Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 10/30/2009
Publication Date: 11/9/2009
Citation: Suarez, D.L. 2009. Modeling as a tool for management of saline soils and irrigation waters. Presented at international seminar entitled Agricultural Valorization of Saline Water, Treated Wastewater and Sludge held in Hammamet, Tunisia November 9-10, 2009. Meeting Abstract. Interpretive Summary:
Technical Abstract: Optimal management of saline soils and irrigation waters requires consideration of many interrelated factors including, climate, water applications and timing, water flow, plant water uptake, soil chemical reactions, plant response to salinity and solution composition, soil hydraulic properties and chemical factors relating to soil hydraulic properties. Models that consider these factors in a process based numerical code can potentially be used to evaluate management practices and strategies. We present here applications using the SWS model, a user friendly version of the UNSATCHEM research model. Among the model predictions shown are: 1) Reclamation of a saline sodic soil with gypsum application and leaching. In this instance alternative management practices include different water applications, depths of gypsum placement, and reclamation via organic manuring in a calcareous soil. 2) Soil and plant response to a multiyear crop rotation with salt tolerant and salt sensitive crops utilizing both fresh and saline waters. 3) Evaluation of use of high B containing water for irrigation, utilizing high and low leaching for different soil types. 4) Comparison of model versus FAO guidelines for plant response to salinity and drought. Model predictions result in management recommendations that are often not intuitive or evident by inspection of the input information. Current models are incomplete in the sense that not all the relevant processes and interactions are represented, thus in many instances the system response is still not well quantified. The models are very useful but application still requires evaluation of the predictions based on field or controlled environment experimentation.