Abstrakti
Droughts pose a critical global risk that affect vast land areas and threaten almost all nations. Yet the impacts of droughts are most concretely felt at the local scale. Here, we assess drought indices in a Finnish basin with limited observations under current and future climate conditions in order to support local drought management. Long time series are needed for deriving drought indices, yet the available data is often a constraint. To increase the sample size available for analysis, we generated a thousand years of weather data with a stochastic weather generator based on observations and Regional Climate Model (RCM) data. The generated meteorological variables were fed into a hydrological model to simulate a large sample of hydrological variables. These large samples of simulated meteorological and hydrological variables were then used to analyse drought events and their characteristics in a past (1990–2019) and a future (2040–2069) time period. The results support the ongoing drought management work being done in South-Western Finland and specifically the Sirppujoki basin. Our results indicate that drought events will most likely become more frequent, especially during the growing season. Such changes would affect particularly the agricultural sector of Finland.
Alkuperäiskieli | Englanti |
---|---|
Artikkeli | 100400 |
Sivumäärä | 14 |
Julkaisu | Climate Services |
Vuosikerta | 31 |
DOI - pysyväislinkit | |
Tila | Julkaistu - elok. 2023 |
OKM-julkaisutyyppi | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä |
Sormenjälki
Sukella tutkimusaiheisiin 'Drought hazard and annual precipitation predicted to increase in the Sirppujoki river basin, Finland'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.Tietoaineistot
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Supplementary Data for manuscript: "Drought hazard and annual precipitation predicted to increase in the Sirppujoki basin, Finland"
Ahopelto, L. (Creator), Aalto University School of Engineering, 23 jouluk. 2021
DOI - pysyväislinkki: 10.24342/d9dc5979-80fc-43e9-941e-0d8b9ac740e7
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Tiedosto