José M. Mirás-Avalos , José M. Escalona , Eva Pilar Pérez-Álvarez , Pascual Romero , Pablo Botia , Josefa Navarro , Nazareth Torres , Luis Gonzaga Santesteban , David Uriarte , Diego S. Intrigliolo , I. Buesa
{"title":"Upgrading and validating a soil water balance model to predict stem water potential in vineyards","authors":"José M. Mirás-Avalos , José M. Escalona , Eva Pilar Pérez-Álvarez , Pascual Romero , Pablo Botia , Josefa Navarro , Nazareth Torres , Luis Gonzaga Santesteban , David Uriarte , Diego S. Intrigliolo , I. Buesa","doi":"10.1016/j.agrformet.2024.110281","DOIUrl":null,"url":null,"abstract":"<div><div>Efficient water management is pivotal for viticulture sustainability. Decision support tools can advise on how to optimize irrigation or on the feasibility of growing grapes in rainfed conditions, but reliable algorithms for assessing vine water status are required. In this context, the aim of the current study was to upgrade a soil water balance model specific for vineyards by incorporating meteorological, soil and vine vigor in equations that transform the fraction of transpirable soil water into midday stem water potential (Ψ<sub>stem</sub>). The model's sensitivity to variations in the magnitude of input parameters was analyzed. Furthermore, the model was tested in a broad scope of Spanish vineyards with different grapevine cultivars (both red and white), rootstocks, plant age, soil and climatic conditions, and water regimes, totaling 129 scenarios. The model was only slightly sensitive to variations in the magnitude of most inputs, except for the fraction of transpirable water at which leaf stomatal conductance begin to decline. Moreover, the model satisfactorily reproduced the evolution of Ψ<sub>stem</sub> over the growing season, although it slightly overestimated the measured Ψ<sub>stem</sub> values, as the slopes of the fitted regression lines were lesser than 1 on most occasions, 76 out of 129. Nonetheless, the coefficients of determination for these relationships were greater than 0.9, except for 21 datasets. Mean errors averaged 0.024 ± 0.015 MPa, while root mean square errors averaged 0.27 ± 0.01 MPa. The index of agreement was greater than 0.75 in 51 datasets, with only three datasets showing an index of agreement lower than 0.5. Nevertheless, the deviations between observed and simulated Ψ<sub>stem</sub> values did not alter the classification of the water stress undergone by grapevines. This upgraded model could constitute the core of a decision support system for water management in vineyards, applicable to both rainfed and irrigated conditions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"359 ","pages":"Article 110281"},"PeriodicalIF":5.6000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural and Forest Meteorology","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168192324003940","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0
Abstract
Efficient water management is pivotal for viticulture sustainability. Decision support tools can advise on how to optimize irrigation or on the feasibility of growing grapes in rainfed conditions, but reliable algorithms for assessing vine water status are required. In this context, the aim of the current study was to upgrade a soil water balance model specific for vineyards by incorporating meteorological, soil and vine vigor in equations that transform the fraction of transpirable soil water into midday stem water potential (Ψstem). The model's sensitivity to variations in the magnitude of input parameters was analyzed. Furthermore, the model was tested in a broad scope of Spanish vineyards with different grapevine cultivars (both red and white), rootstocks, plant age, soil and climatic conditions, and water regimes, totaling 129 scenarios. The model was only slightly sensitive to variations in the magnitude of most inputs, except for the fraction of transpirable water at which leaf stomatal conductance begin to decline. Moreover, the model satisfactorily reproduced the evolution of Ψstem over the growing season, although it slightly overestimated the measured Ψstem values, as the slopes of the fitted regression lines were lesser than 1 on most occasions, 76 out of 129. Nonetheless, the coefficients of determination for these relationships were greater than 0.9, except for 21 datasets. Mean errors averaged 0.024 ± 0.015 MPa, while root mean square errors averaged 0.27 ± 0.01 MPa. The index of agreement was greater than 0.75 in 51 datasets, with only three datasets showing an index of agreement lower than 0.5. Nevertheless, the deviations between observed and simulated Ψstem values did not alter the classification of the water stress undergone by grapevines. This upgraded model could constitute the core of a decision support system for water management in vineyards, applicable to both rainfed and irrigated conditions.
期刊介绍:
Agricultural and Forest Meteorology is an international journal for the publication of original articles and reviews on the inter-relationship between meteorology, agriculture, forestry, and natural ecosystems. Emphasis is on basic and applied scientific research relevant to practical problems in the field of plant and soil sciences, ecology and biogeochemistry as affected by weather as well as climate variability and change. Theoretical models should be tested against experimental data. Articles must appeal to an international audience. Special issues devoted to single topics are also published.
Typical topics include canopy micrometeorology (e.g. canopy radiation transfer, turbulence near the ground, evapotranspiration, energy balance, fluxes of trace gases), micrometeorological instrumentation (e.g., sensors for trace gases, flux measurement instruments, radiation measurement techniques), aerobiology (e.g. the dispersion of pollen, spores, insects and pesticides), biometeorology (e.g. the effect of weather and climate on plant distribution, crop yield, water-use efficiency, and plant phenology), forest-fire/weather interactions, and feedbacks from vegetation to weather and the climate system.