Abstract
Abstract. This paper describes the benefits of using more reliable local climate scenarios to analyse hydrological responses. It assumes that Regional Climate Model (RCM) simulations are more reliable when they provide better approximations to the historical basic and drought statistics after applying a bias correction to them. We have investigated whether the best solutions in terms of their approximation to the local meteorology may also provide the best hydrological assessments. We have carried out a classification of the corrected RCM simulations used for both approximations. This has been applied in the Cenajo basin (south-eastern Spain), where we show that the best approximations of the historical meteorological statistics also provide the best approximations for the hydrological statistics. The selected RCMs were used to generate future (2071–2100) local scenarios under the RCP8.5 emission scenario. The two selected RCMs predict significant changes in mean precipitation (−31.6 % and −44.0 %) and mean temperature (+26.0 % and +32.2 %). They also predict higher frequency (from 5 events in the historical period to 20 and 22 in the future), length (4.8 to 7.4 and 10.5 months), magnitude (2.53 to 6.56 and 9.62 SPI) and intensity (0.48 to 1.00 and 0.94 SPI) of extreme meteorological droughts. These two RCMs also predict higher changes in mean streamflow (−43.5 % and −57.2 %) and hydrological droughts. The two RCMs also predict worrying changes in streamflow (−43.5 % and −57.2 %) and hydrologically extreme droughts: frequency (from 3 to 11 for the first model and 8 events for the second model), length (8.3 to 15.4 and 29.6 months), magnitude (from 3.98 to 11.84 and 31.72 SSI), and intensity (0.63 to 0.90 and 1.52 SSI).
Highlights
During the last few decades large-scale intensive droughts have been observed on all the continents around the globe (Kogan and Guo, 2016)
The performance of the model was assessed by using the Nash–Sutcliffe efficiency (NSE) coefficient, the correlation coefficient (R2) and the root mean squared error (RMSE)
In this paper our aim has been to classify all the corrected Regional Climate Model (RCM) simulations according to their capacity to reproduce the historical statistics
Summary
During the last few decades large-scale intensive droughts have been observed on all the continents around the globe (Kogan and Guo, 2016). We have the Palmer Drought Severity Index (PDSI) (Palmer, 1965), the Crop Moisture Index (CMI) (Palmer, 1968), the Standardized Precipitation Index (SPI) (McKee et al, 1993), the Soil Moisture Drought Index (SMDI) (Hollinger et al, 1993), the Vegetation Condition Index (VCI) (Liu and Kogan, 1996) and the Standardized Precipitation Evapotranspiration Index (SPEI) (Vicente-Serrano et al, 2010) From their names we can deduce that some of them were defined to analyse specific characteristics, such as length, magnitude and intensity, and different types of droughts (meteorological, agricultural or hydrological droughts). Some of these indices can be generalised to analyse most of the characteris-
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
