2 research outputs found
Climate Change Impacts on Rice Farming Systems in Northwestern Sri Lanka
Sri Lanka has achieved tremendous progress since 1950 in crop production and food availability. Yields grew at an impressive rate until leveling off in the mid-eighties. Sri Lanka's population is anticipated to grow in the coming decades, creating an ever-greater demand for food security on the household, sub-district, regional, and national scales.The agricultural sector in Sri Lanka is vulnerable to climate shocks. An unusual succession of droughts and floods from 2008 to 2014 has led to both booms and busts in agricultural production, which were reflected in food prices. In both instances, the majority of farmers and consumers were adversely affected.At present the rice-farming systems are under stress due to inadequate returns for the farmers and difficulty in coping with shocks due to climate, pests, and diseases, and prices for produce. There are government price-support mechanisms, fertilizer-subsidy schemes, and crop insurance schemes, but the levels of the supports are modest and often do not effectively reach the farmers
The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and Protocols
Climate change is expected to alter a multitude of factors important to agricultural
systems, including pests, diseases, weeds, extreme climate events, water resources,
soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration
([CO2]), temperature, andwater (CTW) will be the primary drivers of change
in crop growth and agricultural systems. Therefore, establishing the CTW-change
sensitivity of crop yields is an urgent research need and warrants diverse methods
of investigation. Crop models provide a biophysical, process-based tool to investigate crop
responses across varying environmental conditions and farm management techniques,
and have been applied in climate impact assessment by using a variety of
methods (White et al., 2011, and references therein). However, there is a significant
amount of divergence between various crop models’ responses to CTW changes
(R¨otter et al., 2011). While the application of a site-based crop model is relatively
simple, the coordination of such agricultural impact assessments on larger scales
requires consistent and timely contributions from a large number of crop modelers,
each time a new global climate model (GCM) scenario or downscaling technique
is created. A coordinated, global effort to rapidly examine CTW sensitivity across
multiple crops, crop models, and sites is needed to aid model development and
enhance the assessment of climate impacts (Deser et al., 2012)..