Tamara Ricchi, V. Alagna, G. Villani, F. Tomei, A. Toscano, G. Baroni
{"title":"Sensitivity of the agro-hydrological model CRITERIA-1D to the Leaf Area Index parameter","authors":"Tamara Ricchi, V. Alagna, G. Villani, F. Tomei, A. Toscano, G. Baroni","doi":"10.1109/MetroAgriFor50201.2020.9277614","DOIUrl":null,"url":null,"abstract":"Water availability is strongly variable in space and time, also due to the climate change. Agriculture is a sector specially affected by the water scarcity problem considering that is one of the main users. Irrigation scheduling simulation models play an important role in this context by estimating plant water requirements and supporting best water management practices. Representative model parameters and input data are however fundamental to achieve good model performances. The objective of this work was to assess the sensitivity of the agro-hydrological model CRITERIA-1D to the leaf area index (LAI) parameter, commonly used to characterize the plant status and to represent its developing stages. The model has been set up using, on the one hand, literature LAIMAX and LAIMIN values and, on the other hand, ground measured values, obtained by means of a ceptometer. Results show significant differences between the irrigation water requirements estimated between the two scenarios. For this reason, the study underlines the need to adopt accurate crop parameters and to integrate real-time crop measurements for the estimation of the irrigation water requirement. Smaller differences are quantified, however, when looking at the deep percolation estimated by the model highlighting the importance of considering multiple outputs for a comprehensive assessment of the model.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"251 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277614","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Water availability is strongly variable in space and time, also due to the climate change. Agriculture is a sector specially affected by the water scarcity problem considering that is one of the main users. Irrigation scheduling simulation models play an important role in this context by estimating plant water requirements and supporting best water management practices. Representative model parameters and input data are however fundamental to achieve good model performances. The objective of this work was to assess the sensitivity of the agro-hydrological model CRITERIA-1D to the leaf area index (LAI) parameter, commonly used to characterize the plant status and to represent its developing stages. The model has been set up using, on the one hand, literature LAIMAX and LAIMIN values and, on the other hand, ground measured values, obtained by means of a ceptometer. Results show significant differences between the irrigation water requirements estimated between the two scenarios. For this reason, the study underlines the need to adopt accurate crop parameters and to integrate real-time crop measurements for the estimation of the irrigation water requirement. Smaller differences are quantified, however, when looking at the deep percolation estimated by the model highlighting the importance of considering multiple outputs for a comprehensive assessment of the model.