An extension to the DRASTIC model to assess groundwater vulnerability to pollution: application to the Haouz aquifer of Marrakech (Morocco)

Sinan, Mohamed; Razack, Moumtaz

doi:10.1007/s00254-008-1304-2

Cited by 59 publications

(26 citation statements)

References 14 publications

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“…The availability of freshwater along the coastal area plays an important role in human survival and socioeconomic developments, and it needs to be protected from increasing threats of aquifer contamination (Lake et al 2003;Chae et al 2004;Mohammadi et al 2012). The monitoring and characterization of groundwater quality and quantity of an aquifer along the Indian coast is a prerequisite for efficient and sustainable groundwater resource management (Singh and Gupta 1986;Sinan and Razack 2009;Srinivasamoorthy et al 2011;Krishna Kumar et al 2012a, b;Sarath Prasanth et al 2012;Selvakumar et al 2012;Chandrasekar et al 2013;Krishna Kumar et al 2014). Xiaahu (2008) has pointed out that the hydrochemical properties of the groundwater depend on the processes of mixing of fresh water with relict saline water, ion-exchange processes, silicate weathering, and evaporation.…”

Section: Introductionmentioning

confidence: 99%

Mapping of coastal aquifer vulnerable zone in the south west coast of Kanyakumari, South India, using GIS-based DRASTIC model

Kaliraj

Chandrasekar

Peter

et al. 2014

Environ Monit Assess

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The south west coast of Kanyakumari district in Tamil Nadu, India, is significantly affected by seawater intrusion and diffusion of pollutants into the aquifers due to unregulated beach placer mining and other anthropogenic activities. The present study investigates the vulnerability of the coastal aquifers using Geographic Information System (GIS)-based DRASTIC model. The seven DRASTIC parameters have been analyzed using the statistical equation of this model to demarcate the vulnerable zones for aquifer contamination. The vulnerability index map is prepared from the weighted spatial parameters, and an accounting of total index value ranged from 85 to 213. Based on the categorization of vulnerability classes, the high vulnerable zones are found near the beach placer mining areas between Manavalakurichi and Kodimanal coastal stretches. The aquifers associated with settlements and agricultural lands in the middle-eastern part have experienced high vulnerability due to contaminated water bodies. Similarly, the coastal areas of Thengapattinam and Manakudi estuary and around the South Tamaraikulam have also been falling under high vulnerability condition due to backwater and saltpan. In general, the nearshore region except the placer mining zone and the backwater has a moderately vulnerable condition, and the vulnerability index values range from 149 to180. Significantly, the northern and northeastern uplands and some parts of deposition zones in the middle-south coast have been identified as low to no vulnerable conditions. They are structurally controlled by various geological features such as charnockite, garnet biotite gneiss and granites, and sand dunes, respectively. The aquifer vulnerability assessment has been cross-verified by geochemical indicators such as total dissolved solids (TDS), Cl(-), HCO₃(-), and Cl(-)/HCO₃(-) ratio. The high ranges of TDS (1,842--3,736 mg/l) and Cl(-) (1,412--2,112 mg/l) values are well correlated with the observed high vulnerable zones in the study area. The Cl(-)/HCO₃(-) ratio (7.13 to 12.18) of the high vulnerable zone obviously indicates deterioration of the aquifer contamination. Sensitivity analysis has also been performed to evaluate sensitivity of the individual DRASTIC parameters to aquifer vulnerability. This reveals the net recharge rate and groundwater table depth are becoming more sensitive to aquifer contamination. It is realized that the GIS is an effective platform for aquifer vulnerability mapping with reliable accuracy, and hence, the study is more useful for sustainable water resource management and the aquifer conservation.

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Section: Introductionmentioning

confidence: 99%

Mapping of coastal aquifer vulnerable zone in the south west coast of Kanyakumari, South India, using GIS-based DRASTIC model

Kaliraj

Chandrasekar

Peter

et al. 2014

Environ Monit Assess

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“…These different methods for assessment of vulnerability have been implemented and extended to specific conditions in many countries (e.g. Sinan and Razack 2008), and all aim to assess the intrinsic geological aquifer vulnerability.…”

Section: Introductionmentioning

confidence: 99%

Nitrate vulnerability assessment of aquifers

et al. 2016

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Protection of groundwater against nitrate has a high priority in a country like Denmark with intensive agricultural production and with drinking water production based on groundwater. This paper presents a Site-specific Concept for Aquifer Nitrate Vulnerability Assessment (SCANVA) aimed at protecting groundwater resources. SCANVA is a qualitative dynamic concept adjusted to the specific study area depending on the hydrogeological and geochemical conditions. It comprises a synthesis of very detailed site-specific geological, geophysical, hydrogeological and chemical data, and a definition of nitrate vulnerability founded on redox conditions in the ground. Data are used to interpret the geological architecture of the subsurface, the groundwater flow and the geochemical groundwater conditions. These interpretations are integrated to assess nitrate vulnerability of the aquifers in three dimensions and identifying nitrate-vulnerable zones. The paper demonstrates the practical use of the concept in a Danish intensive agricultural area with a glacially formed landscape. Glaciotectonic has led to a high geological heterogeneity and very complex composition of thrusted and folded layers, which to a large extent affect the nitrate vulnerability of the aquifers. SCANVA can be directly applied to specific hydrogeological conditions anywhere with intensive N loss from agriculture, a groundwaterbased drinking water supply, nitrate reduction in the ground and glacially dominated landscapes and deposits. Potentially, the concept might also be adapted to other specific substances, dominating geochemical processes, and geological settings.

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“…It transports the contaminant and water from soil surface to the aquifer. Soils with clay and silts increase travel time of pollutant (Sinan et al 2009). Digital soil map was prepared from soil maps obtained from the Tamil Nadu Public Works Department.…”

Section: Preparation Of Parameters Mapsmentioning

confidence: 99%

GIS-based assessment of aquifer vulnerability using DRASTIC Model: A case study on Kodaganar basin

et al. 2016

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Groundwater is vulnerable and more susceptible to contamination from various anthropogenic elements. Various steps are taken to measure the groundwater vulnerability for a sustainable groundwater development. The present study estimates the aquifer vulnerability by applying DRASTIC model in the Geographic Information System (GIS) environment. The DRASTIC model uses seven hydrological parameters which include depth to water level, net recharge, aquifer media, soil media, topography, the impact of vadose zone and hydraulic conductivity. DRASTIC index was calculated from DRASTIC model that ranged from 31 to 154. All these parameters characterize the hydrological setting for evaluating aquifer vulnerability. Sensitivity analyses have also been performed to determine the sensitivity of every individual DRASTIC parameter towards the aquifer vulnerability. Sensitivity analysis indicated that all the parameters have an almost similar influence on vulnerability index. Depth to water parameter inflicts larger impact on aquifer vulnerability followed by recharge, topography and soil Media. The whole of Kodaganar basin is classified into very low, low, moderate and high vulnerable zones. Nearly threefourth of the basin has very low and low vulnerability. Incorporating DRASTIC model in the GIS environment has proved efficient in handling large volumes of data and in determining the groundwater vulnerability.El agua subterránea es vulnerable y más susceptible a la contaminación de varios elementos antropogénicos. Se midió la vulnerabilidad del agua subterránea en varias etapas para establecer el desarrollo sustentable de la fuente acuífera. Este trabajo estima la vulnerabilidad del agua subterránea por la aplicación del método DRASTIC en el entorno del Sistema de Información Geográfica (GIS, en inglés). El método DRASTIC utiliza siete parámetros hidrológicos: profundidad del agua subterránea, recarga neta, litología del acuífero, tipo de suelo, topografía naturaleza de la zona no saturada y conductividad hidráulica del acuífero. El índice DRASTIC fue calculado a través de este método y que oscila entre 31 y 154 unidades. Estos parámetros caracterizan la configuración hidrológica para la evaluación de vulnerabilidad del acuífero. También se realizaron los análisis de susceptibilidad para determinar la respuesta de cada parámetro DRASTIC frente a la vulnerabilidad del agua subterránea. El análisis de susceptibilidad indicó que todos los parámetros tienen una influencia similar en el índice de vulnerabilidad. El parámetro de profundidad ocasiona un mayor impacto en el índice de vulnerabilidad, seguido por la recarga, la topografía y el tipo de suelo. Toda la cuenca de Kodaganar se clasifica en zonas de vulnerabilidad muy baja, baja, moderada y alta. La incorporación del método DRASTIC en el entorno GIS prueba la eficiencia en el manejo de grandes volúmenes de información y en la evaluación de vulnerabilidad de aguas subterráneas. ABSTRACT RESUMEN

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An extension to the DRASTIC model to assess groundwater vulnerability to pollution: application to the Haouz aquifer of Marrakech (Morocco)

Cited by 59 publications

References 14 publications

Mapping of coastal aquifer vulnerable zone in the south west coast of Kanyakumari, South India, using GIS-based DRASTIC model

Mapping of coastal aquifer vulnerable zone in the south west coast of Kanyakumari, South India, using GIS-based DRASTIC model

Nitrate vulnerability assessment of aquifers

GIS-based assessment of aquifer vulnerability using DRASTIC Model: A case study on Kodaganar basin

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