Evaluation of Surface Irrigation Management Scenarios and Their Impacts on System Performance Indicators Using SIRMOD: A Case Study of Kabutarabad, Isfahan

Introduction
Surface irrigation remains one of the most widely used irrigation methods in many developing countries. However, its relatively low performance, primarily caused by deep percolation losses and tailwater runoff, necessitates improved management strategies to enhance water productivity. In regions facing increasing water scarcity, climate variability, and recurrent droughts, optimizing surface irrigation systems has become a critical priority for sustainable agricultural production. Furrow irrigation, as a common surface irrigation method, can achieve acceptable performance when properly designed and managed. Key operational parameters such as inflow discharge, furrow length, and time of cutoff strongly influence infiltration dynamics, advance and recession behavior, and ultimately irrigation efficiency. However, field based evaluation of these parameters is often costly, time consuming, and operationally constrained. Consequently, simulation models such as SIRMOD provide a practical and reliable tool for analyzing hydraulic processes and evaluating management scenarios without extensive field experimentation. SIRMOD incorporates hydrodynamic, zero inertia, and kinematic wave approaches to simulate flow and infiltration processes and has been widely validated for furrow irrigation systems. Despite numerous studies employing SIRMOD, most have examined the effect of input variables in isolation, whereas real-world field conditions involve simultaneous changes in multiple parameters. Understanding the combined influence of inflow discharge, time of cutoff, and furrow length on irrigation performance indicators, including application efficiency (Ea), irrigation requirement efficiency (Er), deep percolation ratio (DPR), and tail water ratio (TWR), is therefore essential for identifying optimal management strategies. This study aims to evaluate the simultaneous effects of these parameters using SIRMOD and to determine the most effective combinations for improving water use efficiency under field conditions.
Materials and Methods
The study utilized field data from the Kabutarabad Research Station in Isfahan, Iran, previously reported by Salemi et al. (2022). Soil physical properties, hydraulic characteristics, and furrow geometry were employed as model inputs. The soil texture across the 0–60 cm depth was classified as silty clay loam, with bulk density ranging from 1.34 to 1.41 g/cm³ and field capacity between 34% and 36% (vol.). The baseline furrow characteristics included a length of 120 m, width of 0.6 m, slope of 0.002 m/m, and inflow discharge of 1.5 L/s. Infiltration parameters (K, a, f0) were incorporated based on the Kostiakov–Lewis equation. The hydrodynamic model of SIRMOD, which demonstrated the highest accuracy in predicting advance and recession times in the reference study, was selected for simulations. To assess sensitivity and performance, three key management variables of discharge (Q), cutoff time (Tco), and furrow length (L) were each increased and decreased by 20% relative to their baseline values. This yielded 26 combined scenarios in addition to the reference condition. For each scenario, SIRMOD simulated infiltration, runoff, and water distribution along the furrow. Performance indicators were calculated using standard equations: application efficiency (Ea); defined as the ratio of stored water to applied water; irrigation requirement efficiency (Er), defined as the ratio of stored water to soil moisture deficit; deep percolation ratio (DPR), defined as the ratio of deep percolation to applied water; and tailwater rati (TWR), defined as the ratio of runoff to applied water. Model accuracy was evaluated by comparing simulated and measured infiltration and runoff volumes. All simulations were performed under identical soil and hydraulic conditions to isolate the effects of management parameters.
Results and Discussion
Model validation demonstrated strong agreement between measured and simulated values, with relative errors of 6.55% for runoff, 2.22% for infiltrated water, and 0.68% for advance time, thereby confirming the suitability of the hydrodynamic model for simulating furrow irrigation processes. Scenario analysis revealed that reducing inflow discharge significantly decreased deep percolation ratio (DPR) and tailwater ratio (TWR) while increasing application efficiency (Ea), indicating improved water application uniformity and reduced losses. Conversely, increasing discharge led to higher runoff and deep percolation, reducing overall efficiency. Variations in furrow length showed that longer furrows reduced TWR and increased Ea due to extended opportunity time at downstream sections, whereas shorter furrows increased runoff and diminished efficiency. Among all parameters, Ea and TWR exhibited the greatest sensitivity to furrow length, while Er and DPR were most responsive to cutoff time. Cutoff time exerted the strongest influence on DPR and irrigation requirement efficiency (Er). Shortening the cutoff time minimized deep percolation and increased Ea; however, it reduced Er due to insufficient soil moisture replenishment in downstream portions of the furrow. In contrast, extending the cutoff time substantially increased DPR, indicating excessive infiltration beyond the root zone. The scenario combining reduced discharge, reduced cutoff time, and increased furrow length produced the highest Ea (86.2%) and lowest TWR (13.8%). Conversely, the highest DPR (95.8%) occurred when discharge was held constant while both furrow length and cutoff time were increased. Collectively, these findings underscore the nonlinear and interactive effects of management variables on irrigation performance, highlighting the necessity of integrated, multi‑parameter optimization strategies for improving water use efficiency in surface irrigation systems..
Conclusion
The study demonstrates that effective optimization of furrow irrigation performance cannot be achieved through isolated adjustments of individual management parameters; rather, it necessitates the simultaneous consideration of inflow discharge, cutoff time, and furrow length. The results clearly indicate that reducing inflow discharge and cutoff time while increasing furrow length can substantially improve application efficiency (Ea) and significantly reduce tailwater ratio (TWR). This improvement is primarily attributed to enhanced opportunity time distribution along the furrow, which promotes a more uniform infiltration pattern and minimizes both runoff and deep percolation losses. However, the findings also reveal important trade-offs among management variables. Excessively short cutoff times may result in insufficient soil moisture replenishment in downstream sections of the furrow, thereby reducing irrigation requirement efficiency and potentially inducing water stress within the root zone. Conversely, prolonged cutoff times markedly increase deep percolation losses, particularly in upstream areas, which in turn diminishes overall system performance and water productivity. These results underscore the critical need to balance applied water depth with crop root-zone moisture requirements in order to avoid both under- and over-irrigation conditions. The application of the SIRMOD simulation model proved to be highly effective for evaluating a wide range of management scenarios and identifying optimal combinations of design and operational parameters without the need for extensive, time-consuming field experiments. Based on the simulation outcomes, the study suggests that farmers and irrigation managers can improve water use efficiency by adopting moderate inflow rates, adjusting cutoff times according to advance and recession behavior, and selecting furrow lengths that provide sufficient opportunity time while minimizing runoff and deep percolation losses. Ultimately, integrating simulation‑based decision support tools like SIRMOD into routine irrigation management offers a cost‑effective and practical pathway toward sustainable water resource utilization in regions facing increasing water scarcity.