Development of an adaptation model by applying non-linear programming to compute adaptation deficiency in climatic hotspots

Akter, M., Haque, A., Karim, D., Rahman, M., Salehin, M., Kabir, R., Alim, M., Haq, M

Published in ‘Progress in Disaster Science’

Abstract

For the policy makers, risk-based planning to minimize future climatic risk needs decision on investment priority. This is particularly important where there are resource constraints, and in cases where the decisions depend on socio-political reality of the region. For the policy makers, it is also extremely important to know how a system will behave if investment is made on any specific adaptation in any specific location to minimize climatic risk in the region. To answer these questions, an Adaptation Model is developed in this study to compute adaptation deficiency for a location that will minimize climatic risk in that location. In this methodology, a system approach is followed by applying non-linear programming. The non-linear programming system is formulated by defining future climatic risk as the objective function where the risk is a non-linear function of hazard, exposure, vulnerability, where vulnerability is a linear combination of sensitivity and adaptive capacity. The system is restricted by seven constraints composed of different combinations of hazard, exposure, sensitivity and adaptive capacity. The model can be applied in any part of the world, for any climatic hazard, and for any time domain. In this study, the model is applied in Bangladesh coastal zone to compute adaptation deficiency required to be filled to minimize mid-century storm surge risk in the identified hotspots. The results show that out of 20 identified storm surge risk hotspots in Bangladesh coastal zone, cyclone shelter has the maximum adaptation deficiency in 10 hotspots followed by plantation in 8 hotspots. The output from the model can be used by the policy makers to decide on the most appropriate investment options for risk-based planning that will minimize future risks in the identified hotspots. The model shows the risk limit below which risk cannot be reduced. Any investment attempt on adaptation to reduce the risk beyond this limit will disrupt the system equilibrium and will make this investment a surplus.