Identification of hotspots and cold-spots of groundwater potential using spatial statistics

IF 4.7 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies Pub Date : 2024-09-30 DOI:10.1016/j.ejrh.2024.101977

Tao Liu , Imran Ahmad , Mithas Ahmad Dar , Martina Zelenakova , Lema Misgan Gebrie , Teshome Kifle , Gashaw Sintayehu Angualie

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引用次数: 0

Abstract

Study region

The Guna-Tana landscape is located in Ethiopia. This landscape is seriously facing water scarcity problems, that’s why we studied this landscape and provided the hotspots of groundwater potential areas in this region.

Study focus

In this study the hotspots and cold-spots of groundwater potential at, 99, 95, and 90 % confidence levels has been deciphered. Using Gi-Bin values, four classes has been identified viz., 2–3 (highly favorable), 0–1 (fairly favorable), −2 to −1 (poorly favorable) and −3 (very poorly favorable). The hotspots was subjected to ordinary least squared (OLS) regression to understand the impact of chosen parameters (viz., geology, land-use, soil, rainfall, slope, and distance to rivers) towards groundwater potential.

New hydrological insights for the region

The absence of redundancy among the selected parameters was indicated by the VIF values of the parameters, which were determined to be less than 7.5. It was discovered that the Robust Probability (Robust_Pr) was statistically significant (p < 0.01). The OLS model appears to have captured the variability of exploratory variables, as evidenced by the decreased values of Akaike's Information Criterion (AICc). The Adjusted R-squared value of 0.9119 indicates that exploratory variables has successfully explained 91.19 % of the variance of the model.

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利用空间统计识别地下水潜力的热点和冷点

研究区域古纳-塔纳地貌位于埃塞俄比亚。该地貌正面临着严重的缺水问题，因此我们对该地貌进行了研究，并提供了该地区地下水潜力的热点区域。研究重点本研究破译了置信度分别为 99%、95% 和 90% 的地下水潜力热点和冷点。利用 Gi-Bin 值确定了四个等级，即 2-3（非常有利）、0-1（相当有利）、-2 至-1（不利）和-3（非常不利）。对热点地区进行了普通最小二乘法（OLS）回归，以了解所选参数（即地质、土地利用、土壤、降雨量、坡度和与河流的距离）对地下水潜力的影响。研究发现，稳健概率 (Robust_Pr) 在统计学上具有显著意义（p < 0.01）。从阿凯克信息准则（AICc）值的下降可以看出，OLS 模型似乎捕捉到了探索变量的变异性。调整 R 平方值为 0.9119，表明探索变量成功解释了模型中 91.19 % 的变异。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Hydrology-Regional Studies Earth and Planetary Sciences-Earth and Planetary Sciences (miscellaneous)

CiteScore

6.70

自引率

8.50%

发文量

284

审稿时长

60 days

期刊介绍： Journal of Hydrology: Regional Studies publishes original research papers enhancing the science of hydrology and aiming at region-specific problems, past and future conditions, analysis, review and solutions. The journal particularly welcomes research papers that deliver new insights into region-specific hydrological processes and responses to changing conditions, as well as contributions that incorporate interdisciplinarity and translational science.