The Effect of Observation Data Sampling Methods on Infiltration Areas by Maximum Entropy Model

Statistical modeling methods are based on multivariate regression methods and require the presence and absence location of data for the construction of the model. In most cases, there is no trustworthy absence data. Therefore, other methods that are based only on the presence of the phenomenon are used. Considering the importance of modeling - saving time and cost and the probable prediction of the process - in this paper three sampling methods, Bootstrap, cross-validation (CV) and subsampling, were investigated to estimate areas with groundwater recharge potential using the maximum entropy model in the Marboreh watershed. The information about percolation points in Marboreh watershed, which was gathered using the double ring method and soil sampling, included the location of the samples, soil texture, and percolation rate. Due to the extent of the catchment area and the cost of the sampling process, information from previous studies in the study area, which were gathered from the Regional Water Authority (RWALP) and Agricultural Research, Education and Promotion Organization of Lorestan province (AREPOLP), was also used. The ROC index was used validate model predictions. The validation index indicated that the bootstrap had the best performance (ROC=0.955%). The results showed that each factors in these three methods was somewhat different, which was more than other factors in the drainage density, land use and soil texture. Based on the results of performance index, there is a very slight difference between the three sampling methods, so that they can be differentiated in relation to their different strategies, and this difference in the outputs, is not related to the diversity of the phenomenon studied. In this paper, according to the results and assessments, the Bootstrap method is recommended for the modeling the groundwater recharge areas due to the small number of sampling data compared to the very large area of study. Due to the large extent of the study area, it is suggested that this simulation be performed for more precision at smaller extent large areas with further data to study similar studies. Despite the increase in the number of pixels of high infiltration areas in the Bootstrap sampling method, compared to the other two methods, the performance of the recharge zoning increased slightly.