Location: Sustainable Water Management Research
Project Number: 6066-13000-005-18-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Aug 1, 2018
End Date: Jul 31, 2022
This cooperative research will assess the integration of conservation and irrigation scheduling technologies to protect and enhance soil and water resources while addressing critical water needs of crop production under variable and adverse climate conditions and declining Mississippi River Alluvial Aquifer levels.
Research studies are established at or near the Delta Branch Experiment Station or on privately owned farms throughout the Mississippi Delta region to quantify the contribution of various conservation practices to conserve water, protect and enhance water quality, improve soil health, and improve profitability. Management practices potentially include irrigation technologies, conservation tillage, and cover crops. Research will be performed by combining field reconnaissance, detailed data collection, and computational modeling techniques. Soil moisture sensors and irrigation equipment will be installed to monitor and supply water needs of the crop. The contribution of land preparation methods and irrigation water management strategies on productivity, profitability, and water use efficiency will be assessed. Irrigation water management tools will be deployed and irrigation inflow monitored to supply crop water demand. Crop yield and management inputs will be quantified to obtain an economic analysis of the irrigation production system. Equipment will be installed in some studies to monitor water runoff. Soil physical properties relative to water movement will be evaluated. Qualitative assessment tools (P-Index and N-Index) will be developed, evaluated and/or enhanced to properly represent agricultural management and production conditions and scenarios in the Mississippi Delta. Quantitative assessment tools and models (i.e. APEX, APLE) will be adapted or enhanced to represent management and conservation practices (i.e. irrigation scheduling, tailwater recovery systems) and compared against existing monitored crop yield and water quality data from different scenarios.