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Demographic outbursts and increased food demands invoke excessive use of pesticides in the agricultural field for increasing productivity which leads to the relentless decline of riverine health and its tributaries. These tributaries are connected to a plethora of point and non-point sources that transport pollutants including pesticides into the Ganga river's mainstream. Simultaneous climate change and lack of rainfall significantly increase pesticide concentration in the soil and water matrix of the river basin. This paper is intended to review the paradigm shift of pesticide pollution in the last few decades in the river Ganga and its tributaries. Along with this, a comprehensive review suggests the ecological risk assessment method which facilitates policy development, sustainable riverine ecosystem management, and decision-making. Before 2011, the total mixture of Hexachlorocyclohexane was found at 0.004–0.026 ng/mL in Hooghly, but now, the concentration has increased up to 0.465–4.132 ng/mL. Aftermath of critical review, we observed maximum residual commodities and pesticide contamination reported in Uttar Pradesh > West Bengal > Bihar > Uttara Khand possibly because of agricultural load, increasing settlement, and incompetency of sewage treatment plant in the reclamation of pesticide contamination. [ABSTRACT FROM AUTHOR]

The Indian Institute of Tropical Meteorology (IITM) has generated seasonal and extended range hindcast products for 1981–2008 and 2003–2016, respectively, using the IITM-Climate Forecast System (IITM-CFS) coupled model at various resolutions and configurations. Notably, our observational analysis suggests that for the 1981–2008 period, the tropical Indo-Pacific drivers, namely, the canonical El Niño-Southern Oscillation (ENSO), ENSO Modoki, and Indian Ocean Dipole (IOD). are significantly associated with the observed Kharif rice production (KRP) of various rice-growing Indian states. In this paper, using the available hindcasts, we evaluate whether these state-of-the-art retrospective forecasts capture the relationship of the KRP of multiple states with the local rainfall as well as the tropical Indo-Pacific drivers, namely, the canonical ENSO, ENSO Modoki, and the IOD. Using techniques of anomaly correlation, partial correlation, and pattern correlation, we surmise that the IITM-CFS successfully simulate the observed association of the tropical Indo-Pacific drivers with the local rainfall of many states during the summer monsoon. Significantly, the observed relationship of the local KRP with various climate drivers is predicted well for several Indian states such as United Andhra Pradesh, Karnataka, Odisha, and Bihar. The basis seems to be the model's ability to capture the teleconnections from the tropical Indo-Pacific drivers such as the IOD, canonical and Modoki ENSOs to the local climate, and consequently, the Kharif rice production. [ABSTRACT FROM AUTHOR]

Endowment of fertile Gangetic alluvial soil and abundant water resources, particularly groundwater resources altogether constitute core components for development of agriculture in Bihar. Efforts have been made in this paper to analyze factors responsible for changes in land use pattern, especially increase in current fallows, shrinking net sown area and shifting of land for non-agricultural purposes in the state. A larger concentration of current fallow lands was accounted for in Gaya, Patna, Purnea, Munger, Jehanabad and Kishanganj districts. The rainfall and road length have significant impact on the level of current fallows. Erratic monsoon and labour scarcity during the study period of present century resulted in accumulation of current fallow lands. It was further observed that the non-agricultural use of land was identified as the dominant factor for changes in common lands as it affected the current fallows negatively. It is a challenging task for policy makers to maximize the income of farmers from a continuously declining in net sown area, deteriorating climatic conditions as well as labour scarce conditions, thereby resulting in aggregation of current fallows. In order to boost the production and enhance farmer's income, it is necessary to discourage the rising tendency in current fallows or to bring current fallows under cultivation. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to analyze the trends and variability in extreme temperature indices and its impact on rice-wheat productivity over two districts of Bihar, India, which is part of the middle Indo-Gangetic Basin. Mann-Kendall non-parametric test was employed for detection of trend and Sen slope was determined to quantify the magnitude of such trends. We have analyzed 10 extreme temperature indices for monthly and seasonally. The influence of extreme temperature indices on rice-wheat productivity was determined using correlation analysis. As far as Patna is concerned, if the number of cool days during September ≥10, the rice productivity will increase due to the availability of sufficient duration to fill up the grain. However, higher warm days during all the months except June will affect the productivity. A significant negative correlation was noticed between maximum value of minimum temperature during September and rice productivity. Highly significant positive correlation was noticed between number of cool days during September with rice productivity while it was highly significant negative correlation in the case of number of warm days during the same month. As far as Samastipur is concerned, a negative correlation was noticed between wheat productivity and maximum value of maximum temperature (TXx) during February, but not statistically significant. The higher temperature may affect the kernel weight and thereby yield. It is seen that a critical value of TXx ≥29.2 °C will be harmful to wheat crop during February. A significant positive correlation of number of cool nights with wheat productivity also supports the above relationship. The critical values of extreme temperature indices during rice and wheat growing months provide an indicator to assess the vulnerability of rice-wheat productivity to temperature for Patna and Samastipur districts and there is a need to prepare an adaptive strategy and also develop thermo-insensitive rice-wheat high yielding varieties suitable for this region to sustain rice-wheat productivity under projected climate change situation. [ABSTRACT FROM AUTHOR]

Seasonal climate forecasts (SCFs) have gained popularity in agriculture for climate risk management studies. The available forms of SCFs are not conducive to decision making because of a mismatch in scales over space and time. In this study, available SCFs were disaggregated using the FResampler1 technique to simulate rice yield (cultivar PR 114) under different nitrogen levels and planting dates using DSSAT (Decision Support System for Agrotechnology Transfer) for Sitamarhi district, Bihar, India. Results showed that the late planting of rice predicted the highest yield (3800 kg ha-1) with high variability under SCF (wet) and 200 kg ha-1 application of nitrogen fertilizer. Similarly, for SCF (dry), the late planting of rice simulated high yield (3100 kg ha-1) attributes with 200 kg ha-1 of nitrogen fertilizer. However, rice yield under climatology (3450 kg ha-1) was more than SCF (dry) (3100 kg ha-1). Planting of rice on 15th June 2019 under the SCF (normal) predicted low uncertainty with high mean yields as compared to the mid (05th July 2019), and late (25th July 2019) planting. The present study showed that by applying SCF, we can have a better understanding on "relative" changes in yield attributes with fertilizer doses and planting dates, which may be adopted by the climate adviser to offset the climate risk without compromising productivity. [ABSTRACT FROM AUTHOR]

Land suitability analysis is a necessity to achieve sustainable agricultural productivity with the optimum utilization of the available resources. Lack of proper knowledge on the best combination of factors that suit production of rice and wheat has contributed to low production in the Sone river command, Bihar. The aim of this study is to develop land suitability maps for rice and wheat crop based on physical, chemical and climatic factors of production using a multi-criteria evaluation (MCE) and Geographic Information System (GIS) approach. Biophysical variables of soil, climate and topography have been considered for suitability analysis. This work also evaluates the impact of climate change (CC) on cropland suitability for rice and wheat crops. Climatic variable scenarios of rainfall were obtained from four GCMs (CAN-ESM2, MPI-ESM-MR, CSIRO, CMCC-CMS) for three future time slices (2011–2040, 2041–2070, 2071–2100) of representative concentration pathways (RCP) RCP 2.6, RCP 4.5 and RCP 8.5 scenarios. The observation data (1985–2011) from IMD Pune from 8 meteorological stations were used as the current baseline climatic data of rainfall, which is used to validate the cropland suitability model. The results of CC indicate that there is a significant variability in the distribution of rainfall in the projected period 2011–2100 with respect to the baseline period. The results also show a concomitant increase in the projected crop suitability area of wheat from 17 to 35% and decrease in area for rice from 31 to 21% when compared with baseline for highly suitable area. [ABSTRACT FROM AUTHOR]

The change in future climate will have a prominent impact on crop production and water requirement. Crop production is directly related to climatic variables. Temperature, solar radiation, wind, precipitation, CO2 concentration and other climatic variables dictate crop yield. This study, based on long-term historical data, investigates the patterns and changes in climatic variables (precipitation, temperature, and solar radiation) that would most significantly affect the future crop production in many parts of the world, and especially in India, where most farmers depend on rainfall for rice production. Statistical analyses—box and whisker plot, mean absolute error, Taylor diagram, double mass curve, Mann–Kendall trend test, and projected climate change—were used to assess the significance of the climatic factors for the purpose of agricultural modeling. Large variability in precipitation may cause the flash floods and affect the farming, and at the same time, increase in temperature from baseline period will lead to high water requirement by crops, and may cause drought if rainfall does not occur. Decrease in solar radiation will affect crop growth and development, and thus, would hamper the crop production. The results of this study would be useful in identifying the negative issues arising from climate change in future agricultural practices in Bihar, India. Furthermore, the results can also help in developing management strategies to combat the climate change impact on crop production. [ABSTRACT FROM AUTHOR]