Browsing by Author "Geetika Sonkar"

Now showing 1 - 8 of 8

Disaster Risk Reduction Including Climate Change Adaptation Over South Asia: Challenges and Ways Forward
(Beijing Normal University Press, 2019) Rajesh K. Mall; Ravindra K. Srivastava; Tirthankar Banerjee; Om Prakash Mishra; Diva Bhatt; Geetika Sonkar
South Asia is vulnerable to a variety of hydrometeorological hazards, which are often cross-boundary in nature. Climate change is expected to influence many of these hazards. Thus, climate-related risks over South Asia make disaster risk reduction (DRR) and climate change adaptation (CCA) key policy goals. Recently there is an increasing consensus that DRR including CCA should be embedded in development planning. Disaster risk reduction including CCA has progressively gained importance in global governance. Across South Asia, however, such integration is only in a preliminary stage. This review was to assess the existing status and scope of DRR including CCA in development projects across South Asia, so that an effective and achievable deliberation may be made to regional policymakers. A total of 371 projects relevant to CCA and DRR were reviewed. The project inventory was diverse in nature with respect to location, scale, sectoral focus, and strategic importance. Bangladesh, India, and Bhutan were observed to be proactive in implementing DRR- and CCA-related projects. Meta-analysis of the project inventory suggests an urgent need for an individual and collaborative convergence of processes for DRR and CCA through policies, plans, strategies, and programs. © 2018, The Author(s).
Evaluating the performance of RegCM4.0 climate model for climate change impact assessment on wheat and rice crop in diverse agro-climatic zones of Uttar Pradesh, India
(Springer Netherlands, 2018) R.K. Mall; Nidhi Singh; K.K. Singh; Geetika Sonkar; Akhilesh Gupta
The paper aims to explore the biasness in the RegCM climate model outputs for diverse agro-climatic zones of Uttar Pradesh, India, with emphasis on wheat (Rabi growing season) and rice (Kharif growing season) yields with and without bias correction using quantile mapping approach for the baseline period of 1971–2000. The result shows that RCM highly underestimated the maximum and minimum temperature. There exists a bias towards lower precipitation in annual and Kharif and higher in Rabi along with strikingly low intense warm (maximum temperature > 45 °C and 40 °C) and high cold events (maximum temperature < 20 °C and minimum temperature < 5 °C) in the RCM simulation and biased towards low extreme rainfall > 50 mm/day. Bias correction through quantile mapping approach, however, showed excellent agreement for annual and seasonal maximum and minimum temperature and satisfactory for extreme temperatures but drastically failed to correct rainfall. The study also quantified the biasness in the simulated potential, irrigated, and rainfed wheat and rice yield using DSSAT (Decision Support System for Agro-technology Transfer) crop model by employing observed, RCM baseline, and RCM baseline bias-corrected weather data. The grain yields of RCM-simulated wheat and rice were high while the bias-corrected yield has shown good agreement with corresponding observed yield. Future research must account for the development of more reliable RCM models and explicitly bias correction method in specific to complement future analysis. © 2018, Springer Nature B.V.
Evaluation of RegCM4 climate model for assessment of climate change impact on crop production
(India Meteorological Department, 2018) Nidhi Singh; R.K. Mall; Geetika Sonkar; K.K. Singh; A. Gupta
For evaluating the impacts of climate change on crop yields regional climate models (RCMs) are now considered better than general circulation models (GCMs). In order to assess what extent the climate output of RCM-RegCM4.0 is biased, this is analysed by comparing the base line simulated daily weather with the observed weather for the corresponding year (1971-2000) over Varanasi. The result shows that the RCM output is biased towards lower annual maximum and minimum temperature by 5.4 °C and 1.7 °C respectively. Seasonal analysis shows that the RCM output is underestimating the kharif (Rice) season maximum and minimum temperature by 3.0 °C and 1.5 °C respectively and the rabi (wheat) season maximum and minimum temperature by 6.7 °C and 1.4 °C respectively. The RCM output overestimates the annual and rabi rainfall while it underestimates kharif rainfall. It is also overestimating the annual, kharif and rabi season rainy days. Most importantly, model underestimates the extreme events, i.e., extreme temperature and heavy rainfall. The study also includes assessment of biasness in yields of wheat and rice simulated using CERES-wheat and CERES-rice crop models employing observed and RCM simulated weather data. Due to biasness in the extreme events in RCM baseline data the simulated wheat and rice grain yield during several years were overestimated compared to observed yield. The present RCM output is overestimating the different climatic variables in comparison to present observed climate for annual as well as seasonal. Therefore, framing of better management practices, mitigation programme and planning and policy making based on climate model output must ensure to get the reliable and validated RCM climate output. For that we need more precise and improved regional climate models through more research in climate modelling. © 2018, India Meteorological Department. All rights reserved.
Impact of Climate Variability on the Rice Yield in Uttar Pradesh: an Agro-Climatic Zone Based Study
(Springer Basel, 2019) Diva Bhatt; Geetika Sonkar; R.K. Mall
In the backdrop of the established fact that the climate and agricultural produce foster a close-knit relation, the present study explores the impacts of climate variability on the rice yields across diverse agro-climatic zones of Uttar Pradesh, India. The time-series non-parametric Mann-Kendall trend test was applied to study long term (both annual and seasonal) weather and yield data sets. Minimum temperature, encompassing all the zones, was found to be increasing within the range of 0.06 to 0.44 °C per decade. The ‘kharif’ season maximum temperature trends were found increasing in most zones. In terms of annual and seasonal rainfall trends, the results were mostly non-significant, except for Bhabhar and Tarai Zone which had witnessed a very high decadal trend indicating towards the occurrences of intense rainfall events. North Eastern Plain Zone needs a special mention owing to its large number of extreme rainfall events in three categories (>50 to <100 mm/day; >100 to <150 mm/day; >150 mm/day). Considering the annual/seasonal temperature and rainfall variability in the region, the warming trend along with spatio-temporally uncertain rainfall is likely to inflict significant impact upon the rice crop. Consequently, there is a dire need to devise strategies capable of dealing with the impacts of the prevailing climate variability on rice yields in this state of India through development of suitable adaptation options for sustainable production. The continuous and rigorous studies into this field of agro-meteorology subjected to impact assessment call for international action plans that are designed in a frame of ‘bottom-up approach’ or a ‘local to regional to country level’ strategic implementation of adaptation options to sustain yields in the rice fields. © 2019, Springer Nature Switzerland AG.
Sensitivity of evapotranspiration to climate change using DSSAT model in sub humid climate region of Eastern Uttar Pradesh
(Springer Science and Business Media Deutschland GmbH, 2019) Shoobhangi Tyagi; Nidhi Singh; Geetika Sonkar; R.K. Mall
Climate variability impacts the components of hydrological cycle especially evapotranspiration (ET) and soil moisture, that plays a crucial role in determining water flux of an agriculture system and is thus, essential to study the response of ET to climate change. The present study is an attempt to understand the trend in observed ET (1978–2003) and variation in projected ET RegCM4.0, RCP 4.5 scenario during 2040–2060. Observed ET is compared with simulated ET using NCEP, NASA Power, RegCM4.0 and agriculture field data. Apart from studying the effect of relative humidity (RH), solar radiation (SLR), minimum and maximum temperature and wind speed (WS) on ET, the FAO Penman–Monteith and Priestly–Taylor methods in CERES Rice and CERES Wheat crop model were used to simulate ET. Further, the cumulative impact of rainfall and ET on agriculture drought has been estimated based on standardized Reconnaissance Drought Index (RDIst). The result shows a declining trend of ET during 1978–2003, but an increase during 2040s (2040–2061) for both wheat and rice. Overall, the ET simulated using weather data input from agriculture field shows highest concordance with observed ET, followed by NASA/RegCM4 and NCEP. Moreover, the FAO Penman–Monteith gives more accurate result in comparison to the Priestley–Taylor method. Environmental modification suggests that RH is the most influential parameter for ET followed by temperature, SLR and WS. Based on RDIst it was observed that rainfall is negatively associated with ET and their cumulative effect on water availability can be efficiently estimated using drought index. © 2018, Springer Nature Switzerland AG.
Simulating the Impacts of Climate Change on Sugarcane in Diverse Agro-climatic Zones of Northern India Using CANEGRO-Sugarcane Model
(Springer, 2020) Geetika Sonkar; Nidhi Singh; R.K. Mall; K.K. Singh; Akhilesh Gupta
CANEGRO-Sugarcane model was used to assess the impact of climate change on sugarcane in different combinations of elevated temperature and CO2 concentrations. Additionally, we used dynamically downscaled bias-corrected regional climate model (RCM) data using RegCM4 under RCP4.5 scenario (2040–2060) to project the future change in sugarcane stalk fresh mass (SFM) and sucrose mass (SM). The results showed an increase in temperature, rainfall and solar radiation in the future projections at the study site. The SFM and SM were found to be vulnerable (3–25% decrease) by increasing temperature (1–4 °C), however, a higher concentration (2–14% increase) was observed for both SFM and SM under elevated CO2 levels (450–850 ppm). The combined effect of increased temperature and elevated CO2 had a beneficial effect on SFM but negative on SM (more for rainfed condition). Overall, SFM was projected to increase by 3–39% (rainfed) and 7–47% (irrigated) in 2040–2060 relative to 1971–2000 in diverse agro-climatic zones of the region. Similarly, SM was projected to decrease by 9–69% (rainfed) and 6–37% (irrigated). In general, water stress conditions combined with the projected increase in temperature adversely affected the sugarcane. The findings suggest the development of a efficient water use, heat-tolerant cane variety and improved farm management strategies in the near future to assist the sugar industry and to adapt to the changing climate in northern India. This is required in the greater perspective of decrease in sucrose mass in spite of double-fold increase in CO2. © 2019, Society for Sugar Research & Promotion.
Simulation modeling and climate change: issues and challenges
(2014) R.K. Mall; Diva Bhatt; Geetika Sonkar; T. Banerjee
[No abstract available]
Vulnerability of Indian wheat against rising temperature and aerosols
(Elsevier Ltd, 2019) Geetika Sonkar; R.K. Mall; Tirthankar Banerjee; Nidhi Singh; T.V. Lakshmi Kumar; Ramesh Chand
Effect of different temperature matrices and aerosols was found negative on wheat yield with significant spatial variations. © 2019 Elsevier Ltd; Potential impacts of change in climate on Indian agriculture may be significantly adverse, if not disastrous. There are projections of potential loss in wheat yield due to the rise in daily minimum (Tmin) and maximum (Tmax) temperature, but only few researchers have considered the extent of such loss on a spatial scale. We therefore, systematically studied the effect of change in Tmax, Tmean (daily average temperature) and Tmin, solar radiation (Srad) and precipitation (RAIN) during wheat growing seasons (from 1986 to 2015) on wheat crop yield over five wheat growing zones across India, taking into account the effect modification by aerosol loading (in terms of aerosol optical depth, 2001–2015). We note that for the entire India, 1 °C rise in Tmean resulted a 7% decrease in wheat yield which varied disproportionately across the crop growing zones by a range of −9% (peninsular zone, PZ) to 4% (northern hills zone, NHZ). The effect of Tmean on wheat yield was identical to the marginal effect of Tmax and Tmin, while 1% increase in Srad enhance wheat yield by 4% for all India with small geographical variations (2–5%), except for the northern hill region (−4%). Rise in 1 °C Tmean exclusively during grain filling duration was noted positive for all the wheat growing regions (0–2%) except over central plain zone (−3%). When estimates of weather variables on wheat yield was combined with the estimated impact of aerosols on weather, the most significant impact was noted over the NHZ (−23%), which otherwise varied from −7% to −4%. Overall, the study brings out the conclusive evidence of negative impact of rising temperature on wheat yield across India, which we found spatially inconsistent and highly uncertain when integrated with the compounding effect of aerosols loading. © 2019 Elsevier Ltd