Using ENSO conditions to optimize rice yield for Nepal’s Terai

The direct application of forecasts from seasonal prediction systems (SPSs) in agriculture is limited by their skill, and SPSs are more skilled at El Niño-Southern Oscillation (ENSO) prediction than precipitation prediction. An alternative to the direct application of forecasts from SPSs could be to...

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Main Authors: Jha, Prakash K., Athanasiadis, Panos, Gualdi, Silvio, Trabucco, Antonio, Mereu, Valentina, Shelia, Vakhtang, Hoogenboom, Gerrit
Format: Journal Article
Language:Inglés
Published: Inter-Research Science Center 2022
Subjects:
Online Access:https://hdl.handle.net/10568/120402
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author Jha, Prakash K.
Athanasiadis, Panos
Gualdi, Silvio
Trabucco, Antonio
Mereu, Valentina
Shelia, Vakhtang
Hoogenboom, Gerrit
author_browse Athanasiadis, Panos
Gualdi, Silvio
Hoogenboom, Gerrit
Jha, Prakash K.
Mereu, Valentina
Shelia, Vakhtang
Trabucco, Antonio
author_facet Jha, Prakash K.
Athanasiadis, Panos
Gualdi, Silvio
Trabucco, Antonio
Mereu, Valentina
Shelia, Vakhtang
Hoogenboom, Gerrit
author_sort Jha, Prakash K.
collection Repository of Agricultural Research Outputs (CGSpace)
description The direct application of forecasts from seasonal prediction systems (SPSs) in agriculture is limited by their skill, and SPSs are more skilled at El Niño-Southern Oscillation (ENSO) prediction than precipitation prediction. An alternative to the direct application of forecasts from SPSs could be to link the forecast of ENSO conditions with dynamic crop models to evaluate alternate crop management options prior to the start of the actual planting. Although potential benefits of this approach have been tested in many areas of the world, so far limited evidence exists regarding its application in Nepal’s Terai region. The overall goal of this study was to determine the potential relationship between ENSO and summer monsoon precipitation over Nepal’s Terai and ascertain SPSs’ skill in predicting ENSO. This analysis included disentangling the relative contribution of precipitation to interannual variability in rice yield from other factors using a cropping system model, namely, the Crop Environment Resource Synthesis-Rice (CSM-CERES-Rice). The crop model was also employed to explore options for increasing rice yield and minimizing risk by adjusting crop management. This study found that precipitation was the main variable affecting interannual variability in rice yield, that SPSs are good at predicting ENSO, and that the ENSO signal can be used to predict seasonal precipitation anomalies in the study area in all years except ENSO neutral years. Prior knowledge of seasonal precipitation anomalies can then be used to optimize rice yield using a crop model, and ultimately to assist farmers with decision making.
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spelling CGSpace1204022024-05-01T08:18:10Z Using ENSO conditions to optimize rice yield for Nepal’s Terai Jha, Prakash K. Athanasiadis, Panos Gualdi, Silvio Trabucco, Antonio Mereu, Valentina Shelia, Vakhtang Hoogenboom, Gerrit weather forecasting crop management crop yield precipitation farmer participation pronóstico del tiempo manejo del cultivo rendimiento de cultivos The direct application of forecasts from seasonal prediction systems (SPSs) in agriculture is limited by their skill, and SPSs are more skilled at El Niño-Southern Oscillation (ENSO) prediction than precipitation prediction. An alternative to the direct application of forecasts from SPSs could be to link the forecast of ENSO conditions with dynamic crop models to evaluate alternate crop management options prior to the start of the actual planting. Although potential benefits of this approach have been tested in many areas of the world, so far limited evidence exists regarding its application in Nepal’s Terai region. The overall goal of this study was to determine the potential relationship between ENSO and summer monsoon precipitation over Nepal’s Terai and ascertain SPSs’ skill in predicting ENSO. This analysis included disentangling the relative contribution of precipitation to interannual variability in rice yield from other factors using a cropping system model, namely, the Crop Environment Resource Synthesis-Rice (CSM-CERES-Rice). The crop model was also employed to explore options for increasing rice yield and minimizing risk by adjusting crop management. This study found that precipitation was the main variable affecting interannual variability in rice yield, that SPSs are good at predicting ENSO, and that the ENSO signal can be used to predict seasonal precipitation anomalies in the study area in all years except ENSO neutral years. Prior knowledge of seasonal precipitation anomalies can then be used to optimize rice yield using a crop model, and ultimately to assist farmers with decision making. 2022-07-28 2022-08-02T13:14:20Z 2022-08-02T13:14:20Z Journal Article https://hdl.handle.net/10568/120402 en Limited Access Inter-Research Science Center Jha, P.K.; Athanasiadis, P.; Gualdi, S.; Trabucco, A.; Mereu, V.; Shelia, V.; Hoogenboom, G. (2022) Using ENSO conditions to optimize rice yield for Nepal’s Terai. Climate Research 88 p. 87-100. ISSN: 0936-577X
spellingShingle weather forecasting
crop management
crop yield
precipitation
farmer participation
pronóstico del tiempo
manejo del cultivo
rendimiento de cultivos
Jha, Prakash K.
Athanasiadis, Panos
Gualdi, Silvio
Trabucco, Antonio
Mereu, Valentina
Shelia, Vakhtang
Hoogenboom, Gerrit
Using ENSO conditions to optimize rice yield for Nepal’s Terai
title Using ENSO conditions to optimize rice yield for Nepal’s Terai
title_full Using ENSO conditions to optimize rice yield for Nepal’s Terai
title_fullStr Using ENSO conditions to optimize rice yield for Nepal’s Terai
title_full_unstemmed Using ENSO conditions to optimize rice yield for Nepal’s Terai
title_short Using ENSO conditions to optimize rice yield for Nepal’s Terai
title_sort using enso conditions to optimize rice yield for nepal s terai
topic weather forecasting
crop management
crop yield
precipitation
farmer participation
pronóstico del tiempo
manejo del cultivo
rendimiento de cultivos
url https://hdl.handle.net/10568/120402
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