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The alarming decline in groundwater (GW) storage threatens the sustainable development of the water‐energy‐food linkages of a country. India has experienced severe dry spells during the years 2002, 2004, 2009, and 2012. However, the relative contribution of factors affecting GW depletion (such as variability in precipitation rate and groundwater extraction) still remains unknown. Here, we first evaluate the current GW condition by implementing reliability, resilience, and vulnerability analysis on the 5,988 monitoring well observations spanning over a period of two decades. Our study further improves the existing studies by isolating the quantity of GW depletion due to precipitation and nonprecipitation (GW extraction) factors using a multivariate regression model. Our study indicates that the nonprecipitation factor is most responsible for GW depletion in North India at a rate of 3.5 cm per year. In many parts of India, groundwater (GW) is used as the main source of freshwater for agricultural production. Continuous extraction of GW over the years has led to a reduction in GW storage. This affects agricultural productivity and increases the energy consumption to pump out GW from deeper wells. GW is composed of excess precipitation that percolates through the topsoil and accumulates over the hard rock material that soaks with water. Therefore, low precipitation reduces the replenishment of extracted GW and increases the rate of GW depletion. During the past decade, India has experienced severe low rainfall seasons during the years 2002, 2004, 2009, and 2012. We implement a methodology to monitor the change in GW, caused due to precipitation and nonclimatic factors over India using Gravity Recovery and Climate Experiment satellite and 5,988 monitoring well observations. Our analysis reveals that the continuous extraction of GW and reduced GW refill during low rainfall seasons before 2009 has considerably affected GW over India. Our study further provides insight into the sustainability of GW resources of India, which will help to develop sustainable GW management schemes in India. Groundwater (GW) storage depletion in India has major contributions from nonprecipitation factorsThe analysis of GW based on performance indices indicates low GW storage sustainability over the majority of Indian statesGrowing water demand has increased GW stress on the eastern coast of the Indian peninsula Groundwater (GW) storage depletion in India has major contributions from nonprecipitation factors The analysis of GW based on performance indices indicates low GW storage sustainability over the majority of Indian states Growing water demand has increased GW stress on the eastern coast of the Indian peninsula

Pest infestations in net-houses are not sometimes different from that under open-field conditions, necessitating usage of pesticides. To examine the hypothesis that bioagents may have more potential under restricted plant growing conditions, the predatory potential of green lace wing, Chrysoperla zastrowi sillemiEsben-Peterson (Neuroptera: Chrysopidae) was evaluated against the sucking pests of tomato under screen-house conditions. The rates of release were fixed as 4, 5, and 6 s instar grubs plant−1and a total of 3 releases were made at 7 days interval, with first release at appearance of the aphid, Myzus persicae(Sulzer) and whitefly, Bemisia tabaci(Gennadius). The pooled data for the years 2018 and 2019 revealed that, the release rates 4, 5, and 6 grubs plant−1were not statistically different in reducing the population of these pests. The factorial analysis based on the release rate and time of these releases suggested that single release of C. zastrowi sillemiat 4 grubs plant−1was effective against sucking pests in tomato grown under screen-house conditions.

We present the first observational evidence of changing patterns of extreme streamflows at multiple locations across Western Himalayan (WH) rivers. We find that the frequency of extreme flow events during the period 1980–2003 has doubled with a statistically significant increasing trend in annual maximum streamflow. We postulate that this streamflow change is due to the increased precipitation extremes occurring during both the summer monsoon and the winter seasons. We further found a stepwise increase of “chi‐gradient” in Bhagirathi and Sutlej Rivers, indicative of a landscape that facilitates rapid flow of water generating severe floods downstream. Our results highlight the severity of hydroclimatic changes underway in the WH region and the critical need for a hydro‐infrastructure for flood forecasting to benefit more than 17 million inhabitants and for ecosystem services to mitigate increasing flood hazards. Flooding in the Western Himalayan rivers has caused colossal loss of life and property in the recent decades. We present a first analysis of changing patterns of observed peak streamflow in Western Himalayan rivers at multiple locations, using high‐quality in situ data. With a high degree of confidence, we conclude that the occurrence of extreme flow events during the period of 1980–2003 has doubled with an increasing trend in annual maximum streamflow. Our analysis shows that this streamflow change is due to the increased precipitation extremes during both the summer monsoon and the winter seasons. We also found that the profiles of two Western Himalayan rivers (Bhagirathi and Sutlej) exhibit steep slopes in a stepwise manner, indicative of a landscape that rapidly responds to extreme precipitation by contributing to severe floods. Our results contextualize the severity of hydroclimatic changes underway in the WH region. Results also highlight the critical need for a hydro‐infrastructure and an operational flood forecasting system to benefit more than 17 million inhabitants and for ecosystem services to mitigate increasing flood hazards. First evidence from observations shows that occurrences of extreme streamflow in Western Himalayan rivers have doubled during 1980–2003Increasing trends of rainfall extremes and the geomorphology of the rivers have driven the dramatic increase in extreme streamflowThere is a critical need for a dedicated, high‐resolution, real‐time flood forecasting system for the Western Himalayan region

Accurate nowcasting of short‐lived extreme weather events is essential for saving millions of lives and property. Traditional methods of nowcasting are majorly focused on extrapolation of precipitation derived from radar reflectivity data, which often fail to capture the initiation and decay of weather systems. Earlier studies have shown the ability of high‐resolution Numerical Weather Prediction (NWP) models to better capture the structure and lifecycle of storms compared to data‐driven methods. However, the initial value problem of NWP makes it more challenging to be implemented for nowcasting applications. To handle such uncertainty from initial conditions, we have designed an NWP nowcasting system based on variational approach using WRF model. One of the major challenges of the variational methods in the nowcasting system is the choice of control variables used for generating background error statistics. Thus, we have investigated the impact of control variable options on improving the skill of variational‐based NWP nowcasting system. The proposed nowcasting system was tested for a heavy rainfall event that occurred over the Chennai city, India, on 1 December 2015, by assimilating Doppler Weather Radar data using different control variable options in Weather Research and Forecast—three‐dimensional (3DVAR)‐ and four‐dimensional variational data assimilation (4DVAR)‐based nowcasting system. Results show that control variables choices have a positive impact on 4DVAR analysis, particularly on radial velocity. Our results also indicate that assimilation of Doppler Weather Radar data with zonal and meridional momentum control variable in a 4DVAR system shows more than 30% improvement in precipitation forecast skill compared to the 3DVAR system. The 4DVAR assimilation of DWR data with zonal and momentum control variables improves skill of short term precipitation forecastsThe 4DVAR shows better skill compared to 3DVAR‐based nowcasting systemChoice of Control variables plays a major role in improving the skill of NWP nowcasting system