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A parsimonious crop‐water productivity index: an application to Brazil
Author(s) -
Maneta Marco P,
Singh Purnendu N,
Torres Marcelo,
Wallender Wesley W,
Vosti Stephen A,
Rodrigues Lineu N,
Bassoi Luis H,
Young Julie A
Publication year - 2009
Publication title -
area
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 82
eISSN - 1475-4762
pISSN - 0004-0894
DOI - 10.1111/j.1475-4762.2008.00845.x
Subject(s) - productivity , index (typography) , environmental science , agricultural productivity , agriculture , water use , water resource management , agricultural economics , farm water , poverty , water resources , natural resource economics , water conservation , geography , economics , economic growth , computer science , ecology , archaeology , world wide web , biology
Reducing poverty in rural areas of developing countries requires sustained and sustainable increases in agricultural water productivity. However, aside from traditional measures of precipitation, little is known about water available to farmers or how productively they use it. We present a crop‐water productivity index (a ratio of the value of annual crop production to a dimensionless potential water availability index) for large water basins using readily available low‐resolution data. The index is transferable, permits direct inter‐basin comparisons, and is simple to calculate. We calculate the index for each municipality in the São Francisco river basin in Brazil. No clear patterns linking water availability and value of agricultural output are evident, even though clusters of municípios with high‐ and low‐crop‐water productivity emerge, and the former may be useful in guiding policies aimed at increasing water productivity. Finally, analyses of the effects of information uncertainty on the crop‐water productivity index suggest that the returns to agricultural investments in certain places in the São Francisco river basin are more risky than others. Improvements in data quality and quantity can help refine estimates of the index and reduce their uncertainty.