Impact of intensive groundwater exploitation on an unprotected covered karst aquifer: a case study in Kermanshah Province, western Iran

Abstract

Islam Abad region, located in the southwestern of Kermanshah Province, is a karst region where over-exploitation from the deep karst water resources has directly affected the water balance of the whole area. Using a combination of geophysical investigations and analysis of well log data and other relevant hydrogeological studies, we looked for the actual relationship between over-exploitation from deep-water wells, penetrated into the covered karst aquifer, and the drying out of some of the main karst springs throughout the study area. In total, 20 piezometric wells and 4 main karst springs have been chosen for groundwater monitoring network. By integrating GIS processing system and a classical water balance method together with hydrogeology and hydrogeochemical spatial maps, critical zones of human impacts on groundwater resources, made by water extraction for agricultural demand, were identified. Results show that water balance in the Islam Abad basin is in clear disequilibrium, since 2.15 mcm of water depletes from the main aquifers of the study area, annually. This volume of water shortage has resulted in a 7 m groundwater level decline in the last decade, which caused both drying out and reduction in discharge rate of some of the main karst springs throughout the study area. Depths of penetration of deep-water wells into the covered karst aquifer vary from 1 to 93 m. Hydrogeochemical evaluations, including ion relations and hydrogeochemical diagrams, show interactions between karst and alluvium aquifers. Results showed a broad connection between these two resources and, therefore any pressure on alluvium aquifer will affect the karst aquifer, especially by excessive deep-water wells drilling in mutual alluvial and covered karst aquifers

Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal

“…The interrelationship among factors classes (Fig. 3) and assigning of ranks to factor's sub-classes was established based on author's expertise as well as literature review (Kaliraj et al 2014;Senthil-Kumar and Shankar 2014;Dinesan et al 2015;Razandi et al 2015;Taheri et al 2015;Taheri et al 2016;Jothibasu and Anbazhagan 2016;Senanayake et al 2016;Thapa et al 2016;Zabihi et al 2016). Factors having major influence were marked as major effect and were assigned a weight of 1.0 whereas, minor influence were marked as a minor effect with a weight of 0.5 as shown in Table 1 (Magesh et al 2012).…”

“…Remote sensing and GIS technique facilitate time and cost effective, rapid assessment of groundwater resource, which otherwise through traditional method becomes very costly, laborious and time consuming work (Moore et al 1991;Krishnamurthy et al 2000;Jha et al 2010;Arkoprovo et al 2012;Hammouri et al 2012;Lee et al 2012a;Davoodi et al 2015). To delineate groundwater potential lineament and hydrogeomorphology, groundwater level decline and its impacts on regional subsidences and karst hazards, and groundwater vulnerability to pollution are applied by GIS-based approaches by several researchers (Nag 2005;Taheri et al 2015;Singh et al 2015;Taheri et al 2016). In delineation of groundwater potential zone various factors such as lineament, faults and hydrogeomorphology (Nag 2005;Senthil-Kumar and Shankar 2014;Singh et al 2014;Taheri et al 2015), rainfall, soil, lithology and soil texture (Magesh et al 2012), slope, elevation (Magesh et al 2011;Thomas et al 2012), drainage systems (Rassam et al 2008;Preeja et al 2011;Dabral et al 2013) and groundwater table distribution (Arkoprovo et al 2012) play a crucial role.…”

Sustainability of Underground Hydro-Technologies: From Ancient to Modern Times and toward the Future

“…Overusing groundwater resources to supply water, due to increasing demand of population especially in arid and semi-arid regions, results in deterioration of aquifers, as well as environmental issues including land degradation and water quality problems [73,[93][94][95]. Unfortunately, nowadays, most of the societies in arid and semi-arid regions tend to abandon the historic underground aqueducts, particularly in favor of modern technologies [96].…”

Sinkhole susceptibility mapping: A comparison between Bayes‐based machine learning algorithms

“…The AT map has been generated with the available borehole data and dividing the variable into six classes by the natural break method (Figure 3g). The relative spatial distribution of sinkholes and major faults, as well as some patterns like the elongation and alignment of some sinkholes, suggests that the cavities and the associated subsidence processes may be controlled by tectonic structures (Taheri, Taheri, & Parise, 2016). The DF map was produced with the faults depicted in the available 1:100,000 scale geological maps and categorizing the resulting values into six classes (Figure 3h).…”