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

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2017 Annual Report


Objectives
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.


Approach
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
This is the first report for this project which began in December of 2016. Please see the report for the previous project, 2036-61000-016-00D, “Integrated Field Scale Management Systems for the Use of Degraded Waters”, for additional information. Objective 1: Obtaining additional sensor information while conducting field electromagnetic induction (EMI) or electrical resistivity surveys for salinity mapping has the potential to increase mapping accuracy as well as providing additional information useful to manage irrigated lands. Two soils have been collected, one a loamy clay from the Westside of the San Joaquin Valley, California, and the other a sandy loam from Riverside, California. Several additional soils with a range of properties are still needed. Soil properties were measured including salinity, sodicity, clay content, aluminum, iron oxides, organic matter, and soil solution boron concentration, among others. Soils were equilibrated with various solutions covering a wide range of sodium adsorption ratio (SAR) from 0 to 40. Soils were sieved to remove particles greater than 50 microns (µm), air-dried and packed into shallow plastic trays. Elemental data was collected using a hand held X-ray fluorescence (XRF) unit. Preliminary data indicated that of the elements examined, strontium (Sr) content, may be a useful indicator as the loam soil had twice the values of the clay soil, likely related to feldspar content. Subsequent experiments with a large set of soils, will use XRF measurements of silicon (Si) to quantify sand content and evaluate the instrument sensitivity to detect chlorine (Cl), an indicator of salinity. Objective 2: Ground truth soil salinity data obtained from EMI surveys is needed to improve the current regional-scale model for mapping salinity in the root zone for the San Joaquin Valley and to validate the model. One hundred field sites were identified for Objective 2a.2 using the map of soil salinity for the west side of the San Joaquin Valley developed from research conducted in the previous project. The field sites were selected to provide a range of crops and soil properties, particularly salinity and texture. Fifteen sites were surveyed and sampled out of a minimum of 60 field sites to be finally surveyed. 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 540 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). Soil property data for the georeferenced soil samples were entered into a geographic information system (GIS) and maps were created for each property at each field site. This data set represents the initial collection of data needed to make the current regional-scale model of soil salinity for the west side of the San Joaquin Valley developed under the previous project more robust by adding data related to orchards and vineyards and to serve as a validation data set. Objective 3: Significant 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. In previous studies the effect of SAR values and pH on infiltration in combined rain-irrigation sequences was evaluated, but information on the direct impact of rainfall comparing rain irrigation systems to irrigation with no rainfall was lacking. The long-term (169 days) impact of irrigation water quality on infiltration was examined with waters of varying SAR from 0 to 13 at pH 7, compositions that would generally be regarded as suitable for irrigation and typical of wastewater and many ground waters. Experiments were conducted in outdoor containers under irrigation only and in a combined irrigation-rain management system, utilizing a rain simulator, in all cases allowing for drying between water applications. Reductions in infiltration were observed for all treatments where SAR was more than 0, with decreasing infiltration with increasing SAR. The infiltration rate for treatments at pH 8 was always less than the rate for pH 7 at comparable SAR values. The combined rain-irrigation treatments had a greater reduction in infiltration rate as compared to the irrigation only treatments throughout the experiment. Directly comparing relative rates at pH 7.0 and SAR 13, the infiltration rate with irrigation alone is approximately 50 percent greater than the rate with irrigation and rain. At pH= 8 and SAR= 13, the relative rates are approximately 3 times greater with irrigation as compared to irrigation and rain. Reductions in infiltration in the presence of rain became more critical at high SAR and pH. This new information is of special interest to growers in regions both with and without rain. In areas with rainfall, it suggests that if infiltration is limiting, amendments should be applied even if irrigation water is of very low SAR.


Accomplishments


Review Publications
Scudiero, E., Corwin, D.L., Anderson, R.G., Yemoto, K.K., Clary, W.A., Wang, Z., Skaggs, T.H. 2017. Remote sensing is a viable tool for mapping soil salinity in agricultural lands. California Agriculture. 1-8. doi: 10.3733/ca.2017a0009.
Ors, S., Suarez, D.L. 2017. Spinach biomass yield and physiological response to interactive salinity and water stress. Agricultural Water Management. 190:31-41. doi: 10.1016/j.agwat.2017.05.003.
Goldberg, S., Suarez, D.L. 2017. Effect of dissolved organic carbon in recycled wastewaters on boron adsorption by soils. Soil Science. 182(3):94-100. doi: 10.1097/SS.0000000000000199.
Suarez, D.L., Gonzalez Rubio, A. 2017. Effects of the dissolved organic carbon of treated municipal wastewater on soil infiltration as related to sodium adsorption ratio and pH. Soil Science Society of America Journal. 81(3):602-611. doi: 10.2136/sssaj2016.09.0310.
Scudiero, E., Skaggs, T.H., Corwin, D.L. 2017. Simplifying field-scale assessment of spatiotemporal changes of soil salinity. Science of the Total Environment. 587:273-281. doi: 10.1016/j.scitotenv.2017.02.136.