118 Simulating of Changes in Water Distribution Uniformity Coefficient in Classic Stationary Sprinkler Irrigation Using Data-Mining Models Fariborz Ahmadzadeh Kaleybar 1* | Shahram Shahmohammadi Kalalagh 2 | Sina Fard Moradinia 3 1 Department of Water Sciences and Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran - Sustainable Development Management Research Center of Urmia Lake and Aras River Basin, Tabriz Branch, Islamic Azad University, Tabriz, Iran 2 Department of Water Sciences and Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran 3 Department of Civil Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran Article Info ABSTRACT Article type: Research Article Article history: Received 04 Agust 2024 Received in revised form 31 October 2024 Accepted 10 Novamber 2024 Published online 29 January 2024 Keywords: Gene expression programming Malekan plain Sensitivity analysis Support vector machine Performanceevaluation Objective: The lack of water in the world and its heavy consumption in the crop irrigation sector makes it necessary to use different sciences to increase water efficiency. The coefficient of uniform water distribution in sprinkler irrigation systems is one of the important effective indicators in evaluating their performance. Only high values can justify implementing these systems. The purpose of this research is to use support vector machine (SVM) and gene expression programming (GEP) models to simulate the coefficient of uniform water distribution in the farm conditions of Malekan Plain in the northwest of Iran, placed in the catchment area of the Urmia lake is experiencing severe water stress. Methods: Field experiments were carried out on seven farms equipped with a classic stationary sprinkler irrigation system with a movable sprinkler (Komet 162, 163) with variables of sprinkler intervals on laterals and manifolds, operating pressure, and wind speed. Then, uniform distribution coefficient data were obtained. Two models (SVM) and (GEP) were used to simulate the value of the uniformity coefficient. The sensitivity analysis showed that all three variables should be selected as model inputs. 70% and 30% of data were considered for the share of training and test processes, respectively. Using these data, the adjustment parameters of each model were calculated to reach the most optimal output. The evaluation of the performance of the models was done with four indicators: RMSE (sum of square mean error), MAE (mean absolute error), R2 (explanation coefficient), and DDR (developed difference ratio). Results: The first rank of simulation accuracy was assigned to the GEP model. The values of the indicators (RMSE, MAE, R 2 ) were obtained in the training and test steps, respectively (3.5087, 2.6827, 0.8634) and (1.1787, 0.9494, 0.9833) for GEP. The values of the evaluation indices (RMSE, MAE, R 2 ) for the most optimal SVM model in the test and training steps were obtained (4.8917, 4.2704, 0.7884) and (2.6790, 2.4113, 0.9185) respectively. In the training step, the value of CU(DDR(max)) for GEP and SVM models was calculated as 7.0540 and 5.2925 respectively. The value of this index in the test step for these two models was 20.8355 and 9.2863 respectively. The comparison of the value of this index also showed that the GEP model was more accurate than the SVM model. In general, both models can simulate the amount of water distribution uniformity in sprinkler irrigation in field conditions. However, using the GEP model will lead to better results. * Corresponding author, Email: f.ahmadzadeh@iaut.ac.ir Cite this article: Ahmadzadeh Kaleybar, F., Shahmohammadi Kalalagh, Sh., Fard Moradinia, S (2024). Simulating of Changes in Water Distribution Uniformity Coefficient in Classic Stationary Sprinkler Irrigation Using Data- Mining Models Journal of New Approaches in Water Engineering and Environment , © The Author(s). Publisher: Gonbad Kavous University. DOI: http//doi.org/10.22034/nawee.2024.471274.1100