| Titre : | Evaluating country-scale irrigation demand through parsimonious agro-hydrological modeling (2025) |
| Auteurs : | N.C. Turiano ; M. Tuninetti ; F. Laio ; L. Ridolfi |
| Type de document : | Article |
| Dans : | Hydrology (vol. 12, n. 9, September 2025) |
| Article en page(s) : | p. 240 |
| Langues : | Anglais |
| Langues du résumé : | Anglais |
| Catégories : |
Catégories principales 07 - ENVIRONNEMENT ; 7.3 - Eau. Gestion de l'EauThésaurus IAMM GESTION DES EAUX ; EAU D'IRRIGATION ; BESOIN EN EAU ; EVALUATION ; MODELE ; ITALIE |
| Résumé : | Climate change is expected to reduce water availability during cropping season, while growing populations and rising living standards will increase the global water demand. This creates an urgent need for national water management tools to optimize water allocation. In particular, agriculture requires targeted approaches to improve efficiency. Alongside field measurements and remote sensing, agro-hydrological models have emerged as a particularly valuable resource for assessing and managing agricultural water demand. This study introduces WaterCROPv2, a state-of-the-art agro-hydrological model designed to estimate national-scale irrigation water demand while effectively balancing accuracy with practical data requirements. WaterCROPv2 incorporates innovative features such as hourly time-step computations, advanced rainwater canopy interception modeling, detailed soil-dependent leakage dynamics, and localized daily evapotranspiration patterns based on meteorological data. Through comprehensive analyses, WaterCROPv2 demonstrates significantly enhanced reliability in estimating irrigation water needs across various climatic regions, particularly under contrasting dry and wet conditions. Validation against independent data from the Italian National Institute of Statistics (ISTAT) for maize cultivation in Italy in 2010 confirms the model's accuracy and underscores its potential for broader international applications. A spatial analysis further reveals that the estimation errors align closely with regional precipitation patterns: the model tends to slightly underestimate irrigation needs in the wetter northern regions, whereas it somewhat overestimates demand in the drier southern areas. WaterCROPv2 has also been used to analyze irrigation water requirements for maize cultivation in Italy from 2005 to 2015, highlighting its significant potential as a strategic decision-support tool. The model identifies optimal cultivation areas, such as the Pianura Padana, where the irrigation requirements do not exceed 200 mm for the entire maize growing period, and unsuitable regions, such as Salentino, where over 500 mm per season are required due to the local climatic conditions. In addition, estimates of the water volumes required for the current extent of maize cultivation show that the Pianura Padana region demands nearly three times the amount of water used in the Salentino area. The model has also been used to identify regions where adopting efficient irrigation technologies could lead to substantial water savings. With micro-irrigation currently covering less than 18% of irrigated land, simulations suggest that a complete transition to this system could reduce the national water demand by 21%. Savings could reach 30-40% in traditionally water-rich regions that rely on inefficient irrigation practices but are expected to be increasingly exposed to temperature increases and precipitation shifts. The analysis shows that those regions currently lacking adequate irrigation infrastructure stand to gain the most from targeted irrigation system investments but also highlights how incentives where micro-irrigation is already widespread can provide further 5-10% savings. |
| Cote : | En ligne |
| URL / DOI : | https://doi.org/10.3390/hydrology12090240 |
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