Estimation of Yield Response Factor for Each Growth Stage under Local Conditions Using AquaCrop-OS
We propose a methodology to estimate the yield response factor (i.e., the slope of the water-yield function) under local conditions for a given crop, weather, sowing date, and management at each growth stage using AquaCrop-OS. The methodology was applied to three crops (maize, sugar beet, and wheat)...
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doaj-b363cae84f344c42ba9b29afec79d9972020-11-25T03:54:24ZengMDPI AGWater2073-44412020-04-01121080108010.3390/w12041080Estimation of Yield Response Factor for Each Growth Stage under Local Conditions Using AquaCrop-OSMathias Kuschel-Otárola0Niels Schütze1Eduardo Holzapfel2Alex Godoy-Faúndez3Oleksandr Mialyk4Diego Rivera5Department of Water Resources, School of Agricultural Engineering, University of Concepción, 3812120 Chillán, ChileInstitute of Hydrology and Meteorology, Technische Universität Dresden, 01062 Dresden, GermanyDepartment of Water Resources, School of Agricultural Engineering, University of Concepción, 3812120 Chillán, ChileWater Research Center for Agriculture and Mining (CRHIAM), 3812120 Chillán, ChileInstitute of Hydrology and Meteorology, Technische Universität Dresden, 01062 Dresden, GermanyWater Research Center for Agriculture and Mining (CRHIAM), 3812120 Chillán, ChileWe propose a methodology to estimate the yield response factor (i.e., the slope of the water-yield function) under local conditions for a given crop, weather, sowing date, and management at each growth stage using AquaCrop-OS. The methodology was applied to three crops (maize, sugar beet, and wheat) and four soil types (clay loam, loam, silty clay loam, and silty loam), considering three levels of bulk density: low, medium, and high. Yields are estimated for different weather and management scenarios using a problem-specific algorithm for optimal irrigation scheduling with limited water supply (GET-OPTIS). Our results show a good agreement between benchmarking (mathematical approach) and benchmark (estimated by AquaCrop-OS) using the Normalised Root Mean Square Error (NRMSE), allowing us to estimate reliable yield response factors (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>K</mi> <mi>y</mi> </mrow> </semantics> </math> </inline-formula>) under local conditions and to dispose of the typical simple mathematical approach, which estimates the yield reduction as a result of water scarcity at each growth stage.https://www.mdpi.com/2073-4441/12/4/1080AquaCrop-OScrop yield functionyield response factorgrowth stages |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mathias Kuschel-Otárola Niels Schütze Eduardo Holzapfel Alex Godoy-Faúndez Oleksandr Mialyk Diego Rivera |
spellingShingle |
Mathias Kuschel-Otárola Niels Schütze Eduardo Holzapfel Alex Godoy-Faúndez Oleksandr Mialyk Diego Rivera Estimation of Yield Response Factor for Each Growth Stage under Local Conditions Using AquaCrop-OS Water AquaCrop-OS crop yield function yield response factor growth stages |
author_facet |
Mathias Kuschel-Otárola Niels Schütze Eduardo Holzapfel Alex Godoy-Faúndez Oleksandr Mialyk Diego Rivera |
author_sort |
Mathias Kuschel-Otárola |
title |
Estimation of Yield Response Factor for Each Growth Stage under Local Conditions Using AquaCrop-OS |
title_short |
Estimation of Yield Response Factor for Each Growth Stage under Local Conditions Using AquaCrop-OS |
title_full |
Estimation of Yield Response Factor for Each Growth Stage under Local Conditions Using AquaCrop-OS |
title_fullStr |
Estimation of Yield Response Factor for Each Growth Stage under Local Conditions Using AquaCrop-OS |
title_full_unstemmed |
Estimation of Yield Response Factor for Each Growth Stage under Local Conditions Using AquaCrop-OS |
title_sort |
estimation of yield response factor for each growth stage under local conditions using aquacrop-os |
publisher |
MDPI AG |
series |
Water |
issn |
2073-4441 |
publishDate |
2020-04-01 |
description |
We propose a methodology to estimate the yield response factor (i.e., the slope of the water-yield function) under local conditions for a given crop, weather, sowing date, and management at each growth stage using AquaCrop-OS. The methodology was applied to three crops (maize, sugar beet, and wheat) and four soil types (clay loam, loam, silty clay loam, and silty loam), considering three levels of bulk density: low, medium, and high. Yields are estimated for different weather and management scenarios using a problem-specific algorithm for optimal irrigation scheduling with limited water supply (GET-OPTIS). Our results show a good agreement between benchmarking (mathematical approach) and benchmark (estimated by AquaCrop-OS) using the Normalised Root Mean Square Error (NRMSE), allowing us to estimate reliable yield response factors (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>K</mi> <mi>y</mi> </mrow> </semantics> </math> </inline-formula>) under local conditions and to dispose of the typical simple mathematical approach, which estimates the yield reduction as a result of water scarcity at each growth stage. |
topic |
AquaCrop-OS crop yield function yield response factor growth stages |
url |
https://www.mdpi.com/2073-4441/12/4/1080 |
work_keys_str_mv |
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