Household Determinants of Riverbed Farming in Deukhuri Valley of Western Nepal

Abstract

Riverbed farming (RbF) has become an alternative and attractive form of agriculture, especially to the poor and landless farmers, in Nepal’s Terai. Since agricultural lands close to the rivers have been destroyed every year due to floods and flood-induced riverbank erosions, this form of agriculture has huge potential in such degraded and wastelands in the region. The government and non-government organizations have supported and built capacities of the farmers to adopt this as an effective adaptation strategy in the region. This study analyzes the determinants of riverbed farming at the household level mainly in the Deukhuri valley of the Western Terai, Nepal. A total of 150 households were selected randomly for the study in Sisahaniya rural municipality of the valley for the household survey. In order to analyze the determinants, the adoption of riverbed farming is considered as the dependent variables with 17 independent variables such as age, gender, education, occupation, ethnicity, family size, economically active member, land-holding size (in plains, hills, total holdings, borrowed lands, given to others, land close to river, land affected in last year), crop diversity and livestock diversity. Among them, education and occupation are positively significant for the adoption of riverbed farming whereas the family size is negatively significant. Education helps the farmers to easily understand the RbF processes. Agriculture is the main occupation for them; thus, they are still attracted to RbF as alternative farming. However, all the family members in the household are not actively supporting and contributing to the RbF.

Presenters

Shree Kumar Maharjan
Teaching Fellow, Regional Cultural Studies , Hiroshima University, Japan

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

2021 Special Focus: Responding to Climate Change as an Emergency

KEYWORDS

Adaptation, Agriculture, Riverbed farming, Terai, Nepal

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