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The distribution of snow cover is critical for predicting ecohydrological processes and underpins mountain water supplies in ranges like the Sierra Nevada in the Western United States. Many key water supply areas are covered by montane forests, which have substantial effects on the amount and timing of snowmelt. In-situ observations of snow-forest interactions have limited spatial coverage and remote sensing using optical sensors (e.g. MODIS) cannot observe snow cover below the canopy. In this study, we developed and verified a lidar-based method to detect snow cover under canopy, investigated how fractional snow covered area (fSCA) varies with topography in open versus under canopy areas and developed a correction factor that could be used to improve satellite-derived fSCA products. We developed our new method using three snow-on lidar overflights and verified it with in-situ distributed temperature sensor (DTS) observations at Sagehen Creek watershed in the Sierra Nevada, California, USA. DTS validation of lidar classifications showed excellent agreement at 85–96%, including high agreement and large number of returns in under canopy locations. The lidar-derived fSCA observations generally showed earlier snow disappearance under the canopy than in open positions, which is consistent with relatively warm temperatures and greater longwave radiation. However, in contrast to expectations, areas with high solar exposure (i.e. high southwestness) exhibited higher fSCA under the canopy. Results indicated that the k factor (the ratio of under canopy fSCA to open fSCA) varied systematically with southwestness and elevation. Using this factor to correct the study domain fSCA indicated that the typical assumption that k = 1 could lead to an up to ~0.05 bias (in fSCA units) towards overestimation. However, within 10 and 100-m individual pixels the fSCA overprediction bias can be 25–30% for higher fSCA values. Although uncertainty would be reduced using higher snow-on lidar point densities, our method shows promise to improve the typical assumption that snow disappearance is identical in under the canopy and in the open (k = 1). Future applications of our lidar-based method at different sites with varying climate, topography and vegetation structure has the dual potential to expand understanding of snow-forest interactions in complex terrain and improve operational fSCA products.

This commentary explores the challenges and opportunities associated with a possible transition of Water Resources Research to a publication model where all articles are freely available upon publication (“Gold” open access). It provides a review of the status of open access publishing models, a summary of community input, and a path forward for AGU leadership. The decision to convert to open access is framed by a mix of finances and values. On the one hand, the challenge is to define who pays, and how, and what we can do to improve the affordability of publishing. On the other hand, the challenge is to increase the extent to which science is open and accessible. The next steps for the community include an incisive analysis of the financial feasibility of different cost models, and weighing the financial burden for open access against the desire to further advance open science.

Estimates of potential evaporation often neglect the effects of snow cover on evaporation process. Here, we present a definition of potential evaporation that explicitly accounts for landscapes that are partially covered by snow. We show that, in the presence of snowpack, our evaporation estimates differ from conventional methods that assume evaporation from a free water surface. Specifically, we find that conventional methods overestimate potential evaporation as well as aridity, taken as the ratio of atmospheric water demand to supply, in landscapes where snowfall is significant. With dwindling snow-cover, actual aridity increases, which could explain the reduction in streamflow with decreasing snowfall. We suggest that streamflow, and hence water availability, is more sensitive to temperature changes in colder than in warmer regions. Colder, snow-dominated regions are more likely to experience greater changes in water availability with warming, suggests an analysis that explicitly includes snow cover in potential evaporation estimates.

Stress on California’s salmon fisheries drives a need for effective temperature management in California’s Sacramento River. Shasta Dam has a temperature control device that enables manager...

Due to the complexity and heterogeneity inherent to the hydrologic cycle, the modeling of physical water processes has historically and inevitably been characterized by a broad spectrum of disciplines including data management, visualization, and statistical analyses. This is further complicated by the sub-disciplines within the water science community, where specific aspects of water processes are modeled independently with simplification and model boundary integration receiving little attention. This can hinder current and future research efforts to understand, explore, and advance water science. We developed the Virtual Watershed Platform to improve understanding of hydrologic processes and more generally streamline model-data integration and data integration with tools for data visualization, analysis, and management. Currently, four models have been developed as components and integrated into the overall platform, demonstrating data prepossessing (e.g. sub gridding), data interaction, model execution, and visualization capabilities. The developed data management technologies provide a suite of capabilities, enabling diverse computation capabilities, data storage capacity, connectivity, and accessibility. The developed Virtual Watershed Platform explored the use of virtual reality and 3d visualization for scientific experimentation and learning, provided web services for the transfer of data between models and centralized data storage, enabled the statistical distribution of hydrometeorological model input, and coupled models using multiple methods, both to each other and to a distributed data management and visualization system.

In intensively managed landscapes, interactions between surface (tillage) and subsurface (tile drainage) management with prevailing climate/weather alter landscape characteristics, transport pathways, and transformation rates of surface/subsurface water, soil/sediment, and particulate/dissolved nutrients. To capture the high spatial and temporal variability of constituent transport and residence times in the critical zone (between the bedrock and canopy) of these altered landscapes, both storm event and continuous measurements are needed. The Intensively Managed Landscapes Critical Zone Observatory (IML-CZO) is comprised of three highly characterized, well instrumented, and representative watersheds (i.e., Clear Creek, Iowa; Upper Sangamon River, Illinois; and Minnesota River, Minnesota). It is organized to quantify the heterogeneity in structure and dynamic response of critical zone processes to human activities in the context of the glacial and management (anthropogenic) legacies. Observations of water, sediment, and nutrients are made at nested points of the landscape in the vertical and lateral directions during and between storm events (i.e., continuously). The measurements and corresponding observational strategy are organized as follows. First, reference measurements from surface soil and deep core extractions, geophysical surveys, lidar, and hyperspectral data, which are common across all Critical Zone Observatories, are available. The reference measurements include continuous quantification of energy, water, solutes, and sediment fluxes. The reference measurements are complemented with event-based measurements unique to IML-CZO. These measurements include water table fluctuations, enrichment ratios, and roughness as well as bank erosion, hysteresis, sediment sources, and lake/floodplain sedimentation. The coupling of reference and event-based measurements support testing of the central hypothesis (i.e., system shifts from transformer to transporter in IML-CZO due to the interplay between management and weather/climate). Data collected since 2014 are available through a data repository and through the Geodashboard interface, which can be used for process-based model simulations.

The ability to detect and map invasive plants to the species level, both at high resolution and over large extents, is essential for their targeted management. Yet development of such remote sensing methodology is challenged by the spectral and structural similarities among many invasive and native plant species. We developed a multi-temporal classification approach that uses unoccupied aerial vehicles (UAV) imagery to map two invasive annual grasses to the species level, and to distinguish these from key functional types of native vegetation, based upon differences in plant phenology. For a case study area in the western Great Basin, USA, we intentionally over-sampled with frequent (n = 8) UAV flights over the growing season. Using this information we compared the importance of spectral variation at a given point in time (i.e., with and without near-infrared wavelengths), with spectral variation across multiple time periods. We found that differences in species phenology allowed for accurate classification of nine cover types, including the two annual grass species of interest, using just three dates of imagery that captured species-specific differences in the timing of active growth, seed head production, and senescence. Availability of near-infrared imagery proved less important than true-color RGB imagery collected at appropriate time periods. Thus, multi-temporal information provides a substitute for more extensive spectral information obtained from a single point in time. The substitution of temporal for spectral information is particularly well suited to UAV remote sensing, where the timing of image collection can be flexible. The datasets arising from our multi-temporal classification approach provide high-resolution information for modeling patterns of invasive plant spread, for quantifying plant invasion risk, and for early detection of novel plant invasions when patch sizes are still small. Widespread application and up-scaling of our approach requires advances in our ability to model the variability in phenology that occurs across years and over fine spatial scales, even within a single species.

Rain-fed farming is the primary livelihood of semi-arid west Africa. Changes in land cover have the potential to affect precipitation, the critical resource for production. Turbulent flux measurements from two eddy-covariance towers and additional observations from a dense network of small, wireless meteorological stations combine to relate land cover (savanna forest and agriculture) to evaporation in a small (3.5 km2) catchment in Burkina Faso, west Africa. We observe larger sensible and latent heat fluxes over the savanna forest in the headwater area relative to the agricultural section of the watershed all year. Higher fluxes above the savanna forest are attributed to the greater number of exposed rocks and trees and the higher productivity of the forest compared to rain-fed, hand-farmed agricultural fields. Vegetation cover and soil moisture are found to be primary controls of the evaporative fraction. Satellite-derived vegetation index (NDVI) and soil moisture are determined to be good predictors of evaporative fraction, as indicators of the physical basis of evaporation. Our measurements provide an estimator that can be used to derive evaporative fraction when only NDVI is available. Such large-scale estimates of evaporative fraction from remotely sensed data are valuable where ground-based measurements are lacking, which is the case across the African continent and many other semi-arid areas. Evaporative fraction estimates can be combined, for example, with sensible heat from measurements of temperature variance, to provide an estimate of evaporation when only minimal meteorological measurements are available in remote regions of the world. These findings reinforce local cultural beliefs of the importance of forest fragments for climate regulation and may provide support to local decision makers and rural farmers in the maintenance of the forest areas.

Distributed Acoustic Sensing: Principles and Case Studies; Washington, D.C., 9 December 2018

This study demonstrated a new method for mapping high resolution (spatial: 1 m, and temporal: 1 hour) soil moisture by assimilating distributed temperature sensing (DTS) observed soil temperatures at intermediate scales. In order to provide robust soil moisture and property estimates, we first proposed an adaptive particle batch smoother algorithm (APBS). In the APBS, a tuning factor, which can avoid severe particle weight degeneration, is automatically determined by maximizing the reliability of the soil temperature estimates of each batch window. A multiple truth synthetic test was used to demonstrate the APBS can robustly estimate soil moisture and properties using observed soil temperatures at two shallow depths. The APBS algorithm was then applied to DTS data along a 71 m transect, yielding an hourly soil moisture map with meter resolution. Results show the APBS can draw the prior guessed soil hydraulic and thermal properties significantly closer to the field measured reference values. The improved soil properties in turn remove the soil moisture biases between the prior guessed and reference soil moisture, which was particularly noticeable at depth above 20 cm. This high resolution soil moisture map demonstrates the potential of characterizing soil moisture temporal and spatial variability and reflects patterns consistent with previous studies conducted using intensive point scale soil moisture samples. The intermediate scale high spatial resolution soil moisture information derived from the DTS may facilitate remote sensing soil moisture product calibration and validation. In addition, the APBS algorithm proposed in this study would also be applicable to general hydrological data assimilation problems for robust model state and parameter estimation. This article is protected by copyright. All rights reserved.

Understanding the spatial and temporal characteristics of water flux into or out of shallow aquifers is imperative for water resources management and eco-environmental conservation. In this study, the spatial variability in the vertical specific fluxes and hydraulic conductivities in a streambed were evaluated by integrating distributed temperature sensing (DTS) data and vertical hydraulic gradients into an ensemble Kalman filter (EnKF) and smoother (EnKS) and an empirical thermal-mixing model. The formulation of the EnKF/EnKS assimilation scheme is based on a discretized 1D advection-conduction equation of heat transfer in the streambed. We first systematically tested a synthetic case and performed quantitative and statistical analyses to evaluate the performance of the assimilation schemes. Then a real-world case was evaluated to calculate assimilated specific flux. An initial estimate of the spatial distributions of the vertical hydraulic gradients was obtained from an empirical thermal-mixing model under steady-state conditions using a constant vertical hydraulic conductivity. Then, this initial estimate was updated by repeatedly dividing the assimilated specific flux by estimates of the vertical hydraulic gradients to obtain a refined spatial distribution of vertical hydraulic gradients and vertical hydraulic conductivities. Our results indicate that optimal parameters can be derived with fewer iterations but greater simulation effort using the EnKS compared with the EnKF. For the field application in a stream segment of the Heihe River Basin in northwest China, the average vertical hydraulic conductivities in the streambed varied over three orders of magnitude (5 × 10−1 to 5 × 102 m/d). The specific fluxes ranged from near zero (qz

Author(s): Lucas, Ryan Geoffrey | Advisor(s): Conklin, Martha H | Abstract: We observed polymictic behavior in stream pools in a low gradient montane meadow in the southern Sierra Nevada Mountains, California. Thermal stratification in stream pools has been observed in various environments; stratification generally persists where the buoyancy forces created by a variation in water density, as a function of water temperature, are able to overcome turbulent forces resulting from stream flow. Because the density gradient creates a relatively weak buoyancy force, low flow conditions are generally required in order to overcome the turbulent forces. In some studies, a cold water source in to the pool bottoms can help to increase the density gradient and perpetuate thermal stratification. Our study took place in Long Meadow, Sequoia National Park, California. Long Meadow lies in the Wolverton Creek watershed and is part of the Southern Sierra Critical Zone Observatory. The 1-4 m diameter and 1-2 m deep pools in our study stratified thermally during the day and mixed completely at night. The low gradient of the meadow provided low stream flows. Piezometers in the meadow indicated groundwater discharge into the meadow in the months during which stratification was observed. Radon-222 activity measured in the pools also indicated groundwater influx to the pool bottoms. We used Fluent, a computational fluid dynamics equation solver, to construct a model of one of the observed pools. Initially we attempted to model the physical mechanisms controlling thermal stratification in the pool including stream flow, groundwater discharge, solar radiation, wind speed, and air, stream and ground water temperatures. Ultimately we found the model best agreed with our observed pool temperatures when we considered the light attenuation coefficients as a function of the dissolve organic carbon (DOC) concentration. Elevated DOC concentrations are expected in low stream flow regimes associated with highly organic soils such as a montane meadow. DOC concentrations measured in samples collected from the meadow stream, pools, and ground water wells ranged from 3.09 to 5.25 mg/L. We used a power equation taken from the literature to vary the visible light attenuation with DOC values measured in the meadow system. Light attenuation coefficients determined from measured DOC concentrations ranged from 0.507 m-1 to 0.899 m-1. Conditions consistent with the meadow environment--low gradient and stream flow, high solar loading, groundwater discharge, and high productivity--are such that thermal stratification of stream pools may be prolific. Understanding how these parameters influence thermal stratification of stream pools may allow investigators to appropriately assess thermal stratification when using large scale measurements, such as DTS or FLIR, and may help assess stream pool utilization by temperature sensitive species.

Snowmelt is a major source for summer soil water storage that supports tree growth in the Mediterranean climate of the Sierra Nevada, California. The timing and magnitude of snow-water contributions to soil moisture are controlled by energy and water availability that varies based on climate (and thus weather) and topography (i.e. elevation, slope, and aspect). Few studies, thus far, have explored how transpiration rate is affected by differences in the timing and magnitude of snowmelt across years and locations. Here we used meteorological and hydrological measurements on north and south aspects in the Sagehen Creek catchment (Sierra Nevada, California) to investigate the controls on the timing of conifer sap flow, a proxy for transpiration rate, in response to the timing and magnitude of snowmelt. We found that sap flow prior to its seasonal peak in July was largely controlled by air temperature and that spring sap flow was reduced by cloudy conditions. Years with earlier snow disappearance caused earlier peak sap flow, which was nearly coincident with the beginning of soil moisture limitations than years with later snow disappearance. Because Sagehen Creek receives little summer rainfall, years with earlier snowmelt and peak sap flow had more total days with soil moisture limitation on sap flow. Overall, our results suggest that earlier snow disappearance and more spring rain (both expected to result from climate change) will potentially shift the peak of sap flow earlier in the growing season and increase the duration of water limitations during summer. These insights about the timing and duration of water limitations could be used as benchmarks to test physically based models and better constrain predictions of transpiration rates in snow-dominated landscapes similar to the study site.

Desalination powered by renewable energy sources is an attractive solution to address the worldwide water-shortage problem without contributing significant to greenhouse gas emissions. A promising system for renewable energy desalination is the utilization of low-temperature direct contact membrane distillation (DCMD) driven by a thermal solar energy system, such as a salt-gradient solar pond (SGSP). This investigation presents the first experimental study of fresh water production in a coupled DCMD/SGSP system. The objectives of this work are to determine the experimental fresh water production rates and the energetic requirements of the different components of the system. From the laboratory results, it was found that the coupled DCMD/SGSP system treats approximately six times the water flow treated by a similar system that consisted of an air–gap membrane distillation unit driven by an SGSP. In terms of the energetic requirements, approximately 70% of the heat extracted from the SGSP was utilized to drive thermal desalination and the rest was lost in different locations of the system. In the membrane module, only half of the useful heat was actually used to transport water across the membrane and the remainder was lost by conduction in the membrane. It was also found that by reducing heat losses throughout the system would yield higher water fluxes, pointing out the need to improve the efficiency throughout the DCMD/SGSP coupled system. Therefore, further investigation of membrane properties, insulation of the system, or optimal design of the solar pond must be addressed in the future.

Aquatic ecosystems of North American deserts are frequently very restricted in area and tend to harbour very specialized species endemic to their restricted habitats. Small changes in environmental conditions of these specialized forms may jeopardize their persistence. A notable example of endemic and specialized species that may have been influenced by slight changes in its habitat is the Devils Hole pupfish (Cyprinodon diabolis), which occurs only in a small pool ecosystem in the Mojave Desert of the Southwestern United States. In this study, we use a computational fluid dynamic (CFD) model to examine the physical effects of climate change and local groundwater management on Devils Hole and combine those results with a conceptual ecological model to consider the impacts of those changes on annual recruitment of C. diabolis. The CFD model predicts water temperatures as a response to climate and water level, and the ecological model is used to determine the timing of tipping points that may encourage or suppress the annual recruitment of C. diabolis. The combination of interdisciplinary modelling approaches offers a method to quantify and compare the suitability of habitat under a range of management and climate scenarios. Our results show that the influence of water level on peak temperatures in Devils Hole (and on the ecosystem's suitability for C. diabolis) is an order of magnitude greater than the influence of climate change. Copyright © 2015 John Wiley & Sons, Ltd.

With the green economy being promoted as a path to sustainable development and food security within the African continent, the influx of agricultural land is proliferating at a rapid pace often replacing natural savannah forests. Where agriculture is primarily rainfed, the possible adverse impacts of agricultural land influx on rainfall occurrences in water-limited areas such as West Africa warrant attention. Using field observations complemented by model calculations in southeastern Burkina Faso, the main causes of a 10-30% suppressed daytime rainfall recorded over agricultural fields when referenced to natural savannah forests are examined. Measurements and model runs reveal that the crossing of the mixed layer height and lifting condensation levels, a necessary condition for cloud formation and subsequent rainfall occurrence, was 30% more frequent above the natural savannah forest. This increase in crossing statistics was primarily explained by increases in measured sensible heat flux above the savannah forest rather than differences in lifting condensation heights.

We attack the problem of predicting nitrate concentrations in a stream by using a genetic algorithm to minimize the difference between observed and predicted concentrations on hydrologic nitrate concentration model based on a US Geological Survey collected data set. Nitrate plays a significant role in maintaining ecological balance in aquatic ecosystems and any advances in nitrate prediction accuracy will improve our understanding of the non-linear interplay between the factors that impact aquatic ecosystem health. We compare the genetic algorithm tuned model against the LOADEST estimation tool in current use by hydrologists, and against a random forest, generalized linear regression, decision tree, and gradient booted tree and show that the genetic algorithm does statistically significantly better. These results indicate that genetic algorithms are a viable approach to tuning such non-linear, hydrologic models.

With the effects of the dramatic western US drought still reverberating through the landscape, researchers gathered in advance of the 20th annual Lake Tahoe Summit to discuss western US water issues in the 21st century. This two-day workshop brought together ~40 researchers from universities and agencies (federal and state) to discuss the prospects that transformative new science and forecasting of western water can prepare policy makers and the public to anticipate a changing world. The discussion was motivated by the urgent need to improve knowledge of the resilience versus “brittleness” of western water supplies in the face of changing climate and large scale disturbances including wildfires, floods, droughts and urbanization. With much of the landscape of the west under federal and state management, increasing population growth in cities, and increasing industrial and agricultural demands for water, participants agreed that a bold integration of academic and agency intellectual power is needed. We concluded it is time for a western -focused, integrated research center to bring science and social science-based solutions to addressing water scarcity and resilience, spanning academic institutions and mission-oriented federal and state agencies. Such a center would bring state-of-the-art scientific, engineering and socio-economic findings to bear on critical water issues in context of public policy, planning, and socioeconomic trends. Western water, whether in the atmosphere, rivers or aquifers flows without regard to state or federal boundaries. Scientists, engineers and policy researchers must therefore also work across boundaries to ensure resiliency of water supplies and landscapes through the coming century.

Measuring basal melting of ice shelves is challenging and represents a critical component toward understanding ocean-ice interactions and climate change. In November 2011, moorings containing fiber-optic cables for distributed temperature sensing (DTS) were installed through the McMurdo Ice Shelf, Antarctica, (~200 m) and extending ~600 m into the ice shelf cavity. The high spatial resolution of DTS allows for transient monitoring of the thermal gradient within the ice shelf. The gradient near the ice-ocean interface is extrapolated to the in situ freezing temperature in order to continuously track the ice-ocean interface. Seasonal melt rates are calculated to be ~1.0 mm d−1 and 8.6 mm d−1, and maximum melting corresponds to the arrival of seasonal warm surface water in the ice shelf cavity between January and April. The development of continuous, surface-based techniques for measuring basal melting represents a significant advance in monitoring ice shelf stability and ice-ocean interactions.

The Devils Hole pupfish (Cyprinodon diabolis) is a federally listed endangered species living solely within the confines of Devils Hole, a geothermal pool ecosystem in the Mojave Desert of the American Southwest. This unique species has suffered a significant, yet unexplained, population decline in the past two decades, with a record low survey of 35 individuals in early 2013. The species survives on a highly variable seasonal input of nutrients and has evolved in a thermal regime lethal to other pupfish species. The short lifespan of the species (approximately 1 year) makes annual recruitment in Devils Hole critical to the persistence of the species, and elevated temperatures on the shallow shelf that comprises the optimal spawning habitat in the ecosystem can significantly reduce egg viability and increase larval mortality. Here we combine computational fluid dynamic modeling and ecological analysis to investigate the timing of thresholds in the seasonal cycles of food supply and temperature. Numerical results indicate a warming climate most impacts the heat loss from the water column, resulting in warming temperatures and reduced buoyancy-driven circulation. Observed climate change is shown to have already warmed the shallow shelf, and climate change by 2050 is shown to shorten the window of optimum conditions for recruitment by as much as 2 weeks. While there are many possible reasons for the precipitous decline of this species, the changing climate of the Mojave region is shown to produce thermal and nutrient conditions likely to reduce the success of annual recruitment of young C. diabolis in the future, leading to continued threats to the survival of this unique and enigmatic species.

Solar ponds are low-cost, large-scale solar collectors with integrated storage that can be used as an energy source in many thermal systems. Experimental solar pond investigations at smaller scales have proven to be useful when trying to understand how different factors affect the pond’s efficiency, but they do not necessarily represent the expected performance of large-scale solar ponds. Consequently, it is important to investigate how the results of small-scale solar pond experiments can be scaled up. In this work, we show how models based on laboratory-scale observations can be utilized to understand the expected performance of large-scale solar ponds. This paper presents an approach that combines high-resolution thermal observations with computational fluid dynamics to investigate how different physical processes affect solar pond performance at different scales. The main factors that result in differences between small- and large-scale solar pond performances are boundary effects, light radiation spectrum and intensity, and turbidity. Boundary effects (e.g., pond geometry, thermal insulation) reduce the energy that reaches the storage zone of small-scale solar ponds. Different types of lights result in different radiation spectrum and intensity, which affects the energy reaching the storage zone. Turbidity is typically not important in small-scale solar ponds subject to controlled environmental conditions. However, it is an important factor in outdoor solar ponds in which the pond is prone to particles that can deposit onto the water surface or become suspended in the gradient zone. In general, the combination of these factors results in less energy collected in small-scale solar ponds than in large-scale solar ponds, even though large-scale solar ponds are typically subject to more extreme environmental conditions. High-resolution thermal observations combined with numerical simulations to understand the expected performance of large-scale solar ponds seems to be a promising tool for improving both efficiency and operation of these solar energy systems.

This paper describes a new, environmentally friendly drilling technique for making short-and long-term access boreholes in shelf glaciers using lightweight drills. The new drilling technique was successfully developed for installation of small-diameter sensors under the Ross Ice Shelf through ~ 193 m thick ice at Windless Bight, McMurdo Ice Shelf, Antarctica. The two access boreholes were drilled and sensors installed in 110 working hours. The total weight of the drilling equipment including the power system and fuel is

Evaporation represents a significant challenge to the successful operation of solar ponds. In this work, the suppression of evaporative losses from a salt-gradient solar pond was investigated in the laboratory. Two floating element designs (floating discs and floating hemispheres) and a continuous cover were tested; all three covers/elements were non-opaque, which is unique from previous studies of evaporation suppression in ponds or pools where increasing temperature and heat content are not desired. It was found that floating discs were the most effective element; full (88%) coverage of the solar pond with the floating discs decreases the evaporation rate from 4.8 to 2.5 mm/day (47% decrease), increases the highest achieved temperature from 34 °C to 43 °C (26% increase), and increases heat content from 179 to 220 MJ (22% increase). As a result of reduced evaporative losses at the surface, the amount of heat lost to the atmosphere is also reduced, which results in lower conductive losses from the NCZ and the LCZ and hence, increased temperatures in the NCZ and LCZ. The magnitude of evaporation reduction observed in this work is important as it may enable solar pond operation in locations with limited water supply for replenishment. The increase in heat content allows more heat to be withdrawn from the pond for use in external applications, which significantly improves the thermal efficiencies of solar ponds.

[1] A 6 month temperature record collected below McMurdo Ice Shelf in 2011–2012 shows the temporal and spatial structure of the summertime warm water signal that penetrates beneath the ice shelf. The strength and duration of the warm water intrusion suggest an annual melt rate at Windless Bight of 0.71 m/yr. A Ross Sea numerical model demonstrates a seasonal warm water pathway leading from the west side of the Ross Sea Polynya (RSP) toward McMurdo Sound. The warm water enters McMurdo Sound, subducts beneath the ice shelf and causes accelerated summer melting. Temperature data were recorded using Distributed Temperature Sensing fiber optics, which gives a vertical temperature profile at a 1 m vertical resolution. This study constitutes one of the first successful implementations of this technology in Polar Regions.

The rhizosphere, the soil immediately surrounding roots, provides a critical bridge for water and nutrient uptake. The rhizosphere is influenced by various forms of root–soil interactions of which mechanical deformation due to root growth and its effects on the hydraulics of the rhizosphere are the least studied. In this work, we focus on developing new experimental and numerical tools to assess these changes. This study combines X-ray micro-tomography (XMT) with coupled numerical simulation of fluid and soil deformation in the rhizosphere. The study provides a new set of tools to mechanistically investigate root-induced rhizosphere compaction and its effect on root water uptake. The numerical simulator was tested on highly deformable soil to document its ability to handle a large degree of strain. Our experimental results indicate that measured rhizosphere compaction by roots via localized soil compaction increased the simulated water flow to the roots by 27 % as compared to an uncompacted fine-textured soil of low bulk density characteristic of seed beds or forest topsoils. This increased water flow primarily occurred due to local deformation of the soil aggregates as seen in the XMT images, which increased hydraulic conductivity of the soil. Further simulated root growth and deformation beyond that observed in the XMT images led to water uptake enhancement of ~50 % beyond that due to root diameter increase alone and demonstrated the positive benefits of root compaction in low density soils. The development of numerical models to quantify the coupling of root driven compaction and fluid flow provides new tools to improve the understanding of plant water uptake, nutrient availability and agricultural efficiency. This study demonstrated that plants, particularly during early growth in highly deformable low density soils, are involved in active mechanical management of their surroundings. These modeling approaches may now be used to quantify compaction and root growth impacts in a wide range of soils.

[1] Accurate estimates of water losses by evaporation from shallow water tables are important for hydrological, agricultural, and climatic purposes. An experiment was conducted in a weighing lysimeter to characterize the diurnal dynamics of evaporation under natural conditions. Sampling revealed a completely dry surface sand layer after 5 days of evaporation. Its thickness was

Devils Hole, a fracture in the carbonate aquifer underlying the Death Valley Regional Groundwater Flow system, is home to the only extant population of Devils Hole pupfish (Cyprinodon diabolis). Since 1995, the population of C. diabolis has shown an unexplained decline, and a number of hypotheses have been advanced to explain this. Here, we examine the thermal regime of Devils Hole and its influence on the pupfish population. We present a computational fluid dynamic (CFD) model of thermal convection on the shallow shelf of Devils Hole, which provides critical habitat for C. diabolis to spawn and forage for food. Driven by meteorological data collected at Devils Hole, the model is calibrated with temperature data recorded in the summer of 2010 and validated against temperatures observed on the shallow shelf between 1999 and 2001.The shallow shelf experiences both seasonal and diel variations in water temperature, and the model results reflect these changes. A sensitivity analysis shows that the water temperatures respond to relatively small changes in the ambient air temperature (on the order of 1 °C), and a review of local climate data shows that average annual air temperatures in the Mojave Desert have increased by up to 2 °C over the past 30 years. The CFD simulations and local climate data show that climate change may be partially responsible for the observed decline in the population of C. diabolis that began in 1995.

Monitoring of ice-shelf and sub-ice-shelf ocean temperatures represents an important component in understanding ice-sheet stability. Continuous monitoring is challenging due to difficult surface access, difficulties in penetrating the ice shelf, and the need for long-term operation of non-recoverable sensors. We aim to develop rapid lightweight drilling and near-continuous fiber-optic temperature-monitoring methods to meet these challenges. During November 2011, two instrumented moorings were installed within and below the McMurdo Ice Shelf (a sub-region of the Ross Ice Shelf, Antarctica) at Windless Bight. We used a combination of ice coring for the upper portion of each shelf borehole and hot-point drilling for penetration into the ocean. The boreholes provided temporary access to the ice-shelf cavity, into which distributed temperature sensing (DTS) fiber-optic cables and conventional pressure/temperature transducers were installed. The DTS moorings provided near-continuous (in time and depth) observations of ice and ocean temperatures to a depth of almost 800 m beneath the ice-shelf surface. Data received document the presence of near-freezing water throughout the cavity from November through January, followed by an influx of warmer water reaching ∼150 m beneath the ice-shelf base during February and March. The observations demonstrate prospects for achieving much higher spatial sampling of temperature than more conventional oceanographic moorings.

In shallow thermohaline-driven lakes it is important to measure temperature on fine spatial and temporal scales to detect stratification or different hydrodynamic regimes. Raman spectra distributed temperature sensing (DTS) is an approach available to provide high spatial and temporal temperature resolution. A vertical high-resolution DTS system was constructed to overcome the problems of typical methods used in the past, i.e., without disturbing the water column, and with resistance to corrosive environments. This paper describes a method to quantitatively assess accuracy, precision and other limitations of DTS systems to fully utilize the capacity of this technology, with a focus on vertical high-resolution to measure temperatures in shallow thermohaline environments. It also presents a new method to manually calibrate temperatures along the optical fiber achieving significant improved resolution. The vertical high-resolution DTS system is used to monitor the thermal behavior of a salt-gradient solar pond, which is an engineered shallow thermohaline system that allows collection and storage of solar energy for a long period of time. The vertical high-resolution DTS system monitors the temperature profile each 1.1 cm vertically and in time averages as small as 10 s. Temperature resolution as low as 0.035 °C is obtained when the data are collected at 5-min intervals.

A salt-gradient solar pond is a low-cost, large-scale solar collector with integrated storage that can be used as a source of energy in low-grade-heat thermal desalination systems. This work presents the thermal evolution of an experimental solar pond for both the maturation and heat extraction time periods. The temperature profile was measured every 1.1 cm using a vertical high-resolution distributed temperature sensing (DTS) system, with a temperature resolution of 0.04ºC. Temperatures of 34 and 45ºC were achieved in the bottom of the pond when the lights were on for 12 and 24 hours per day, respectively. Heat was extracted at a rate of 139 W from the solar pond, which corresponded to an efficiency of 29%. Stratification and mixing were clearly observed inside the solar pond using the vertical high-resolution DTS system.

Soil compaction represents one of the most ubiquitous environmental impacts of human development, decreasing bulk-scale soil porosity and hydraulic conductivity, thereby reducing soil productivity and fertility. At the aggregate-scale however, this study shows that natural root-induced compaction increases contact areas between aggregates, leading to an increase in unsaturated hydraulic conductivity of the soils adjacent to the roots. Contrary to intuition, water flow may therefore be locally enhanced due to root-induced compaction. This study investigates these processes by using recent advances in X-ray microtomography (XMT) imaging and numerical water flow modeling to show evolution in interaggregate contact and its implications for water flow between aggregates under partially saturated conditions. Numerical modeling showed that the effective hydraulic conductivity of a pair of aggregates undergoing uniaxial deformation increased following a nonlinear relationship as the interaggregate contact area increased due to increasing aggregate deformation. Numerical modeling using actual XMT images of aggregated soil around a root surrogate demonstrated how root-induced deformation increases unsaturated water flow toward the root, providing insight into the growth, function, and water uptake patterns of roots in natural soils.

Many desert soil profiles of the southwestern United States show substantial accumulations of nitrate beneath the active rooting zone. At present, the mechanisms and processes for such enrichment are not well understood. This study focuses on the role of availability of water (depth to groundwater), soil (C:N) and vegetation (root density) associated with vadose zone nitrate accumulation in mesic desert regions of Nevada. The field study was conducted at four locations in Spanish Spring Valley, Nevada under native vegetation (Artemesia tridentata, Chrysothamnus nauseosus or mixed) with varying groundwater depths. Soil samples were collected from shallow root zone (0–45 cm) and deep vadose zones and analysed for nitrate-nitrogen (NO3−-N), ammonium (NH4+-N) and chloride (Cl−). From the shallow root zone samples root densities and soil C:N were determined. Soil profiles developed under deep water table conditions showed an accumulation of NO3−-N (800 mg l−1) in the vadose zone, while very little nitrogen accumulation was found in presence of shallow groundwater location. Availability of water controlled vegetation (root growth) and soil C:N. We conclude that soil resources (water and organic carbon) and rare leaching events are the primary factors lead to accumulation of NO3−-N in this region.

The water content dynamics in the upper soil surface during evaporation is a key element in land–atmosphere exchanges. Previous experimental studies have suggested that the soil water content increases at the depth of 5 to 15 cm below the soil surface during evaporation, while the layer in the immediate vicinity of the soil surface is drying. In this study, the dynamics of water content profiles exposed to solar radiative forcing was monitored at a high temporal resolution using dielectric methods both in the presence and absence of evaporation. A 4-d comparison of reported moisture content in coarse sand in covered and uncovered buckets using a commercial dielectric-based probe (70 MHz ECH2O-5TE, Decagon Devices, Pullman, WA) and the standard 1-GHz time domain reflectometry method. Both sensors reported a positive correlation between temperature and water content in the 5- to 10-cm depth, most pronounced in the morning during heating and in the afternoon during cooling. Such positive correlation might have a physical origin induced by evaporation at the surface and redistribution due to liquid water fluxes resulting from the temperature-gradient dynamics within the sand profile at those depths. Our experimental data suggest that the combined effect of surface evaporation and temperature-gradient dynamics should be considered to analyze experimental soil water profiles. Additional effects related to the frequency of operation and to protocols for temperature compensation of the dielectric sensors may also affect the probes response during large temperature changes.

A fully coupled two-dimensional, numerical model that evaluates, for the first time, the effects of double-diffusive convection in the thermal performance and stability of a salt-gradient solar pond is presented. The inclusion of circulation in the upper and lower convective zone clearly shows that erosion of the non-convective zone occurs. Model results show that in a two-week period, the temperature in the bottom of the solar pond increased from 20 °C to approximately 52 °C and, even though the insulating layer is being eroded by double-diffusive convection, the solar pond remained stable. Results from previous models that neglect the effect of double-diffusive convection are shown to over-estimate the temperatures in the bottom of the solar pond. Incorporation of convective mixing is shown to have profound impacts on the overall stability of a solar pond, and demonstrates the need to actively manage the mixing and heat transfer to maintain stability and an insulating non-convective zone.

Evaporation from small reservoirs, wetlands, and lakes continues to be a theoretical and practical problem in surface hydrology and micrometeorology because atmospheric flows above such systems can rarely be approximated as stationary and planar-homogeneous with no mean subsidence (hereafter referred to as idealized flow state). Here, the turbulence statistics of temperature(T)and water vapor (q)most pertinent to lake evaporation measurementsover three water bodies differing in climate, thermal inertia and degree of advective conditions are explored. The three systems included Lac Le´man in Switzerland (high thermal inertia, near homogeneous conditions with no appreciable advection due to long upwind fetch), Eshkol reservoir in Israel (intermediate thermal inertia, frequent strong advective conditions) and Tilopozo wetland in Chile (low thermal inertia, frequent but moderate advection). The data analysis focused on how similarity constants for the flux-variance approach, CT/Cq, and relative transport efficiencies RwT/Rwq, are perturbed from unity with increased advection or the active role of temperature. When advection is small and thermal inertia is large, CT/Cq 1)primarily due to the active role of temperature, which is consistent with a large number of studies conducted over bare soil and vegetated surfaces. However, when advection is significantly large, then CT/Cq >1 (orRwT/Rwq < 1). When advection is moderate and thermal inertia is low, then CT/Cq �1. This latter equality, while consistent with Monin–Obukhov similarity theory (MOST), is due to the fact that advection tends to increase CT/Cq above unity while the active role of temperature tends to decrease CT/Cq below unity. A simplified scaling analysis derived from the scalar variance budget equation, explained qualitatively how advection could per¬turb MOST scaling (assumed to represent the idealized flow state).

Snowpack base temperatures vary during accumulation and diurnally. Their measurement provides insight into physical, biological and chemical processes occurring at the snow/soil interface. Recent advances in Raman-spectra instruments, which use the scattered light in a standard telecommunications fiber-optic cable to infer absolute temperature along the entire length of the fiber, offer a unique opportunity to obtain basal snow temperatures at resolutions of 1 m, 10 s and 0.1°C. Measurements along a 330 m fiber over 24 hours during late-spring snowmelt at Mammoth Mountain, California, USA, showed basal snow temperatures of 0 ± 0.2°C using 10 s averages. Where the fiber-optic cable traversed bare ground, surface temperatures approached 40°C during midday. The durability of the fiber optic was excellent; no major damage or breaks occurred through the winter of burial. Data from the Dry Creek experimental watershed in Idaho across a small stream valley showed little variability of temperature on the northeast-facing, snow-covered slope, but clearly showed melting patterns and the effects of solar heating on southwest-facing slopes. These proof-of-concept experiments show that the technology enables more detailed spatial and temporal coverage than traditional point measurements of temperature.

A prototype temperature-sensing pair of waders is introduced and tested. The water temperature at the streambed is interesting both for scientists studying the hyporheic zone and for, e.g., fishers spotting good fishing locations. A temperature sensor incorporated into waders worn by members of the public can give scientists an additional source of information on stream-water–groundwater interaction. A pair of waders was equipped with a thermistor and calibrated in the lab. Tests with both the waders and a reference thermometer in a deep polder ditch with a known localized groundwater contribution (i.e., boil) showed that the temperature-sensing waders are capable of identifying the boil location. However, the temperature-sensing waders showed a less pronounced response to changing water temperature compared to the reference thermometer, most likely due to the heat capacity of the person in the waders. This research showed that data from temperature-sensing waders worn by the public and shared with scientists can be used to decide where the most interesting places are to do more detailed and more expensive research.

First direct measurements of heat flux from Lake Whillans may explain abundance of subglacial lakes and ice streams in region., The geothermal heat flux is a critical thermal boundary condition that influences the melting, flow, and mass balance of ice sheets, but measurements of this parameter are difficult to make in ice-covered regions. We report the first direct measurement of geothermal heat flux into the base of the West Antarctic Ice Sheet (WAIS), below Subglacial Lake Whillans, determined from the thermal gradient and the thermal conductivity of sediment under the lake. The heat flux at this site is 285 ± 80 mW/m2, significantly higher than the continental and regional averages estimated for this site using regional geophysical and glaciological models. Independent temperature measurements in the ice indicate an upward heat flux through the WAIS of 105 ± 13 mW/m2. The difference between these heat flux values could contribute to basal melting and/or be advected from Subglacial Lake Whillans by flowing water. The high geothermal heat flux may help to explain why ice streams and subglacial lakes are so abundant and dynamic in this region.