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Research Project: Management of Degraded Waters for Irrigation: Integrated Field-scale Systems using Multi-sensor Technology


2018 Annual Report

The overarching goal of this project is to integrate multi-sensor technology, knowledge of chemical and physical processes, and computer modeling of water, solute, and trace element transport into a water management system for optimal use of fresh, degraded, and recycled waters for irrigation with the following objectives. Objective 1: Develop a set of sensing technologies that measure soil and solution properties relevant to the use of low quality waters for irrigation, including salinity, sodicity, clay content, aluminum, iron oxides, organic matter, and soil solution boron concentration. Sensor technologies will include near-infrared (NIR), mid-infrared (MIR), and x-ray fluorescence (XRF) spectroscopy. Objective 2: Develop and evaluate an integrated system of tools for site-specific irrigation management to control soil salinity and related adverse conditions when using degraded waters. The integrated multiple-sensor system will combine the use of geospatial apparent soil electrical conductivity (ECa), y-ray spectrometry, and multi-spectral imagery. Subobjective 2a: Develop and evaluate an integrated multiple-sensor system (1) to delineate matric and osmotic stress patterns at field scale and (2) to enhance the robustness of regional-scale salinity assessment modeling. Subobjective 2b: Develop a set of integrated tools to diagnose and manage infiltration problems due to sodic conditions by modeling the chemical effects on infiltration reduction and quantifying soil sodicity.

Objective 1 Hypothesis: Portable near-infrared (NIR), mid-infrared (MIR) and x-ray fluorescence ( XRF) sensors can be calibrated in the lab to measure soil chemical properties, and used to observe changes in soil properties for management. Sensors will be tested under different soil conditions. Three portable sensors will be used: NIR, MIR, and XRF. Four experiments have been conceived. The 1st experiment evaluates in the lab the influence of texture, mineralogy, EC, pH, ESP, water content, and surface roughness on sensor measurements. Statistical relationships between properties and sensor will be quantified. The 2nd experiment looks at the sensors’ spectra and evaluates each sensor’s ability to identify soil properties of interest. The 3rd experiment evaluates the findings of experiments 1 and 2. The 4th experiment develops site-specific sensor calibrations for fields in Subobjective 2a. Objective 2a Hypothesis: A multi-sensor platform of y-ray and electromagnetic induction (EMI) combined with Landsat 7 multi-spectral imagery will improve the spatial delineation of salinity and texture to better identify field-scale matric and osmotic stress patterns. Spatial distribution of salinity and texture using EMI alone, EMI and y-ray in combination, and EMI and y-ray in combination with spectral imagery will be compared to ground-truth measurements. Sensor platform will be tested on 3 fields varying in texture, water content, salinity, sodicity, trace elements and parent material. An initial exploratory statistical analysis determines correlation coefficients between sensors and soil properties followed by a more extensive statistical analysis using spatial regression models. The goal is to enhance the robustness and credibility of the regional-scale salinity model developed at the US Salinity Lab by: (a) incorporation of orchards and vineyards into the model, (b) evaluation of a hybrid model that combines the annual integral approach with the multi-year approach, (c) validation of the model with an independent data set, and (d) establishment of the model’s temporal stability by comparing model prediction and measured data for the 1st & 5th years. Objective 2b Hypothesis: Long-term effects of irrigation and rainfall on the infiltration of water in soils at various SAR, pH, and EC will demonstrate a greater Na hazard than traditionally based short-term laboratory leaching studies. Experimental Design: Evaluate changes in infiltration over an 8-month period both under combined simulated rain and irrigation alone for a sandy loam soil, with irrigation treatments of 3 levels of pH and 5 levels of SAR (0, 2, 4, 6, 8, and 10). Soils will be prepared and irrigated or rain applied at a soil water potential of -50MPa. The calculated infiltration rates will be related to soil texture, and soil chemical conditions (EC, SAR, and pH).

Progress Report
Objective 1: Significant progress was made under this objective. Eight soils of varying texture and mineralogy were analyzed for texture and various soil chemical properties in the laboratory. They are to be used as standards in the evaluation of hand-held sensors which are then used in the field to predict chemical and physical information relevant to the mapping and management of saline soils. The measurement of chemical elements using a hand held portable x-ray fluorescence (PXRF) instrument was initiated. Using soils of known soil properties, the effect of water content and different soil textures, sodium adsorption ratio (SAR) and salinity on elemental composition without external calibration was evaluated. It was established that the sensor was affected by water content, with increased water content attenuating the signal for all elements. The instrument was relatively stable under low water content conditions, thus suitable for field application using surface soils. It was determined that chloride (Cl-) content could be semi-quantitatively determined to Cl- concentrations of 20 milliequivalents per liter (Cl- concentration expressed in the standard format of saturation extract). This information is of direct use to researchers working on remote sensing of salinity and is expected to improve field scale diagnosis. Collaboration with the University of California, Davis, Cooperative Extension and the seasonal hiring of limited appointments has helped to a limited extent to offset the lack of qualified technical support to conduct ECa-directed soil sampling surveys with EMI equipment, which are crucial to provide ground truth measures of salinity to improve regional-scale model development. Subsequently, 6 additional field sites have been surveyed and sampled. Soil samples were collected at 0.3 meters (m) depth increments to a depth of 1.2 m at 6-12 locations within each field site. All collected, 192 soil samples were sieved, ground, and analyzed for a range of soil properties known to influence crop yields in the San Juan Valley: electrical conductivity of the saturation extract (ECe), gravimetric water content, saturation percentage (SP), SAR, Cl-, and potential of hydrogen (pH) of the saturation extract (pHe). The 6 additional field sites combined with the 15 field sites from 2017 make up a database of 21 fields, which falls significantly short of the minimum of 60 fields needed to improve the robustness of the regional-scale model for mapping salinity in the San Joaquin Valley and to validate the model. Even though progress in obtaining field ECa-directed soil sampling data is behind schedule, the analysis of existing data collected from 21 fields in the SJV has provided insight into a problem that must be resolved to meet the goals of Objective 2. The complex 2-Dimensional and 3-Dimensional spatial patterns of soil salinity under micro-irrigation regimes was characterized. As the use of micro-irrigation systems expands in water scarce and drought prone agricultural areas such as the San Joaquin Valley, the ability to measure the complex 3-Dimensional salinity distribution patterns will be of paramount importance for salinity management. The ECa-directed soil sampling protocols used to measure soil salinity at field scale and to measure the salinity associated with pixels of satellite imagery were developed for fields under flood and sprinkler irrigation. The local-scale (less than 1 square meter (<1 m2) variation of salinity) is considerably less substantial for flood and sprinkler systems than for micro-irrigation systems. Current ECa-directed soil sampling protocols fail to develop a robust ECa-salinity calibration for micro-irrigation systems due to inherent soil sampling design inadequacies. Since improving the robustness of the regional-scale salinity model for the San Joaquin Valley depends on the incorporation of orchards and vineyards, which are almost completely under drip irrigation, the development of revised ECa-directed soil sampling protocols specific to micro-irrigation are essential to Sub-objective 2a. Over the past year sufficient spatial data was collected to confirm the source of the problem and how to correct it through additional soil sampling and improved sampling design based on 2-Dimensional salt transport modeling of drip irrigation and local-scale salinity distribution data from numerous field locations under drip irrigation. Subsequently, revised ECa-directed soil sampling protocols and guidelines specifically for fields under micro-irrigation have been developed. Results indicate that many of the 21 fields that have been assessed for salinity will need additional soil sampling, which will further delay reaching a goal of a minimum of 60 fields surveyed and sampled using ECa-directed soil sampling. An additional part of this sub-objective is the development and evaluation of a hybrid regional-scale salinity model that combines an annual integral approach with a multi-year approach. The combined use of integrated seasonal satellite data and multi-year data is designed to improve accuracy and temporal stability. Substantial progress has been made from an analysis of collected temporal satellite and ground data. The analysis combined a novel regional-scale soil salinity modeling approach using plant-performance metrics with multi-year satellite data, making the model more reliable and temporally stable than previous modeling approaches and increasing its potential for application to climate regimes outside the southwestern U.S. A manuscript was published on the findings. Sub-objective 2b: Considerable progress was made under this objective. Sustaining irrigated agriculture in arid and semi-arid regions will require the use of less fresh water and corresponding increases in alternative water supplies of lower quality. Experiments were conducted in outdoor containers under irrigation only and compared to irrigation and simulated rain sequences using a rain simulator. The irrigation water treatments consisted of several levels of SAR and pH. The data was statistically analyzed. Reductions were found in infiltration for all treatments with SAR above 0. Reductions in infiltration were also significantly greater in treatments where sequences of rain and irrigation were examined. Reductions in infiltration in the presence of rain became more critical at high SAR and pH. This information is of major interest to growers in regions where there is measurable rainfall, suggesting that, in order to maintain infiltration, amendments are recommended to be applied whenever SAR of the irrigation water is above 3. A draft of a manuscript detailing this experiment has been prepared.

1. Geophysical techniques for assessing soil salinity across multiple scales. Knowledge of salinity within a field or multiple fields is valuable information for producers to optimize local production while knowledge of salinity across hundreds of square miles is valuable to state-level policy and decision makers to assess the state-wide impacts changing weather patterns. However, developing maps of soil salinity at any scale are a technological challenge because soils are highly variable in their properties, especially salinity. The compendium of work by an ARS scientist in Riverside, California, has resulted in an integrated system to map soil salinity across multiple scales consisting of (1) a platform of ground and satellite sensors, (2) protocols and guidelines for mapping soil salinity, and (3) software for selecting sampling sites to calibrate sensors. The integrated system provides stakeholders with reliable, repeatable, and accurate maps of soil salinity for use in inventorying, monitoring, and managing salinity across multiple scales. Demonstrated real-world applications of this technology include maps of soil salinity from field to regional scale, soil quality assessment, modeling salt loads to tile drains for an irrigation district, delineating site-specific management units for irrigation and salinity management, monitoring the reclamation of saline-sodic soil, monitoring degraded water reuse impacts on soil, assessing the feasibility of biofuel production on marginally productive salt-affected soil, and monitoring the impact of climate change on soil salinity in the San Joaquin Valley. As a direct consequence of this accomplishment, reliable quantitative determinations of the reduction in agricultural revenues due to soil salinity are now possible.

2. Assessing climate change impacts on soil salinity development with proximal and satellite sensors. Changes in climate patterns have dramatically influenced some agricultural areas, such as the recent historic 5-year drought in California’s San Joaquin Valley (SJV) and the 20-year above average annual rainfall in the Red River Valley (RRV) of the Midwestern U.S. Inventorying and monitoring climate change impacts on salinity are crucial to evaluate the extent of the problem, to recognize trends, and to formulate irrigation and crop management strategies that will maintain the agricultural productivity of these areas. An ARS scientist in Riverside, California, and colleagues from Stanford University and the University of California, have combined ground and satellite sensors to assess soil salinity at multiple scales: field, landscape, and regional scales. This sensor technology was used to evaluate the impact climate change has on salinity development in the SJV and RRV and its implications on agricultural sustainability. Results indicate that salt-affected soils in the SJV have increased 22 percent from 1984 to 2013 while in the RRV from 1979 to 2007 there was an approximate 30 percent increase in agricultural land with high salinity. This serves as a warning flag for natural resource conservation specialists, producers, farm advisers, and cooperative extension specialists that increased leaching of salts and/or the selection of more salt tolerant crops may be needed if altered weather patterns continue in the SJV and RRV.

Review Publications
Corwin, D.L., Yemoto, K.K., Clary, W., Banuelos, G.S., Skaggs, T.H., Lesch, S.M., Scudiero, E. 2017. Evaluating oilseed biofuel production feasibility in California's San Joaquin Valley using geophysical and remote sensing techniques. Sensors. 17(10):2343.
Corwin, D.L., Yemoto, K.K. 2017. Salinity: Electrical conductivity and total dissolved solids. In: Nilsson, M., Hmielowski, T., editors. Methods of Soil Analysis. 2nd volume. Madison, WI:Soil Science Society of America. p. 1-16.
Corwin, D.L., Grattan, S.R. 2018. Are existing irrigation salinity leaching requirement guidelines overly conservative or obsolete? Journal of Irrigation and Drainage Engineering. 144(8):02518001.
Scudiero, E., Corwin, D.L., Anderson, R.G., Skaggs, T.H. 2016. Moving forward on remote sensing of soil salinity at regional scale. Frontiers in Environmental Science. 4:65.
Abbas, M., Ahmad, H.R., Corwin, D.L., Sabir, M., Ozturk, M. 2017. Influence of farmyard manure on retention and availability of nickel, zinc and lead in metal-contaminated calcareous loam soils. Journal of Environmental Engineering and Landscape Management. 25(3)289-296.
Whitney, K., Scudiero, E., El-Askary, H.M., Skaggs, T.H., Allali, M., Corwin, D.L. 2018. Validating the use of MODIS time series for salinity assessment over agricultural soils in California, USA. Ecological Indicators. 93:889-898.
Allred, B.J., Adamchuk, V.I., Viscarra Rossel, R.A., Doolittle, J., Freeland, R.S., Grote, K.R., Corwin, D.L. 2016. Geophysical methods. In: Lal, R. editor. Encylopedia of Soil Science. 3rd edition. New York, New York: CRC Press. Vol II:1004-1011.
Schiavon, M., Meihls, A., Leinauer, B., Suarez, D.L., Biard, J. 2017. Varying evapotranspiration and salinity level of irrigation water influence soil quality and performance of perennial ryegrass (lolium perenne l.). Urban Forestry and Urban Greening. 26:184-190.