To provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation methods using ground measurements from basin-scale wireless sensor networks: one based on wet-bulb temperature Twet and the other based on snow-depth measurements of accumulation and ablation. With data from 17 spatially distributed clusters (178 nodes) from two networks, in the American and Feather River basins of California’s Sierra Nevada, we analyzed transition elevation during 76 storm events in 2014–18. A Twet threshold of 0.58C best matched the transition elevation defined by snow depth. Transition elevations using Twet in upper elevations of the basins generally agreed with atmospheric snow level from radars located at lower elevations, while radar snow level was;100 m higher due to snow-level lowering on windward mountainsides during orographic lifting. Diurnal patterns of the difference between transition elevation and radar snow level were observed in the American basin, related to diurnal ground-temperature variations. However, these patterns were not found in the Feather basin due to complex terrain and higher uncertainties in transition-elevation estimates. The American basin tends to exhibit 100-m-higher transition elevations than does the Feather basin, consistent with the Feather basin being about 18 latitude farther north. Transition elevation averaged 155 m higher in intense atmospheric river events than in other events; meanwhile, snow-level lowering was enhanced with a 90-m-larger difference between radar snow level and transition elevation. On-the-ground continuous observations from distributed sensor networks can complement radar data and provide important ground truth and spatially resolved information on transition elevations in mountain basins.

This study reports on a blending approach using snowpack measurements from a wireless-sensor network, gauge precipitation, and atmospheric-moisture data to estimate mountain precipitation amount and phase. We applied the approach in California's American River basin, using dense measurements from a network consisting of over 130 sensor nodes distributed across the upper, more snow-dominated part of the basin (≥1,500 m elevation). Analysis of 60 precipitation events in water years 2014–2017 showed that the approach provides estimates of precipitation and orographic enhancement that reduce uncertainty from apparent snow undercatch by limited gauges. This approach also infers total precipitation based on snow measurements during rain-on-snow events. The sensor network and blending approach yielded median upper-basin orographic precipitation gradients (OPGs) of 0.57 km−1, smaller than the also-positive lower-basin (<1,500 m) medians OPGs from precipitation gauges and a gauge-based gridded data set of 1.23 and 1.00 km−1, respectively. However, during 73% of the events, both gauges and the gridded product showed negative OPGs in the upper basin, inconsistent with typically positive values from the distributed sensor network. Upper-basin OPGs from gauges and the gridded product were more negative (p-values < 0.03) during heavy events related to atmospheric rivers and Sierra barrier jets than during milder events, revealing the challenges for gauges to reliably measure precipitation from large moisture transport by strong winds. In snow-dominated headwater areas, precipitation from the blending approach is recommended as being more accurate for decision support, providing critical rain-versus-snow amounts and complementing precipitation-gauge data.

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra's wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

Large uncertainty remains in the spatial distribution of deep soil organic carbon (OC) storage and how climate controls belowground OC. This research aims to quantify OC stocks, characterize soil OC age and chemical composition, and evaluate climatic impacts on OC storage from the soil surface through the deep critical zone to bedrock. These objectives were carried out at four sites along a bio-climosequence in the Sierra Nevada, California. On average, 74% of OC was stored below the A horizon, and up to 30% of OC was stored in saprock (friable weakly weathered bedrock). Radiocarbon, spectroscopic, and isotopic analyses revealed the coexistence of very old organic matter (OM) (mean radiocarbon age = 20 300 years) with relatively recent OM (mean radiocarbon age = 4800 years) and highly decomposed organic compounds with relatively less decomposed material in deep soil and saprock. This co-mingling of OM suggests OC is prone to both active cycling and long-term protection from degradation. In addition to having direct effects on OC cycling, climate indirectly controls deep OC storage through its impact on the degree of regolith weathering (e.g. thickening). Although deep OC concentrations are low relative to soil, thick saprock represents a large, previously unrealized OC pool.

The conversion of bedrock to regolith marks the inception of critical zone processes, but the factors that regulate it remain poorly understood. Although the thickness and degree of weathering of regolith are widely thought to be important regulators of the development of regolith and its water-storage potential, the functional relationships between regolith properties and the processes that generate it remain poorly documented. This is due in part to the fact that regolith is difficult to characterize by direct observations over the broad scales needed for process-based understanding of the critical zone. Here we use seismic refraction and resistivity imaging techniques to estimate variations in regolith thickness and porosity across a forested slope and swampy meadow in the Southern Sierra Critical Zone Observatory (SSCZO). Inferred seismic velocities and electrical resistivities image a weathering zone ranging in thickness from 10 to 35m (average=23m) along one intensively studied transect. The inferred weathering zone consists of roughly equal thicknesses of saprolite (P-velocity<2kms-1) and moderately weathered bedrock (P-velocity=2-4kms-1). A minimum-porosity model assuming dry pore space shows porosities as high as 50% near the surface, decreasing to near zero at the base of weathered rock. Physical properties of saprolite samples from hand augering and push cores are consistent with our rock physics model when variations in pore saturation are taken into account. Our results indicate that saprolite is a crucial reservoir of water, potentially storing an average of 3m3m-2 of water along a forested slope in the headwaters of the SSCZO. When coupled with published erosion rates from cosmogenic nuclides, our geophysical estimates of weathering zone thickness imply regolith residence times on the order of 105years. Thus, soils at the surface today may integrate weathering over glacial-interglacial fluctuations in climate. © 2013 John Wiley & Sons, Ltd.

Sensor networks within the Southern Sierra Critical Zone Observatory (SSCZO) and Kings River Experimental Watersheds (KREW) document changes in the water cycle spanning the west slope of the southern Sierra Nevada in California. The networks were established to document water dynamics throughout the critical zone spanning profile, hillslope, catchment, and watershed scales at key locations that reflect systematic differences in bioclimatic conditions imposed by a strong elevation gradient. The critical zone observatory attempts to constrain the hydrologic budget via representative measurements of streamflow, eddy flux covariance, snow depth, meteorological conditions, and water content and water potential in soil and deep regolith. These measurements reveal the complexity of interactions among all aspects of the water balance (runoff, storage, evapotranspiration [ET], and precipitation) through daily, seasonal, and annual timescales. Multiyear drought, catastrophic wildfires, insect outbreaks, and disease have caused widespread tree mortality in the Sierra Nevada. These disturbances offer a window into the future for this region, which is expected to undergo significant change in response to global warming. This hydrological observatory provides valuable hydrometric attributes and fluxes across the stream–groundwater– vadose zone–soil–vegetation–atmosphere continuum.

Mountain runoff ultimately reflects the difference between precipitation (P) and evapotranspiration (ET), as modulated by biogeophysical mechanisms that intensify or alleviate drought impacts. These modulating mechanisms are seldom measured and not fully understood. The impact of the warm 2012-15 California drought on the heavily instrumented Kings River basin provides an extraordinary opportunity to enumerate four mechanisms that controlled the impact of drought on mountain hydrology. Two mechanisms intensified the impact: (i) evaporative processes have first access to local precipitation, which decreased the fractional allocation of P to runoff in 2012-15 and reduced P-ET by 30% relative to previous years, and (ii) 2012-15 was 1 °C warmer than the previous decade, which increased ET relative to previous years and reduced P-ET by 5%. The other two mechanisms alleviated the impact: (iii) spatial heterogeneity and the continuing supply of runoff from higher elevations increased 2012-15 P-ET by 10% relative to that expected for a homogenous basin, and iv) drought-associated dieback and wildfire thinned the forest and decreased ET, which increased 2016 P-ET by 15%. These mechanisms are all important and may offset each other; analyses that neglect one or more will over or underestimate the impact of drought and warming on mountain runoff.

Using data from a water-balance instrument cluster with spatially distributed sensors we determined the magnitude and within-catchment variability of components of the catchmentscale water balance, focusing on the relationship of seasonal evapotranspiration to changes in snowpack and soil moisture storage. Co-located, continuous snow depth and soil moisture measurements were deployed in a rain-snow transition catchment in the mixed-conifer forest in the Southern Sierra Nevada. At each elevation sensors were placed in the open, under the canopy, and at the drip edge on both north- and south-facing slopes. Snow sensors were placed at 27 locations, with soil moisture and temperature sensors placed at depths of 10, 30, 60, and 90 cm beneath the snow sensor. Soils are weakly developed (Inceptisols and Entisols) and formed from decomposed granite with properties that change with elevation. The soil- bedrock interface is hard in upper reaches of the basin (>2000 m) where glaciers have scoured the parent material approximately 18,000 yr ago. Below an elevation of 2000 m soils have a paralithic contact (weathered saprolite) that can extend beyond a depth of 1.5 m, facilitating pathways for deep percolation. Soils are wet and not frozen in winter, and dry out in the weeks following spring snowmelt and rain. Based on data from two snowmelt seasons, it was found that soils dry out following snowmelt at relatively uniform rates; however, the timing of drying at a given site may be offset by up to 4 wk because of heterogeneity in snowmelt at different elevations and aspects. Spring and summer rainfall mainly affected sites in the open, with drying after a rain event being faster than following snowmelt. Water loss rates from soil of 0.5 to 1.0 cm d -1 during the winter and snowmelt season reflect a combination of evapotranspiration and deep drainage, as stream baseflow remains relatively low. About one-third of annual evapotranspiration comes from water storage below the 1-m depth, that is, below mapped soil. We speculate that much of the deep drainage is stored locally in the deeper regolith during periods of high precipitation, being available for tree transpiration during summer and fall months when shallow soil water storage is limiting. Total annual evapotranspiration for water year 2009 was estimated to be approximately 76 cm. © Soil Science Society of America.

Enhanced understanding of subsurface water storage will improve prediction of future impacts of climate change, including drought, forest mortality, wildland fire, and strained water security. Previous research has examined the importance of plant-accessible water in soil, but in upland landscapes within Mediterranean climates, soil often accounts for only a fraction of subsurface water storage. We draw insights from previous research and a case study of the Southern Sierra Critical Zone Observatory to define attributes of subsurface storage; review observed patterns in their distribu-tion; highlight nested methods for estimating them across scales; and showcase the fundamental processes controlling their formation. We review observations that highlight how forest ecosystems subsist on lasting plant-accessible stores of subsurface water during the summer dry period and during multiyear droughts. The data suggest that trees in these forest ecosystems are rooted deeply in the weathered, highly porous saprolite or saprock, which reaches up to 10–20 m beneath the surface. This review confirms that the system harbors large volumes of subsurface water and shows that they are vital to supporting the ecosystem through the summer dry season and extended droughts. This research enhances understanding of deep subsurface water storage across landscapes and identifies key remaining challenges in predicting and managing response to climate and land use change in mountain ecosystems of the Sierra Nevada and in other Mediterranean climates worldwide. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water Extremes Water and Life > Nature of Freshwater Ecosystems.

Understanding potential response of forest carbon (C) and nutrient storage to warming is important for climate mitigation policies. Unfortunately, those responses are difficult to predict in seasonally dry forests, in part, because ecosystem processes are highly sensitive to both changes in temperature and precipitation. We investigated how warming might alter stocks of C, nitrogen (N), and phosphorus (P) in vegetation and the entire regolith (soil + weathered bedrock or “saprock”) using a space-for-time substitution along a bioclimatic gradient in the Sierra Nevada, California. The pine-oak and mixed-conifer forests between 1,160–2,015 m elevation have more optimal climates (not too dry or hot) for ecosystem productivity, soil weathering, and cycling of essential elements than the oak savannah (405 m) and subalpine forest (2,700 m). We found decreases in overstory vegetation nutrient stocks with decreasing elevation because of enhanced water limitation and greater occurrence of disturbances. Stocks of C, N, and P in the entire regolith peaked at the pine-oak and mixed-conifer forests across the bioclimatic gradient, driven by thicker regolith profiles and greater nutrient input rates. These observations suggest long-term warming will decrease ecosystem nutrient storage at the warmer, transitional pine-oak zone, but will increase nutrient storage at the colder, subalpine zone. Assuming steady-state conditions, we found the mean residence time of ecosystem C decreased with projected rising air temperatures and increased following a major drought event across the bioclimatic gradient. Our study emphasizes potentially elevation-dependent changes in nutrient storage and C persistence with warming in seasonally dry forests.