Optimizing Irrigation and Water Productivity for Maize Based on Soil Moisture Deficit and Crop Water Stress

초록

Erratic rainfall due to climate change in the Kenya’s Arid and Semi-Arid Lands, particularly Makueni County, threatens rain-fed maize production andfood security. This study explores deficit irrigation to optimize water use, aiming to improve water productivity, stabilize yields and enhance resilience,aligning with Sustainable Development Goals on water management and climate action. The Soil-Water-Atmosphere-Plant (SWAP) model is used forestimating soil moisture/transpiration and managing irrigation and drainage across diverse climatic and environmental contexts from 2013 to 2022. Wederived the Soil Moisture Deficit Index (SMDI) and Crop Water Stress Index CWSI to assess drought conditions and optimize irrigation schedules. Several numerical experiments were conducted to validate and test SWAP in balancing water use and productivity at the field-scale. The SMDI-basedirrigation interval (7-day) consistently outperformed in achieving water productivity up to 25.2 kg ha-1 mm-1 compared to the results(22.5 kg ha-1 mm-1) of CWSI. SMDI showed better crop yields and water savings, especially in the dry years, while CWSI performed better in thewetter years but consumed more water. The 7-day interval with SMDI offered the best balance between water efficiency and productivity. AlthoughSMDI requires advanced soil moisture monitoring, it proved more efficient than CWSI, which may be suitable for less-resourced areas.

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