• Energy Research

Sub-Saharan Africa (SSA) is predicted to experience considerable negative impacts of climate change. The IPCC Fourth Assessment emphasizes that adaptation strategies are essential. Addressing adaptation in thecontext of small-scale, semi-subsistence agriculture raises special challenges. High data demands includingsite-specific bio-physical and economic data are an important constraint. This paper applies a newapproach to impact assessment, the Tradeoff Analysis model for Multi-Dimensional Impact Assessment(TOA-MD), which simulates technology adoption and associated economic, environmental and social outcomes in a heterogeneous farm population for a regional impact assessment. The methodology uses thekinds of survey, experimental and modeled data that are typically available in countries where semi-subsistencesystems are important, combined with future socio-economic scenarios based on new scenario pathway concepts being developed by the climate change and impact assessment modeling communities. Characteristics of current and future agricultural systems, including land use, output, output price, cost of production, and farm and household size are analyzed and compared for both current and projected future climate (2030), with and without adaptation, and for different socio-economic scenarios. The methodology is applied to two study areas in Kenya. These case studies show the potential of this approach to provide a flexible, generic framework that can use available and modeled data to evaluate climate impact and adaptation strategies under a range of socio-economic scenarios.

Sub-Saharan Africa (SSA) is predicted to experience considerable negative impacts of climate change. The IPCC Fourth Assessment emphasizes that adaptation strategies are essential. Addressing adaptation in thecontext of small-scale, semi-subsistence agriculture raises special challenges. High data demands includingsite-specific bio-physical and economic data are an important constraint. This paper applies a newapproach to impact assessment, the Tradeoff Analysis model for Multi-Dimensional Impact Assessment(TOA-MD), which simulates technology adoption and associated economic, environmental and social outcomes in a heterogeneous farm population for a regional impact assessment. The methodology uses thekinds of survey, experimental and modeled data that are typically available in countries where semi-subsistencesystems are important, combined with future socio-economic scenarios based on new scenario pathway concepts being developed by the climate change and impact assessment modeling communities. Characteristics of current and future agricultural systems, including land use, output, output price, cost of production, and farm and household size are analyzed and compared for both current and projected future climate (2030), with and without adaptation, and for different socio-economic scenarios. The methodology is applied to two study areas in Kenya. These case studies show the potential of this approach to provide a flexible, generic framework that can use available and modeled data to evaluate climate impact and adaptation strategies under a range of socio-economic scenarios.

The predicted effects of climate change call for a multi-dimensional method to assess the performance of various agricultural systems across economic, environmental and social dimensions. Climate smart agriculture (CSA) recognizes that the three goals of climate adaptation, mitigation and resilience must be integrated into the framework of a sustainable agricultural system. However, current methods to determine a systems’ ability to achieve CSA goals are lacking. This paper presents a new simulation-based method based on the Regional Integrated Assessment (RIA) methods developed by the Agricultural Model Inter-comparison and Improvement Project (AgMIP) for climate impact assessment. This method combines available data, field- and stakeholder-based surveys, biophysical and economic models, and future climate and socio-economic scenarios. It features an integrated farm and household approach and accounts for heterogeneity across biophysical and socioeconomic variables as well as temporal variability of climate indicators. This method allows for assessment of the technologies and practices of an agricultural system to achieve the three goals of CSA. The case study of a mixed crop livestock system in western Zimbabwe is highlighted as a typical smallholder agricultural systems in Africa.

The predicted effects of climate change call for a multi-dimensional method to assess the performance of various agricultural systems across economic, environmental and social dimensions. Climate smart agriculture (CSA) recognizes that the three goals of climate adaptation, mitigation and resilience must be integrated into the framework of a sustainable agricultural system. However, current methods to determine a systems’ ability to achieve CSA goals are lacking. This paper presents a new simulation-based method based on the Regional Integrated Assessment (RIA) methods developed by the Agricultural Model Inter-comparison and Improvement Project (AgMIP) for climate impact assessment. This method combines available data, field- and stakeholder-based surveys, biophysical and economic models, and future climate and socio-economic scenarios. It features an integrated farm and household approach and accounts for heterogeneity across biophysical and socioeconomic variables as well as temporal variability of climate indicators. This method allows for assessment of the technologies and practices of an agricultural system to achieve the three goals of CSA. The case study of a mixed crop livestock system in western Zimbabwe is highlighted as a typical smallholder agricultural systems in Africa.

AbstractThe Indo-Gangetic Basin (IGB) is characterised by cereal-based farming systems where livestock is an integral part of farm economy. Majority of the population derives their livelihood from agriculture sector which is dominated by small land holdings (<2ha). Cereal crops (mainly rice and wheat) are crucial to ensuring the food security in the region, but sustaining their productivity has become a major challenge due to climate variability and uncertainty. This paper uses an integrated climate-crop- economic modelling framework (using AgMIP protocols) to make an integrated assessment of climate change and adaptation strategy for rice-wheat growing farms of Meerut district (India) in the IGB. This framework enables integration of location- and farm-specific climate and crop modelling output for assessing economic impact on the farming systems using trade-off analysis (TOA-MD) model. The assessment clearly shows likely impact of climate change on agricultural production systems, and how adaptation strategies can reduce climate change vulnerabilities. Sensitivity analysis shows that under current production system, rice mean yield declines 8–23% while wheat yield declines by 17-29% under five climate scenarios. Though decline in mean net farm returns and per capita income appears small, a large proportion of farm population (53-79%) remains vulnerable to climate change. Assessment of future agricultural systems (2050s) shows that though the mean net farm returns and per capita income decline by 3–9% and 2–6%, respectively, under different climate scenarios, a large proportion of farms (39–64%) incur losses due to climate change. The adaptation strategy for existing farming system shows positive impacts on crop yield, farm returns and per capita income. However, a comprehensive assessment of more sites for climate change impacts on future agricultural production systems would be useful in devising appropriate adaptation strategy to improve the livelihoods and food security in the IGB region.

AbstractThe Indo-Gangetic Basin (IGB) is characterised by cereal-based farming systems where livestock is an integral part of farm economy. Majority of the population derives their livelihood from agriculture sector which is dominated by small land holdings (<2ha). Cereal crops (mainly rice and wheat) are crucial to ensuring the food security in the region, but sustaining their productivity has become a major challenge due to climate variability and uncertainty. This paper uses an integrated climate-crop- economic modelling framework (using AgMIP protocols) to make an integrated assessment of climate change and adaptation strategy for rice-wheat growing farms of Meerut district (India) in the IGB. This framework enables integration of location- and farm-specific climate and crop modelling output for assessing economic impact on the farming systems using trade-off analysis (TOA-MD) model. The assessment clearly shows likely impact of climate change on agricultural production systems, and how adaptation strategies can reduce climate change vulnerabilities. Sensitivity analysis shows that under current production system, rice mean yield declines 8–23% while wheat yield declines by 17-29% under five climate scenarios. Though decline in mean net farm returns and per capita income appears small, a large proportion of farm population (53-79%) remains vulnerable to climate change. Assessment of future agricultural systems (2050s) shows that though the mean net farm returns and per capita income decline by 3–9% and 2–6%, respectively, under different climate scenarios, a large proportion of farms (39–64%) incur losses due to climate change. The adaptation strategy for existing farming system shows positive impacts on crop yield, farm returns and per capita income. However, a comprehensive assessment of more sites for climate change impacts on future agricultural production systems would be useful in devising appropriate adaptation strategy to improve the livelihoods and food security in the IGB region.