Your search found 3 records
1 Ojha, H. R.; Sulaiman, R. V.; Sultana, P.; Dahal, K.; Thapa, D.; Mittal, N.; Thompson, P.; Bhatta, G. D.; Ghimire, L.; Aggarwal, P. 2014. Is South Asian agriculture adapting to climate change?: evidence from the Indo-Gangetic Plains. Agroecology and Sustainable Food Systems, 38:505-531. [doi: https://doi.org/10.1080/21683565.2013.841607]
Climate change ; Weather hazards ; Adaptation ; Agriculture ; Cropping systems ; Farmers ; Technological changes ; Socioeconomic environment ; Case studies / South Asia / India / Pakistan / Bangladesh / Nepal / Punjab / Indo-Gangetic Plains
(Location: IWMI HQ Call no: e-copy only Record No: H047253)
(0.35 MB)
Despite growing scientific consensus that agriculture is affected by climate change and variability, there is still limited knowledge on how agricultural systems respond to climate risks under different circumstances. Drawing on three case studies conducted in the Indo-Gangetic Plains, covering Nepal, Bangladesh, and the Indian state of Punjab, this article analyzes agricultural adaptation practices to climate change. In particular, we examine how farmers and other agricultural actors understand and respond to climate change. We identify a variety of adaptation practices related to changes in cropping system, technological innovations, and institutional changes. We also explore key challenges related to such emerging adaptive innovation processes in the region.
2 Mittal, N.; Bhave, A. G.; Mishra, A.; Singh, R. 2016. Impact of human intervention and climate change on natural flow regime. Water Resources Management, 30(2):685-699. [doi: https://doi.org/10.1007/s11269-015-1185-6]
River basins ; Stream flow ; Climate change ; Anthropogenic factors ; Human behavior ; Dam construction ; Hydrology ; Models ; Calibration ; Performance evaluation ; Ecosystems ; Monsoon climate / India / Kangsabati River
(Location: IWMI HQ Call no: e-copy only Record No: H047779)
(1.01 MB)
According to the ‘natural flow paradigm’, any departure from the natural flow condition will alter the river ecosystem. River flow regimes have been modified by anthropogenic interventions and climate change is further expected to affect the biotic interactions and the distribution of stream biota by altering streamflow. This study aims to evaluate the hydrologic alteration caused by dam construction and climatic changes in a mesoscale river basin, which is prone to both droughts and monsoonal floods. To analyse the natural flow regime, 15 years of observed streamflow (1950–1965) prior to dam construction is used. Future flow regime is simulated by a calibrated hydrological model Soil and Water Assessment Tool (SWAT), using ensemble of four high resolution (~25 km) Regional Climate Model (RCM) simulations for the near future (2021–2050) based on the SRES A1B scenario. Finally, to quantify the hydrological alterations of different flow characteristics, the Indicators of Hydrological Alteration (IHA) program based on the Range of Variability Approach (RVA) is used. This approach enables the assessment of ecologically sensitive streamflow parameters for the pre- and post-impact periods in the regions where availability of long-term ecological data is a limiting factor. Results indicate that flow variability has been significantly reduced due to dam construction with high flows being absorbed and pre-monsoon low flows being enhanced by the reservoir. Climate change alone may reduce high peak flows while a combination of dam and climate change may significantly reduce variability by affecting both high and low flows, thereby further disrupting the functioning of riverine ecosystems. We find that, in the Kangsabati River basin, influence of dam is greater than that of the climate change, thereby emphasizing the significance of direct human intervention.
3 Streefkerk, I. N.; van den Homberg, M. J. C.; Whitfield, S.; Mittal, N.; Pope, E.; Werner, M.; Winsemius, H. C.; Comes, T.; Ertsen, M. W. 2022. Contextualising seasonal climate forecasts by integrating local knowledge on drought in Malawi. Climate Services, 25:100268. [doi: https://doi.org/10.1016/j.cliser.2021.100268]
Climate change ; Drought ; Forecasting ; Local knowledge ; Rainfed farming ; Farmers ; Decision making ; Weather data ; Indicators ; Climatic zones ; Highlands ; Models / Malawi / Salima / Mangochi / Zomba
(Location: IWMI HQ Call no: e-copy only Record No: H050933)
https://www.sciencedirect.com/science/article/pii/S240588072100056X/pdfft?md5=2b30c30ffb45eb7db61622ee78e3aa8e&pid=1-s2.0-S240588072100056X-main.pdf
https://vlibrary.iwmi.org/pdf/H050933.pdf
https://vlibrary.iwmi.org/pdf/H050933.pdf
(4.76 MB) (4.76 MB)
Droughts and changing rainfall patterns due to natural climate variability and climate change, threaten the livelihoods of Malawi’s smallholder farmers, who constitute 80% of the population. Provision of seasonal climate forecasts (SCFs) is one means to potentially increase the resilience of rainfed farming to drought by informing farmers in their agricultural decisions. Local knowledge can play an important role in improving the value of SCFs, by making the forecast better-suited to the local environment and decision-making. This study explores whether the contextual relevance of the information provided in SCFs can be improved through the integration of farmers’ local knowledge in three districts in central and southern Malawi. A forecast threshold model is established that uses meteorological indicators before the rainy season as predictors of dry conditions during that season. Local knowledge informs our selection of the meteorological indicators as potential predictors. Verification of forecasts made with this model shows that meteorological indicators based on local knowledge have a predictive value for forecasting dry conditions in the rainy season. The forecast skill differs per location, with increased skill in the Southern Highlands climate zone. In addition, the local knowledge indicators show increased predictive value in forecasting locally relevant dry conditions, in comparison to the currently-used El Niño-Southern Oscillation (ENSO) indicators. We argue that the inclusion of local knowledge in the current drought information system of Malawi may improve the SCFs for farmers. We show that it is possible to capture local knowledge using observed station and climate reanalysis data. Our approach could benefit National Meteorological and Hydrological Services in the development of relevant climate services and support drought-risk reduction by humanitarian actors.
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