TY - JOUR
T1 - Estimation of Yield Response Factor for Each Growth Stage under Local Conditions Using AquaCrop-OS
AU - Kuschel-otárola, Mathias
AU - Schütze, Niels
AU - Holzapfel, Eduardo
AU - Godoy-Faúndez, Alex
AU - Mialyk, Oleksandr
AU - Rivera, Diego
PY - 2020/4/10
Y1 - 2020/4/10
N2 - 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 (Ky) 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.
AB - 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 (Ky) 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.
KW - AquaCrop-OS
KW - Crop yield function
KW - Growth stages
KW - Yield response factor
UR - http://www.scopus.com/inward/record.url?scp=85084642492&partnerID=8YFLogxK
U2 - 10.3390/w12041080
DO - 10.3390/w12041080
M3 - Article
VL - 12
SP - 1080
JO - Water
JF - Water
SN - 2073-4441
IS - 4
M1 - 1080
ER -