چكيده لاتين :
Introduction Groundwater resources are the most important parts of the available freshwater to humans. Due to the uneven distribution of time and location of surface waters and the high potential of these waters pollution, demand for groundwater for drinking, agricultural and industrial purposes is increasing. Therefore, it can be noted that groundwater resources and groundwater recharge are very important and identification of groundwater infiltration zones is a key component in arid and semi-arid regions studies. One of the most important methods of groundwater study is the study of factors affecting this process such as lithology, lineaments and fault density, vegetation, drainage system density, precipitation, temperature, slope, aspect, elevation, effective landforms in infiltration, soil type, infiltration coefficient is a survey of geological and topographic maps using remote sensing tools with satellite data processing, geological mapping and topography. In this study, we evaluated the infiltration potential using the AHP, APLIS and Modified APLIS models in the Roein Esfarayen basin. The basin has an area of 127.8 km in the eastern Alborz Zone (Binalud-Aladagh Zone), where significant lithology variation is evident. This basin is a part of the Aladagh-Binalud earth-tectonic zone, due to its large and tectonics, which is hard-fisted, faulty, and friable, with a large or large reverse fault angle.
Methodology
Initially, according to various studies about the recharge of groundwater resources, the factors controlling nutrition in the study area include lithology, lineament and fault density, vegetation cover, drainage system density, elevation, precipitation, temperature, soil cover, slope, aspect, intensity of vegetation cover (NDVI), effective landforms in nutrition and correction factor have been evaluated. The abovementioned data are from geological maps of the Organization of Geology and Mineral Exploration of the country with a scale of 1: 100,000, topographic maps with a scale of 1: 25,000 mapping organizations, precipitation data and annual temperature of the Ministry of Energy, land use map of the Natural Resources Organization, Landsat satellite images The ETM + sensor is derived from frames with passes and rows of 161-034 for 2017 (at appropriate times without cloudy and dusty images) and analyzed in ArcGIS 10.4, ERDAS IMAGINE 9.1 and EXPERT CHOICE 11.0 software packages.
Results and discussion
After preparing thematic maps of different layers of information, it is necessary to combine them together to produce the final map. An important issue in integrating these layers is to determine the relative importance of each layer of information, which varies depending on the model used. In this study, three models of AHP, APLIS and modified APLIS were used.
In present study, a pair comparison method was used in the AHP model. By multiplying weights in the factor, then their summation was obtained in accordance with the following equation of the potential influence map. The map was then classified in five qualitative classes, from very low Infiltration potential to very high Infiltration potential.
RP = 0.444 * L + 0.080 * S + 0.056 * A + 0.122 * P + 0.203 * F + 0.023 * T + 0.049 * V + 0.023 * D
In which L is lithology, S is slope, A is aspect, P is precipitation, F is lineament density, T is temperature, V is vegetation, D is drainage network density and RP is recharge potential.
In APLIS model, according to the weights table, the different classes and the quantitative relationship developed by Andreo et al. (2008), the final Infiltration potential map was obtained. The map was then classified in five qualitative classes, from very low Infiltration potential to very high Infiltration potential.
R = (A + P + 3 * L + 2 * I + S) /0.9
In modified APLIS model, according to the weights table, the different classes and the quantitative relationship developed by Andrew et al. (2008), the final Infiltration potential map was obtained. The map was then classified in five qualitative classes, from very low infiltration potential to very high infiltration potential. Marin (2009) modified the APLIS method with the introduction of a new factor called correction factor (Fh), as well as the extension of the "Effective Feed Layers (I)" domain name and modified it to Modified-APLIS. With regard to this, the relationship between the apple model and the following was changed. Then, based on the weights table, different classes and modified quantitative relationship, the final map of infiltration potential was prepared and classified into five qualitative classes.
R = [(A + P + 3 * L + 2 * I + S) /0.9] * Fh
Conclusion
The results of the AHP model, with five classes of infiltration capacity, indicate that the area with low infiltration potential in the basin is negligible and close to zero. The infiltration potential of low, moderate, high and very high classes are, respectively 8.1%, 15.1%, 47.7% and 29.1%, and the high infiltration class has the highest area of the basin (about 50%). In the APLIS methods, the areas of very low, moderate, high and very high infiltration classes are 15.1%, 17.9%, 65.1% and 1.9%, respectively, and in the modified APLIS model, respectively 20.9, 1.0, 13, 63.4% and 1.5% of the basin area. In general, it can be noted that the modified APLIS model with the highest correlation coefficient (0.85) and then the AHP model (0.82), have the highest coefficient of identification of Infiltration potential in the region. However, all three models show an acceptable prediction of basin infiltration assessment. Highly influential areas in these three models are located on the central and eastern part of the basin, which, by comparing it with the geology of the area, mainly correspond of the mozdoran-Lar Formation, in which the purity of lime and dolomite is higher. Also, areas with high Infiltration Potential are consistent with low drainage areas.
