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Groundwater in north India remains a vital food and water security resource for more than one billion people. Both summer monsoon drying, and winter warming pose considerable challenges for rapidly declining groundwater. However, their impacts on irrigation water demands and groundwater storage under the observed and projected future climate remain unexplored. Using in situ observations, satellite data, and a hydrological model that considers the role of irrigation and groundwater pumping, we show that summer monsoon drying and winter warming accelerate groundwater depletion in north India during the observed climate, which will continue in the projected future climate. Summer monsoon precipitation has significantly (P‐value = 0.04) declined (∼8%) while winters have become warmer in north India during 1951–2021. Both satellite (GRACE/GRACE‐FO) and hydrological model‐based estimates show a rapid groundwater depletion (∼1.5 cm/year) in north India with a net loss of 450 km3 of groundwater during 2002–2021. The summer monsoon drying followed by winter warming cause a substantial reduction in groundwater storage due to reduced groundwater recharge and enhanced pumping to meet irrigation demands. Summer monsoon drying and winter warming will continue to affect groundwater storage in north India in the future. For instance, summer monsoon drying (10%–15% deficit for near‐far periods) followed by substantial winter warming (1–4°C) in the future will further accelerate groundwater depletion by increasing (6%–20%) irrigation water demands and reducing groundwater recharge (6%–12%). Groundwater sustainability measures including reducing groundwater abstraction and enhancing the groundwater recharge during the summer monsoon seasons are needed to ensure future agricultural production. Plain Language Summary: Groundwater in north India is facing rapid depletion due to summer monsoon drying and winter warming. The decline in summer monsoon precipitation and warmer winters have led to major droughts, resulting in a massive loss of groundwater between 2002 and 2021. Summer monsoon drying coupled with winter warming climate will increase irrigation water demands and reduce groundwater recharge. This necessitates the implementation of groundwater sustainability measures to ensure future agricultural production during monsoon droughts. Key Points: Examined the role summer monsoon drying and winter warming on groundwater storage in IndiaRapid groundwater depletion (∼1.5 cm/year) resulted in a net loss of 450 km3 of groundwater during 2002–2021Summer monsoon drying followed by substantial winter warming under the warming climate will further accelerate groundwater depletion [ABSTRACT FROM AUTHOR]

Precipitation is considered one of the most important forcing data in scientific investigations involving agriculture, water management, and climate variability. Knowledge of precipitation variation during rainy seasons is the key to the understanding of the precipitation variability under the effect of climate change. This study evaluated some rainy season features (e.g., onset, retreat, and rainy-season precipitation) over the Yellow River basin (YRB), China, and the influence of the El Niño-Southern Oscillation (ENSO). The multi-scale moving t-test was applied to capture the onset and retreat of rainy season. The possible linkage between ENSO-induced precipitation and monsoon and atmospheric circulation was also explored. From the analysis, four conclusions can be drawn: (1) Rainy season began the earliest (latest) and ended the latest (earliest) in the southern (northern) YRB, with rainy-season precipitation increasing from northwest to southeast. (2) Rainy-season precipitation showed strong correlation to SST in Niño regions. Precipitation can reach up to 20% above the average precipitation for decaying central Pacific warming (CPW) and down to 35% below the average precipitation for developing eastern Pacific warming (EPW) in most areas of the YRB. (3) Developing El Niño showed the strongest dry signals among developing ENSO and ENSO Modoki phases. Decaying El Niño and El Niño Modoki indicated overall increasing precipitation, with La Niña and La Niña Modoki during the corresponding period showing the opposite tendency. (4) Different performances of ENSO-induced precipitation attributed to the combined influence of the monsoon from the India Ocean and the atmospheric circulation in the Western North Pacific (WNP). Stronger anti-cyclone and monsoon are related to increasing rainy-season precipitation. These findings can improve the predictability of rainy season features and ENSO-induced precipitation. [ABSTRACT FROM AUTHOR]

Significant groundwater depletion in regions where grains are procured for public distribution is a primary sustainability challenge in India. We identify specific changes in the Indian Government's Procurement & Distribution System as a primary solution lever. Irrigation, using groundwater, facilitated by subsidized electricity, is seen as vital for meeting India's food security goals. Using over a century of daily climate data and recent spatially detailed economic, crop yield, and related parameters, we use an optimization model to show that by shifting the geographies where crops are procured from and grown, the government's procurement targets could be met on average even without irrigation, while increasing net farm income and arresting groundwater depletion. Allowing irrigation increases the average net farm income by 30%. The associated reduction in electricity subsidies in areas with significant groundwater depletion can help offset the needed spatial re-distribution of farm income, a key political obstacle to changes in the procurement system. Using optimization models with climate, crop & economic data, the authors show that India can stop groundwater depletion, reduce energy use and meet food/nutrition targets by changing where it sources crops for its food procurement and distribution system. [ABSTRACT FROM AUTHOR]

A novel Bayesian Hierarchical Network Model (BHNM) for ensemble forecasts of daily streamflow is presented that uses the spatial dependence induced by the river network topology and hydrometeorological variables from the upstream contributing area between station gauges. Model parameters are allowed to vary with time as functions of selected covariates for each day. Using the network structure to incorporate flow information from upstream gauges and precipitation from the immediate contributing area as covariates allows one to model the spatial correlation of flows simultaneously and parsimoniously. An application to daily monsoon period (July–August) streamflow at three gauges in the Narmada basin in central India for the period 1978–2014 is presented. The best set of covariates include daily streamflow from upstream gauges or from the gauge above the upstream gauges depending on travel times and daily precipitation from the area between two stations. The model validation indicates that the model is highly skillful relative to a null‐model of generalized linear regression, which represents the analogous non‐Bayesian forecast. The ensemble spread of BHNM accounts for the forecast uncertainty leading to reliable and skillful streamflow predictions. Key Points: We developed a Bayesian Hierarchical Network Model for ensemble forecasts of daily streamflow with the attendant uncertaintiesThe model provides ensemble forecasts at all the locations on a river network simultaneously, capturing the spatial and temporal correlationThe framework can be applied to any river network and with appropriate covariates [ABSTRACT FROM AUTHOR]

Contract farming is a growing practice in developing countries and first-world economies alike. It generates necessary guarantees to sustain the continued operations of vulnerable farmers while enabling the manufacturers to manage the aggregate supply and price risk. We consider a single manufacturer who owns several manufacturing plants, each with a random demand for the crop. The manufacturer selects a set of farmers to offer a menu of contracts, which is exogenously specified or endogenously determined. Each "selected" farmer chooses a contract from this menu in advance of the growing season. After the growing season, under known demands and supplies, the manufacturer minimizes the distribution costs from the selected farmers to the production facilities. We formulate this problem as a Stackelberg game with asymmetric information, where the manufacturer is the leader and the farmers are the followers. The manufacturer's problem is a two-stage stochastic planning program for which we develop two solution approaches. We have applied our model to problem instances anchored on data from a large manufacturer of potato chips contracting with thousands of small farmers in India. We report on the performance of the solution methods compared with a lower bound based on the Lagrangean dual of the problem and show that the optimality gap is below 1%, for problem instances with 1,000 potential farmers. We also show how our model can be used to gain various managerial insights. As an example, when constructing the contract menu endogenously, often a small number of contract options suffices, depending on the degree of heterogeneity among the farmer pool. Thus, relatively simple menus often suffice. The online appendices are available at https://doi.org/10.1287/msom.2018.0735. This paper has been accepted for the Manufacturing & Service Operations Management Special Issue on Value Chain Innovations in Developing Economies. [ABSTRACT FROM AUTHOR]

India, the world's largest groundwater user, withdraws about 230‐billion‐m3 groundwater annually for irrigation. Excessive groundwater pumping in India leads to rapid groundwater depletion and CO2 emissions. Here using multiple data sources (observation wells and Gravity Recovery Climate Experiment) to estimate groundwater depletion in India, as well as the associated chemistry and the pumping energy requirements, we provide the first estimate of the potential CO2 emissions due to bicarbonate extraction (CO2 release due to lowering of groundwater table) and groundwater pumping. We show that combined annual CO2 release due to bicarbonate extraction and pumping in India is approximately 32.01–131.74 million tons (31.29–131.02 million tons for pumping and 0.72 million tons for bicarbonate). The total estimated groundwater depletion in India is in the range of 122 to 199 billion m3 from the observation wells (1996–2016) and Gravity Recovery Climate Experiment (2002–2016). The CO2 emissions due to bicarbonate (~0.72 million tons/year) are dominated by those due to groundwater pumping (31.29–131.02 million tons/year) in India. However, the total (pumping and bicarbonate) estimated annual CO2 emission from groundwater is less than 2–7% of the total (annual) CO2 emission from India. Based on our unique data set collected from more than 500 farmers in Punjab, we show that a low‐cost intervention for irrigation scheduling based on soil moisture information can provide a sustainable solution by reducing groundwater pumping and CO2 emissions. The environmental problem of groundwater depletion in India is much more serious than the associated CO2 emissions, and hence, there is an urgent need for a regulation of groundwater use. Plain Language Summary: Groundwater depletion in India remains one of the most critical issues related to future food and freshwater security. Groundwater depletion causes a significant emission of CO2 in the United States as shown in the previous study. Since India is the largest consumer of groundwater, we hypothesized that CO2 emission due to groundwater depletion in India would be considerable. We, however, find that CO2 emission in India due to groundwater depletion and pumping is only about 2% of the total emissions combined from all the sectors. Our results show a significant decline (200 billion m3) in groundwater in India, especially in the northwestern and northcentral regions. We show that curbing the depletion of groundwater in India is a major challenge rather than reducing CO2 emission due to groundwater depletion and pumping. Key Points: The total estimated groundwater depletion in India is in the range of 122 to 199 billion m3The CO2 emissions due to bicarbonate is ~0.72 million tons/yearThe environmental problem of groundwater depletion in India is much more serious than the associated CO2 emissions [ABSTRACT FROM AUTHOR]

Water risk management is a ubiquitous challenge faced by stakeholders in the water or agricultural sector. We present a methodological framework for forecasting water storage requirements and present an application of this methodology to risk assessment in India. The application focused on forecasting crop water stress for potatoes grown during the monsoon season in the Satara district of Maharashtra. Pre-season large-scale climate predictors used to forecast water stress were selected based on an exhaustive search method that evaluates for highest ranked probability skill score and lowest root-mean-squared error in a leave-one-out cross-validation mode. Adaptive forecasts were made in the years 2001 to 2013 using the identified predictors and a non-parametric k-nearest neighbors approach. The accuracy of the adaptive forecasts (2001-2013) was judged based on directional concordance and contingency metrics such as hit/miss rate and false alarms. Based on these criteria, our forecasts were correct 9 out of 13 times, with two misses and two false alarms. The results of these drought forecasts were compared with precipitation forecasts from the Indian Meteorological Department (IMD). We assert that it is necessary to couple informative water stress indices with an effective forecasting methodology to maximize the utility of such indices, thereby optimizing water management decisions. [ABSTRACT FROM AUTHOR]

This article assesses the impact of the tensiometer on the consumption of groundwater and electric power in paddy cultivation in Indian Punjab, and its subsequent economic benefits. We find that compared to the continuous flooding method, the tensiometer-based application of irrigation reduces water and power consumption by 13%, cutting variable costs by 7% without any yield penalty. If 30% of the paddy area is irrigated following tensiometer-based schedules, then the state could save a total of 0.67 million ha m of water and 1516 million kWh of electric power in 2010-2025, with aggregate economic benefits of US$ 459 million. [ABSTRACT FROM AUTHOR]

India is a poster child for groundwater depletion and chronic water stress. Often, water sustainability is measured through an estimate of the difference between the average supply and demand in a region. However, water supply and demand are highly variable in time and space. Hence, measures of scarcity need to reflect temporal imbalances even for a fixed location. We introduce spatially distributed indices of water stress that integrate over time variations in water supply and demand. The indices reflect the maximum cumulative deficit in a regional water balance within year and across years. This can be interpreted as the amount that needs to be drawn from external storage (either aquifers or surface reservoirs or interarea transfers) to meet the current demand pattern given a variable climate and renewable water supply. A simulation over a long period of record (historical or projected) provides the ability to quantify risk. We present an application at a district level in India considering more than a 100 year data set of rainfall as the renewable supply, and the recent water use pattern for each district. Consumption data are available through surveys at the district level, and consequently, we use this rather than river basins as the unit of analysis. The rainfall endogenous to each district is used as a potentially renewable water supply to reflect the supply-demand imbalances directly at the district level, independent of potential transfers due to upstream-induced runoff or canals. The index is useful for indicating whether small or large surface storage will suffice, or whether the extent of groundwater storage or external transfers, or changes in demand are needed to achieve a sustainable solution. Implications of the analysis for India and for other applications are discussed. [ABSTRACT FROM AUTHOR]

Summary: Here we analyze the variability of MAM (March–April–May) and JJAS (June–July–August–September) seasonal Satluj River flow into the Bhakra dam in India through Pearson anomaly correlation and composite analyses with antecedent and concurrent seasonal climatic and atmospheric circulation patterns. The MAM seasonal inflow of Bhakra dam is significantly correlated with winter (DJF/FM) precipitation and temperature of the Satluj basin while the correlation with FM was more prominent for precipitation (snow=+0.72, rainfall=+0.60), and temperature (diurnal temperature range (DTR)=−0.76 and maximum temperature (T max)=−0.57). The JJAS inflow was also positively correlated with DJF/FM as well as JJAS precipitation of the Satluj basin while the correlation with basin average FM was the largest (+0.54). These suggested that both MAM and JJAS inflow anomalies are linked with DJF/FM climate over the Western Himalayas and adjoining north and central Indian plains, which were also found to be linked with the fluctuation of equatorial concurrent Sea Surface Temperature anomalies over the western Indian Ocean (max anomaly correlation was>+0.70) and mean sea level pressure over western pole of the Southern Oscillation sea-saw region (max Pearson anomaly correlation was∼+0.60). Low (high) MAM inflow was found to be associated with negative (positive) precipitation anomalies over the basin and north India in DJF and FM while FM precipitation anomaly is more concentrated over the Western Himalayas. In addition, low (high) JJAS inflow is also associated with negative (positive) precipitation anomalies over the basin and north India in DJF and over the Western Himalaya in FM and JJAS. Negative geopotential height anomaly at 500hPa (Z500) over Siberia and northwestern pacific in DJF, and positive Z500 anomaly over the northwest India in FM were noticed in low MAM inflow years. Whereas high inflow in MAM was linked with a negative Z500 anomaly between two positive Z500 anomaly regions – one over eastern Siberia stretched up to northern Pacific and second over the Eastern Europe in DJF, which gets stronger in FM. We also found southwesterly (northeasterly) wind vectors at 850hPa pressure level (uv850) bringing more (less) moisture to the Western Himalayas in DJF and FM in high (low) MAM/JJAS flow years. [Copyright &y& Elsevier]

The excessive exploitation of groundwater aquifers is emerging as a worldwide problem, but it is nowhere as dramatic and consequential as it is in India, the world's largest consumer, where hundreds of millions of people depend on it. Usually the problem is framed in terms of a long-term decline in water tables and its consequence for extraction costs, resource depletion, and the sustainability of irrigated agriculture. Here a comparative analysis is provided of coupled groundwater, energy, and irrigation dynamics in two groundwater intensive regions in India that differ in their underlying hydrogeology--the Indian Punjab with its deep alluvial aquifers and the Telangana region in south-central India with its shallow hard rock aquifers. Using a simple modeling framework and piezometric and agricultural time series, we show that in shallow aquifers the sense in which extraction is excessive is different, and is related to the short-term reliability of water supply rather than long-term sustainability. This has important repercussions for irrigated agricultural economies. [ABSTRACT FROM AUTHOR]

The excessive exploitation of groundwater aquifers is emerging as a worldwide problem, but it is nowhere as dramatic and consequential as it is in India, the world's largest consumer, where hundreds of millions of people depend on it. Usually the problem is framed in terms of a long-term decline in water tables and its consequence for extraction costs, resource depletion, and the sustainability of irrigated agriculture. Here a comparative analysis is provided of coupled groundwater, energy, and irrigation dynamics in two groundwater intensive regions in India that differ in their underlying hydrogeology-the Indian Punjab with its deep alluvial aquifers and the Telangana region in south-central India with its shallow hard rock aquifers. Using a simple modeling framework and piezometric and agricultural time series, we show that in shallow aquifers the sense in which extraction is excessive is different, and is related to the short-term reliability of water supply rather than long-term sustainability. This has important repercussions for irrigated agricultural economies. [ABSTRACT FROM AUTHOR]

The agriculture sector in India accounts for more than 85% of the total water use for irrigation. Within irrigation, the share of groundwater in the net irrigated area is around 50% to 55%, which is responsible for two-thirds of the total agricultural production. Agriculture also accounts for non-point-source pollution that arises from excessive use of fertilizers and pesticides. The Green Revolution was partly based on increased fertilizer use and intensive irrigation. During the past three decades, food production was tripled and poverty witnessed a decline. However, agriculture intensification led to overexploitation and pollution of groundwater resources, causing degradation of the environment and depletion of natural resources. Over and above, absence of significant public investment in surface water-based irrigation infrastructure, free or highly subsidized electricity, unregulated groundwater pumping, and irrational pricing policies have promoted cropping choices independent of resource endowments of water and energy. Over the long term, the current trends toward resource depletion and degradation, combined with a lack of proper reforms and policies that ensure agricultural sustainability and threats from climate change, pose a huge risk to farmers' income and can force poorer farmers out of the agricultural sector. In turn, these problems would lead to increased migration and poverty and decreased crop production, which are serious threats to food security. In this paper, we have discussed various challenges to water sustainability and food security of India. [ABSTRACT FROM AUTHOR]

Using a 1951–2003 gridded daily rainfall dataset for India, the authors assess trends in the intensity and frequency of exceedance of thresholds derived from the 90th and the 99th percentile of daily rainfall. A nonparametric method is used to test for monotonic trends at each location. A field significance test is also applied at the national level to assess whether the individual trends identified could occur by chance in an analysis of the large number of time series analyzed. Statistically significant increasing trends in extremes of rainfall are identified over many parts of India, consistent with the indications from climate change models and the hypothesis that the hydrological cycle will intensify as the planet warms. Specifically, for the exceedance of the 99th percentile of daily rainfall, all locations where a significant increasing trend in frequency of exceedance is identified also exhibit a significant trend in rainfall intensity. However, extreme precipitation frequency over many parts of India also appears to exhibit a decreasing trend, especially for the exceedance of the 90th percentile of daily rainfall. Predominantly increasing trends in the intensity of extreme rainfall are observed for both exceedance thresholds. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an operational approach to setting prices for groundwater in accordance with the interannual variability of monsoon rainfall and the dynamic cost of groundwater use to society. The pricing system is designed for the state of Tamil Nadu, India, where groundwater is largely unregulated and the electricity for pumping is heavily subsidized. Depletion of aquifers during the primary growing season causes environmental damage and drying of wells. The proposed price-setting system estimates the marginal social cost of groundwater use based on the current state of aquifer storage and the forecast of the coming monsoon. Prices are set prior to onset of the monsoon so farmers can plan crop rotations according to the expectation of seasonal rainfall as reflected in the pricing signal. During years that forecasts accurately characterize the probability distribution of monsoon outcomes the market signal encourages economically efficient use of the resource. When monsoons differ from the expected outcome farmers are cushioned by ancillary effects of the pricing system. [Copyright &y& Elsevier]

India is one of the largest user of groundwater with an annual abstraction rate of 230billion-m3for irrigation. The excessive abstraction of groundwater releases CO2due to theburning of fossil fuels for pumping and the presence of bicarbonate ion in the pumped water.With the help of different data sources, we estimated the CO2 emission in India fromgroundwater pumping and bicarbonate ion concentration. We estimated groundwaterdepletion from well level observations and Gravity Recovery and Climate Experiment(GRACE) groundwater storage observations. The estimated CO2 emission from groundwaterpumping is (31.29–131.02 million tons/year) is much higher than the emission frombicarbonate concentration (∼0.72 million tons/year). The estimated total CO2emission(pumping + bicarbonate) from groundwater is 32.01 – 131.74 million tons/yearwhich is less than 2-7 % of the annual CO2 emission from India. Based on theexperimental data collected from 500 farmers in Punjab suggests innovative intervention inirrigation based on soil moisture information can significantly reduce the pumpingwater requirement and thus CO2 emission. Our study proposes the urgent need forsustainable groundwater management in India since the environmental problemsdue to groundwater depletion are much severe than the associated CO2 emission. [ABSTRACT FROM AUTHOR]