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Assessing irrigation water management using trend analysis and autocorrelation
Amadou Keita1*, Hamma Yacouba1, Laszlo G. Hayde2, Bart Schultz2
1.Laboratory of Hydrology and Water Resources, International Institute for Water and Environmental Engineering (2iE), Ouagadougou, Burkina Faso;
2. Department of Water Science and Engineering, UNESCO-IHE- Institute for Water Education, Delft, the Netherlands
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Abstract Gravity irrigation is very frequent in West Africa while the amount of water used is rarely follow up or analyzed. Such a work was carried out in the case of the 16 ha Tropical Savannah irrigated rice valley bottom scheme of Tiefora in Burkina Faso (West Africa). Using the flow equation of the concrete weir at the headwork, daily water use volumes were calculated as time series covering three irrigation seasons (two dry and one wet). The moving average trend analysis reveals that during both rainy season (1200 mm of rainfall) and dry season (no rainfall), the main canal gate is almost never closed, keeping a minimum discharge of 200 m3/day for 4 ha (50 mm/day vs. a local evapotranspiration of 7 mm/day). That stresses the necessity of a more rigorous water management. Furthermore, the autocorrelation analysis using ARIMA model showed that the irrigation cycle that ensures equity in water distribution among farm plots is 20 days instead of five. The knowledge of this fact can defuse potential conflicts about equity among farmers: the lack of water in day 4 may be compensated later during the 20-day cycle. It appeared that a simple water level measuring device – installed at the headwork of the main irrigation canal – can produce a time series to which autoregressive moving average model can be applied to yield, at low cost, a thorough assessment of water management in this surface irrigation system.
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Amadou Keita1*
Hamma Yacouba1
Laszlo G. Hayde2
Bart Schultz2
Key wordsirrigation autocorrelation   irrigation trend analysis   Tropical Savannahvalley bottoms   rice water management     
Received: 2014-10-19; Published: 2016-01-13
Corresponding Authors: Amadou Keita Email: amadou.keita@2ie-edu.org   
Cite this article:   
Amadou Keita1*,Hamma Yacouba1,Laszlo G. Hayde2 et al. Assessing irrigation water management using trend analysis and autocorrelation[J]. IAEJ, 2016, 25(2): 30-43.
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