Climate change impact assessment on the hydrology of a large river basin in Ethiopia using a local-scale climate modelling approach
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F20%3A00525409" target="_blank" >RIV/86652079:_____/20:00525409 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0048969720340262" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0048969720340262</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.scitotenv.2020.140504" target="_blank" >10.1016/j.scitotenv.2020.140504</a>
Alternative languages
Result language
angličtina
Original language name
Climate change impact assessment on the hydrology of a large river basin in Ethiopia using a local-scale climate modelling approach
Original language description
Local-scale climate change adaptation is receiving more attention to reduce the adverse effects of climate change. The process of developing adaptation measures at local-scale (e.g., river basins) requires high-quality climate information with higher resolution. Climate projections are available at a coarser spatial resolution from Global Climate Models (GCMs) and require spatial downscaling and bias correction to drive hydrological models. We used the hybrid multiple linear regression and stochastic weather generator model (Statistical Down-Scaling Model, SDSM) to develop a location-based climate projection, equivalent to future station data, from GCMs. Meteorological data from 24 ground stations and the most accurate satellite and reanalysis products identified for the region, such as Climate Hazards Group InfraRed Precipitation with Station Data were used. The Soil Water Assessment Tool (SWAT) was used to assess the impacts of the projected climate on hydrology. Both SDSM and SWAT were calibrated and validated using the observed climate and streamflow data, respectively. Climate projection based on SDSM, in one of the large and agricultural intensive basins in Ethiopia (i.e., Awash), show high variability in precipitation but an increase in maximum (Tmax) and minimum (Tmin) temperature, which agrees with global warming. On average, the projection shows an increase in annual precipitation (>10%), Tmax (>0.4 °C), Tmin (>0.2 °C) and streamflow (>34%) in the 2020s (2011–2040), 2050s (2041–2070), and 2080s (2071–2100) under RCP2.6-RCP8.5. Although no significant trend in precipitation is found, streamflow during March–May and June–September is projected to increase throughout the 21 century by an average of more than 1.1% and 24%, respectively. However, streamflow is projected to decrease during January–February and October–November by more than 6%. Overall, considering the projected warming and changes in seasonal flow, local-scale adaptation measures to limit the impact on agriculture, water and energy sectors are required.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10510 - Climatic research
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Science of the Total Environment
ISSN
0048-9697
e-ISSN
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Volume of the periodical
742
Issue of the periodical within the volume
NOV
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
13
Pages from-to
140504
UT code for WoS article
000569416600015
EID of the result in the Scopus database
2-s2.0-85087283327