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.

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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.

Incipient groundwater salinization has been identified in many arid and semi-arid regions where groundwater is increasingly used for irrigation, but the dominant processes at stake in such context are yet uncertain. Groundwater solutes originates from various sources such as atmospheric inputs, rock dissolution and fertilizer residues, and their concentration is controlled by hydrological processes, in particular evapotranspiration. Here, we propose a deconvolution method to identify the sources and processes governing the groundwater Chloride concentration in agricultural catchments, using the relative variations of Sodium and chloride and using a neighbouring pristine catchment as a reference for the release rate of Na by weathering. We applied the deconvolution method to the case of the Kabini Critical Zone Observatory, South India, where groundwater was sampled in 188 farm tubewells in the semi-arid catchment of Berambadi and in 5 piezometers in the pristine catchment of Mule Hole. In Berambadi, groundwater composition displayed a large spatial variability with Cl contents spanning 3 orders of magnitude. The results showed that the concentration factor due to evapotranspiration was on average about 3 times more than in the natural system, with higher values in the valley bottoms with deep Vertisols. Linked with this process, large concentration of Chloride originating from rain was found only in these areas. At the catchment scale, about 60 percent of the Chloride found in groundwater originates from fertilizer inputs. These results show that Potassium fertilization as KCl is an important source of groundwater salinization in semi-arid context, and stress that identifying dominant drivers is crucial for designing efficient mitigation policies.

Background and aims The benefits of Si for crops is well evidenced but the biogeochemical cycle of Si in agriculture remains poorly documented. This study aims at identifying and quantifying the Si sources (primary and secondary soil minerals, amorphous silica, irrigation, Si-fertilizer) to rice plants. Method Field experiments were carried out with and without application of diatomaceous earth (DE) under rice and bare conditions to determine the water and dissolved mass balance in paddy fields (Karnataka, Southern India). The fate of the Si brought by irrigation (DSi) (uptake by rice, uptake by diatoms, adsorption) was assessed through a solute mass balance combined with silicon isotopic signatures. Results Above the ground-surface, about one third of the DSi flux brought by borewell irrigation (545 mmol Si.m-2) to bare plots and half of DSi in rice plots were removed from solution within minutes or hours following irrigation. Such rate is consistent with the rate of DSi adsorption onto Fe-oxyhydroxides but not with diatom blooms. In rice and rice+DE experiments, the Purity index (Si-Al)/Si molar Algal mat ASi Soil ASi Clay fraction (<2µm) rice straw Diatom earth isotopic fractionation factor (30 ε) between bore well and stagnant water compositions is close to-1 ‰, i.e. the isotopic fractionation factor known for rice, indicating that above-ground DSi removal would be dominated by plant uptake upon adsorption. Within the soil layer, pore water DSi decreases much faster in rice experiments than in bare ones, demonstrating the efficiency of DSi rice uptake upon adsorption. Total irrigation-DSi to plant-Si would then represent 24 to 36 % in rice experiments (over 1460 ± 270 mmol Si m-2 in biomass) and 15 to 23 % in rice+DE ones (over 2250 ± 180 mmol Si m-2). The δ 30 Si signature of whole plants was significantly different in the rice+DE plot analyzed, 0.99 ± 0.07 ‰, than in the rice one, 1.29 ± 0.07 ‰. According to these δ 30 Si signatures, the main Si source from the soil would be the amorphous silica pool (ASi). A slight contribution of DE to the rice plant could be detected from the Si isotopic signature of rice. Conclusions The δ 30 Si signatures of the various soil-plant compartments, when associated to Si mass balance at scale, constitute a reliable proxy of the Si behavior in paddy fields. The solute Si balance is controlled by rice uptake in rice plots and by adsorption and diatom uptake in bare ones. The main Si sources for the rice plants were soil ASi, irrigation Si and to a lesser extent Si fertilizer when it was applied.

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Despite the importance of tropical ecosystems for climate regulation, biodiversity, water and nutrient cycles, only a few Critical Zone Observatories (CZOs) are located in the tropics. Among these, most are in humid climates, while very few data exist for semi-arid and sub-humid climates, due to the difficulty of estimating hydrogeochemical balances in catchments with ephemeral streams. We contribute to fill this gap by presenting a meteorological and hydro-geochemical dataset acquired at the Mule Hole catchment (4.1 km 2 ), a pristine dry deciduous forest located in a biosphere reserve in south India. The dataset consists of time series of variables related to (i) meteorology, including rainfall, air temperature, relative humidity, wind speed and direction, and global radiation, (ii) hydrology, including water level and discharge at the catchment outlet, (iii) hydrogeology, including manual (monthly) and/or automated (from 15 min to hourly) groundwater levels in nine piezometers and (iv) geochemistry, including suspended sediment content in the stream and chemical composition of rainfall (event based), groundwater (monthly sampling) and stream water (storm events, 15 min to hourly frequency with an automatic sampler). The time series extend from 2003 to 2019. Measurement errors are minimized by frequent calibration of sensors and quality checks, both in the field and in the laboratory. Despite these precautions, several data gaps exist, due to occasional access restriction to the site and instrument destruction by wildlife. Results show that large seasonal and interannual variations of climatic conditions were reflected in the large variations of stream flow and groundwater recharge, as well as in water chemical composition. Notably, they reveal a long-term evolution of groundwater storage, suggesting hydrogeological cycles on a decadal scale. This dataset, alone or in combination with other data, has already allowed to better understand water and element

Groundwater has become a major source of irrigation in the past few decades in India, but as it comes from millions of individual borewells owned by smallholders irrigating small fields, it is difficult to quantify the actual irrigated area across seasons and years. This study’s main goal was to monitor seasonal irrigated cropland using multiple optical satellite images. The proposed research was performed over the Berambadi watershed, an experimental site in southern peninsular India. While cloud cover during crop growth is the greatest obstacle to optical remote sensing in tropical regions, the cloud-free images from multiple optical satellite platforms (Landsat-8 (OLI), EO1 (ALI), IRS-P6 (LISS3 and LISS4), and Spot5Take5 (HRG2)) were used to fill data gaps during crop growth periods. The seasonal cumulative normalized difference vegetation index (NDVI) was calculated and resampled at 5 m spatial resolution for various cropping seasons. The support vector machine (SVM) classification was applied to seasonal cumulative NDVI images for irrigated cropland area classification. Validation of the classified irrigated cropland was performed by calculating kappa coefficients for three cropping seasons (summer, kharif, and rabi) from 2014–2016 using ground observations. Kappa coefficients ranged from 0.81–0.96 for 2014–2015 and 0.62–0.89 for 2015–2016, except for summer 2016, when it was 1.00. Groundwater irrigation in the watershed ranged from 4.6% to 16.5% of total cropland during these cropping seasons. These results showed that multi-source optical satellite data are relevant for quantifying areas under groundwater irrigation in tropical regions.