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Leaching is an important aspect of irrigation water management, as it must be minimal to save available irrigation water resources, prevent shallow groundwater tables, and reduce nutrient loadings to the groundwater. However, at the same time, leaching should be sufficient to maintain root zone salinity levels below the threshold to prevent yield reduction. Therefore, monitoring leaching is the key component in evaluation and optimization of irrigation water management practices. Water balance (WB) is a common approach used to estimate leaching in agricultural fields and was applied in this study to assess field-scale leaching and the associated uncertainties for an almond orchard under drip and micro-sprinkler irrigation systems. In this study, we showed that change is soil water storage (ΔS) is highly influenced by the extent of monitoring depth, the location and number of monitoring points. Local measurement of WB parameters showed that leaching is highly variable across the field, thereby introducing considerable uncertainty on estimated leaching using WB approach. It was also shown that unknown input of water through fog interception added to the complexity of closing water balance at field scale.

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.

Large spatial and temporal variability in water flow and N transport dynamics poses significant challenges to accurately estimating N losses form orchards. A 2-yr study was conducted to explore nitrate (NO3−) leaching below the root zone of an almond [Prunus dulcis (Mill.) D. A. Webb] orchard. Temporal changes in water content, pore water NO3− concentrations and soil water potential were monitored within and below the root zone to a soil depth of 3 m at eight sites, which represented spatial variations in soil profiles within an almond orchard in California. Orchard monthly average NO3− concentrations below the root zone ranged from 225 to 710 mg L−1 with mean annual concentration of 468 and 333 mg L−1 for the 2014 and 2015 growing seasons, respectively. Despite the huge variability in pore water NO3− concentration between sites, the larger spatiotemporal scale N losses estimated at the annual orchard scale from surface N mass balance, vadose zone based water and N mass balance, flow calculations, and HYDRUS modeling were all on the same order of magnitude (80-240 kg N ha−1 y−1). All methods indicated that most of the N losses occur early in the growing season (February-May) when fertilizer is applied to wet soil profiles. Simple mass balance (i.e., N load applied minus N load removed) provided a good proxy of the annual N accumulation in the soil profile at the orchard scale. Reduction of N losses at the orchard scale would require alternative fertigation and irrigation practices to decrease the difference between the N load removed and the N load applied to orchards.

A 2-year study was conducted to explore the impact of current and alternative best management practices (BMPs) of irrigation and fertigation on nitrate (NO3-) leaching below the root zone. Using a fully randomized complete block design, three fertigation strategies were compared: current BMP with and without accounting for NO3--N in irrigation-water, and a high frequency fertigation treatment with low-N concentration applications. Temporal changes in water content, pore water NO3- concentrations and soil water potential were monitored within and below the root zone to a soil depth of 3 m at eight sites in an almond and a pistachio orchard. NO3- concentrations below the root zone ranged from

Accurate modeling of water and air flow in porous media requires the definition of the relevant hydraulic properties, namely, the water retention curve (WRC) and the relative hydraulic conductivity function (RHC), as well as the definition of the relative air permeability function (RAP). Capitalizing on the approach developed previously to represent the RHC, a new model allowing the prediction of RAP based on information resulting from the WRC is proposed. The power value ηa in the model is a decreasing exponential function of the coefficient of variation, ɛ, characterizing the pore size distribution of the porous medium, and derived from its WRC. The model was calibrated using data from 22 disturbed and undisturbed soil samples and was validated using data from eight soil types ranging from quartz sand to silty clay loam. The proposed model provided accurate prediction of the soil RAP and performed in some cases (sandy loam and silty clay loam soils) better than available alternative models.

Estimation of field spatial variability of tree actual evapotranspiration (ETa) in orchards is key when quantifying water and associated nutrient leaching at the field scale. Though ETa is often measured at the field scale, spatial variations between individual trees are likely due to local differences in soil water availability and canopy cover. It is therefore that we propose seeking a statistical relation between field ETa, tree midday stem water potential (MSWP), soil water storage (WS), and tree potential evapotranspiration (ETc) with relative tree canopy cover (Crel). Four years of soil and almond trees water status data were used to optimize an artificial neural network (ANN), to predict field scale ETa first, followed by downscaling to the individual tree scale. ANN's using two hidden neurons (11 parameters) proved to be the most accurate (RMSE=0.0246mm/h, R2=0.944), seemingly because adding more neurons generated overfitting of noise in the training dataset. Crel was the main source of variability of ETa, while MSWP was the controlling factor for the tree-scale relative ET. At a given soil WS, almond trees of the drip-irrigated block were less affected by root zone water stress than the fanjet micro-sprinklers block, likely because of soil textural differences between the two main experimental blocks. In wet conditions, the predicted tree ETa followed a normal distribution (with relative standard deviation of about 5%), which was close to the Crel distribution. However, standard deviation values increased (7.6% for the whole orchard) during periods of water stress.

The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate-change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.

The conventional tensiometer is among the most accurate devices for soil water matric potential measurements, as well as for estimations of soil water flux from soil water potential gradients. Uncertainties associated with conventional tensiometers such as caused by ambient temperature effects and the draining of the tensiometer tube, as well as their limitation for deep soil monitoring, has prevented their widespread use for vadose zone monitoring, despite their superior accuracy in general. We introduce an alternative tensiometer design that offers the accuracy of the conventional tensiometer, while minimizing the aforementioned uncertainties and limitations. The proposed alternative tensiometer largely eliminates temperature-induced diurnal fluctuations and uncertainties associated with draining of the tensiometer tube and removes the limitation in installation depth. In addition, the manufacturing costs of this alternative tensiometer design are close to those of the conventional tensiometer, while it is especially suited for monitoring of soil water potential gradients as required for soil water flux measurements.

The dual-probe heat-pulse (DPHP) method is attractive for measuring soil thermal properties and volumetric water content. The purpose of this study was to develop and test a DPHP sensor having rigid probes made from thickwalled stainless steel tubing (2.38-mm outside diameter). The probes of this sensor are much more resistant to deflection than those of conventional DPHP sensors, decreasing measurement error caused by probe deflection during insertion into the soil. Laboratory experiments were conducted across a wide range of saturation levels with glass beads and three soils of different textures. For inferring soil properties from the proposed sensor, we applied the recently developed identical cylindrical perfect conductors (ICPC) model instead of the infinite line source (ILS) model that is typically used. The ICPC model improves solution for heat transport through the probe-soil system by accounting for the heat capacity and radius of the probes. Our results show a root mean square error of 1.4% volumetric water content and elimination of the measurement bias typically encountered with DPHP measurements. We conclude that the improved sensor, in combination with the ICPC model, provides a general, soil-independent water content estimate that is especially suitable for field soil water content monitoring because of its robust design with rigid probes. Because of its simplicity and measurements independent of soil type, we propose the presented DPHP method as an excellent alternative to other available measurement techniques for soil water content.

Nitrate is often present in surface water, soil solution, and groundwater at undesirable or toxic levels. This study follows development of an in situ nitrate monitoring probe and examines its performance in the presence of potentially interfering ionic species and dissolved organic carbon (DOC). Ultraviolet (UV) absorption spectroscopy measurements of aqueous NO3− were obtained under conditions where prevalent ionic species (i.e., Na+, K+, Ca2+, Mg2+, NH4+, Zn2+, Cu2+ Mn2+, Fe2+, Fe3+, Al3+, Cl−H2PO4−, HPO42−, SO42−, and HCO3−) and DOC were present at maximum characteristic concentrations for a range of pH levels, allowing UV interference on NO3− concentrations from individual ions to be investigated. While most solutions did not show interference, Fe2+ ions and DOC absorbed ultraviolet light strongly in regions of the spectrum where NO3− also exhibited significant absorption. Natural water samples showed very low concentrations of Fe2+, which do not cause interference with nitrate measurements. A two-wavelength measurement scheme was adopted to correct for the potential interference of DOC in measurements of aqueous NO3−. A multivariate calibration is presented to account for possible interference from both DOC and other ions in solution. The application of the UV spectroscopy probe is especially useful for deep vadose zone measurements of nitrate, as typically DOC concentrations will exponentially decrease with depth, and ion interference will be low.

Background: Climate-smart agriculture (CSA) addresses the challenge of meeting the growing demand for food, fibre and fuel, despite the changing climate and fewer opportunities for agricultural expansion on additional lands. CSA focuses on contributing to economic development, poverty reduction and food security; maintaining and enhancing the productivity and resilience of natural and agricultural ecosystem functions, thus building natural capital; and reducing trade-offs involved in meeting these goals. Current gaps in knowledge, work within CSA, and agendas for interdisciplinary research and science-based actions identified at the 2013 Global Science Conference on Climate-Smart Agriculture (Davis, CA, USA) are described here within three themes: (1) farm and food systems, (2) landscape and regional issues and (3) institutional and policy aspects. The first two themes comprise crop physiology and genetics, mitigation and adaptation for livestock and agriculture, barriers to adoption of CSA practices, climate risk management and energy and biofuels (theme 1); and modelling adaptation and uncertainty, achieving multifunctionality, food and fishery systems, forest biodiversity and ecosystem services, rural migration from climate change and metrics (theme 2). Theme 3 comprises designing research that bridges disciplines, integrating stakeholder input to directly link science, action and governance. Outcomes: In addition to interdisciplinary research among these themes, imperatives include developing (1) models that include adaptation and transformation at either the farm or landscape level; (2) capacity approaches to examine multifunctional solutions for agronomic, ecological and socioeconomic challenges; (3) scenarios that are validated by direct evidence and metrics to support behaviours that foster resilience and natural capital; (4) reductions in the risk that can present formidable barriers for farmers during adoption of new technology and practices; and (5) an understanding of how climate affects the rural labour force, land tenure and cultural integrity, and thus the stability of food production. Effective work in CSA will involve stakeholders, address governance issues, examine uncertainties, incorporate social benefits with technological change, and establish climate finance within a green development framework. Here, the socioecological approach is intended to reduce development controversies associated with CSA and to identify technologies, policies and approaches leading to sustainable food production and consumption patterns in a changing climate.

Simultaneous scaling of soil water retention and hydraulic conductivity functions provides an effective means to characterize the heterogeneity and spatial variability of soil hydraulic properties in a given study area. The statistical significance of this approach largely depends on the number of soil samples collected. Unfortunately, direct measurement of the soil hydraulic functions is tedious, expensive and time consuming. Here we present a simple and cost-effective hybrid scaling approach that combines the use of ancillary information (e.g., particle-size distribution and soil bulk density) with direct measurements of saturated soil water content and saturated hydraulic conductivity. Our results demonstrate that the presented approach requires far fewer laboratory measurements than conventional scaling methods to adequately capture the spatial variability of soil hydraulic properties. © 2013. American Geophysical Union. All Rights Reserved.

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.

Low-cost, accurate soil water sensors combined with wireless communication in an internet of things (IoT) framework can be harnessed to enhance the benefits of precision irrigation. However, the accuracy of low-cost sensors (e.g., based on resistivity or capacitance) can be affected by many factors, including salinity, temperature, and soil structure. Recent developments in wireless sensor networks offer new possibilities for field-scale monitoring of soil water content (SWC) at high spatiotemporal scales, but to install many sensors in the network, the cost of the sensors must be low, and the mechanism of operation needs to be robust, simple, and consume low energy for the technology to be practically relevant. This study evaluated the performance of a resistivity-capacitance-based wireless sensor (Sensoterra BV, 1018LE Amsterdam, Netherlands) under different salinity levels, temperature, and soil types in a laboratory. The sensors were evaluated in glass beads, Oso Flaco sand, Columbia loam, and Yolo clay loam soils. A nonlinear relationship was exhibited between the sensor measured resistance (Ω) and volumetric soil water content ( θ ). The Ω-θ relationship differed by soil type and was affected by soil solution salinity. The sensor was extremely sensitive at higher water contents with high uncertainty, and insensitive at low soil water content accompanied by low uncertainty. The soil solution salinity effects on the Ω-θ relationship were found to be reduced from sand to sandy loam to clay loam. In clay soils, surface electrical conductivity ( EC s ) of soil particles had a more dominant effect on sensor performance compared to the effect of solution electrical conductivity ( EC w ). The effect of temperature on sensor performance was minimal, but sensor-to-sensor variability was substantial. The relationship between bulk electrical conductivity ( EC b ) and volumetric soil water content was also characterized in this study. The results of this study reveal that if the sensor is properly calibrated, this low-cost wireless soil water sensor has the potential of improving soil water monitoring for precision irrigation and other applications at high spatiotemporal scales, due to the ease of integration into IoT frameworks.

Although only representing 0.05% of global freshwater, or 0.001% of all global water, soil water supports all terrestrial biological life. Soil moisture behaviour in most models is constrained by hydraulic parameters that do not change. Here we argue that biological feedbacks from plants, macro-fauna and the microbiome influence soil structure, and thus the soil hydraulic parameters and the soil water content signals we observe. Incorporating biological feedbacks into soil hydrological models is therefore important for understanding environmental change and its impacts on ecosystems. We anticipate that environmental change will accelerate and modify soil hydraulic function. Increasingly, we understand the vital role that soil moisture exerts on the carbon cycle and other environmental threats such as heatwaves, droughts and floods, wildfires, regional precipitation patterns, disease regulation and infrastructure stability, in addition to agricultural production. Biological feedbacks may result in changes to soil hydraulic function that could be irreversible, resulting in alternative stable states (ASS) of soil moisture. To explore this, we need models that consider all the major feedbacks between soil properties and soil-plant-faunal-microbial-atmospheric processes, which is something we currently do not have. Therefore, a new direction is required to incorporate a dynamic description of soil structure and hydraulic property evolution into soil-plant-atmosphere, or land surface, models that consider feedbacks from land use and climate drivers of change, so as to better model ecosystem dynamics., (© 2019 John Wiley & Sons Ltd.)

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.

Human security has and will continue to rely on Earth's diverse soil resources. Yet we have now exploited the planet's most productive soils. Soil erosion greatly exceeds rates of production in many agricultural regions. Nitrogen produced by fossil fuel and geological reservoirs of other fertilizers are headed toward possible scarcity, increased cost, and/or geopolitical conflict. Climate change is accelerating the microbial release of greenhouse gases from soil organic matter and will likely play a large role in our near-term climate future. In this Review, we highlight challenges facing Earth's soil resources in the coming century. The direct and indirect response of soils to past and future human activities will play a major role in human prosperity and survival., (Copyright © 2015, American Association for the Advancement of Science.)

• Despite the importance of rhizosphere properties for water flow from soil to roots, there is limited quantitative information on the distribution of water in the rhizosphere of plants. • Here, we used neutron tomography to quantify and visualize the water content in the rhizosphere of the plant species chickpea (Cicer arietinum), white lupin (Lupinus albus), and maize (Zea mays) 12 d after planting. • We clearly observed increasing soil water contents (θ) towards the root surface for all three plant species, as opposed to the usual assumption of decreasing water content. This was true for tap roots and lateral roots of both upper and lower parts of the root system. Furthermore, water gradients around the lower part of the roots were smaller and extended further into bulk soil compared with the upper part, where the gradients in water content were steeper. • Incorporating the hydraulic conductivity and water retention parameters of the rhizosphere into our model, we could simulate the gradual changes of θ towards the root surface, in agreement with the observations. The modelling result suggests that roots in their rhizosphere may modify the hydraulic properties of soil in a way that improves uptake under dry conditions., (© 2011 The Authors. New Phytologist © 2011 New Phytologist Trust.)

Subsurface drip irrigation systems apply effluent from onsite wastewater systems in a more uniform manner at a lower rate than has been possible with other effluent dispersal methods. The effluent is dispersed in a biologically active part of the soil profile for optimal treatment and where the water and nutrients can be utilized by landscape plants. Container tests were performed to determine the fate of water and nitrogen compounds applied to packed loamy sand, sandy loam, and silt loam soils. Nitrogen removal rates measured in the container tests ranged from 63 to 95% despite relatively low levels of available carbon. A Hydrus 2D vadose zone model with nitrification and denitrification rate coefficients calculated as a function of soil moisture content fit the container test results reasonably well. Model results were sensitive to the denitrification rate moisture content function. Two-phase transport parameters were needed to model the preferential flow conditions in the finer soils. Applying the model to generic soil types, the greatest nitrogen losses (30 to 70%) were predicted for medium to fine texture soils and soils with restrictive layers or capillary breaks. The slow transport with subsurface drip irrigation enhanced total nitrogen losses and plant nitrogen uptake opportunity., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Increasing human appropriation of freshwater resources presents a tangible limit to the sustainability of cities, agriculture, and ecosystems in the western United States. Marc Reisner tackles this theme in his 1986 classic Cadillac Desert: The American West and Its Disappearing Water. Reisner's analysis paints a portrait of region-wide hydrologic dysfunction in the western United States, suggesting that the storage capacity of reservoirs will be impaired by sediment infilling, croplands will be rendered infertile by salt, and water scarcity will pit growing desert cities against agribusiness in the face of dwindling water resources. Here we evaluate these claims using the best available data and scientific tools. Our analysis provides strong scientific support for many of Reisner's claims, except the notion that reservoir storage is imminently threatened by sediment. More broadly, we estimate that the equivalent of nearly 76% of streamflow in the Cadillac Desert region is currently appropriated by humans, and this figure could rise to nearly 86% under a doubling of the region's population. Thus, Reisner's incisive journalism led him to the same conclusions as those rendered by copious data, modern scientific tools, and the application of a more genuine scientific method. We close with a prospectus for reclaiming freshwater sustainability in the Cadillac Desert, including a suite of recommendations for reducing region-wide human appropriation of streamflow to a target level of 60%.

The sustainability of irrigated agriculture in many arid and semiarid areas of the world is at risk because of a combination of several interrelated factors, including lack of fresh water, lack of drainage, the presence of high water tables, and salinization of soil and groundwater resources. Nowhere in the United States are these issues more apparent than in the San Joaquin Valley of California. A solid understanding of salinization processes at regional spatial and decadal time scales is required to evaluate the sustainability of irrigated agriculture. A hydro-salinity model was developed to integrate subsurface hydrology with reactive salt transport for a 1,400-km(2) study area in the San Joaquin Valley. The model was used to reconstruct historical changes in salt storage by irrigated agriculture over the past 60 years. We show that patterns in soil and groundwater salinity were caused by spatial variations in soil hydrology, the change from local groundwater to snowmelt water as the main irrigation water supply, and by occasional droughts. Gypsum dissolution was a critical component of the regional salt balance. Although results show that the total salt input and output were about equal for the past 20 years, the model also predicts salinization of the deeper aquifers, thereby questioning the sustainability of irrigated agriculture.