2012
DOI: 10.1080/15715124.2012.664551
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Multiple water use as an approach for increased basin productivity and improved adaptation: a case study from Bangladesh

Abstract: This study, supported by the Challenge Program Water and Food (CPWF-Project 35), demonstrates the case of multiple-use of water through seasonal aquaculture interventions for improved rice-fish production systems in the Bangladesh floodplains. The project focused on community-based fish culture initiatives, increasingly adopted in the agro-ecological zones of the major floodplains of the Padma, Testa, and Brahmaputra basin. The productivity of water and fish is used as an indicator to explain this case. We hyp… Show more

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Cited by 12 publications
(8 citation statements)
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“…These evaluations will require the development of a set of robust indicators for assessing the impacts on ecosystem function (Rodrigues et al 2010;SDSN 2013). Additionally, quantifying changes in water productivity (i.e., yield per unit of water used), total factor productivity (i.e., ratio of all outputs produced to all inputs used, accounting for technological change and technical efficiency change), and nutrient-and energyuse efficiency should be critical components of implementing and adapting productivity interventions to optimize sustainability (Phiri et al 2003;Nagabhatla et al 2012;Asche et al 2013). Tools such as life cycle assessment, total factor productivity, the use of planetary boundaries, risk assessment, environmental impact assessment, and environmental impact quotient may be valuable in determining the environmental implications of productivity interventions in aquatic agricultural systems across scales (Rockström et al 2009;Renkow 2011;Henriksson et al 2012).…”
Section: Lessons and Challengesmentioning
confidence: 99%
“…These evaluations will require the development of a set of robust indicators for assessing the impacts on ecosystem function (Rodrigues et al 2010;SDSN 2013). Additionally, quantifying changes in water productivity (i.e., yield per unit of water used), total factor productivity (i.e., ratio of all outputs produced to all inputs used, accounting for technological change and technical efficiency change), and nutrient-and energyuse efficiency should be critical components of implementing and adapting productivity interventions to optimize sustainability (Phiri et al 2003;Nagabhatla et al 2012;Asche et al 2013). Tools such as life cycle assessment, total factor productivity, the use of planetary boundaries, risk assessment, environmental impact assessment, and environmental impact quotient may be valuable in determining the environmental implications of productivity interventions in aquatic agricultural systems across scales (Rockström et al 2009;Renkow 2011;Henriksson et al 2012).…”
Section: Lessons and Challengesmentioning
confidence: 99%
“…Strengthening the knowledge base and developing information and monitoring systems for regions prone to drought, flood and salinity is a significant dimension in climate change adaptation planning [32]. In general, crop production depends on various biotic and abiotic factors.…”
Section: Discussionmentioning
confidence: 99%
“…The agricultural sector is a large contributor to economic development of the country: contributing to 16.33% of its GDP and employing more than 53% of the population [2]. Most scientific surveys list Bangladesh as the most vulnerable country to the impacts of the global environmental phenomenon [32]. Therefore, developing measures that can ensure food and livelihood security, especially in the face of accelerating extreme climate events such as droughts, erratic rainfall patterns, cyclones and floods, is a priority.…”
Section: Introductionmentioning
confidence: 99%
“…However, strategies for increasing agricultural productivity have been mainly concentrated on crop cultivation (see, for example, Wichelns 2015). Culture of fish in seasonal floodplains can be an important tool for sustainably improving agricultural and floodplain productivity and for strengthening rural economies (Rahman et al 1999;Dey et al 2005a;Dey and Prein 2006;Nagabhatla et al 2012).…”
Section: Introductionmentioning
confidence: 99%