Who regulates the regulators?
In the context of groundwater policy, who will keep an independent check on government data collection methods and analysis which informs groundwater policy decisions.
It would be nice if government scientist themselves keep refining their methods, but equally needed are independent researchers from Universities and research institutions. Rahul Gokhale and Milind Sohoni of IIT Bombay analyze Maharashtra statewide groundwater data collected over the past few decades by the government Groundwater Surveys and Development Agency. The Agency in October of each year puts out a report on the groundwater outlook for the upcoming dry season (until June of the following year). This report relies on measured groundwater levels from ~ 5000 wells and the State rainfall data. However, there is substantial variation in groundwater levels throughout the dry season and between years in most wells. By subjecting this data to statistical analysis and modelling study Gokhale and Sohoni conclude that aggregate rainfall data is a poor predictor of groundwater levels and that unmeasured factors like extraction patterns and land use influence groundwater availability. They point a way toward refining groundwater assessment methodology by incorporating local socio-economic and groundwater use data.
Now, on the face of it the finding seems somewhat banal, that groundwater levels and availability is controlled not just by rainfall patterns but other anthropogenic factors as well. However, it is important that someone dives into large government data sets and teases out these quantitative relationships between various interacting parameters. And it is good to see an Indian government agency share data willingly.
Abstract:
This paper looks at the crucial issue of dry-season groundwater-availability in the state of Maharashtra, India. We look at the two key hydro-climatological measurements which are used to implement groundwater policy in the state, viz., water levels in 5000+ observation wells across the state and aggregate rainfall data. We see that there is substantial variation in groundwater levels within and across the years in most wells. We argue that for a large number of these observation well locations, aggregate rainfall data is inadequate to model or to predict groundwater levels. For this, we use a novel random rainfall coefficient model for the purpose of modelling the effect of rainfall in a composite setting where extraction and changing land-use data is unknown. The observed high variance of this coefficient points to significant variations in groundwater levels, which may only be explained by unmeasured anthropogenic factors. Next, we see that the uncertainty in actual groundwater levels along with scarcity are two distinct features of groundwater availability and will elicit different behaviours from the typical user. Finally, we recommend that quantitative groundwater assessment protocols of the state should move to incorporating data from which extraction and land-use may be modelled. We believe this is one of the first studies where large spatio-temporal scale data gathered by state agencies have been analysed for scientific adequacy.
and a relevant finding and recommendation:
It is necessary to recognize that scarcity and uncertainty are mutually distinct features of a groundwater regime. For example, if groundwater was scarce but certain, the groundwater-user may make a different set of socio-economic decisions as compared to when it were both scarce and uncertain. In the first case, it incentivizes efficient use of groundwater, while in the second case, it may well lead to competitive extraction and a race to the bottom, worsening the scarcity. Indeed, the spatial coincidence of large σα with σρ seems to suggest this. This leads us to the following policy recommendations: (i) recognition of scarcity and uncertainty as separate attributes of groundwater-availability and developing indices to measure uncertainty, (ii) further work into the incorporation of socioeconomic data along with hydrogeologic and climatic data for building groundwater assessment tools. Perhaps, one relevant avenue for this is the periodic water balance computation carried out by GSDA for each watershed, every 3–5 years (see GEC’97 1997). This incorporates considerable data on extraction, irrigation, surface water bodies, and estimates of other stocks and flows. A refinement of this water balance exercise may yield better inputs for the yearly outlook for the dry season.
Download paper here.
In the context of groundwater policy, who will keep an independent check on government data collection methods and analysis which informs groundwater policy decisions.
It would be nice if government scientist themselves keep refining their methods, but equally needed are independent researchers from Universities and research institutions. Rahul Gokhale and Milind Sohoni of IIT Bombay analyze Maharashtra statewide groundwater data collected over the past few decades by the government Groundwater Surveys and Development Agency. The Agency in October of each year puts out a report on the groundwater outlook for the upcoming dry season (until June of the following year). This report relies on measured groundwater levels from ~ 5000 wells and the State rainfall data. However, there is substantial variation in groundwater levels throughout the dry season and between years in most wells. By subjecting this data to statistical analysis and modelling study Gokhale and Sohoni conclude that aggregate rainfall data is a poor predictor of groundwater levels and that unmeasured factors like extraction patterns and land use influence groundwater availability. They point a way toward refining groundwater assessment methodology by incorporating local socio-economic and groundwater use data.
Now, on the face of it the finding seems somewhat banal, that groundwater levels and availability is controlled not just by rainfall patterns but other anthropogenic factors as well. However, it is important that someone dives into large government data sets and teases out these quantitative relationships between various interacting parameters. And it is good to see an Indian government agency share data willingly.
Abstract:
This paper looks at the crucial issue of dry-season groundwater-availability in the state of Maharashtra, India. We look at the two key hydro-climatological measurements which are used to implement groundwater policy in the state, viz., water levels in 5000+ observation wells across the state and aggregate rainfall data. We see that there is substantial variation in groundwater levels within and across the years in most wells. We argue that for a large number of these observation well locations, aggregate rainfall data is inadequate to model or to predict groundwater levels. For this, we use a novel random rainfall coefficient model for the purpose of modelling the effect of rainfall in a composite setting where extraction and changing land-use data is unknown. The observed high variance of this coefficient points to significant variations in groundwater levels, which may only be explained by unmeasured anthropogenic factors. Next, we see that the uncertainty in actual groundwater levels along with scarcity are two distinct features of groundwater availability and will elicit different behaviours from the typical user. Finally, we recommend that quantitative groundwater assessment protocols of the state should move to incorporating data from which extraction and land-use may be modelled. We believe this is one of the first studies where large spatio-temporal scale data gathered by state agencies have been analysed for scientific adequacy.
and a relevant finding and recommendation:
It is necessary to recognize that scarcity and uncertainty are mutually distinct features of a groundwater regime. For example, if groundwater was scarce but certain, the groundwater-user may make a different set of socio-economic decisions as compared to when it were both scarce and uncertain. In the first case, it incentivizes efficient use of groundwater, while in the second case, it may well lead to competitive extraction and a race to the bottom, worsening the scarcity. Indeed, the spatial coincidence of large σα with σρ seems to suggest this. This leads us to the following policy recommendations: (i) recognition of scarcity and uncertainty as separate attributes of groundwater-availability and developing indices to measure uncertainty, (ii) further work into the incorporation of socioeconomic data along with hydrogeologic and climatic data for building groundwater assessment tools. Perhaps, one relevant avenue for this is the periodic water balance computation carried out by GSDA for each watershed, every 3–5 years (see GEC’97 1997). This incorporates considerable data on extraction, irrigation, surface water bodies, and estimates of other stocks and flows. A refinement of this water balance exercise may yield better inputs for the yearly outlook for the dry season.
Download paper here.
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