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Ali Sorman
Department of Civil Engineering, Eskisehir Technical University, Eskisehir 26555, Turkey

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Journal article
Published: 19 July 2021 in Water
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In recent years, the potential impacts of climate change on water resources and the hydrologic cycle have gained importance especially for snow-dominated mountainous basins. Within this scope, the Euphrates-Tigris Basin, a snow-fed transboundary river with several large dams, was selected to investigate the effects of changing climate on seasonal snow and runoff. In this study, two headwater basins of the Euphrates River, ranging in elevation between 1500–3500 m, were assigned and SWAT was employed as a hydrological modeling tool. Model calibration and validation were conducted in a stepwise manner for snow and runoff consecutively. For the snow routine, model parameters were adjusted using MODIS daily snow-covered area, achieving hit rates of more than 95% between MODIS and SWAT. Other model parameters were calibrated successively and later validated according to daily runoff, reaching a Nash-Sutcliffe efficiency of 0.64–0.82 in both basins. After the modeling stage, the focus was drawn to the impacts of climate change under two different climate scenarios (RCP4.5 and RCP8.5) in two 30-year projection periods (2041–2070 and 2071–2099). From the results, it is estimated that on average snow water equivalent decreases in the order of 30–39% and snow-covered days shorten by 37–43 days for the two basins until 2099. In terms of runoff, a slight reduction of at most 5% on average volume is projected but more notably, runoff center-time is expected to shift 1–2 weeks earlier by the end of the century.

ACS Style

Ismail Peker; Ali Sorman. Application of SWAT Using Snow Data and Detecting Climate Change Impacts in the Mountainous Eastern Regions of Turkey. Water 2021, 13, 1982 .

AMA Style

Ismail Peker, Ali Sorman. Application of SWAT Using Snow Data and Detecting Climate Change Impacts in the Mountainous Eastern Regions of Turkey. Water. 2021; 13 (14):1982.

Chicago/Turabian Style

Ismail Peker; Ali Sorman. 2021. "Application of SWAT Using Snow Data and Detecting Climate Change Impacts in the Mountainous Eastern Regions of Turkey." Water 13, no. 14: 1982.

Preprint content
Published: 04 March 2021
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Evaluation of problems related to water resources development and management require accurate precipitation estimates. Although ground-based stations provide direct physical measurement of precipitation, the accuracy of gauge-based precipitation data in terms of quality and spatial pattern may still be controversial. On the other hand, Gridded Precipitation Datasets (GPDs) provide high spatial and temporal precipitation estimates. GPDs are continuously changing with the improving technology and updating of retrospective algorithms, but they still need to be assessed over different regions both in space and time before being used for hydro-climatic studies. This study attempts to evaluate the spatio-temporal consistency of 13 different GPDs (CPCv1, MSWEPv2.2, ERA5, CHIRPSv2.0, CHIRPv2.0, IMERGHHFv06, IMERGHHEv06, IMERGHHLv06, TMPA-3b42v07, TMPA-3b42RTv07, PERSIANN-CDR, PERSIANN-CCS and PERSIANN) over Turkey which is a country characterized by diverse climate and complex terrain. The evaluation is performed for daily and monthly time scales considering the entire period of 2015-2019 as well as seasonal (spring, summer, autumn and winter) variability. Precipitation data from 130 stations are provided as reference data for point-to-grid comparison of GPDs. The modified Kling Gupta Efficiency (KGE) is selected for qualitative analysis whereas the Hanssen–Kuipers Score (HKS) is used to identify the ability of GPDs for capturing various precipitation events. The Probability Density Function (PDF) is selected to evaluate the intensity frequency of 13 GPDs for individual daily-based precipitation events. The results indicate that all GPDs have a median KGE performance ranging between -0.11 and 0.53 for daily precipitation while their performance increases in the monthly case (median KGE from 0.16 to 0.82). Gauge-corrected GPDs exhibit slightly better results over the uncorrected datasets in comparison with ground observations. GPDs from multi-source merging perform better than only satellite-based and reanalysis precipitation datasets. Among uncorrected GPDs, ERA5 and CHIRPv2.0 perform better while PERSIANN perform worse in all conditions. MSWEPv2.2 suffers from high-altitude conditions during winter and CHIRPSv2.0 shows poor performance during dry seasons. On the overall, MSWEPv2.2 performs better than CHIRPSv2.0 during daily/monthly, while CHIRPv2.0 performs better than CHIRPSv2.0 for daily time scale.

ACS Style

Gokcen Uysal; Hamed Hafizi; Ali Arda Sorman. Spatial and temporal evaluation of multiple gridded precipitation datasets over complex topography and variable climate of Turkey. 2021, 1 .

AMA Style

Gokcen Uysal, Hamed Hafizi, Ali Arda Sorman. Spatial and temporal evaluation of multiple gridded precipitation datasets over complex topography and variable climate of Turkey. . 2021; ():1.

Chicago/Turabian Style

Gokcen Uysal; Hamed Hafizi; Ali Arda Sorman. 2021. "Spatial and temporal evaluation of multiple gridded precipitation datasets over complex topography and variable climate of Turkey." , no. : 1.

Preprint content
Published: 23 March 2020
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Water has an essential effect on climate change, global warming, drought, flood and all kinds of living life as a result of the continuous movement between earth and atmosphere. In high latitude and elevated regions of the world, most of the annual total precipitation occurs in the form of snow and snow melting provides the majority of usable water. Due to the large impact of snow cover on water/energy balance, the quantity, spatial and temporal distribution of the snow is very important in the hydrological system.

Turkey is the 4th highest country in Europe, after Andorra, Georgia and Switzerland, with an average elevation of 1140 m. Therefore, snow frequently occurs and may stay on the ground more than half of the year especially in the north, east and central regions. Snowmelt runoff in the mountainous eastern part of Turkey, where large dams are located, is of great importance as it constitutes 2/3 in volume of the yearly total runoff during spring and early summer months. Therefore, determining the amount and timing of snowmelt is of utmost value in order to use the water resources of the country in an optimal manner.

In this study; conceptual snowpack model SNOW-17, which has a common usage in the literature, is applied in a fully distributed manner in the Upper Euphrates Basin. SNOW-17 is a conceptual model using air temperature as the sole index to determine the energy exchange across the snow-air interface. The model results of snowpack components, such as height of snow (HS) and snow water equivalent (SWE) are evaluated with independent pointwise in-situ measurements and spatially distributed satellite images. The snow model results show an average success of 0.81 and 0.66 in terms of Nash-Sutcliffe Efficiency (NSE) for the calibration and validation periods, respectively. In addition, the extreme snowfall and early snowmelt event that occurred in 2004 snow season is further evaluated by the snow model and satellite products.

ACS Style

Ali Arda Sorman; Mustafa Cansaran Ertas. Assessment of Distributed Snow Modeling using Ground and Remote Sensing Data in Mountainous Eastern Turkey. 2020, 1 .

AMA Style

Ali Arda Sorman, Mustafa Cansaran Ertas. Assessment of Distributed Snow Modeling using Ground and Remote Sensing Data in Mountainous Eastern Turkey. . 2020; ():1.

Chicago/Turabian Style

Ali Arda Sorman; Mustafa Cansaran Ertas. 2020. "Assessment of Distributed Snow Modeling using Ground and Remote Sensing Data in Mountainous Eastern Turkey." , no. : 1.