Groundwater recharge is an important impact of various water harvesting interventions. A direct consequence of increased groundwater recharge in an aquifer is a range of social and economic benefits accruing from it – through improved provisioning of drinking water, irrigation and other uses. One of the visible economic benefits is often through supplemental irrigation to crops and increase in cropping intensity. The question often arising is how much of the agrarian impact is normative, attributable to broader changes in the economy, environment and society; and how much of it can be attributed to the specific intervention of water harvesting resulting in groundwater recharge. Taking an example of river basin scale interventions by AKRSP (I) on decentralized water harvesting, we propose different methodological possibilities to overcome this problem. Since these different methods utilize varied data sets, approaches and assumptions, they potentially provide us an
opportunity to triangulate and arrive at ranges of attributable impacts. With increasing availability of remotely sensed images and public data sets, these methods are going to be easier to implement and could present viable alternatives to current methods for attributing impacts.
Groundwater recharge is an important impact of various water harvesting interventions. A direct consequence of increased groundwater recharge in an aquifer is a range of social and economic benefits accruing from it – through improved provisioning of drinking water, irrigation and other uses. One of the visible economic benefits is often through supplemental irrigation to crops and increase in cropping intensity. The question often arising is how much of the agrarian impact is normative, attributable to broader changes in the economy, environment and society; and how much of it can be attributed to the specific intervention of water harvesting resulting in groundwater recharge. Taking an example of river basin scale interventions by AKRSP (I) on decentralized water harvesting, we propose different methodological possibilities to overcome this problem. Since these different methods utilize varied data sets, approaches and assumptions, they potentially provide us an
opportunity to triangulate and arrive at ranges of attributable impacts. With increasing availability of remotely sensed images and public data sets, these methods are going to be easier to implement and could present viable alternatives to current methods for attributing impacts.
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