Assessing different sources of uncertainty in hydrological projections of high and low flows: case study for Omerli Basi...Published: 21 June 2017 by Springer Nature in Environmental Monitoring and Assessment
This study investigates the assessment of uncertainty contribution in projected changes of high and low flows from parameterization of a hydrological model and inputs of ensemble regional climate models (RCM). An ensemble of climate projections including 15 global circulation model (GCM)/RCM combinations and two bias corrections (change factor (CF) and bias correction in mean (BC)) was used to generate streamflow series for a reference and future period using the Hydrologiska Byråns Vattenbalansavdelning (HBV) model with the 25 best-fit parameter sets based on four objective functions. The occurrence time of high flows is also assessed through seasonality index calculation. Results indicated that the inputs of hydrological model from ensemble climate models accounts for greater contribution to the uncertainty related to projected changes in high flows comparing to the contribution from hydrological model parameterization. However, the uncertainty contribution is opposite for low flows, particularly for CF method. Both CF and BC increases the total mean variance of high and low flows. The variability in the occurrence time of high flows through RCMs is greater than the variability resulted from hydrological model parameters with and without statistical downscaling. The CF provides more accurate timing than BC and it shows the most pronounced changes in flood seasonality.
Climate change impacts on extreme precipitation of water supply area in Istanbul: Use of ensemble climate modelling and ...Published: 14 July 2016 by Informa UK Limited in Hydrological Sciences Journal
Climate change effects on extreme flows of water supply area in Istanbul: utility of regional climate models and downsca...Published: 22 August 2015 by Springer Nature in Environmental Monitoring and Assessment
This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960–1990) and scenario (2071–2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained.
This study investigates whether snowmelt runoff for the selected 15 streamflow stations located in the Euphrates, Tigris, Aras, and Çoruh basins in eastern Anatolia, Turkey, has shown a consistent hydrologic response to global climatic changes over the past several decades. It also investigates the future runoff changes in these basins. The analysis utilizes streamflow and meteorological data from 1970 to 2010 available within the study area to identify spatial and temporal patterns of trends in the seasonality of streamflow, temperature, and precipitation. Results indicate significant temperature increases (average 1.3 °C across the stations) over the time period. They also indicate increases in annual precipitation (average 7.5% across the stations) but the increases are not significant, in general. The streamflow timings in the mountainous basins are found to have already shifted to earlier days in the year (9 days on average), and this is a clear indication of earlier spring melting of snowpack due to increasing temperatures in recent years. Eight among fifteen stream gauging stations in the basins show significant time shifts in snowmelt runoff according to statistical trend tests (based on 90% confidence level). A regional climate change simulation based on a high emissions scenario suggests 10–30% declines in the annual surface runoffs of Aras, Euphrates, and Tigris basins and a slight increase (about 4%) in the annual surface runoff of Coruh basin by the end of the present century. It further indicates that the timing of the peak flows will continue to shift earlier (by about 4 weeks over the century) in response to further warming, increasing the fraction of winter runoff while decreasing the fraction of spring runoff in the year in all these basins.
This study investigated the performance of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU-NCAR) Mesoscale Model (MM5) in calculating the aerosol forcing on cloud cover, incoming surface solar radiation, and near-surface air temperature via the implementation of aerosol optical depth in the shortwave radiation parameterization. MM5 simulations with and without aerosol data are performed in the periods of 6–7 August 2003 and 19–21 September 2003 during which strong aerosol forcing was observed with Moderate Resolution Imaging Spectroradiometer (MODIS) data in the mid-Atlantic region. Both periods clearly showed that aerosols had a direct negative effect on surface solar radiation through aerosol scattering. For example, every 0.1 change in MODIS aerosol optical thickness (AOT) results in 44 and 59 W m−2 decreases in surface solar radiation for the first and second periods, respectively. A magnitude of 0.1 increment in MODIS AOT reduces air temperature 0.36 and 0.56 K for the first and second periods, respectively. Comparisons with satellite-derived surface solar radiation retrievals showed that aerosol implementation in MM5 consistently showed better incoming surface solar radiation than that of the non-aerosol case. This helps to reduce uncertainties related to the radiation–cloud–aerosol interaction in numerical weather modelling systems.