Abstract:The scale difference between point in situ soil moisture measurements and low resolution satellite products limits the quality of any validation efforts in heterogeneous regions.

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 km 2 ) 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.

In the last decades, globally several small experimental watersheds were set up to study the climate and agricultural influences on water and biogeochemical cycles. Recently, the concept and importance of Critical Zone Observatory (CZO) was made and this resulted in developing such observatories in several countries including a global network of CZOs. The CZOs combine characterization, long term monitoring and modeling to allow understanding of the processes governing water and biogeochemical cycles in a small experimental watershed or network of watersheds. The Kabini CZO too was formed from similar twin experimental watersheds (forested and cultivated) developed during the last decade in the Kabini river basin in the south western part of India. A summary of the salient studies performed on water and biogeochemical cycles under the influence of climate and agriculture during the last ten years in the Kabini CZO are reported here.

The INCOMPASS field campaign combines airborne and ground measurements of the 2016 Indian monsoon, towards the ultimate goal of better predicting monsoon rainfall. The monsoon supplies the majority of water in South Asia, but forecasting from days to the season ahead is limited by large, rapidly developing errors in model parametrizations. The lack of detailed observations prevents thorough understanding of the monsoon circulation and its interaction with the land surface: a process governed by boundary‐layer and convective‐cloud dynamics. INCOMPASS used the UK Facility for Airborne Atmospheric Measurements (FAAM) BAe‐146 aircraft for the first project of this scale in India, to accrue almost 100 h of observations in June and July 2016. Flights from Lucknow in the northern plains sampled the dramatic contrast in surface and boundary‐layer structures between dry desert air in the west and the humid environment over the northern Bay of Bengal. These flights were repeated in pre‐monsoon and monsoon conditions. Flights from a second base at Bengaluru in southern India measured atmospheric contrasts from the Arabian Sea, over the Western Ghats mountains, to the rain shadow of southeast India and the south Bay of Bengal. Flight planning was aided by forecasts from bespoke 4 km convection‐permitting limited‐area models at the Met Office and India's NCMRWF. On the ground, INCOMPASS installed eddy‐covariance flux towers on a range of surface types, to provide detailed measurements of surface fluxes and their modulation by diurnal and seasonal cycles. These data will be used to better quantify the impacts of the atmosphere on the land surface, and vice versa. INCOMPASS also installed ground instrumentation supersites at Kanpur and Bhubaneswar. Here we motivate and describe the INCOMPASS field campaign. We use examples from two flights to illustrate contrasts in atmospheric structure, in particular the retreating mid‐level dry intrusion during the monsoon onset.

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Farmers' production decisions and agricultural practices directly and indirectly influence the quantity and quality of natural resources, some being depleted common resources such as groundwater. Representing farming systems while accounting for their flexibility is needed to evaluate targeted, regional water management policies. Farmers' decisions regarding investing in irrigation and adopting cropping systems are inherently dynamic and must adapt to changes in climate and agronomic, economic and social, and institutional, conditions. To represent this diversity, we developed a typology of Indian farmers from a survey of 684 farms in Berambadi, an agricultural watershed in southern India (state of Karnataka). The survey provided information on farm structure, the cropping system and farm practices, water management for irrigation, and economic performances of the farm. Descriptive statistics and multivariate analysis (Multiple Correspondence Analysis and Agglomerative Hierarchical Clustering) were used to analyze relationships between observed factors and establish the farm typology. We identified three main types of farms: (1) large diversified and productivist farms; (2) small and marginal rainfed farms, and (3) small irrigated marketing farms. This typology represents the heterogeneity of farms in the Berambadi watershed.

No abstract

Connectivity of groundwater flow within crystalline-rock aquifers controls the sustainability of abstraction and baseflow to rivers, yet is often poorly constrained at a catchment scale. Here groundwater connectivity in a sheared gneiss aquifer is investigated by studying the intensively abstracted Berambadi catchment (84 km 2) in the Cauvery River Basin, southern India, with geological characterisation, aquifer properties testing, hydrograph analysis, hydrochemical tracers and a numerical groundwater flow model. The study indicates a well-connected system, both laterally and vertically, that has evolved with high abstraction from a laterally to a vertically dominated flow system. Likely as a result of shearing, a high degree of lateral connectivity remains at low groundwater levels. Because of their low storage and logarithmic reduction in hydraulic conductivity with depth, crystalline-rock aquifers in environments such as this, with high abstraction and variable seasonal recharge, constitute a highly variable water resource, meaning farmers must adapt to varying water availability. Importantly, this study indicates that abstraction is reducing baseflow to the river, which, if also occurring in other similar catchments, will have implications downstream in the Cauvery River Basin.