SIMULATING SOIL WATER MOVEMENT IN AUTOMATED DRIP-IRRIGATED OKRA FIELDS UNDER PLASTIC MULCH: A NUMERICAL PERSPECTIVE

Abstract

Agriculture, accounting for over 70% of global freshwater consumption, plays a pivotal role in worldwide water resource utilization, primarily driven by crop irrigation. However, the average irrigation efficiency stands at approximately 50-60%, necessitating improved strategies to optimize water usage. This issue is exacerbated by impending water shortages, with estimates projecting severe deficits in India by 2050. Given that water profoundly influences crop yields, ensuring adequate irrigation is essential. This study focuses on soil moisture monitoring, a key aspect of irrigation management, using various sensor technologies such as watermark sensors, tensiometers, and capacitance probes. The choice of sensors depends on factors like soil moisture range, cost, ease of use, and reliability.

The application of soil moisture data derived from granular matrix (GM) and dielectric sensors is explored as an economical irrigation decision-making tool. However, these sensors' performance is contingent upon diverse variables like soil type, weather conditions, root zone depth, salinity, and temperature. Calibration, installation procedures, and location specificity are also important considerations when selecting sensors. While traditional evapotranspiration-based irrigation scheduling methods exist, this study emphasizes a sensor-driven approach that directly measures soil moisture to determine irrigation timing.

Challenges arise when dealing with soils of varying textures, making precise moisture measurement difficult. Simulation models like HYDRUS-2D, designed to simulate water, heat, and solute movement in porous media, offer solutions. Such models aid in evaluating soil-crop-atmosphere water dynamics, enabling estimation of water stress-related parameters. However, their complexity derives from numerous variables and self-regulation processes.

This research investigates alternative irrigation systems, considering easily adoptable practices by farmers to address water scarcity issues. The study evaluates automated switching tensiometers, evapotranspiration-based irrigation, and standard schedule irrigation management, analyzing their effects on plant growth and yield parameters. Furthermore, the efficiency of the HYDRUS-2D model in estimating soil water content for developing effective irrigation systems is assessed. This study's findings hold significance for optimizing agricultural practices in the face of impending water scarcity and the need for sustainable water management.