Comprehensive Disaster Risk Modeling for Agriculture

Pane Stojanovski, Robert Muir-Wood


The paper identifies the needs of the public sector (governments) to have access to comprehensive disaster risk models for agriculture (‘AgriCat’) capable of quantifying the risk across the entire agricultural enterprise.  This is particularly the case for countries exposed to disasters, where significant proportions of economic activity, poverty eradication, human development, and livelihoods are associated with agriculture. The proposed AgriCat risk modeling framework is based on the principles of structured physical risk modeling for property CAT risk, employing the probabilistic event based approach. It delivers four outputs relevant for the agricultural enterprise: a)   loss of capital stock (barns, equipment, land, etc.),  b) direct loss of income (from crops, livestock, fish etc.) due to the disaster, c)  loss of nutrition (i.e. in particular when production is providing nutrition to the producer), and d) indirect loss of future production (in years following the disaster).  The outputs also include “functionality restoration time†information – defined as time to replant and grow to maturity the crops (seasonal and permanent), and time to repair and restore functionality of other capital assets (e.g.  Livestock, warehouses, silos, the land, etc.).  Fully accounting for the disaster impacts using this modeling approach would enable governments to promote, , comprehensive agricultural risk management programs, involving improved resilience of the agricultural sector as well as risk transfer through  insurance / reinsurance mechanisms. 


Comprehensive Disaster Risk Modelling for Agriculture, AgriCat Modelling, Holistic Risk Management, Agricultural Risk, Public Private Partnerships, Disaster Risk Quantification, Public Agricultural Enterprise

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