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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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10510 - Climatic research

Result continuities

  • Project

  • 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

  • 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