ICRISAT Archival Report 2010

Special Project Funding:
Asian Development Bank (ADB)
Intermediate output target in 2010: NARS partners Capacity building: Training Course on Cropping System
Models Cropping System Models: Application in Land Resource Management
Achievement of Output Target:
100%
Countries Involved:
India, China, Bangladesh, Sri Lanka, Thailand and Vietnam
Partner Institutions:
The course was attended by 32 participants from India, the Philippines, Bangladesh, Thailand, Sri Lanka, China,
Colombia, USA, Vietnam and Botswana. The India Meteorological Department (IMD), Govt. of India, has
sponsored 10 participants for this course, the ADB-ICRISAT project on `Adaptation Strategies to Climate
Change’ has sponsored 6 participants, and IFPRI sponsored 3 participants.
Objectives/Rationale:
The ADB funded project also aims at developing a more informed coping strategies and safety nets which can
be honed specifically by developing the knowledge and capacity of implementing agencies implementing the
project on Vulnerability to climate change: adaptation strategies and layers of resilience. This will help the to
consolidate the best practices and institutional innovations for mitigating effects of climate change, and develop
strategies to address socio-economic problems relating to changing weather patterns, improved livelihood
resilience of risk-averse farmers and concurrent investment by stakeholders. This effort will be greatly enhanced
through a better quantification of the temporal and spatial impact of climate risk. Such an effort will enable
identification, promotion and adoption of innovations that have a high probability of success and impact in the
context of variable climates This will science-based solutions and pro-poor approaches to adapting agricultural
systems to climate change for the benefit of the rural poor and the most vulnerable farmers in the semi-arid
regions of Asia, particularly Bangladesh, India, Pakistan, Sri Lanka and the People’s Republic of China (PRC),
Thailand and Vietnam. Hence, ICRISAT (EA) trained NARS staff in modeling activities on biotic, abiotic and
socio-economic variables in order to improve the understanding of climate change variability and its impact on
agriculture.
Methodology:
The areas where capacity building training workshop include:
• Geostatistical methods for the spatial analysis of environmental during 5-9 April, 2010
• Cropping System Models: Application in Land Resource Management during 18-22 October, 2010
Progress/Results:
The capacity of national program partners as well as key staff benefited significantly through the training
programs undertaken through ADB project. After conducting training of partners in the areas like;
Methodologies and Conduct of Surveys, vulnerability ad agro-climatic analysis, data collection through
qualitative and quantitative tools including social tools and familiarity with rapid rural appraisal instrument
developed exclusively for data collection in 2009, it was felt necessary to provide somewhat advanced training
incorporating both theoretical and practical knowledge regarding different research methods, simulation
modeling, geospatial analysis and issues associated with climatic studies. Hence, two trainings with expert
trainers from University of Florida were organized under aegis of Knowledge, Management and Sharing
(KMS). The details are as under:
(a) Training on Geostatistical Analysis of Environmental Data from 5 to 9 April 2010 ICRISAT, Patancheru,
Andhra Pradesh
Resource Person: Dr Pierre Goovaerts, Associate professor, University of Florida
This course introduced a suite of geostatistical methods for the spatial analysis of environmental data.
Participants learn how to apply geostatistics for the description of spatial patterns and identification of scales of
variability, spatial interpolation and stochastic modeling of environmental attributes, creation of risk maps and
their Use in decision-making. After completion of this course, trainees are provided skills to enable them to
Import, visualize and analyze your own data in a space-time information system.
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