Understanding Groundwater Storage Changes and Recharge in Rajasthan, India through Remote Sensing

Abstract

Abstract:Groundwater management practices need to take hydrogeology, the agro-climate and demand for groundwater into account. Since agroclimatic zones have already been demarcated by the Government of India, it would aid policy makers to understand the status of groundwater recharge and discharge in each agroclimatic zone. However, developing effective policies to manage groundwater at agroclimatic zone and state levels is constrained due to a paucity of temporal data and information. With the launch of the Gravity Recovery and Climate Experiment (GRACE) mission in 2002, it is now possible to obtain frequent data at broad spatial scales and use it to examine past trends in rain induced recharge and groundwater use. In this study, the GRACE data were used to estimate changes to monthly total water storage (TWS) and groundwater storage in different agroclimatic zones of Rajasthan, India. Furthermore, the long-term annual and seasonal groundwater storage trends in the state were estimated using the GRACE data and the trends were compared with those in rainfall data. The methodology based on GRACE data was found to be useful in detecting large scale trends in groundwater storage changes covering different agroclimatic zones. The analysis of data shows that groundwater storage trends depend on rainfall in previous years and, therefore, on the antecedent moisture conditions. Overall, the study indicates that if suitable groundwater recharge methods and sites are identified for the state, there is OPEN ACCESSWater 2015, 7 5548 potential to achieve more groundwater recharge than what is currently occurring and, thus, enhancing the availability of water for irrigated agriculture.

Quantifying temporal variations in water resources of a vulnerable middle eastern transboundary aquifer system

“…Variations in the GRACE‐derived TWS (TWS grace ) represent variations in one or more of the following reservoirs: snow/ice, surface water, soil moisture, groundwater, and wet biomass (e.g., Wahr, Molenaar, & Bryan, ). GRACE data have been extensively used to quantify aquifers recharge and depletion rates (Ahmed, Sultan, Yan, & Wahr, ; Ahmed et al, ; Ahmed et al, ; Al‐Zyoud, Rühaak, Forootan, & Sass, ; Castellazzi, Martel, Galloway, Longuevergne, & Rivera, ; Castle et al, ; Chinnasamy & Agoramoorthy, ; Chinnasamy, Maheshwari, & Prathapar, ; Chinnasamy & Sunde, ; Döll, Müller Schmied, Schuh, Portmann, & Eicker, ; Ellett, Walker, Western, & Rodell, ; Feng et al, ; Gonçalvès, Petersen, Deschamps, Hamelin, & Baba‐Sy, ; Huang, Pavlic, Rivera, Palombi, & Smerdon, ; Huang et al, ; Huo et al, ; Jiang, Ferreira, & Chen, ; Joodaki, Wahr, & Swenson, ; Lakshmi, ; Lenk, ; Li & Rodell, ; Long et al, ; Mohamed, Sultan, Ahmed, Yan, & Ahmed, ; Rodell, Velicogna, & Famiglietti, ; Tiwari, Wahr, & Swenson, ; Veit & Conrad, ; Voss et al, ; Wada et al, ; Wouters, Bonin, Chambers, Sasgen, & Wahr, ; Yosri, Abd‐Elmegeed, & Hassan, ).…”

“…Variations in the GRACE-derived TWS (TWS grace ) represent variations in one or more of the following reservoirs: snow/ice, surface water, soil moisture, groundwater, and wet biomass (e.g., Wahr, Molenaar, & Bryan, 1998). GRACE data have been extensively used to quantify aquifers recharge and depletion rates (Ahmed, Sultan, Yan, & Wahr, 2016;Ahmed et al, 2011;Ahmed et al, 2014;Al-Zyoud, Rühaak, Forootan, & Sass, 2015;Castellazzi, Martel, Galloway, Longuevergne, & Rivera, 2016;Castle et al, 2014;Chinnasamy & Agoramoorthy, 2015;Chinnasamy, Maheshwari, & Prathapar, 2015;Chinnasamy & Sunde, 2016;Döll, Müller Schmied, Schuh, Portmann, & Eicker, 2014;Ellett, Walker, Western, & Rodell, 2006;Feng et al, 2013;Gonçalvès, Petersen, Deschamps, Hamelin, & Baba-Sy, 2013;Huang, Pavlic, Rivera, Palombi, & Smerdon, 2016;Huang et al, 2015;Huo et al, 2016;Jiang, Ferreira, & Chen, 2016;Joodaki, Wahr, & Swenson, 2014;Lakshmi, 2016;Lenk, 2013;Li & Rodell, 2015;Long et al, 2016;Mohamed, Sultan, Ahmed, Yan, & Ahmed, 2016;Rodell, Velicogna, & Famiglietti, 2009;Tiwari, Wahr, & Swenson, 2009; Veit derived groundwater storage (GWS grace ) over the Saq aquifer system ( Figure 1) to explore the natural and anthropogenic drivers of these variations. The calculated GWS grace estimates were then correlated and validated against field measurements from 15 groundwater wells distributed across the Saq aquifer system ( Figure 1 The Saq aquifer system is characterized by a thick sedimentary succession of Cambrian sandstone that overly the crystalline basement rocks of the Red Sea hills.…”

Water Resources Management: Innovation and Challenges in a Changing World

“…The publication by Chinnasamy et al, Understanding Groundwater Storage Changes and Recharge in Rajasthan, India through Remote Sensing [8], provides a study of how temporal and spatial data collected using remote sensing platforms can be utilized innovatively to bridge current knowledge gaps in relation to groundwater resources. The importance of such approaches needs to be viewed from the fact that the management of groundwater resources needs to take into account, hydrogeology, the agro-climate and demand.…”

Community-based groundwater and ecosystem restoration in semi-arid north Rajasthan (3): Evidence from remote sensing

“…The potential of remote sensing (RS) for groundwater monitoring has been explored extensively over the past thirty or so years (Heilman and Moore, 1982;Meijerink, 1996;Edet et al, 1998;Rosenberry, 2000;Jin et al, 2007;Lv et al, 2012;Chinnasamy et al, 2015) and reviewed by Becker (2006) and Pérez Hoyos (2016). Becker's (2006) observation regarding the key constraint on RS application in groundwater studies remains true today: current space and airborne sensors have little capacity to penetrate the ground surface.…”

“…As a more recent alternative approach, the launch of the Gravity Recovery And Climate Experiment (GRACE) satellite mission in 2002 enables detection of changes in the gravitational field of the Earth, which is affected by the presence of large volumes of water. Chinnasamy et al (2015) used GRACE data to investigate groundwater storage and recharge within different agroclimatic zones in Rajasthan, India. Their methodology proved useful for detecting large-scale trends, but found trends were highly dependent on antecedent moisture conditions.…”