9th International Symposium on Integrated Water Resources Management (IWRM) | 14th International Workshop on Statistical Hydrology (STAHY) | I EBHE - Encontro Brasileiro de Hidrologia Estatística

Data: 04/11/2024 à 07/11/2024
Local: Florianópolis-SC
Mais informações: https://www.abrhidro.org.br/iebhe

The uncertainty of agricultural production: a case study from Pianura Padana

Código

I-EBHE0222

Autores

Maria Cristina Rulli

Tema

WG 2.5: The Water-Energy-Food-Ecosystem (WEFE) nexus: pathways to resilience

Resumo

Climate variability and change often challenge agricultural production. Increasingly, we hear about how drought periods are expected to become more intense and prolonged in the future, severely damaging agricultural output. Already in 2022, the Po Valley, one of Italy's breadbaskets, experienced an unprecedented drought, resulting in agricultural production losses of up to 60%. To propose effective and resilient solutions, a deeper understanding of the phenomenon is required; this is achieved here by combining agro-hydrological modeling with in-depth statistical analysis. By analyzing approximately 30 years of observations in the Po Valley, synthetic rainfall and temperature data have been generated for a period of about 5000 years and used as input to an agro-climatic model called WATNEEDS. This model, developed at the Politecnico di Milano, allows for solving the vertical water balance in the active soil layer to assess the potential and actual water consumption of crops. The model uses the FAO approach for evaluating plant water requirements and provides as outputs the volumes of green water (i.e., rainfall water that the plant can utilize) and blue water (i.e., irrigation water) needed to ensure growth under stress conditions. Two of the most widespread crops in the area, irrigated maize (planted in April and harvested in October) and winter rainfed wheat (planted in November and harvested in June), were considered for illustrative purposes. Continuous-time simulation of the agro-hydrological system allows for a statistical prediction of the blue water volumes. This type of information, as anticipated, is fundamental for proper management and planning in the use of water resources.

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