The current study presents an algorithm to retrieve surface Soil Moisture (SM) from multi-temporal Synthetic Aperture Radar (SAR) data. The developed algorithm is based on the Cumulative Density Function (CDF) transformation of multi-temporal RADARSAT-2 backscatter coefficient (BC) to obtain relative SM values, and then converts relative SM values into absolute SM values using soil information. The algorithm is tested in a semi-arid tropical region in South India using 30 satellite images of RADARSAT-2, SMOS L2 SM products, and 1262 SM field measurements in 50 plots spanning over 4 years. The validation with the field data showed the ability of the developed algorithm to retrieve SM with RMSE ranging from 0.02 to 0. and a correlation coefficient of approximately 0.9. The developed model is compared and found to be better than the change detection and delta index model. The approach does not require calibration of any parameter to obtain relative SM and hence can easily be extended to any region having time series of SAR data available.Remote Sens. 2015, 7 8129

Electronic health record (EHR) is increasingly being implemented in many developing countries. It is the need of the hour because it improves the quality of health care and is also cost-effective. Technologies can introduce some hazards hence safety of information in the system is a real challenge. Recent news of security breaches has put a question mark on this system. Despite its increased usefulness, and increasing enthusiasm in its adoption, not much attention is being paid to the ethical issues that might arise. Securing EHR with an encrypted password is a probable option. The purpose of this article is to discuss the various ethical issues arising in the use of the EHRs and their possible solutions.

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.

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.

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Agriculture in rural areas facing critical issues such as irrigation with the increase in water crises followed by some other issues line seed quality, poor fertilizers and many others. The recent advances suggest that IoT and Blockchain Technology along with artificial intelligence will be most dominant technologies in near future. In this article, the integration of Internet of Things (IoT) with Blockchain technology is implemented for monitoring agricultural fields efficiently. An efficient seed quality monitoring and smart water management system is design using IoT and Blockchain Technology for managing and coordinating the use of good quality seeds and water resources among communities. The Blockchain network is implemented for securing the information and supporting trust among the members of community. The Blockchain network is also implemented for sporting trust among commercial resource constrained systems, which are communicating with the Blockchain network consisting of a hardware platform. The design of a prototype and its performance evaluation based on implementation is also presented.

Pollution control measures have resulted in replacement of chlorine by peroxide as bleaching chemical. Change of chemical affects corrosion aspects, the suitability of existing plant metallurgy and materials of construction of bleach plants. Accordingly long term immersion and electrochemical corrosion tests were conducted on stainless steel 304L, 316L, 2205 and 6% Mo and mild steel in peroxide solutions of pH 10. The materials were tested for uniform corrosion, pitting and crevice corrosion and attack around the weld area. Corrosion attack estimated from long term immersion tests is found in agreement, by and large, with that analyzed from electrochemical test. E-pH diagrams drawn for water-peroxide system have been used to understand the corrosivity of the peroxide media. An attempt has been made to suggest a suitable material of construction for handling the test media on the basis of degree of corrosion attack on them and their cost and the mechanical properties.

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