Achieving Sustainable Development Goal for Clean Water in India: Influence of Natural and Anthropogenic Factors on Groundwater Microbial Pollution.

Worldwide, >2 billion people (~1/3 world population), mostly living in economically stressed areas of Africa and South Asia, still do not have access to basic sanitation, and ~1 billion still practice open defecation. Water pollution due to open defecation may primarily be linked to economy, and other factors such as social and hygiene practices, land use and hydrogeological parameters could also have sufficient influence. The present study describes the effect of human development index (HDI, 2001-2015) and economic development (NL, 1992-2013) on groundwater microbial pollution (FC, 2002-2017) across India. Economic development pattern suggested discernable inverse relationship with FC in most areas, although areas with inferior water quality, improper human practices were found to outweigh economic development. Vulnerability modelling, using these data, along with measured FC in groundwater-sourced drinking water locations (n = 235) demonstrated the heterogeneity of FC distribution potential in areas of homogenous economy, social practices, and land use. High-resolution numerical modelling of the advective transport of the hypothetical FC particles in the aquifers, suggest up to ~24 times faster movement of pollutants under irrigation-induced pumping regimes. Hence, the results of our study highlight and quantify the potential pitfalls that are possible hindrance for achieving the United Nations sustainable development goal, despite social and economic development, across the spatial scales.

Using night time lights to find regional inequality in India and its relationship with economic development.

Due to unavailability of consistent income data at the sub-state or district level in developing countries, it is difficult to generate consistent and reliable economic inequality estimates at the disaggregated level. To address this issue, this paper employs the association between night time lights and economic activities for India at the sub-state or district-level, and calculates regional income inequality using Gini coefficients. Additionally, we estimate the relationship between night time lights and socio-economic development for regions in India. We employ a newly available data on regional socio-economic development (Social Progress Index), as well as an index that represents institutional quality or governance. Robust to the choice of socio-economic development indicators, our findings indicate that regional inequality measured by night time lights follow the Kuznets curve pattern. This implies that starting from low levels of socio-economic development or quality of institutions, inequality rises as regional socio-economic factors or quality of institutions improve, and with subsequent progress in socio-economic factors or quality of institutions, regional inequality declines.

Author Correction: Impact of sanitation and socio-economy on groundwater fecal pollution and human health towards achieving sustainable development goals across India from ground-observations and satellite-derived nightlight.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Impact of sanitation and socio-economy on groundwater fecal pollution and human health towards achieving sustainable development goals across India from ground-observations and satellite-derived nightlight.

Globally, ~1 billion people, mostly residing in Africa and South Asia (e.g. India), still lack access to clean drinking water and sanitation. Resulting, unsafe disposal of fecal waste from open-defecation to nearby drinking water sources severely endanger public health. Until recently, India had a huge open-defecating population, leading declining public health from water-borne diseases like diarrhoea by ingesting polluted water, mostly sourced to groundwater. However, in recent past, sanitation development to achieve Sustainable Development Goals (SDGs) has been encouraged throughout India, but their effect to groundwater quality and human health conditions are yet-unquantified. Here, for the first time, using long term, high-spatial resolution measurements (>1.7 million) across India and analyses, we quantified that over the years, groundwater fecal coliform concentration (2002-2017, -2.56 ± 0.06%/year) and acute diarrheal cases (1990-2016, -3.05 ± 0.01%/year) have significantly reduced, potentially influenced by sanitation development (1990-2017, 2.63 ± 0.01%/year). Enhanced alleviation of groundwater quality and human health have been observed since 2014, with initiation of acceletated constructions of sanitation infrastructures through Clean India (Swachh Bharat) Mission. However, the goal of completely faecal-pollution free, clean drinking water is yet to be achieved. We also evaluated the suitability of using satellite-derived night-time light (NLan, 1992-2013, 4.26 ± 0.05%/year) as potential predictor for such economic development. We observed that in more than 80% of the study region, night-time light demonstrated to be a strong predictor for observed changes in groundwater quality, sanitation development and water-borne disease cases. While sanitation and economic development can improve public health, poor education level and improper human practices can strongly influence on water-borne diseases loads and thus health in parts of India.

Human motion capture data compression by model-based indexing: a power aware approach.

Human Motion Capture (MoCap) data can be used for animation of virtual human-like characters in distributed virtual reality applications and networked games. MoCap data compressed using the standard MPEG-4 encoding pipeline comprising of predictive encoding (and/or DCT decorrelation), quantization, and arithmetic/Huffman encoding, entails significant power consumption for the purpose of decompression. In this paper, we propose a novel algorithm for compression of MoCap data, which is based on smart indexing of the MoCap data by exploiting structural information derived from the skeletal virtual human model. The indexing algorithm can be fine-controlled using three predefined quality control parameters (QCPs). We demonstrate how an efficient combination of the three QCPs results in a lower network bandwidth requirement and reduced power consumption for data decompression at the client end when compared to standard MPEG-4 compression. Since the proposed algorithm exploits structural information derived from the skeletal virtual human model, it is observed to result in virtual human animation of visually acceptable quality upon decompression.

Groundwater rejuvenation in parts of India influenced by water-policy change implementation.

The dwindling groundwater resource of India, supporting almost one fifth of the global population and also the largest groundwater user, has been of great concern in recent years. However, in contrary to the well documented Indian groundwater depletion due to rapid and unmanaged groundwater withdrawal, here for the first time, we report regional-scale groundwater storage (GWS) replenishment through long-term (1996-2014, using more than 19000 observation locations) in situ and decadal (2003-2014) satellite-based groundwater storage measurements in western and southern parts of India. In parts of western and southern India, in situ GWS (GWSobs) has been decreasing at the rate of -5.81 ± 0.38 km3/year (in 1996-2001) and -0.92 ± 0.12 km3/year (in 1996-2002), and reversed to replenish at the rate of 2.04 ± 0.20 km3/year (in 2002-2014) and 0.76 ± 0.08 km3/year (in 2003-2014), respectively. Here, using statistical analyses and simulation results of groundwater management policy change effect on groundwater storage in western and southern India, we show that paradigm shift in Indian groundwater withdrawal and management policies for sustainable water utilization appear to have started replenishing the aquifers in western and southern parts of India.