Invisible water, visible impact: How unsustainable groundwater use challenges sustainability of Indian agriculture under climate change

India is one of the world’s largest food producers, making the sustainability of its agricultural system of global significance. Groundwater irrigation underpins India’s agriculture, currently boosting crop production by enough to feed 170 million people. Groundwater overexploitation has led to drastic declines in groundwater levels, threatening to push this vital resource out of reach for millions of small-scale farmers who are the backbone of India’s food security. Historically, losing access to groundwater has decreased agricultural production and increased poverty. We take a multidisciplinary approach to assess climate change challenges facing India’s agricultural system, and to assess the effectiveness of large-scale water infrastructure projects designed to meet these challenges. We find that even in areas that experience climate change induced precipitation increases, expansion of irrigated agriculture will require increasing amounts of unsustainable groundwater. The large proposed national river linking project has limited capacity to alleviate groundwater stress. Thus, without intervention, poverty and food insecurity in rural India is likely to worsen

Mapping global hotspots and trends of water quality (1992–2010): a data driven approach

Clean water is key for sustainable development. However, large gaps in monitoring data limit our understanding of global hotspots of poor water quality and their evolution over time. We demonstrate the value added of a data-driven approach (here, random forest) to provide accurate high-frequency estimates of surface water quality worldwide over the period 1992-2010. We assess water quality for six indicators (temperature, dissolved oxygen, pH, salinity, nitrate-nitrite, phosphorus) relevant for the sustainable development goals. The performance of our modeling approach compares well to, or exceeds, the performance of recently published process-based models. The model’s outputs indicate that poor water quality is a global problem that impacts low-, middle- and high-income countries but with different pollutants. When countries become richer, water pollution does not disappear but evolves. Water quality exhibited a signif icant change between 1992 and 2010 with a higher percentage of grid cells where water quality shows a statistically significant deterioration (30%) compared to where water quality improved (22%)

Water in the Balance: The Impact of Water Infrastructure on Agricultural Adaptation to Rainfall Shocks in India

Investments in water infrastructure remain key to climate change adaptation plans in many countries, and rank high in adaptation costs for developing countries (Narain et al., 2011). In this paper, we use district-level panel data from 1970-2005 across India’s major agricultural states to investigate the role played by subsidized access to electricity, groundwater wells, tank and dam projects in mediating the vulnerabilities associated with monsoonal variation. We focus on wheat, a staple of India’s food supply, as it requires irrigation and represents a significant portion of India’s total agricultural output. Results show that the impact of negative precipitation shocks is significantly dampened when a particular district has access to a more reliable source of irrigation – e.g., access to tubewells helps to dampen the impact of negative precipitation shocks on irrigation decisions associated with wheat, while upstream dams do not significantly contribute to this dampening effect. In contrast, having access to dugwells exacerbates the impact of a fall in monsoon precipitation curtailing irrigation of wheat. Our results suggest that historical agricultural policies that increased access to tubewells and the subsequent electrification of regions naturally endowed with more groundwater have equipped farmers with the ability to withstand monsoonal shocks and fluctuations

The impact of water access on short-term migration in rural India

Migration is an important risk-reduction strategy for households in developing countries. In this paper, we examine the impact of rainfall variability and irrigation availability on short-term migration decisions in India. Our results show that both rainfall shocks and the availability of irrigation impact the decisions of households to dispatch migrants. For irrigation, we find that migration responds to costs and that deep fossil-water wells, which provide a constant source of water, eliminate any benefit of short-term migration. This suggests that regions with access to more secure and stable sources of water are less likely to rely on migration as an income-smoothing mechanism, at least in the short run. Whether this holds in the long run will depend on the continued stability and availability of irrigation water

Adapting to Monsoon Variability in India: the Case for Irrigation

How will future changes in precipitation affect irrigation demand and supply in India? This paper provides econometric evidence for the demand side of the analysis by examining the relationship between monsoon changes and irrigation variability for one of the world’s most water stressed countries, India. Using detailed crop-wise agriculture and weather data spanning 35 years, the econometric model isolates the historical impact of the distribution and total supply of monsoon precipitation on irrigation demand via the use of irrigated area for crops grown in the dry(Rabi) and wet(Kharif) seasons. We find differential impacts of the monsoon by crop, by season and by source of irrigation. In general, for crops grown in the wet season, irrigation is sensitive to both distribution and total monsoon rainfall but not to ground or surface water availability. For crops grown in the dry season, total monsoon rainfall matters most, and its effect is sensitive to groundwater availability. Over the historic period of analysis, the effect of the monsoon on irrigation has remained relatively stable. The econometric analysis, when combined with a process based hydrology model that accounts for the supply side response of water availability, can help quantify the (un)sustainable water use trajectory that different regions within India will face

Mapping global hotspots and trends of water quality (1992–2010): a data driven approach

International audienceClean water is key for sustainable development. However, large gaps in monitoring data limit our understanding of global hotspots of poor water quality and their evolution over time. We demonstrate the value added of a data-driven approach (here, random forest) to provide accurate high-frequency estimates of surface water quality worldwide over the period 1992-2010. We assess water quality for six indicators (temperature, dissolved oxygen, pH, salinity, nitrate-nitrite, phosphorus) relevant for the sustainable development goals. The performance of our modeling approach compares well to, or exceeds, the performance of recently published process-based models. The model's outputs indicate that poor water quality is a global problem that impacts low-, middle-and high-income countries but with different pollutants. When countries become richer, water pollution does not disappear but evolves. Water quality exhibited a signif icant change between 1992 and 2010 with a higher percentage of grid cells where water quality shows a statistically significant deterioration (30%) compared to where water quality improved (22%)

Impact of green water anomalies on global rainfed crop yields

| openaire: EC/H2020/819202/EU//SOS.aquaterraThe importance of green water (moisture from rain stored in soils) for global food and water security is widely recognized, with process-based simulation models and field-level studies demonstrating its role in supporting rainfed agriculture. Despite this evidence, the relationship between green water anomalies and rainfed agriculture has not yet been investigated using statistical models that identify a causal relationship between the variables. Here, we address this gap and use disaggregated statistical regression (panel data analysis) at the 30 arc-min grid level to study the response of observed yields (1982-2010) of four main crops (maize, rice, soybean and wheat) to green water anomalies globally over rainfed areas. Dry green water anomalies (1 or 2 standard deviations below long-term average) decrease rainfed crop yields worldwide. This effect is more pronounced for wheat and maize, whose yields decline by 12%-18% and 7%-12% respectively. Globally, agricultural production benefits from wet green water anomalies. This effect is intensified in arid climates and weakened in humid climates where, for wheat, soybean and rice, periods of green water availability 2 standard deviations above long-term averages lead to declines in crop yield. This confirms existing evidence that excess soil moisture is detrimental to crop yield. These findings (1) advance our understanding of the impact of green water on rainfed food production and (2) provide empirical evidence supporting arguments for better management of local green water resources to reduce the impact of agricultural drought and waterlogging on rainfed crop production and capture the yield increasing effects of positive green water anomalies.Peer reviewe

Mapping global hotspots and trends of water quality (1992-2010): a data driven approach

Clean water is key for sustainable development. However, large gaps in monitoring data limit our understanding of global hotspots of water quality and their evolution over time. We demonstrate the value added of a data-driven approach to provide accurate high-frequency estimates of surface water quality worldwide over the period 1992-2010. We assess water quality for six indicators (temperature, dissolved oxygen, pH, salinity, nitrate-nitrite, phosphorus) relevant for the Sustainable Development Goals (SDG). The performance of our modelling approach compares well to, or exceeds, the performance of recently published process-based models. The model's outputs indicate that poor water quality is a global problem that impacts low-, middle-and high-income countries but with different pollutants. When countries become richer, water pollution does not disappear but evolves

Invisible water, visible impact: groundwater use and Indian agriculture under climate change

India is one of the world’s largest food producers, making the sustainability of its agricultural system of global significance. Groundwater irrigation underpins India’s agriculture, currently boosting crop production by enough to feed 170 million people. Groundwater overexploitation has led to drastic declines in groundwater levels, threatening to push this vital resource out of reach for millions of small-scale farmers who are the backbone of India’s food security. Historically, losing access to groundwater has decreased agricultural production and increased poverty. We take a multidisciplinary approach to assess climate change challenges facing India’s agricultural system, and to assess the effectiveness of large-scale water infrastructure projects designed to meet these challenges. We find that even in areas that experience climate change induced precipitation increases, expansion of irrigated agriculture will require increasing amounts of unsustainable groundwater. The large proposed national river linking project has limited capacity to alleviate groundwater stress. Thus, without intervention, poverty and food insecurity in rural India is likely to worsen