Your search found 10 records
1 Kumar, S. N.; Aggarwal, Pramod; Rani, S.; Jain, S.; Saxena, R.; Chauhan, N. 2011. Impact of climate change on crop productivity in Western Ghats, coastal and northeastern regions of India. Current Science, 101(3):332-341.
Climate change ; Crop production ; Impact assessment ; Simulation models ; Coastal area ; Irrigated farming ; Rainfed farming ; Irrigated rice ; Potatoes ; Maize ; Wheat ; Mustard ; Sorghum / India / Western Ghats
(Location: IWMI HQ Call no: e-copy only Record No: H044599)
(8.86 MB) (8.86MB)
Assessment on impact of climate change on major crops in ecologically sensitive areas, viz. the Western Ghats (WG), coastal districts and northeastern (NE) states of India, using InfoCrop simulation model, projected varying impacts depending on location, climate, projected climate scenario, type of crop and its management. Irrigated rice and potato in the NE region, rice in the eastern coastal region and coconut in the WG are likely to gain. Irrigated maize, wheat and mustard in the NE and coastal regions, and rice, sorghum and maize in the WG may lose. Adaptation strategies such as change in variety and altered agronomy can, however, offset the impacts of climate change.
2 Kumar, S. N.; Aggarwal, Kumar Pramod; Uttam, K.; Surabhi, J.; Rani, D. N. S.; Chauhan, N.; Saxena, R. 2016. Vulnerability of Indian mustard (Brassica juncea (L.) Czernj. Cosson) to climate variability and future adaptation strategies. Mitigation and Adaptation Strategies for Global Change, 21:403-420. [doi: https://doi.org/10.1007/s11027-014-9606-z]
Climate change ; Adaptation ; Models ; Temperature ; Rain ; Carbon dioxide ; Irrigated farming ; Crop yield ; Mustard / India
(Location: IWMI HQ Call no: e-copy only Record No: H046904)
A simulation study has been carried out using the InfoCrop mustard model to assess the impact of climate change and adaptation gains and to delineate the vulnerable regions for mustard (Brassica juncea (L.) Czernj. Cosson) production in India. On an all India basis, climate change is projected to reduce mustard grain yield by ~2 % in 2020 (2010–2039), ~7.9 % in 2050 (2040–2069) and ~15 % in 2080 (2070–2099) climate scenarios of MIROC3.2.HI (a global climate model) and Providing Regional Climates for Impact Studies (PRECIS, a regional climate model) models, if no adaptation is followed. However, spatiotemporal variations exist for the magnitude of impacts. Yield is projected to reduce in regions with current mean seasonal temperature regimes above 25/10 °C during crop growth. Adapting to climate change through a combination of improved input efficiency, additional fertilizers and adjusting the sowing time of current varieties can increase yield by ~17 %. With improved varieties, yield can be enhanced by ~25 % in 2020 climate scenario. But, projected benefits may reduce thereafter. Development of short-duration varieties and improved crop husbandry becomes essential for sustaining mustard yield in future climates. As climatically suitable period for mustard cultivation may reduce in future, short-duration (<130 days) cultivars with 63 % pod filling period will become more adaptable. There is a need to look beyond the suggested adaptation strategy to minimize the yield reduction in net vulnerable regions.
3 Asseng, S.; Ewert, F.; Martre, P.; Rotter, R. P.; Lobell, D. B.; Cammarano, D.; Kimball, B. A.; Ottman, M. J.; Wall, G. W.; White, J. W.; Reynolds, M. P.; Alderman, P. D.; Prasad, P. V. V.; Aggarwal, Pramod Kumar; Anothai, J.; Basso, B.; Biernath, C.; Challinor, A. J.; De Sanctis, G.; Doltra, J.; Fereres, E.; Garcia-Vila, M.; Gayler, S.; Hoogenboom, G.; Hunt, L. A.; Izaurralde, R. C.; Jabloun, M.; Jones, C. D.; Kersebaum, K. C.; Koehler, A-K.; Muller, C.; Kumar, S. N.; Nendel, C.; O’Leary, G.; Olesen, J. E.; Palosuo, T.; Priesack, E.; Rezaei, E. E.; Ruane, A. C.; Semenov, M. A.; Shcherbak, I.; Stockle, C.; Stratonovitch, P.; Streck, T.; Supit, I; Tao, F.; Thorburn, P. J.; Waha, K.; Wang, E.; Wallach, D.; Wolf, J.; Zhao, Z.; Zhu, Y. 2015. Rising temperatures reduce global wheat production. Nature Climate Change, 5:143-147. [doi: https://doi.org/10.1038/nclimate2470]
(Location: IWMI HQ Call no: e-copy only Record No: H046906)
Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time.
4 Kumar, S. N.; Aggarwal, Pramod Kumar; Rani, D. N. S.; Saxena, R.; Chauhan, N.; Jain, S. 2014. Vulnerability of wheat production to climate change in India. Climate Research, 59(3):173-187. [doi: https://doi.org/10.3354/cr01212]
Climate change ; Adaptation ; Temperature ; Agricultural production ; Crop production ; Wheat ; Models ; Carbon dioxide ; Fertilization ; Emission ; Soils / India
(Location: IWMI HQ Call no: e-copy only Record No: H046905)
The production of wheat, a crop sensitive to weather, may be influenced by climate change. The regional vulnerability of wheat production to climate change in India was assessed by quantifying the impacts and adaptation gains in a simulation analysis using the InfoCrop-WHEAT model. This study projects that climate change will reduce the wheat yield in India in the range of 6 to 23% by 2050 and 15 to 25% by 2080. Even though the magnitude of the projected impacts is variable, the direction is similar in the climate scenarios of both a global (GCMMIROC3.2.HI) and a regional climate model (RCM-PRECIS). Negative impacts of climate change are projected to be less severe in low-emission scenarios than in high-emission scenarios. The magnitude of uncertainty varies spatially and increases with time. Differences in sowing time is one of the major reasons for variable impacts on yield. Late-sown areas are projected to suffer more than the timely-sown ones. Considerable spatial variation in impacts is projected. Warmer central and south-central regions of India may be more affected. Despite CO2 fertilization benefits in future climate, wheat yield is projected to be reduced in areas with mean seasonal maximum and minimum temperatures in excess of 27 and 13°C, respectively. However, simple adaptation options, such as change in sowing times, and increased and efficient use of inputs, could not only offset yield reduction, but could also improve yields until the middle of the century. Converting late-sown areas into timely-sown regions could further significantly improve yield even with the existing varieties in the near future. However, some regions may still remain vulnerable despite the adaptation interventions considered. Therefore, this study emphasises the need for intensive, innovative and location-specific adaptations to improve wheat productivity in the future climate.
5 Zacharias, M.; Kumar, S. N.; Singh, S. D.; Rani, D. N. S.; Aggarwal, Pramod Kumar. 2014. Assessment of impacts of climate change on rice and wheat in the Indo-Gangetic plains. Journal of Agrometeorology, 16(1):9-17.
Climate change ; Monsoon climate ; Temperature ; Rain ; Crop modelling ; Crop management ; Rice ; Wheat / India / Pakistan / Bangladesh / Indo-Gangetic Plains
(Location: IWMI HQ Call no: e-copy only Record No: H046907)
In this paper, the climate change scenarios of A2 and B2 for 2070-2100 time scale (denoted as 2080) for several key locations of India and its impact on rice and wheat crops based on regional climate model (PRECIS) were described. The PRECIS projects an increase in temperature over most parts of India especially in the IGP (Indo-Gangetic Plains), the region that presently experiences relatively low temperatures. Extreme high temperature episodes and rainfall intensity days are projected to become more frequent and the monsoon rainfall is also projected to increase. Rabi (mid Nov-March) season is likely to experience higher increase in temperature which could impact and hence become threat to the crops which really require low temperature for their growth. Climatic variability is also projected to increase in both A2 and B2 scenarios. All these projected changes are likely to reduce the wheat and rice yields in Indo-Gangetic plains of India. It is likely that there will be more number of years with low yields occurs towards the end of the century. Such yield reductions in rice and wheat crops due to climate change are mediated through reduction in crop duration, grain number and grain filling duration. The yield loss will be more in A2 scenario compared to B2. These quantitative estimates still have uncertainties associated with them, largely due to uncertainties in climate change projections, future technology growth, availability of inputs such as water for irrigation, changes in crop management and genotype. These projections nevertheless provide a direction of likely change in crop productivity in future climate change scenarios.
6 Islam, A.; Shirsath, P. B.; Kumar, S. N.; Subash, N.; Sikka, A. K.; Aggarwal, Pramod Kumar. 2014. Modeling water management and food security in India under climate change. In Ahuja, L. R.; Ma, L.; Lascano, R. J. (Eds.). Advances in agricultural systems modeling transdisciplinary research, synthesis, and applications: practical applications of agricultural system models to optimize the use of limited water. Madison, WI, USA: American Society of Agronomy; Crop Science Society of America; Soil Science Society of America. pp.267-315. [doi: https://doi.org/10.2134/advagricsystmodel5.c11]
Water management ; Water availability ; Water allocation ; Water supply ; Water resources ; Water productivity ; Irrigation water ; Irrigation schemes ; Irrigation canals ; Food security ; Climate change ; Impact assessment ; Adaptation ; Temperature ; Rain ; Precipitation ; Evapotranspiration ; Hydrology ; Simulation models ; Erosion ; Crop production ; Crop yield ; Rice ; Maize ; Wheat ; Watershed management ; River basins ; Carbon dioxide / India
(Location: IWMI HQ Call no: e-copy only Record No: H046908)
Climate change and variability will impact water availability and the food security of India. Trend analyses of historical data indicate an increase in temperature and changes in rainfall pattern in different parts of the country. The general circulation models (GCMs) also project increased warming and changes in precipitation patterns over India. This chapter presents examples of model applications in water management and crop yield simulation in India, focusing on climate change impact assessment. Simulation models have been successfully applied for rotational water allocation, deficit irrigation scheduling, etc. in different canal commands. Application of a universal soil loss equation in a distributed parametric modeling approach by partitioning watershed into erosion response units suggests that by treating only 14% of the watershed area, a 47% reduction in soil loss can be achieved. Simulation studies conducted using different hydrological models with different climate change projections and downscaling approaches showed varied hydrological responses of different river basins to the future climate change scenarios, depending on the hydrological model, climate change scenarios, and downscaling approaches used. Crop yield modeling showed decreases in irrigated and rainfed rice (Oryza sativa L.) yields under the future climate change scenarios, but the decrease is marginal for rainfed rice. Maize (Zea mays L.) yields in monsoon may be adversely affected by a rise in atmospheric temperature, but increased rain can partly offset those losses. Wheat (Triticum aestivum L.) yields are likely to be reduced by 6 to 23% and 15 to 25% during the 2050s and 2080s, respectively. A combined bottom-up participatory process and top-down integrated modeling tool could provide valuable information for locally relevant climate change adaptation planning.
7 Gebrezgabher, Solomie; Kumar, S. N.; Vishwanath, P. S.; Otoo, Miriam. 2018. Municipal solid waste composting with carbon credits for profit (IL&FS, Okhla, India) - Case Study. In Otoo, Miriam; Drechsel, Pay (Eds.). Resource recovery from waste: business models for energy, nutrient and water reuse in low- and middle-income countries. Oxon, UK: Routledge - Earthscan. pp.391-399.
Municipal wastes ; Solid wastes ; Composting ; Carbon credits ; Organic fertilizers ; Public-private cooperation ; Partnerships ; Supply chain ; Business models ; Financing ; Case studies / India / Okhla
(Location: IWMI HQ Call no: IWMI Record No: H048661)
(0.98 MB)
8 Otoo, Miriam; Kumar, S. N.; Vishwanath, P. S.; Hope, L. 2018. Partnership-driven municipal solid waste composting at scale (KCDC, India) - Case Study. In Otoo, Miriam; Drechsel, Pay (Eds.). Resource recovery from waste: business models for energy, nutrient and water reuse in low- and middle-income countries. Oxon, UK: Routledge - Earthscan. pp.400-410.
Partnerships ; Municipal wastes ; Solid wastes ; Composting ; Waste management ; Cost recovery ; Socioeconomic environment ; Business models ; Supply chain ; Government agencies ; Sanitation ; Local government / India / Bangalore / Karnataka
(Location: IWMI HQ Call no: IWMI Record No: H048662)
(1.04 MB)
9 Otoo, Miriam; Hope, L.; Kumar, S. N.; Vishwanath, P. S.; Atukorala, I. 2018. Franchising approach to municipal solid waste composting for profit (Terra Firma, India) - Case Study. In Otoo, Miriam; Drechsel, Pay (Eds.). Resource recovery from waste: business models for energy, nutrient and water reuse in low- and middle-income countries. Oxon, UK: Routledge - Earthscan. pp.411-421.
Municipal wastes ; Solid wastes ; Composting ; Waste management ; Organic fertilizers ; Biogas ; Plastics ; Recycling ; Public bodies ; Resource recovery ; Market economies ; Business models ; Supply chain / India / Bangalore / Karnataka
(Location: IWMI HQ Call no: IWMI Record No: H048663)
(1.14 MB)
10 Panjwani, Shweta; Kumar, S. N.. 2023. Techniques to preprocess the climate projections—a review. Theoretical and Applied Climatology, 152(1-2):521-533. [doi: https://doi.org/10.1007/s00704-023-04431-2]
Climate prediction ; Techniques ; Climate change ; Climate models ; Climatic data ; Decision making ; Impact assessment ; Extreme weather events
(Location: IWMI HQ Call no: e-copy only Record No: H052035)
(0.95 MB)
Model-derived climate projections have been used by decision-makers for climate change impact assessment, adaptation, and vulnerability studies at large scale. However, they are reported to have significant bias against observed data. The accuracy of dynamically downscaled data depends on the large-scale forcings; however, they still have some systematic errors, so it requires further bias correction. Before using these data for further studies, they need to be processed for performance evaluation. This review article provides current understanding in the field of analyzing global climate projections. It includes studies from the multi-criteria decision-making approaches along with its pros/cons to the performance evaluation of climate models. Moreover, this article discusses several bias correction approaches, multi-model ensemble approaches, and their applications for climate change studies.
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