Southern Sierra Critical Zone Observatory Research Articles

Impacts of the 2012-2015 Californian drought on carbon, water and energy fluxes in the Californian Sierras: Results from an imaging spectrometry-constrained terrestrial biosphere model.

Accurate descriptions of current ecosystem composition are essential for improving terrestrial biosphere model predictions of how ecosystems are responding to climate variability and change. This study investigates how imaging spectrometry-derived ecosystem composition can constrain and improve terrestrial biosphere model predictions of regional-scale carbon, water and energy fluxes. Incorporating imaging spectrometry-derived composition of five plant functional types (Grasses/Shrubs, Oaks/Western Hardwoods, Western Pines, Fir/Cedar and High-elevation Pines) into the Ecosystem Demography (ED2) terrestrial biosphere model improves predictions of net ecosystem productivity (NEP) and gross primary productivity (GPP) across four flux towers of the Southern Sierra Critical Zone Observatory (SSCZO) spanning a 2250m elevational gradient in the western Sierra Nevada. NEP and GPP root-mean-square-errors were reduced by 23%-82% and 19%-89%, respectively, and water flux predictions improved at the mid-elevation pine (Soaproot), fir/cedar (P301) and high-elevation pine (Shorthair) flux tower sites, but not at the oak savanna (San Joaquin Experimental Range [SJER]) site. These improvements in carbon and water predictions are similar to those achieved with model initializations using ground-based inventory composition. The imaging spectrometry-constrained ED2model was then used to predict carbon, water and energy fluxes and above-ground biomass (AGB) dynamics over a 737km2 region to gain insight into the regional ecosystem impacts of the 2012-2015 Californian drought. The analysis indicates that the drought reduced regional NEP, GPP and transpiration by 83%, 40% and 33%, respectively, with the largest reductions occurring in the functionally diverse, high basal area mid-elevation forests. This was accompanied by a 54% decline in AGB growth in 2012, followed by a marked increase (823%) in AGB mortality in 2014, reflecting an approximately 10-fold increase in per capita tree mortality from ~55 treeskm-2 year-1 in 2010-2011, to ~535 treeskm-2 year-1 in 2014. These findings illustrate how imaging spectrometry estimates of ecosystem composition can constrain and improve terrestrial biosphere model predictions of regional carbon, water, and energy fluxes, and biomass dynamics.

How realistic are water‐balance closure assumptions? A demonstration from the southern sierra critical zone observatory and kings river experimental watersheds

AbstractThe water balance is an essential tool for hydrologic studies and quantifying water‐balance components is the focus of many research catchments. A fundamental question remains regarding the appropriateness of water‐balance closure assumptions when not all components are available. In this study, we leverage in‐situ measurements of water fluxes and storage from the Southern Sierra Critical Zone Observatory (SSCZO) and the Kings River Experimental Watersheds (KREW) to investigate annual water‐balance closure errors across large (1016–5389 km2) river basins and small (0.5–5 km2) headwater‐catchment scales in the southern Sierra Nevada. The results showed that while long‐term water balance in river basins can be closed within 10% of precipitation, in the smaller headwater catchments as much as a quarter of precipitation remained unaccounted for. A detailed diagnosis of this water‐balance closure error using distributed soil moisture measurements in the top 1 m suggests an unaccounted deeper storage and a net groundwater export from the headwater catchments. This imbalance was also found to be very sensitive to the timescales over which water‐balance closures were attempted. While some of the closure errors in the simple water balance can be attributed to measurement uncertainties, we argue for a broader consideration of groundwater exchange when evaluating hydrological processes at headwater scales, as the assumption of negligible net groundwater exchange may lead to an overestimation of fluxes derived from the water balance method.

Simplified Method for the In Situ Collection and Laboratory Analysis of Cosmogenic Tracers (Sulfur-35 and Sodium-22) to Determine Residence Time Distributions and Water Ages

The use of cosmogenically produced sulfur-35 (T1/2 = 87 days) and sodium-22 (T1/2 = 2.6 years) as intrinsic tracers can provide valuable information on catchment hydrology, flow paths, and subsurface storage. A new and straightforward method was created to determine the activities of both 35S and 22Na in various water sources by pumping large volumes (up to 1000 L) of water through cation- and anion-exchange resin columns in the field to collect sodium and sulfate ions and simple chemistry in the lab. Samples are counted for 35S using liquid scintillation counting (LSC) and for 22Na via γ spectroscopy. Our novel in situ method provides faster sample throughput as well as better counting statistics and lower detection limits. Both methods were successfully applied at the Southern Sierra Critical Zone Observatory.

Cosmogenic Isotopes Unravel the Hydrochronology and Water Storage Dynamics of the Southern Sierra Critical Zone

AbstractOne of the principal questions in hydrology is how and when water leaves the critical zone storage as either stream flow or evapotranspiration. We investigated subsurface water storage and storage selection of the Southern Sierra Critical Zone Observatory (California, USA) within the age‐ranked storage selection framework, constrained by a novel combination of cosmogenic radioactive and stable isotopes: tritium, sodium‐22, sulfur‐35, and oxygen‐18. We found a significant positive correlation between tritium and stream flow rate and between sulfur‐35 and stream flow rate, indicating that the age distribution of stream flow varies with stream flow rate. Storage selection functions that vary with stream flow rate are better able to reproduce tritium concentrations in stream flow than functions that are constant in time. For the Southern Sierra Critical Zone, there is a strong preference to discharge the oldest water in storage during dry conditions but only a weak preference for younger water during wet conditions. The preference of evapotranspiration for younger water, constrained by oxygen‐18 in stream water, is essential to parameterize subsurface storage but needs to be confirmed by isotopic or other investigations of evapotranspiration. This is the first study to illustrate how a combination of cosmogenic radioactive isotopes reveals the hydrochronology and water storage dynamics of catchments, constrains the subsurface architecture of the critical zone, and provides insight into landscape evolution.

Spatially distributed water-balance and meteorological data from the rain–snow transition, southern Sierra Nevada, California

Abstract. We strategically placed spatially distributed sensors to provide representative measures of changes in snowpack and subsurface water storage, plus the fluxes affecting these stores, in a set of nested headwater catchments. The high temporal frequency and distributed coverage make the resulting data appropriate for process studies of snow accumulation and melt, infiltration, evapotranspiration, catchment water balance, (bio)geochemistry, and other critical-zone processes. We present 8 years of hourly snow-depth, soil-moisture, and soil-temperature data, as well as 14 years of quarter-hourly streamflow and meteorological data that detail water-balance processes at Providence Creek, the upper part of which is at the current 50 % rain versus snow transition of the southern Sierra Nevada, California. Providence Creek is the long-term study cooperatively run by the Southern Sierra Critical Zone Observatory (SSCZO) and the USDA Forest Service Pacific Southwest Research Station's Kings River Experimental Watersheds (KREW). The 4.6 km2 montane Providence Creek catchment spans the current lower rain–snow transition elevation of 1500–2100 m. Two meteorological stations bracket the high and low elevations of the catchment, measuring air temperature, relative humidity, solar radiation, precipitation, wind speed and direction, and snow depth, and at the higher station, snow water equivalent. Paired flumes at three subcatchments and a V-notch weir at the integrating catchment measure quarter-hourly streamflow. Measurements of meteorological and streamflow data began in 2002. Between 2008 and 2010, 50 sensor nodes were added to measure distributed snow depth, air temperature, soil temperature, and soil moisture within the top 1 m below the surface. These sensor nodes were installed to capture the lateral differences of aspect and canopy coverage. Data are available at hourly and daily intervals by water year (1 October–30 September) in nonproprietary formats from online data repositories. Data for the Southern Sierra Critical Zone Observatory distributed snow and soil datasets are at https://doi.org/10.6071/Z7WC73. Kings River Experimental Watersheds meteorological data are available from https://doi.org/10.2737/RDS-2018-0028 and stream-discharge data are available from https://doi.org/10.2737/RDS-2017-0037.

Dynamic process connectivity explains ecohydrologic responses to rainfall pulses and drought

Ecohydrologic fluxes within atmosphere, vegetation, and soil systems exhibit a joint variability that arises from forcing and feedback interactions. These interactions cause fluctuations to propagate between variables at many time scales. In an ecosystem, this connectivity dictates responses to climate change, land-cover change, and weather events and must be characterized to understand resilience and sensitivity. We use an information theory-based approach to quantify connectivity in the form of information flow associated with the propagation of fluctuations between variables. We apply this approach to study ecosystems that experience changes in dry-season moisture availability due to rainfall and drought conditions. We use data from two transects with flux towers located along elevation gradients and quantify redundant, synergistic, and unique flow of information between lagged sources and targets to characterize joint asynchronous time dependencies. At the Reynolds Creek Critical Zone Observatory in Idaho, a dry-season rainfall pulse leads to increased connectivity from soil and atmospheric variables to heat and carbon fluxes. At the Southern Sierra Critical Zone Observatory in California, separate sets of dominant drivers characterize two sites at which fluxes exhibit different drought responses. For both cases, our information flow-based connectivity characterizes dominant drivers and joint variability before, during, and after disturbances. This approach to gauge the responsiveness of ecosystem fluxes under multiple sources of variability furthers our understanding of complex ecohydrologic systems.

Subsurface plant‐accessible water in mountain ecosystems with a Mediterranean climate

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 distribution; 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

Southern Sierra Critical Zone Observatory and Kings River Experimental Watersheds: A Synthesis of Measurements, New Insights, and Future Directions

Core Ideas Water quality and stream flow have temporal and spatial trends in response to variable climate. Our work reveals how Sierra Nevada forests responded to and recovered from multiyear drought. Regolith thickness trends reveal water storage capacity differences with elevation. Monitoring shows deep‐water changes via plant utilization or capillary flow during drought. 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.

Analysis of air mass trajectories to explain observed variability of tritium in precipitation at the Southern Sierra Critical Zone Observatory, California, USA

Understanding the behavior of tritium, a radioactive isotope of hydrogen, in the environment is important to evaluate the exposure risk of anthropogenic releases, and for its application as a tracer in hydrology and oceanography. To understand and predict the variability of tritium in precipitation, HYSPLIT air mass trajectories were analyzed for 16 aggregate precipitation samples collected over a 2 year period at irregular intervals at a research site located at 2000 m elevation in the southern Sierra Nevada (California, USA). Attributing the variation in tritium to specific source areas confirms the hypothesis that higher latitude or inland sources bring higher tritium levels in precipitation than precipitation originating in the lower latitude Pacific Ocean. In this case, the source of precipitation accounts for 79% of the variation observed in tritium concentrations. Air mass trajectory analysis is a promising tool to improve the predictions of tritium in precipitation at unmonitored locations and thoroughly understand the processes controlling transport of tritium in the environment.

Quantifying nutrient uptake as driver of rock weathering in forest ecosystems by magnesium stable isotopes

Abstract. Plants and soil microbiota play an active role in rock weathering and potentially couple weathering at depth with erosion at the soil surface. The nature of this coupling is still unresolved because we lacked means to quantify the passage of chemical elements from rock through higher plants. In a temperate forested landscape characterised by relatively fast (∼ 220 t km−2 yr−1) denudation and a kinetically limited weathering regime of the Southern Sierra Critical Zone Observatory (SSCZO), California, we measured magnesium (Mg) stable isotopes that are sensitive indicators of Mg utilisation by biota. We find that Mg is highly bio-utilised: 50–100 % of the Mg released by chemical weathering is taken up by forest trees. To estimate the tree uptake of other bio-utilised elements (K, Ca, P and Si) we compared the dissolved fluxes of these elements and Mg in rivers with their solubilisation fluxes from rock (rock dissolution flux minus secondary mineral formation flux). We find a deficit in the dissolved fluxes throughout, which we attribute to the nutrient uptake by forest trees. Therefore both the Mg isotopes and the flux comparison suggest that a substantial part of the major element weathering flux is consumed by the tree biomass. The enrichment of 26Mg over 24Mg in tree trunks relative to leaves suggests that tree trunks account for a substantial fraction of the net uptake of Mg. This isotopic and elemental compartment separation is prevented from obliteration (which would occur by Mg redissolution) by two potential effects. Either the mineral nutrients accumulate today in regrowing forest biomass after clear cutting, or they are exported in litter and coarse woody debris (CWD) such that they remain in solid biomass. Over pre-forest-management weathering timescales, this removal flux might have been in operation in the form of natural erosion of CWD. Regardless of the removal mechanism, our approach provides entirely novel means towards the direct quantification of biogenic uptake following weathering. We find that Mg and other nutrients and the plant-beneficial element Si (bio-elements) are taken up by trees at up to 6 m depth, and surface recycling of all bio-elements but P is minimal. Thus, in the watersheds of the SSCZO, the coupling between erosion and weathering might be established by bio-elements that are taken up by trees, are not recycled and are missing in the dissolved river flux due to erosion as CWD and as leaf-derived bio-opal for Si. We suggest that the partitioning of a biogenic weathering flux into eroded plant debris might represent a significant global contribution to element export after weathering in eroding mountain catchments that are characterised by a continuous supply of fresh mineral nutrients.

Microbial Community Structure of Subalpine Snow in the Sierra Nevada, California

ABSTRCTMounting evidence suggests that Earth’s cryosphere harbors diverse and active microbial communities. However, our understanding of microbial composition and diversity in seasonal snowpack of montane ecosystems remains limited. We sequenced the 16S rRNA gene to determine microbial structure (composition and diversity) of snow at two depths (0–15 and 15–30 cm) of a subalpine site in the Southern Sierra Critical Zone Observatory, California, U.S.A. Proteobacteria dominated both depths (~72% of sequences), and this phylum was composed mostly of bacteria within the Rhodospirillales order. Cyanobacteria were almost exclusively present in the upper snow layer, while Actinobacteria and Firmicutes were more abundant in the deep snow layer. Many of the most abundant phylotypes were Acetobacteraceae. Phylotype NCR4874, which comprised 22%–32% of the sequences, was most closely related to the N2-fixing bacteria Asaia siamensis, suggesting that N2 fixation may be an important process within the Sierra snowpack. In addition, just under half (45%) of the numerically dominant phylotypes shared >98% similarity with sequences recovered from other cold environments. Our results suggest that microbial communities of subalpine Sierra Nevada snowpack are diverse, with both snow depths harboring distinct but overlapping communities consisting largely of cold-adapted bacteria.

Optimizing embedded sensor network design for catchment-scale snow-depth estimation using LiDAR and machine learning

PUBLICATIONS Water Resources Research RESEARCH ARTICLE 10.1002/2016WR018896 Key Points: A machine-learning algorithm for optimizing snow sensor placements is compared to expert placements in an existing sensor network The spatial and temporal transferability of the algorithm is then assessed in 14 total LiDAR surveys in two uninstrumented catchments The accuracy of the snow depth estimated from the sensor measurements is higher than expert and randomized placements in each of the surveys Correspondence to: C. A. Oroza, coroza@berkeley.edu Citation: Oroza, C. A., Z. Zheng, S. D. Glaser, and D. Tuia (2016), Optimizing embedded sensor network design for catchment- scale snow-depth estimation using LiDAR and machine learning, Water Resour. Res., 52, 8174–8189, doi:10.1002/2016WR018896. Received 11 MAR 2016 Accepted 23 SEP 2016 Accepted article online 27 SEP 2016 Published online 22 OCT 2016 Optimizing embedded sensor network design for catchment-scale snow-depth estimation using LiDAR and machine learning Carlos A. Oroza 1 , Zeshi Zheng 1 , Steven D. Glaser 1 , Devis Tuia 2 , and Roger C. Bales 1,3 Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA, 2 Department of Geography, University of Zurich, Zurich, Switzerland, 3 Sierra Nevada Research Institute, University of California, Merced, California, USA Abstract We evaluate the accuracy of a machine-learning algorithm that uses LiDAR data to optimize ground-based sensor placements for catchment-scale snow measurements. Sampling locations that best represent catchment physiographic variables are identified with the Expectation Maximization algorithm for a Gaussian mixture model. A Gaussian process is then used to model the snow depth in a 1 km 2 area sur- rounding the network, and additional sensors are placed to minimize the model uncertainty. The aim of the study is to determine the distribution of sensors that minimizes the bias and RMSE of the model. We com- pare the accuracy of the snow-depth model using the proposed placements to an existing sensor network at the Southern Sierra Critical Zone Observatory. Each model is validated with a 1 m 2 LiDAR-derived snow-depth raster from 14 March 2010. The proposed algorithm exhibits higher accuracy with fewer sensors (8 sensors, RMSE 38.3 cm, bias 5 3.49 cm) than the existing network (23 sensors, RMSE 53.0 cm, bias 5 15.5 cm) and randomized placements (8 sensors, RMSE 63.7 cm, bias 5 24.7 cm). We then evaluate the spatial and temporal transferability of the method using 14 LiDAR scenes from two catchments within the JPL Airborne Snow Observatory. In each region, the optimized sensor placements are determined using the first available snow raster for the year. The accuracy in the remaining LiDAR surveys is then com- pared to 100 configurations of sensors selected at random. We find the error statistics (bias and RMSE) to be more consistent across the additional surveys than the average random configuration. 1. Introduction A major challenge of hydrologic science in montane regions relates to estimating the spatial variability of snow cover [Bales et al., 2006; Trujillo and Lehning, 2015; McCreight et al., 2014; Guan et al., 2013]. Multiple independent variables govern the distribution of snow cover, including elevation, slope, aspect, and the dis- tribution of canopy [Faria et al., 2000; Musselman et al., 2008; Lehning et al., 2011; Helfricht et al., 2014]. Non- stationary effects such as climate warming and changes in vegetation structure may significantly alter the timing and magnitude of storage and runoff in these watersheds [Goulden and Bales, 2014; Flanner et al., 2009]. Existing regression-based hydrologic models, which use statistical relations from historical hydro- graphs to predict runoff and inform allocation decisions [Perkins et al., 2009; Rosenberg et al., 2011; Rango and Martinec, 1995] will have limited accuracy as conditions deviate from historical norms and thus may prove to be inadequate for predictions in water management. C 2016. American Geophysical Union. V All Rights Reserved. OROZA ET AL. Recent research has focused on improving hydrologic models by assimilating remote-sensing and in situ measurements with distributed energy-balance models to better estimate storage and runoff [Guan et al., 2013]. These methods use well-developed remote-sensing [Painter et al., 2003; Rosenthal and Dozier, 1996; € lli et al., 2002; Egli et al., 2012] and energy-balance models [Marks et al., 1992; Link and Marks, Dozier, 1989; P a 1999; Brubaker et al., 1996] to estimate snow and snowmelt processes across basins. In situ measurements for these methods are presently limited to snow pillows and snow courses, which largely sample flat, open terrain [Molotch and Bales, 2006], yet the distribution of snow cover can vary considerably as a function of topographic features. To address this, in situ sensor measurements can be deployed to capture the mean and variance of the snow depth, which can be used to inform models that use these statistics as inputs [e.g., Essery and Pomeroy, 2004]. Alternatively, individual sensor measurements can be used together with OPTIMIZING SNOW SENSOR PLACEMENTS

CLM과 VIC 모형을 활용한 지표 에너지 플럭스 산정

전 지구 지표 순환 분석을 위하여 지표와 대기 사이의 에너지 교환에 대한 분석이 필수적이다. 이러한 에너지 교환의 정량화를 위하여 다양한 지면 모형에 대한 연구가 진행되고 있다. 다양한 모형들 중 Common Land Model(CLM)과 Variable Infiltration Capacity(VIC) 모형을 활용한 연구가 활발히 수행되고 있다. CLM은 발전된 지면 모형의 형태로 적은 사용자 변수로 현실적인 결과를 산출한다는 장점이 있다. VIC 모형 또한 대표적인 지면 모형 중 하나로 에너지 인자 및 유출량 모의를 위하여 전 세계적으로 다양한 분야에서 활용되고 있다. 본 연구에서는 미국 캘리포니아 주 SS-CZO 사이트를 대상으로 CLM과 VIC 모형을 활용하여 주요 에너지 인자 인 순복사량, 현열, 잠열을 모의하였다. 순복사량과 현열 모두 두 모형에서 양호한 결과를 보이나, 강우 발생 시 CLM은 잠열과 현열을 과소모의하는 경향을 나타내었다. 잠열은 CLM의 모의 결과가 잠열을 과소모의 한 VIC 모형에 비하여 관측된 잠열의 경향을 더 잘 모의하는 것으로 나타났다. 이러한 에너지 인자 모의 및 모형의 장단점에 대한 분석을 통하여 CLM과 VIC 모형의 활용가능성 및 다양한 모형 활용의 필요성을 확인하였다. Accurate understanding of land surface is essential to analyze energy exchanges between earth surface and atmosphere. For the quantization of energy fluxes, the various researches about Land Surface Model(LSM) have been progressed. Among the various LSMs, the researches using Common Land Model(CLM) and Variable Infiltration Capacity(VIC) model are performed briskly. The CLM which is advanced LSM can calculate realistic results with few user defined parameters. The VIC model which is also typical LSM is widely used for estimation of energy fluxes and runoff in various fields. In this study, the energy fluxes which are net radiation, sensible heat flux, and latent heat flux were estimated using CLM and VIC model at Southern Sierra-Critical Zone Observatory(SS-CZO) site in California, United States. In case of net radiation and sensible heat flux, both models showed good agreement with observations, however, the CLM showed underestimated patterns of net radiation and sensible heat flux during precipitation period. In case of latent heat flux, the CLM represented better estimation of latent heat flux than VIC model which underestimated the latent heat flux. Through the estimation of energy fluxes and analysis of models' pros and cons, the applicability of CLM and VIC models and need of multi-model application were identified.

Polymictic pool behaviour in a montane meadow, Sierra Nevada, CA

AbstractWe observed polymictic behaviour in stream pools in Long Meadow, Sequoia National Park, California—part of the Southern Sierra Critical Zone Observatory. Stream pools stratified thermally during the day time and were isothermal at night—this pattern persists from the middle of summer into the fall. We found that four characteristics typical of a mountain meadow environment—low stream flow, open sky, cold groundwater discharge, and elevated organic carbon concentrations—are particularly conducive to pool stratification. Incoming shortwave radiation was the dominant energy input to heat pool water while nighttime emitted longwave radiation was the major cooling mechanism. Relatively cold groundwater discharge into the pool bottom increased density stratification within the pool. Elevated DOC concentrations increased the capacity of the pool to absorb photosynthetically active radiation and also promoted stratification. Stream velocities in the meadow were generally insufficient to meet threshold Richardson numbers and mix the pools during the daytime; smaller stream cross sectional areas would have potential for destabilizing pools in the daytime. We propose a conceptual model for describing polymictic stream pools and assessing the potential for polymictic pools to occur. Copyright © 2016 John Wiley & Sons, Ltd.

Geophysical constraints on deep weathering and water storage potential in the Southern Sierra Critical Zone Observatory

ABSTRACTThe 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 35 m (average = 23 m) along one intensively studied transect. The inferred weathering zone consists of roughly equal thicknesses of saprolite (P‐velocity < 2 km s−1) and moderately weathered bedrock (P‐velocity = 2–4 km s−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 3 m3 m−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 105 years. Thus, soils at the surface today may integrate weathering over glacial–interglacial fluctuations in climate. Copyright © 2013 John Wiley & Sons, Ltd.

Landscape response to tipping points in granite weathering: The case of stepped topography in the Southern Sierra Critical Zone Observatory

The dynamics of granitic landscapes are modulated by bimodal weathering, which produces patchy granular soils and expanses of bare rock ranging from meter-scale boulders to mountain-scale domes. We used terrain analysis and with cosmogenic nuclide measurements of erosion rates to quantitatively explore Wahrhaftig’s decades-old hypothesis for the development of “stepped topography” by differential weathering of bare and soil-mantled granite. According to Wahrhaftig’s hypothesis, bare granite weathers slower than soil-mantled granite; thus random erosional exposure of bare rock leads to an alternating sequence of steep, slowly weathering bedrock “steps” and gently sloped, but rapidly weathering, soil-mantled “treads.” Our investigation focused on the terrain surrounding the Southern Sierra Critical Zone Observatory (CZO), which is underlain by granitic bedrock and lies outside the limits of recent glaciation, in the heart of the stepped topography described by Wahrhaftig. Our digital terrain analysis confirms that steep steps often grade into gentle treads, consistent with Wahrhaftig’s hypothesis. However, we observe a mix-and-match of soil and bare rock on treads and steps, contrary to one of the hypothesis’ major underpinnings – that bare rock should be much more common on steps than on treads. Moreover, the data show that bare rock is not as common as expected at step tops; Wahrhaftig’s hypothesis dictates that step tops should act as slowly eroding base levels for the treads above them. The data indicate that, within each landscape class (i.e., the steps and treads), bare rock erodes more slowly than surrounding soil. This suggests that the coupling between soil production and denudation in granitic landscapes harbors a tipping point wherein erosion rates decrease when soils are stripped to bedrock. Although broadly consistent with the differential weathering invoked by Wahrhaftig, the data also show that steps are eroding faster than treads, undermining Wahrhaftig’s explanation for the origins of the steps. The revised interpretation proposed here is that the landscape evolves by back-wearing of steps in addition to differential erosion due to differences in weathering of bare and soil-mantled granite.