability across the range of rain- to snow-dominated precipitation regimes. The Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI) were used to capture the hydrologic drought signal, and MODIS vegetation indices (i.e., the normalized difference vegetation index and the enhanced vegetation index) were used to evaluate the vegetation and evapotranspiration response in three headwater catchments. The study catchments comprised a low elevation rain-dominated site (Caspar Creek) on the northern California coast, a mid-elevation site with a mix of rain and snow (Providence Creek) in the California Sierra Nevada, and a high elevation snow-dominated site (Bull Creek) in the Sierra Nevada. Lowest SPI values occurred in the third drought year of 2014 for all sites. Lowest SRI was in 2014 for Caspar, but in 2015 for Providence and Bull, reflecting differences in snowpack-delayed runoff and subsurface storage capacity between the lower and higher elevation watersheds. The most accurate water balance closure using evapotranspiration estimates from vegetation indices was within 10% of measured precipitation at snow-dominated Bull. The rain-dominated Caspar watershed had the highest vegetation index values and annual evapotranspiration, with the lowest variability over the previous 13 years (2004–2016). Vegetation index values and annual evapotranspiration decreased with increasing elevation and snow contribution to precipitation. Both snow-influenced Sierra Nevada watersheds showed elevated vegetation and evapotranspiration responses to interannual climate variability. There remains a need for institutional support to expand long-term observations in remote forested mountain watersheds to monitor and research these changing and extreme environmental conditions in source watershed regions.

Verification of Ensemble Water Supply Forecasts for Sierra Nevada Watersheds

This study verifies the skill and reliability of ensemble water supply forecasts issued by an innovative operational Hydrologic Ensemble Forecast Service (HEFS) of the U.S. National Weather Service (NWS) at eight Sierra Nevada watersheds in the State of California. The factors potentially influencing the forecast skill and reliability are also explored. Retrospective ensemble forecasts of April–July runoff with 60 traces for these watersheds from 1985 to 2010 are generated with the HEFS driven by raw precipitation and temperature reforecasts from operational Global Ensemble Forecast System (GEFS) for the first 15 days and climatology from day 16 up to day 365. Results indicate that the forecast skill is limited when the lead time is long (over three months or before January) but increases through the forecast period. There is generally a negative bias in the most probable forecast (median forecast) for most study watersheds. When the mean forecast is investigated instead, the bias becomes mostly positive and generally smaller in magnitude. The forecasts, particularly the wet forecasts (with less than 10% exceedance probability) are reliable on the average. The low April–July flows (with higher than 90% exceedance probability) are forecast more frequently than their actual occurrence frequency, while the medium April–July flows (90% to 10% exceedance) are forecast to occur less frequently. The forecast skill and reliability tend to be sensitive to extreme conditions. Particularly, the wet extremes show more significant impact than the dry extremes. Using different forcing data, including pure climatology and Climate Forecast System version 2 (CFSv2) shows no consistent improvement in the forecast skill and reliability, neither does using a longer (than the study period 1985–2010) period of record. Overall, this study is meaningful in the context of (1) establishing a benchmark for future enhancements (i.e., newer version of HEFS, GEFS and CFSv2) to ensemble water supply forecasting systems and (2) providing critical information (on what skill and reliability to expect at a given lead time, water year type and location) to water resources managers in making uncertainty-informed decisions in maximizing the reliability of the water supply.

Effects of Model Spatial Resolution on Ecohydrologic Predictions and Their Sensitivity to Inter-Annual Climate Variability

The effect of fine-scale topographic variability on model estimates of ecohydrologic responses to climate variability in California’s Sierra Nevada watersheds has not been adequately quantified and may be important for supporting reliable climate-impact assessments. This study tested the effect of digital elevation model (DEM) resolution on model accuracy and estimates of the sensitivity of ecohydrologic responses to inter-annual climate variability. The Regional Hydro-Ecologic Simulation System (RHESSys) was applied to eight headwater, high-elevation watersheds located in the Kings River drainage basin. Each watershed was calibrated with measured snow depth (or snow water equivalent) and daily streamflow. Modeled streamflow estimates were sensitive to DEM resolution, even with resolution-specific calibration of soil drainage parameters. For model resolutions coarser than 10 m, the accuracy of streamflow estimates largely decreased. Reduced model accuracy was related to the reduction in spatial variance of a topographic wetness index with coarser DEM resolutions. This study also found that among the long-term average ecohydrologic estimates, summer flow estimates were the most sensitive to DEM resolution, and coarser resolution models overestimated the climatic sensitivity for evapotranspiration and net primary productivity. Therefore, accounting for fine-scale topographic variability in ecohydrologic modeling may be necessary for reliably assessing climate change effects on lower-order Sierra Nevada watersheds (≤2.3 km2).

Skill Assessment of Water Supply Forecasts for Western Sierra Nevada Watersheds

Skill Assessment of Water Supply Forecasts for Western Sierra Nevada Watersheds

Forest thinning may increase water yield from the Sierra Nevada

Research news Forest thinning may increase water yield from the Sierra Nevada D iscussions of California’s limited water supplies often leave out the biggest water users of all — forests. Elena Zhukova About 60% of California’s developed water supply originates in the Sierra Nevada. But an average of roughly 50% of the precipita- tion that falls in the Sierra Nevada never makes it to the state’s rivers, groundwater basins, reservoirs and aqueducts. Instead, it sustains trees and other vegeta- tion, or evaporates. A team of UC researchers is investigating how thinning forests could increase the water yield of the Sierra Nevada, which supplies about 60% of the sur- face water used by California’s cities and farms. The Sierra Nevada Watershed Ecosystem Enhancement Project (SWEEP) builds on prior re- search that indicates that forest thinning — removing a fraction of trees and other vegetation — can improve the health of remaining trees and reduce the risk of severe wildfire (Bales et al. 2011; Collins et al. 2014). The research team aims to quantify how invest- ments in forest management translate to increases in the amount of runoff from a given watershed. While research from a variety of sites around the world shows that thinning can increase water yield, the CALIFORNIA AGRICULTURE • VOLUME 69 , NUMBER 1 magnitude of that effect varies widely depending on climate, elevation and other variables, and it isn’t well studied in the Sierra Nevada. Better data on the benefits of vegetation manage- ment — for water availability as well as forest health, fire vulnerability, wildlife habitat and other ecosystem services — could form the basis for deals creating new sources of funding for forest management. Owners of hydroelectric dams, for instance, might chip in for watershed management if it was clearly established that a healthier forest would mean more water flowing through turbines downstream. But such transactions would need to be based on solid research. “You need good data if you’re going to ask people to pay for it,” said Roger Bales, a hydrologist and pro- fessor of engineering at UC Merced and a lead SWEEP researcher. Marketing the ecosystem benefits of forest thinning could help address a key problem in forest manage- ment: While there is wide agreement that tree density is higher than desirable on much California forest- land, funding is scarce for thinning, which typically costs $300 to $500 per acre. Preliminary estimates suggest that reducing forest cover by 40% could be ex- pected to increase water yield about 9%. Bill Stewart, a UC Cooperative Extension special- ist who is studying the economic aspects of SWEEP,

Snow water equivalent in the Sierra Nevada: Blending snow sensor observations with snowmelt model simulations

We estimate the spatial distribution of daily melt‐season snow water equivalent (SWE) over the Sierra Nevada for March to August, 2000–2012, by two methods: reconstruction by combining remotely sensed snow cover images with a spatially distributed snowmelt model and a blended method in which the reconstruction is combined with in situ snow sensor observations. We validate the methods with 17 snow surveys at six locations with spatial sampling and with the operational snow sensor network. We also compare the methods with NOAA's operational Snow Data Assimilation System (SNODAS). Mean biases of the methods compared to the snow surveys are −0.193 m (reconstruction), 0.001 m (blended), and −0.181 m (SNODAS). Corresponding root‐mean‐square errors are 0.252, 0.205, and 0.254 m. Comparison between blended and snow sensor SWE suggests that the current sensor network inadequately represents SWE in the Sierra Nevada because of the low spatial density of sensors in the lower/higher elevations. Mean correlation with streamflow in 19 Sierra Nevada watersheds is better with reconstructed SWE (r = 0.91) versus blended SWE (r = 0.81), snow sensor SWE (r = 0.85), and SNODAS SWE (r = 0.86). On the other hand, the correlation with blended SWE is generally better than with reconstructed, snow sensor, and SNODAS SWE late in the snowmelt season when snow sensors report zero SWE but snow remains in the higher elevations. Sensitivity tests indicate downwelling longwave radiation, snow albedo, forest density, and turbulent fluxes are potentially important sources of errors/uncertainties in reconstructed SWE, and domain‐mean blended SWE is relatively insensitive to the number of snow sensors blended.

Snowpack and runoff response to climate change in Owens Valley and Mono Lake watersheds

Precipitation from the Eastern Sierra Nevada watersheds of Owens Lake and Mono Lake is one of the main water sources for Los Angeles’ over 4 million people, and plays a major role in the ecology of Mono Lake and of these watersheds. We use the Variable Infiltration Capacity (VIC) hydrologic model at daily time scale, forced by climate projections from 16 global climate models under greenhouse gas emissions scenarios B1 and A2, to evaluate likely hydrologic responses in these watersheds for 1950–2099. Comparing climate in the latter half of the 20th Century to projections for 2070–2099, we find that all projections indicate continued temperature increases, by 2–5 °C, but differ on precipitation changes, ranging from −24 % to +56 %. As a result, the fraction of precipitation falling as rain is projected to increase, from a historical 0.19 to a range of 0.26–0.52 (depending on the GCM and emission scenario), leading to earlier timing of the annual hydrograph’s center, by a range of 9–37 days. Snowpack accumulation depends on temperature and even more strongly on precipitation due to the high elevation of these watersheds (reaching 4,000 m), and projected changes for April 1 snow water equivalent range from −67 % to +9 %. We characterize the watershed’s hydrologic response using variables integrated in space over the entire simulated area and aggregated in time over 30-year periods. We show that from the complex dynamics acting at fine time scales (seasonal and sub-seasonal) simple dynamics emerge at this multi-year time scale. Of particular interest are the dynamic effects of temperature. Warming anticipates hydrograph timing, by raising the fraction of precipitation falling as rain, reducing the volume of snowmelt, and initiating snowmelt earlier. This timing shift results in the depletion of soil moisture in summer, when potential evapotranspiration is highest. Summer evapotranspiration losses are limited by soil moisture availability, and as a result the watershed’s water balance at the annual and longer scales is insensitive to warming. Mean annual runoff changes at base-of-mountain stations are thus strongly determined by precipitation changes.

Stream temperature sensitivity to climate warming in California’s Sierra Nevada: impacts to coldwater habitat

Water temperature influences the distribution, abundance, and health of aquatic organisms in stream ecosystems, so understanding the impacts of climate warming on stream temperature will help guide management and restoration. This study assesses climate warming impacts on stream temperatures in California’s west-slope Sierra Nevada watersheds, and explores stream temperature modeling at the mesoscale. We used natural flow hydrology to isolate climate induced changes from those of water operations and land use changes. A 21 year time series of weekly streamflow estimates from WEAP21, a spatially explicit rainfall-runoff model were passed to RTEMP, an equilibrium temperature model, to estimate stream temperatures. Air temperature was uniformly increased by 2°C, 4°C, and 6°C as a sensitivity analysis to bracket the range of likely outcomes for stream temperatures. Other meteorological conditions, including precipitation, were unchanged from historical values. Raising air temperature affects precipitation partitioning into snowpack, runoff, and snowmelt in WEAP21, which change runoff volume and timing as well as stream temperatures. Overall, stream temperatures increased by an average of 1.6°C for each 2°C rise in air temperature, and increased most during spring and at middle elevations. Viable coldwater habitat shifted to higher elevations and will likely be reduced in California. Thermal heterogeneity existed within and between basins, with the high elevations of the southern Sierra Nevada and the Feather River watershed most resilient to climate warming. The regional equilibrium temperature modeling approach used here is well suited for climate change analysis because it incorporates mechanistic heat exchange, is not overly data or computationally intensive, and can highlight which watersheds are less vulnerable to climate warming. Understanding potential changes to stream temperatures from climate warming will affect how fish and wildlife are managed, and should be incorporated into modeling studies, restoration assessments, and licensing operations of hydropower facilities to best estimate future conditions and achieve desired outcomes.

Impact of Summer Cattle Grazing on the Sierra Nevada Watershed: Aquatic Algae and Bacteria

Introduction. We evaluated periphytic algal and microbial communities to assess the influence of human and cattle impact on Sierra water quality. Methods. 64 sites (lakes and streams from Lake Tahoe to Sequoia National Park, California) were sampled for suspended indicator bacteria and algae following standardized procedures. The potential for nonpoint pollution was divided into three categories: cattle-grazing areas (C), recreation use areas (R), or remote wildlife areas (W). Results. Periphyton was found at 100% of C sites, 89% of R sites, but only 25% of W sites. Eleven species of periphytic algae were identified, including Zygnema, Ulothrix, Chlorella, Spirogyra, mixed Diatoms, and Cladophoria. Mean benthic algae coverage was 66% at C sites compared to 2% at W sites (P < 0.05). The prevalence of E. coli associated with periphyton was 100% at C sites, 25% of R sites, and 0% of W sites. Mean E. coli CFU/gm of algae detected was: C = 173,000, R = 700, W = 0. (P < 0.05). Analysis of neighboring water for E. coli bacteria >100 CFU/100 mL: C = 91%, R = 8%, W = 0 (P < 0.05). Conclusion. Higher periphytic algal biomass and uniform presence of periphyton-attached E. coli corresponded to watersheds exposed to summer cattle grazing. These differences suggest cattle grazing compromises water quality.

Hydrologic Response and Watershed Sensitivity to Climate Warming in California's Sierra Nevada

This study focuses on the differential hydrologic response of individual watersheds to climate warming within the Sierra Nevada mountain region of California. We describe climate warming models for 15 west-slope Sierra Nevada watersheds in California under unimpaired conditions using WEAP21, a weekly one-dimensional rainfall-runoff model. Incremental climate warming alternatives increase air temperature uniformly by 2°, 4°, and 6°C, but leave other climatic variables unchanged from observed values. Results are analyzed for changes in mean annual flow, peak runoff timing, and duration of low flow conditions to highlight which watersheds are most resilient to climate warming within a region, and how individual watersheds may be affected by changes to runoff quantity and timing. Results are compared with current water resources development and ecosystem services in each watershed to gain insight into how regional climate warming may affect water supply, hydropower generation, and montane ecosystems. Overall, watersheds in the northern Sierra Nevada are most vulnerable to decreased mean annual flow, southern-central watersheds are most susceptible to runoff timing changes, and the central portion of the range is most affected by longer periods with low flow conditions. Modeling results suggest the American and Mokelumne Rivers are most vulnerable to all three metrics, and the Kern River is the most resilient, in part from the high elevations of the watershed. Our research seeks to bridge information gaps between climate change modeling and regional management planning, helping to incorporate climate change into the development of regional adaptation strategies for Sierra Nevada watersheds.

Reducing the impact of summer cattle grazing on water quality in the Sierra Nevada Mountains of California: a proposal

The Sierra Nevada Mountain range serves as an important source of drinking water for the State of California. However, summer cattle grazing on federal lands affects the overall water quality yield from this essential watershed as cattle manure is washed into the lakes and streams or directly deposited into these bodies of water. This organic pollution introduces harmful microorganisms and also provides nutrients such as nitrogen and phosphorus which increase algae growth causing eutrophication of otherwise naturally oligotrophic mountain lakes and streams. Disinfection and filtration of this water by municipal water districts after it flows downstream will become increasingly costly. This will be compounded by increasing surface water temperatures and the potential for toxins release by cyanobacteria blooms. With increasing demands for clean water for a state population approaching 40 million, steps need to be implemented to mitigate the impact of cattle on the Sierra Nevada watershed. Compared to lower elevations, high elevation grazing has the greatest impact on the watershed because of fragile unforgiving ecosystems. The societal costs from non-point pollution exceed the benefit achieved through grazing of relatively few cattle at the higher elevations. We propose limiting summer cattle grazing on public lands to lower elevations, with a final goal of allowing summer grazing on public lands only below 1,500 m elevation in the Central and Northern Sierra and 2,000 m elevation in the Southern Sierra.

English

Sierra Nevada snowpack is a critical water source for California’s growing population and agricultural industry. However, because mountain winters and springs are warming, on average, precipitation as snowfall relative to rain is decreasing, and snowmelt is earlier. The changes are stronger at mid-elevations than at higher elevations. The result is that the water supply provided by snowpack is diminishing. In this paper, we describe principal hydrologic responses to climatic and spatial geologic variations as gleaned from a series of observations including snowpack, stream-flow, and bedrock geology. Our analysis focused on peak (maximum) and base (minimum) daily discharge of the annual snowmelt-driven hydrographs from 18 Sierra Nevada watersheds and 24 stream gage locations using standard correlation methods. Insights into the importance of the relative magnitudes of peak flow and soil water storage led us to develop a hydrologic classification of mountain watersheds based on runoff versus base flow as a percentage of peak flow. Our findings suggest that watersheds with a stronger base flow response store more soil water than watersheds with a stronger peak-flow response. Further, the influence of antecedent wet or dry years is greater in watersheds with high base flow, measured as a percentage of peak flow. The strong correlation between 1) the magnitude of peak flow, and 2) snow water equivalent can be used to predict peak flow weeks in advance. A weaker but similar correlation can be used to predict the magnitude of base flow months in advance. Most of the watersheds show a trend that peak flow is occurring earlier in the year.

Evaluation of hydrologic equilibrium in a mountainous watershed: incorporating forest canopy spatial adjustment to soil biogeochemical processes

Hydrologic equilibrium theory has been used to describe both short-term regulation of gas exchange and long-term adjustment of forest canopy density. However, by focusing on water and atmospheric conditions alone a hydrologic equilibrium may impose an oversimplification of the growth of forests adjusted to hydrology. In this study nitrogen is incorporated as a third regulation of catchment level forest dynamics and gas exchange. This was examined with an integrated distributed hydrology and forest growth model in a central Sierra Nevada watershed covered primarily by old-growth coniferous forest. Water and atmospheric conditions reasonably reproduced daily latent heat flux, and predicted the expected catenary trend of leaf area index (LAI). However, it was not until the model was provided a spatially detailed description of initial soil carbon and nitrogen pools that spatial patterns of LAI were generated. This latter problem was attributed to a lack of soil history or memory in the initialization of the simulations. Finally, by reducing stomatal sensitivity to vapor pressure deficit (VPD) the canopy density increased when water and nitrogen limitations were not present. The results support a three-control hydrologic equilibrium in the Sierra Nevada watershed. This has implications for modeling catchment level soil–vegetation–atmospheric interactions over interannual, decade, and century time-scales.

Chemistry and mineralogy of a granitic, glacial soil chronosequence, Sierra Nevada Mountains, California

The bulk chemical composition, mineral chemistry and clay mineralogy of soils developed on granodiorite parent materials were investigated in Yosemite National Park in the Sierra Nevada, CA. The soils studied were developed on glacial moraines estimated to be ∼20 Ka (Tioga), ∼130 Ka (Tahoe) and ∼300 Ka (pre-Tahoe) in age, thus constituting a soil chronosequence. In addition to granodiorite bedrock minerals such as plagioclase, K-feldspar, quartz, biotite and hornblende, volcanic glass is also found disseminated throughout the soils in amounts up to 15% of the <2-mm size fraction by volume. Glass concentrations decrease with increasing depth for all soils. This suggests initial deposition of volcanic ash on preexisting soil surfaces with subsequent translocation downward into the soil profile. The volcanic ash is believed to have been derived from Pleistocene and Holocene volcanic centers located in the Mono/Inyo Craters region, approximately 50 km east of the study site. The clay mineralogy of the soils is dominated by kaolinite, gibbsite and vermiculite, with lesser amounts of soil illite. The total amount of clay in the soils increases with soil age. In the soil <2-μm size fractions, the weight proportion of kaolinite ranges from 20 to 70%, gibbsite ranges from 10 to 45%, vermiculite ranges from 10 to 40%, and soil illite ranges from 1 to 15%. Ti and Zr concentrations vary sporadically throughout the soils due either to heterogeneous distribution of Ti and Zr within the soil parent material, extensive mobility of Ti and Zr within the soil profile, and/or the dilution of soil Ti and Zr concentrations with the addition of low Ti and Zr volcanic glass. The dominance of gibbsite as a weathering product in these young soils (which are located in a cool, temperate setting) is counter to the common notion that gibbsite-dominated soils are restricted to old soils in humid tropical regions. The surprisingly large quantities of gibbsite may be due to the rapid weathering of volcanic ash, as has been observed in other predominantly volcanic soils. We suggest that volcanic glass, especially due to its high reactivity, must be considered as a significant factor when studying the soil, streamwater and isotopic geochemistry of Sierra Nevada watersheds.