Abstract
Dwarka River basin in Birbhum, West Bengal (India), is an agriculture-dominated area where groundwater plays a crucial role. The basin experiences seasonal water stress conditions with a scarcity of surface water. In the presented study, delineation of groundwater potential zones (GWPZs) is carried out using a geospatial multi-influencing factor technique. Geology, geomorphology, soil type, land use/land cover, rainfall, lineament and fault density, drainage density, slope, and elevation of the study area were considered for the delineation of GWPZs in the study area. About 9.3, 71.9 and 18.8% of the study area falls within good, moderate and poor groundwater potential zones, respectively. The potential groundwater yield data corroborate the outcome of the model, with maximum yield in the older floodplain and minimum yield in the hard-rock terrains in the western and south-western regions. Validation of the GWPZs using the yield of 148 wells shows very high accuracy of the model prediction, i.e., 89.1% on superimposition and 85.1 and 81.3% on success and prediction rates, respectively. Measurement of the seasonal water-table fluctuation with a multiplicative model of time series for predicting the short-term trend of the water table, followed by chi-square analysis between the predicted and observed water-table depth, indicates a trend of falling groundwater levels, with a 5% level of significance and a p-value of 0.233. The rainfall pattern for the last 3 years of the study shows a moderately positive correlation (R 2 = 0.308) with the average water-table depth in the study area.
Résumé
Le bassin de la Rivière Dwarka à Birbhum, au Bengale occidental (Inde), est. une zone dominée par l’agriculture où les eaux souterraines jouent un rôle crucial. Le bassin connaît des conditions de stress hydrique saisonnier avec une pénurie en eau de surface. Dans l’étude présentée, la délimitation des zones d’aquifères potentiels (ZAP) est. réalisée à l’aide d’une technique géospatiale multi-facteurs. La géologie, la géomorphologie, le type de sol, l’utilisation des terres et la couverture végétale, les précipitations, la densité de linéaments et de failles, la densité du drainage, la pente et l’élévation de la zone d’étude ont été pris en compte pour la délimitation des ZAP de la zone d’étude. Environ 9.3, 71.9 et 18.8% de la zone d’étude se situent dans des zones aquifères potentiels bonnes, modérées et faibles, respectivement. Les données de productivité des aquifères corroborent les résultats du modèle, avec une productivité maximale dans l’ancienne plaine d’inondation et une productivité minimum dans les terrains de socle dans les régions ouest et sud-ouest. La validation des ZAP en utilisant la productivité de 148 puits montre la très grande précision de la prévision du modèle, c’est.-à-dire 89.1% sur la surimposition et 85.1 et 81.3% sur les taux de succès et de prévision, respectivement. La mesure de la fluctuation saisonnière de la nappe phréatique à l’aide d’un modèle multiplicatif des séries chronologiques pour prédire la tendance à court terme du niveau piézométrique, suivie d’une analyse de chi carré entre les profondeurs prédites et observées, indique une tendance à la baisse des niveaux piézométriques, avec un niveau de signification de 5% et une valeur de p de 0.233. Le schéma de pluviométrie des trois dernières années de la zone d’étude montre une corrélation modérément positive (R 2 = 0.308) avec la profondeur moyenne de la nappe phréatique dans la zone d’étude.
Resumen
La cuenca del río Dwarka en Birbhum, Bengala Occidental (India), es un área dominada por la agricultura donde el agua subterránea desempeña un papel crucial. La cuenca experimenta condiciones estacionales de estrés hídrico con escasez de agua superficial. En el estudio presentado, la delimitación de las zonas potenciales de agua subterránea (GWPZs) se lleva a cabo utilizando una técnica geoespacial de criterios múltiples. Se consideraron la geología, la geomorfología, el tipo de suelo, el uso del suelo/cobertura del suelo, la precipitación, la densidad de lineamientos y fallas, la densidad de drenaje, la pendiente y la elevación del área de estudio para definir GWPZs en el área de estudio. Aproximadamente el 9.3, el 71.9 y el 18.8% del área de estudio se sitúa dentro de zonas potenciales de agua subterránea buena, moderada y pobre, respectivamente. Los datos potenciales del rendimiento del agua subterránea corroboran el resultado del modelo, con un rendimiento máximo en la planicie de inundación más antigua y un rendimiento mínimo en los terrenos de roca dura en las regiones occidental y suroeste. La validación de las GWPZ utilizando el rendimiento de 148 pozos muestra una precisión muy alta en la predicción del modelo, es decir, 89.1% en superposición y 85.1 y 81.3% en los índices de éxito y predicción, respectivamente. La medición de la fluctuación estacional del nivel freático con un modelo multiplicativo de series de tiempo para predecir la tendencia a corto plazo de la capa freática, seguida del análisis de chi cuadrado entre la profundidad pronosticada y observada, indica una tendencia a la profundización de los niveles freáticos, con un nivel de significación de 5% y un valor de p de 0.233. El patrón de lluvia de los últimos tres años del estudio muestra una correlación moderadamente positiva (R 2 = 0.308) con la profundidad promedio de la capa freática en el área de estudio.
摘要
(印度)西孟加拉邦比尔普姆地区的Dwarka河流域是一个农业占主导地位的地区,那里的地下水发挥着至关重要的作用。该流域地表水匮乏,常常出现季节性缺水压力。在本研究中,采用地质空间多重影响因子技术对地下水潜力带进行了描述。在描述该研究区地下水潜力带时考虑了地质、地貌、土壤类型、土地利用/土地覆盖、降雨、线性结构和断层密度、坡度及高程。研究区内大约9.3、71.9和18.8%的区域分别为为好、中等和差的地下水潜力带。潜在的地下水出水量数据证实了模型的结果,较老的洪水平原出水量最大,西部和西南地区的硬岩地势中出水量最小。利用148口井的出水量对地下水潜力带进行了验证,显示出模型预测非常精确,也就是说,重叠量为89.1%,成功和预测率为85.1和81.3%。用时间序列乘法模型测量季节性水位波动来预测水位的短期趋势,然后对预测和观测到的水位深度进行了卡方分析,结果表明地下水位有下降趋势,达5%, p-值为0.233。研究区最近三年的降雨模式显示出与平均水位深度呈适度正相关(R 2 = 0.308)。
Resumo
A bacia do Rio Dwarka em Birbhum, Bengala Ocidental (Índia), é uma área dominada por agricultura onde as águas subterrâneas exercem um papel crucial. A bacia vivencia condições de estresse hídrico sazonais com uma escassez de águas superficiais. No presente estudo, o delineamento de zonas potenciais para águas subterrâneas (ZPAS) é conduzido usando técnicas de fatores multinfluência. Geologia, geomorfologia, tipo de solo, uso e cobertura da terra, precipitação, lineamentos e densidade de fraturas, densidade de drenagem, declividade e elevação da área de estudo foram considerados no delineamento de ZPAS na área de estudo. Cerca de 9.3, 71.9 e 18.8% da área de estudo came dentro de bom, moderado e pobre potencial para águas subterrâneas, respectivamente. Dados sobre a produção potencial das águas subterrâneas corroboram as saídas do modelo, com uma produção máxima na planície de inundação mais antiga e produção mínima em terrenos cristalinos nas regiões oeste e sudoeste. A validação das ZPAS usando a produtividade de 148 poços mostrou uma predição do modelo altamente acurada, p. ex., 89.1% em superposição e 85.1 e 81.3% em taxas de sucesso e predição, respectivamente. A mensuração da flutuação sazonal do lençol freático com um modelo multiplicativo de séries temporais para prever a tendência de curto prazo do lençol freático, seguida da análise do qui-quadrado entre a profundidade do lençol freático previsto e observado, indica uma tendência de queda dos níveis de água subterrânea, com um nível de significância de 5% e um valor-p de 0.233. O padrão de precipitação nos últimos três anos do estudo mostra uma correlação positiva moderada (R 2 = 0.308) com a profundidade média do lençol freático na área de estudo.
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The author expresses his heartiest gratitude to the Department of Science and Technology (project No. SB/ES-687/2013 dated 11.11.2014), Government of India, for financial support to the project. The author would also like to thank the Central Ground Water Board, Survey of India, and Geological Survey of India for their help and support.
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Thapa, R., Gupta, S., Gupta, A. et al. Use of geospatial technology for delineating groundwater potential zones with an emphasis on water-table analysis in Dwarka River basin, Birbhum, India. Hydrogeol J 26, 899–922 (2018). https://doi.org/10.1007/s10040-017-1683-0
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DOI: https://doi.org/10.1007/s10040-017-1683-0