Novel Ensemble Machine Learning Modeling Approach for Groundwater Potential Mapping in Parbhani District of Maharashtra, India
نویسندگان
چکیده
Groundwater is an essential source of water especially in arid and semi-arid regions the world. The demand for due to exponential increase population has created stresses on available groundwater resources. Further, climate change affected quantity globally. Many parts Indian cities are experiencing scarcity. Thus, assessment potential necessary sustainable utilization management We utilized a novel ensemble approach using artificial neural network multi-layer perceptron (ANN-MLP), random forest (RF), M5 prime (M5P) support vector machine regression (SMOReg) models assessing Parbhani district Maharashtra India. Ten site-specific influencing factors, elevation, slope, aspect, drainage density, rainfall, table depth, lineament land use cover, geomorphology, soil types, were integrated preparation zones. results revealed that largest area was found under moderate category GWP zone followed by poor, good, very good poor. Spatial distribution zones showed Poor GWPZs spread over north, central southern district. Very poor mostly north-western study calls policy implications conserve manage these parts. ensembled model proved be effective outcome may help stakeholders efficiently utilize devise suitable strategies its management. Other geographical find methodology adopted this assessment.
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ژورنال
عنوان ژورنال: Water
سال: 2023
ISSN: ['2073-4441']
DOI: https://doi.org/10.3390/w15030419