Real Risk

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Macroeconomic and financial modules were developed to

assess the impact on various sectors of the state economy; the

fiscal implications for the state budget; and for making sugges-

tions on cost-effective risk financing and risk transfer

arrangements.

The probabilistic drought risk assessment model ensured

accurate and extensive drought risk assessment with statistical

outputs, such as average annual loss (AAL), and loss exceedance

curve (LEC) calculations. It further formed a powerful tool to

investigate the impact of risk coping strategies and climate

scenarios on crop yield and production in each block of the

drought-prone districts selected for the study.

The model was calibrated using local experience in manage-

ment practices and crop phenology in the selected districts. Its

validation proved extremely successful for the five major crops

grown in these districts, i.e. paddy, maize, jowar (sorghum),

sunflower and groundnut.

Droughts generate significant indirect losses, as compared to

direct losses in crop production. These indirect losses were

estimated through a macroeconometric and an input-output

analysis. A critical task was to link drought risk analysis at the

block level for the selected districts to the statewide macroeco-

nomic analysis. A prototype macroeconometric model was

developed to explain how the variability of the value of crop

production in selected districts impacts the variability of the

state gross value added (GVA) in the main economic sectors of

Andhra Pradesh. The input-output model, the first ever devel-

oped for Andhra Pradesh, was used to provide details of the

linkages between the different sectors and sub-sectors of the

economy, the flow of goods and services, and employment.

Contrary to rapid onset disasters, droughts normally lack

highly visible impacts. Instead, their impacts are generally

nonstructural and spread over long periods and large areas.

Therefore, though our approach broadly followed the general

catastrophe risk-modelling framework used for assessing the

impacts of rapid onset disasters (such as cyclones, floods and

earthquakes), it was customized to be applicable for slow onset

events.

Case study 3: Addressing vulnerability to climate vari-

ability and climate change – an integrated modelling

system development

Nearly two-thirds of India’s population lives in rural areas and

is greatly dependent on climate-sensitive sectors such as rain-

fed agriculture, forestry and fisheries, which are highly

vulnerable to current climatic variability, particularly floods and

droughts. Moreover, agriculture represents a core part of the

Indian economy and provides food and livelihood activities to

a major portion of the Indian population.

While the magnitude of the impact of climate change varies

by region, it generally has an impact on agricultural productiv-

ity and shifting crop patterns.

The overall objective of this study was to assess the impact of

climate change, which in turn would help determine how the

climate is expected to change at the regional level; what will be

the projected impact of increased climate variability and climate

change on water and agriculture resources; which regions are

vulnerable to climate-induced changes in water resources, and

the impact of these on agricultural crops.

The study was carried out for three regions of India: Pennar

basin in Andhra Pradesh, Lower Mahanadi basin in Orissa, and

the Godavari basin in Maharashgra.

An integrated modelling system (IMS) was developed to estab-

lish functional links between water and agriculture resources.

Under this study, water and main cereal crop productivity was

assessed with an emphasis on water management to clarify its

vulnerability to climate change. The assessment included:

• Baseline climatology and meteorology

Anantapur

Mahabubnagar

Cuddapah

Kurnool

Rangareddy

Chittor

Nalgonda

Prakasam

8 districts

AAL of production value as a percentage of normal year for each of the

selected eight districts and also the consolidated AAL for all districts

Source: RMSI

0.5

1.5

2.5

Yield (t/ha)

Jowar

Rice

Maize

Groundnut Sunflower

Simulated Kharif

Reported Kharif

Crop yield validation for select crops in

the Ananthpur district of Andhra Pradesh

Source: RMSI