Flood devastation creates panic situation during rainy season. In Bihar, the loss due to flood is estimated to be

about Rs. 64 crores annually, which accounts for about 35 per cent of the total loss incurred in the country due

to floods. It not only affects the agricultural production, properties and lives but also interferes in the labour

productivity, employment and wages of agricultural labours which force them to migrate elsewhere either

seasonally or permanently. About 90 per cent of the flood prone area of the state lies in North Bihar, which is

one of the major factors of the backwardness of this region. In Bihar, on average, 8.47 lakh hectares of total

areas and 3.16 lakh hectare of crop land areas are submerged annually for several weeks in the river belts of

Ganga, Burhi Gandak, Kosi, Bagmati and Sone in the state and affects 271 blocks of 15 districts and cause

huge individual and public losses to the exchequer. About 300 agricultural labourers migrate per day from

Bihar. The causes of migration are irregular and scarcity of employment opportunities and low wages in their

Bihar. In North Bihar, Darbhanga district is highly flood prone. So, the field survey was conducted in two

villages of highly flood prone block, namely Hayaghat of Darghanga district during the year 2023-24. A

sample of 25 households from each size group of farms i.e., landless (having no land), marginal (below 1 ha

land), small (1 to 2 ha land) and large (more than 2 ha land) making a total sample size of 100 households.

Data regarding employment, labour productivity, migration and wage rates were collected with the help of

schedules and questionnaires by survey methods. Tabular analysis was done to interpret the results. However,

Cobb-Douglus production function was used wherever needed.

Before discussing the employment, labour productivity and extent of migration of agricultural labour for

different categories of households in the flood affected area, analysis of input use in agriculture production has

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insecticide and pesticides in Rs.

could not provide more than one irrigation to the crops because cost of irrigation by pump set is too costly to

be afforded by them. So, the area under irrigation provides an illusive figure in the flood prone area. Average

use of human labour per hectare was found 108-man days. The highest per hectare labour use was found 122-

man days in marginal farm size group as compared to small (114-man days) and large (87-man days) farm size

group because they have surplus labours. The highest per hectare bullock labour use was found 20 bullock

days in both marginal and small farm size groups as compared to large farm size groups (11 bullock labour

days) due to mechanization on large farm size groups. Machine labour per hectare was found higher on large

farm size group (3.41 days/ ha) as compared to small (3.18 days/ ha) and marginal (3.14 days/ ha) farm size

group. On average, the expenditure on purchased inputs i.e., seed, manures, fertilizer, insecticides and

pesticides were found Rs. 546 per hectare. The highest expenditure per hectare on use of these inputs was

The table reveals that per worker per year employment was observed to be 162-man days. Farming sector,

which was the main occupation of most workers in flood affected area, observed to be 25.32 per cent. On the

other hand. non-farming sector provided 74.68 percent of employment. Among different size group of farms in

flood prone area, per worker employment was comparatively higher on small farm (202-man days) followed

by large farm (193-man days), marginal farm (162-man days) and Figure in parentheses indicate percentage of

total employment landless (141-man days). It was further observed from the table that as the size of holding

increased the percentage employment in non-farming sector increased showing a positive relationship with size

of holding and non-farm employment.

Table 2 Pattern of employment on different size groups of households in flood prone area

201.58

161.88

Sources: - Self collected primary data from Oct 2024 to Dec 2024, compiled and analysis.

Per-worker employment in agriculture as main occupation on different size groups of farms in flood affected

(prone) has been presented in table 3.

Table 3 Per worker Employment in agriculture as main occupation on different size group of farms in flood

prone area

Source: - Self collected primary data during specific period

Per worker employment in agriculture as occupation on different size group of farms in flood affected area

revealed that total number of workers in agriculture as a main occupation was observed to be 133-man days

and per workers annual employment was 56.60-man days. Among the different size group of farms per worker

employment in agriculture was comparatively higher on landless labour household which was accounted to be

71.41-man days. As the size of holding increased the per worker employment as main occupation decreased in

agriculture because farmers of large size groups did not prefer to work in field due to false sense of prestige.

The wage rate has direct bearing with productivity of labour. It is generally said that the agricultural labours

are getting less wages than their marginal value productivity. In this regard, the regression coefficient of human

Source: - Self statistical calculations of the collected data

contributed to their family. The result has been presented in table 5.

It has been observed from the table that the number of male migrants was higher (92.31 per cent) than female

migrants in flood prone area. Female migrants were found in landless household only. The most revealing fact

is the absence of migration of agricultural labour was found on small and large size groups of farms. The

majority of landless category of migrants (77.78 per cent) could find employment as wage earner in agriculture

sector. Majority of migrants of marginal group of households had preference for non-agriculture job. About

77.78 per cent of migrants of landless class in flood affected areas were seasonal migrants.

The study further revealed that many migrants of sample households of landless and marginal size group

preferred to go outside the state like Punjab, Delhi and other cities for better wage rates. It may be also

observed from the table that average wage rate in migrated places was comparatively higher in non-

Small scale industries like beekeeping, poultry farming, and vegetable and fruits processing in flooded areas