Abstract
Groundwater has rapidly evolved as a primary source for irrigation in Indian agriculture. Over-exploitation of the groundwater substantially depletes the natural water table and has negative impacts on the water resource availability. The overarching goal of the proposed research is to identify the historical evolution of irrigated cropland for the post-monsoon (rabi) and summer cropping seasons in the Berambadi watershed (Area = 89 km2) of Kabini River basin, southern India. Approximately five-year interval irrigated area maps were generated using 30 m spatial resolution Landsat satellite images for the period from 1990 to 2016. The potential of Support Vector Machine (SVM) was assessed to discriminate irrigated and non-irrigated croplands. Three indices, Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI) and Enhanced Vegetation Index (EVI), were derived from multi-temporal Landsat satellite images. Spatially distributed intensive ground observations were collected for training and validation of the SVM models. The irrigated and non-irrigated croplands were estimated with high classification accuracy (kappa coefficient greater than 0.9). At the watershed scale, this approach allowed highlighting the contrasted evolution of multiple-cropping (two successive crops in rabi and summer seasons that often imply dual irrigation) with a steady increase in the upstream and a recent decrease in the downstream of the watershed. Moreover, the multiple-cropping was found to be much more frequent in the valleys. These intensive practices were found to have significant impacts on the water resources, with a drastic decline in the water table level (more than 50 m). It also impacted the ecosystem: Groundwater level decline was more pronounced in the valleys and the rivers are no more fed by the base flow.
Highlights
The development of groundwater irrigation in the past few decades has helped in securing crop yield in many semi-arid parts of the world, especially in India [1]
Remote sensing data for retrieving area under irrigation and its historical evolution are extremely useful for water management
Use of optical satellite data in the case of Indian agriculture is challenging as (i) it is dominated by small farm holdings, (ii) tropical regions with high cloud cover led to less availability of high-resolution satellite images with high temporal revisit during various cropping seasons, (iii) it has a large diversity of crops and agricultural practices that are difficult to capture by existing indices [5,6] and (iv) many of these crops have a short cycle of 3 to 4 months
Summary
The development of groundwater irrigation in the past few decades has helped in securing crop yield in many semi-arid parts of the world, especially in India [1]. In areas where a diversity of crops is present, spatial variations of vegetation cover might be due to timings of crop rotations, the difference in rooting depth for different species or presence of trees For this reason, the use of a single index for detecting irrigation is increasingly questioned [32,33] for the case of humid regions. One index was not able to consistently classify irrigated area using a single image, while in a combination of multiple indices high and consistent accuracy was observed While applying this method to a watershed in India, we characterized the spatial heterogeneity in the dynamics of irrigation development across the watershed, and it links with the groundwater resource depletion
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