Sensitivity analysis and mapping the potential groundwater vulnerability zones in Birbhum district, India: A comparative approach between vulnerability models

Abstract

The assessment of groundwater vulnerability is essential especially in developing areas, where agriculture is the main source of the population. In the present study, four different overlay and index method, namely, DRASTIC, modified DRASTIC, pesticide DRASTIC and modified pesticide DRASTIC are implemented with a view to identifying the most appropriate method that predicts the vulnerable zone to groundwater pollution. Sensitivity analysis reveals that net recharge is the most influential parameter of the vulnerability index. Cross comparison of model output shows the highest similarity of 97% is observed between drastic and modified drastic while the maximum difference in models prediction of 49% is observed between modified drastic and pesticide drastic. Reported nitrate concentrations in groundwater are considered for validation of model-generated final output map. The prediction power of the models are assessed using success and prediction rate method and it highlights DRASTIC model as the most suitable model with 89.69% and 84.54% of the area under area under the curve (AUC) for success and prediction rate respectively.

Spatial Prediction of Groundwater Potentiality Mapping Using Machine Learning Algorithms

“…This study area also falls under gneisses and associated rocks, older alluvium, and older alluvium with lateritic types of aquifer media. The older alluvium has moderate to high yield prospects, where older alluvium with laterite rocks has adverse or limited yield prospects within 100 to 700 gpd/ft 2 hydraulic conductivity in the study area (Nakhaei et al, 2015;Thapa et al, 2018).…”

Pemetaan Zona Kerentanan Air Tanah Di Pulau Bakalan, Kabupaten Banggai Kepulauan, Indonesia

“…Potensi perkembangan rongga, celah mapun saluran pada batuan yang terbentuk oleh pelarutan dapat mengakibatkan sumber polutan (sumber pencemar) masuk kedalam sistem airtanah (Ferreira et al, 2004;White et al, 2017). Sifat akuifer karst sangat permeabel dan rentan terhadap kontaminasi (Linggasari et al, 2019;Thapa et al, 2018;Vrba & Zaporozec, 1994).…”

“…Kelas dan nilai (R) parameter kerentanan air tanah terhadap pencemaran dengan metode DRASTIC Penentuan kelas kerentanan pencemaran airtanah dengan metode DRASTIC, mengacu pada pembagian kelas menurut Pacheco et al, (2015) dan Thapa et al, (2018). Pembagian kelas kerentanan airtanah tersebut, dibagi menjadi lima (5) kelas, yaitu sangat rendah, rendah, sedang, tinggi dan sangat tinggi dengan rentang nilai seperti pada Tabel 4.…”

“…Pendekatan rumus yang digunakan untuk menghitung nilai total dari indeks kerentanan(Aller et al, 1987b), seperti pada Persamaan 2. Kerentanan = DRDW + RRRW + ARAW + SRSW + TRTW + IRIW + CRCW........................... .................. (2) dimana: (R) : nilai untuk masing-masing parameter (W) : bobot untuk masing-masing parameter (D) : Depth to water / kedalaman muka airtanah (R) : Recharge/Imbuhan aAir (A) : Aquifer/jenis akufer (S) : Soil media/tekstur tanah (T) : Topography/kemiringan lereng, (I) : Impact of vadose zone media/jenis zona tak jenuh, (C): Conductivity hydraulic/konduktivitas hidraulis akuifer et al, (2015);Thapa et al, (2018)…”

Kajian Spasial Multi Kriteria DRASTIC Kerentanan Air tanah Pesisir Akuifer Batugamping di Tanjungbumi Madura

“…Seluruh nilai parameter di hitung jumlah total nilai yang sudah diberikan nilai pemberat atau bobot. Pendekatan rumus yang digunakan untuk perhitungan adalah perhitungan linier setiap parameter kerentanan (Febriarta dan Oktama, 2020;Thapa et al, 2018…”