Alice Ajassa
Development of a Data-Driven Model for the Estimate of Drought Risk for Agriculture.
Rel. Jost-Diedrich Graf Von Hardenberg, Bartolo Albanese. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Per L'Ambiente E Il Territorio, 2024
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (2MB) | Preview |
Abstract
This thesis draws inspiration from the European Drought Risk Atlas to quantify the impacts of agricultural drought on maize production in Italy. The goal is to develop a preliminary predictive model that can be refined and expanded in future research. Historical climatic data, including temperature and precipitation, were sourced from the VHR-REA_IT dataset, while projections under the RCP 8.5 scenario (2030–2070) were obtained from the VHR-PRO_IT dataset. The provincial-level maize cultivation data, sourced from ISTAT, focused on Northern Italy, where sufficient agricultural records were available. A regression analysis was conducted to assess yield anomalies, with five regression models implemented, optimized, and evaluated using various metrics.
Although overall model performance leaves room for improvement, the Extra Trees Regressor was identified as the most reliable model based on its performance on the baseline data and its consistency with existing literature
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
Aziende collaboratrici
URI
![]() |
Modifica (riservato agli operatori) |
