accurate estimation of mean rain at the cost of variability estimation. The version 3.1 data is not homogenized and thus allows for better variability estimates. The estimates of rainfall near international boundaries are not less reliable as compared with those in the interior of the country, as the CRU estimation utilizes data from all the weather stations in the region.

To arrive at the Upazila level rainfall estimates from the CRU data, we use area weighted averages. For example if an Upazila covers two half degree grid cells for which CRU has rainfall estimates. We use the average rainfall of the two grid-cells, where the weights are the proportion of the area of the Upazila in each grid-cell. **Map 3** shows the locations of rainfall stations in Bangladesh in relation with the Upazilas and compares it with the 0.5 degree of the CRU rainfall data.

We use coefficient of variation as the measure of local rainfall variability.<sup>4</sup> Total rainfall for the monsoon season of June-September is calculated for each year for the 30 year period 1980-2009 for each Upazila. The long term historical local variability is then calculated as the coefficient of variation in total monsoon rain for this 30 year period. **Map 4** shows the spatial rainfall variability by Upazilas based on the CRU data.

Bangladesh Water Development Board characterizes the 1998 flood as: The 1998 flood in Bangladesh has been characterized as one of the catastrophic deluge on record. River water levels exceeded danger levels for country’s all of the major rivers. It was combined with local rainfall in catchment areas of small rivers. All these influences including overbank flow and drainage congestion resulted in a flood that extended over most of the country with duration of weeks to months.

Thus, the 1998 flood indicator identifies historically flood prone areas for the whole nation. We identify an Upazila to be historically flood prone if 50% or more of the area in the Upazila were flooded during any of the three periods of August 26, September 10, and September 17 of 1998 for which the percent of Upazila flooded information is available. By this measure about 51 percent of the 333 Upazilas in the survey are historically flood prone. Historically flood prone and non-flood prone Upazilas are identified in **Map 5** . The map shows that the flood prone Upazilas are concentrated around the GangesBrahmaputra-Meghna river-basins.

# **4. Methodology**

## **_Occupational focus_**

We consider two types of occupational choices made by household members. First, a member may choose between the economic sector to work in such as agriculture, construction, transport and public utilities, manufacturing, trade and business, services, and others. The household member may also decide on the type of employment, and choose between wage and self employment. Sectoral diversification may be ideal when the risks are sector specific, such as flood and rainfall variability may affect agricultural and non-agricultural sectors differently. However, opportunities, access to human, 4 Coefficient of variation is the ratio of standard deviation and mean. We also tried the mean and standard deviation as two separate indicators of rainfall parameters, and they provide similar results and are not reported.

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