27 research outputs found
Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales
No full textThis Special Issue is expected to advance our understanding of these emerging patterns, teleconnections, and extreme events in a changing world for more accurate prediction or projection of their changes especially on different spatial–time scales
Train performance analysis using heterogeneous statistical models
No full textThis study investigated the eect of harsh winter climate on the performance of high speed passenger trains in northern Sweden. Novel approaches based on heterogeneous statistical models were introduced to analyse the train performance in order to take the time-varying risks of train delays into consideration. Specically, stratied Cox model and heterogeneous Markov chain model were used for modelling primary delays and arrival delays, respectively. Our results showed that the weather variables including temperature, humidity, snow depth, and ice/snow precipitation have signicant impact on the train performance.Special issue, also published as printed edition:Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales / [ed] Ankit Agarwal, Naiming Yuan, Kevin K.W. Cheung and Roopam Shukla. ISBN 978-3-0365-2953-0 (Hbk); ISBN 978-3-0365-2952-3 (PDF); DOI 10.3390/books978-3-0365-2952-3NoIC
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Farmer typology to understand differentiated climate change adaptation in Himalaya
No full textSmallholder farmers’ responses to the climate-induced agricultural changes are not uniform but rather diverse, as response adaptation strategies are embedded in the heterogonous agronomic, social, economic, and institutional conditions. There is an urgent need to understand the diversity within the farming households, identify the main drivers and understand its relationship with household adaptation strategies. Typology construction provides an efficient method to understand farmer diversity by delineating groups with common characteristics. In the present study, based in the Uttarakhand state of Indian Western Himalayas, five farmer types were identified on the basis of resource endowment and agriculture orientation characteristics. Factor analysis followed by sequential agglomerative hierarchial and K-means clustering was use to delineate farmer types. Examination of adaptation strategies across the identified farmer types revealed that mostly contrasting and type-specific bundle of strategies are adopted by farmers to ensure livelihood security. Our findings show that strategies that incurred high investment, such as infrastructural development, are limited to high resource-endowed farmers. In contrast, the low resourced farmers reported being progressively disengaging with farming as a livelihood option. Our results suggest that the proponents of effective adaptation policies in the Himalayan region need to be cognizant of the nuances within the farming communities to capture the diverse and multiple adaptation needs and constraints of the farming households. © 2019, The Author(s)
Demystifying vulnerability assessment of agriculture communities in the Himalayas: a systematic review
No full textEffect of Al doping on thermoelectric power of Mg1−xAlxB2 phonon drag and carrier diffusion contribution
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From hectares to households:Farmer centric crop-modelling to assess differential climate change impacts and adaptation response
No full textCrop simulation models (CSMs) are an important decision support tool in climate risk assessments and in designing resilient agricultural systems. However, these crop models simplify complex farming household diversity and systemic heterogeneities as they consider only the “mean” farmer. In this paper, we are particularly interested to understand how egalitarian is the crop simulation modeling approach in terms of its capacity to provide a more nuanced picture of impacts across different farmer types (classified based on assess and endowment of resources). To do this, we investigated the impact of climate change on maize and sorghum yield for different types of farming households through an ex-ante assessment, and the yield response to adaptation strategies (supplementary irrigation, switching varieties and agroforestry) in Northern Ghana. We find that with the same intensity of changes in climatic variables, yield impacts are different between maize and sorghum, with more impacts on maize across scenarios. We further observe that the highest impacts on maize (16% for low emission scenario and 25% for high emission scenario) and sorghum (6% low emission scenario and 14% for high emission scenario) are on the medium resource endowed farmer (MRE), whose yield losses are in order of magnitude of about twice of the low resource endowed farmer (LRE) and the high resource endowed (HRE) farmer. The yield response to adaptation measures was also different across the three farmer types and crops. Irrigation was the most effective adaptation strategy but was more effective for the MRE farmer for maize (52% low emission scenario and 66% for high emission scenario) and sorghum (74% low emission scenario and 76% for high emission scenario). However, using an improved variety was only effective for maize for the MRE farmer but not so much for sorghum across the farmer types. Our findings underline the critical need to integrate farming household diversity into crop simulation models, to understand the differential impacts of climate change and the prioritized adaptation responses within the same region. These differential impacts and responses should be considered in designing and implementing climate change resilience initiatives
Consistency in Vulnerability Assessments of Wheat to Climate Change—A District-Level Analysis in India
No full textIn India, a reduction in wheat crop yield would lead to a widespread impact on food security. In particular, the most vulnerable people are severely exposed to food insecurity. This study estimates the climate change vulnerability of wheat crops with respect to heterogeneities in time, space, and weighting methods. The study uses the Intergovernmental Panel on Climate Change (IPCC) framework of vulnerability while using composite indices of 27 indicators to explain exposure, sensitivity, and adaptive capacity. We used climate projections under current (1975–2005) conditions and two future (2021–2050) Representation Concentration Pathways (RCPs), 4.5 and 8.5, to estimate exposure to climatic risks. Consistency across three weighting methods (Analytical Hierarchy Process (AHP), Principal Component Analysis (PCA), and Equal Weights (EWs)) was evaluated. Results of the vulnerability profile suggest high vulnerability of the wheat crop in northern and central India. In particular, the districts Unnao, Sirsa, Hardoi, and Bathinda show high vulnerability and high consistency across current and future climate scenarios. In total, 84% of the districts show more than 75% consistency in the current climate, and 83% and 68% of the districts show more than 75% consistency for RCP 4.5 and RCP 8.5 climate scenario for the three weighting methods, respectively. By using different weighting methods, it was possible to quantify “method uncertainty” in vulnerability assessment and enhance robustness in identifying most vulnerable regions. Finally, we emphasize the importance of communicating uncertainties, both in data and methods in vulnerability research, to effectively guide adaptation planning. The results of this study would serve as the basis for designing climate impacts adjusted adaptation measures for policy interventions
