Investigation the effect of diffrent number of presence points, raster resolution and sample size scenarios on the groundwater potential map prediction using data mining model in Namroud catchment, Tehran

Document Type : Research Paper

Authors

1 Master Science Student, Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

2 Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

3 Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.

Abstract

In the present study, the potential map of groundwater springs was prepared using the famous and efficient Maxent model as a benchmark in Namroud catchment, Tehran province. In this study, the effect of three different scenarios on the number of presence points (100,500,800 springs), raster resolution (100,50,30) and sample size (10/90, 20/80, 30/70, 50/50) on the predicted map was evaluated. First, 18 factors affecting the emergence of springs including lithological formations, the distance from the fault, fault density, elevation classes, slope percentage, slope direction, slope length factor, curvature maps, the distance from the waterway, waterway density, the distance from the road, topographic moisture index, relative slope position, flow power index, soil texture, surface roughness index and land use cover were selected and their maps were prepared in the ArcGIS10.5 and SAGA systems. After the correlation test and classification of the effective layers, the percentage and frequency of groundwater potential in each class were obtained using the frequency ratio method, which calculates the exact weight of each class. The relative operating characteristic curve (ROC) was used to evaluate the performance of these models. The results showed that the combination of raster resolution scenarios: 30-number of points: 100-sample size: 90/20 with the highest AUC (0.953 in training phase and 0.927 in validation phase) has goodness-of-fit and prediction accuracy compared to the combinations of other scenarios. In addition, about 9.14% of the study area had high and very high potential for groundwater. Based on the combination of the best scenario, the factors of distance from the waterway, relative slope position, drainage density and topographic moisture index with values of 17.3, 14.2, 13.8 and 10.2%, respectively, are the main factors of spatial control in the study area influencing the spring occurrence.

Keywords

Main Subjects

Investigation the effect of diffrent number of presence points, raster resolution and sample size scenarios on the groundwater potential map prediction using data mining model in Namroud catchment, Tehran

EXTENDED ABSTRACT

 

Introduction

Groundwater is one of the most important sources of fresh water for humans. With the significant increase in agricultural, industrial and domestic activities in recent years, the need for quality water to meet growing needs has increased. In order to meet this growing demand, groundwater has a higher priority than surface water due to its low pollution potential and wide and balanced distribution. Groundwater is not an unlimited resource, so the planning of its consumption should be based on understanding the behavior of groundwater systems by ensuring its sustainable use. As the demand for fresh groundwater in the world is increasing, the mapping of potential groundwater source areas has become an important tool for the successful implementation of groundwater conservation and management programs.

 

Materials and Methods

In the present study, the potential map of groundwater springs was prepared using the famous and efficient Maxent model as a benchmark in Namroud catchment, Tehran province.

 

Results and discussion

In this study, the effect of three different scenarios on the number of presence points (100,500,800 springs), raster resolution (100,50,30) and sample size (10/90, 20/80, 30/70, 50/50) on the predicted map was evaluated. First, 18 factors affecting the emergence of springs including lithological formations, the distance from the fault, fault density, elevation classes, slope percentage, slope direction, slope length factor, curvature maps, the distance from the waterway, waterway density, the distance from the road, topographic moisture index, relative slope position, flow power index, soil texture, surface roughness index and land use cover were selected and their maps were prepared in the ArcGIS10.5 and SAGA systems. After the correlation test and classification of the effective layers, the percentage and frequency of groundwater potential in each class were obtained using the frequency ratio method, which calculates the exact weight of each class. The relative operating characteristic curve (ROC) was used to evaluate the performance of these models. The results showed that the combination of raster resolution scenarios: 30-number of points: 100-sample size: 90/20 with the highest AUC (0.953 in training phase and 0.927 in validation phase) has goodness-of-fit and prediction accuracy compared to the combinations of other scenarios. Then, this map is classified into five categories: very low, low, medium, high and very high. Based on the combination of the best scenario, the factors of distance from the stream, relative slope position, drainage density and topographic humidity index are respectively identified as the most important environmental factors affecting the spatial prediction of spring occurrence in the studied area. The results indicate that the factors affecting the determination of groundwater potential in different regions are different due to different climatic conditions, soil science, vegetation, etc.

 

Conclusion

In addition, about 9.14% of the study area had high and very high potential for groundwater. Based on the combination of the best scenario, the factors of distance from the waterway, relative slope position, drainage density and topographic moisture index with values of 17.3, 14.2, 13.8 and 10.2%, respectively, are the main factors of spatial control in the study area influencing the spring occurrence.

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Iranian Journal of Soil and Water Research
Volume 54, Issue 5
August 2023
Pages 713-736

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