Environmental modelling of drip irrigation system using HYDRUS-2D program by studying the moisture distribution of surface and subsurface
Year: 2025
Type: article
Abstract: As competition for water demand increases in all life sections, the agricultural sector has observed a gradual decrease in water consumption. In order to sustain or enhance agricultural productivity, innovative irrigation methods, like surface and subsurface drip irrigation systems, enhance the efficiency of water utilization compared to conventional systems. Multiple models have been established to forecast the dimensions of moisture distribution, which have significance for constructing an efficient drip irrigation system. This study evaluates the performance of surface and subsurface drip irrigation systems using the HYDRUS-2D model to predict soil moisture distribution under varying conditions of time, emitter spacing, and emitter depth. The results indicate a high level of agreement between simulated and observed moisture distributions, demonstrating the reliability of HYDRUS-2D as a predictive tool for modeling soil water dynamics. The study demonstrates the effectiveness of HYDRUS-2D in simulating soil moisture distribution for surface and subsurface drip irrigation systems under varying conditions of time, emitter spacing, and depth. Subsurface irrigation at 20 cm depth showed the highest simulation accuracy, with RMSE as low as 0.008798 and R² up to 0.9839, particularly at shorter intervals. Closer emitter spacing (20 cm) provided more uniform moisture distribution, while increased spacing (40 cm) led to less consistent patterns. Emitters placed at 20 cm depth achieved the optimal balance between precision and efficiency by minimizing evaporation and effectively targeting the root zone. These findings underline the utility of HYDRUS-2D as a reliable tool for optimizing drip irrigation design, improving water-use efficiency, and supporting sustainable agricultural practices in water-scarce regions.
Source: Applied Chemical Engineering
Institution: Al-Qasim Green University
Language: English
Subfield: Soil Science
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4407209358