Suchergebnisse

Abstract
Because of declining public investments in irrigation projects in India, the growth of irrigated agricultural production has increasingly become reliant on unsustainable allocation of groundwater. As a result, groundwater resources are increasingly depleted and their role in buffering climate variability is lost. Given future climate and food supply uncertainty under mounting population pressure, it is vital that the connections between climate variability, unsustainable irrigation practices, and their impacts on regional-scale agricultural production are quantified.
Here, the focus is on rice and maize production in the semiarid Telangana region in Andhra Pradesh, where the advent of inexpensive pump technology in the late twentieth century, coupled with governmentally subsidized electricity, has allowed year-round planting of water-intensive crops. Using a 35-yr climate and agricultural dataset from Telangana, nonlinear Gaussian process district-level regression models are developed to model dry-season irrigated area, which is a proxy for total groundwater use, in the function of climate-related predictors. The resulting models are able to accurately reproduce dry-season cropped area in most districts. Interannual climate variations play a significant role in determining groundwater use for irrigation. Nonlinear interactions between selected climate features are likely to influence irrigation water use significantly. These results suggest that the authors' modeling approach, combined with monsoon predictions, allow the forecasting of cropped area and agricultural water requirements at seasonal time scales within the bounds of uncertainty. The usefulness of such data to decision makers and stakeholders is discussed, as they attempt to use scarce surface and subsurface water resources more efficiently and sustainably.

Groundwater depletion is becoming a global threat to food security, yet the ultimate impacts of depletion on agricultural production and the efficacy of available adaptation strategies remain poorly quantified. We use high-resolution satellite and census data from India, the world's largest consumer of groundwater, to quantify the impacts of groundwater depletion on cropping intensity, a crucial driver of agricultural production. Our results suggest that, given current depletion trends, cropping intensity may decrease by 20% nationwide and by 68% in groundwater-depleted regions. Even if surface irrigation delivery is increased as a supply-side adaptation strategy, which is being widely promoted by the Indian government, cropping intensity will decrease, become more vulnerable to interannual rainfall variability, and become more spatially uneven. We find that groundwater and canal irrigation are not substitutable and that additional adaptation strategies will be necessary to maintain current levels of production in the face of groundwater depletion.

Groundwater depletion is becoming a global threat to food security, yet the ultimate impacts of depletion on agricultural production and the efficacy of available adaptation strategies remain poorly quantified. We use high-resolution satellite and census data from India, the world's largest consumer of groundwater, to quantify the impacts of groundwater depletion on cropping intensity, a crucial driver of agricultural production. Our results suggest that, given current depletion trends, cropping intensity may decrease by 20% nationwide and by 68% in groundwater-depleted regions. Even if surface irrigation delivery is increased as a supply-side adaptation strategy, which is being widely promoted by the Indian government, cropping intensity will decrease, become more vulnerable to interannual rainfall variability, and become more spatially uneven. We find that groundwater and canal irrigation are not substitutable and that additional adaptation strategies will be necessary to maintain current levels of production in the face of groundwater depletion.