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This paper studies the Upper Tigris River (UTR) drainage basin in Turkey for climate change impacted runoff estimations. Statistical downscaling method (SDM) is used by taking into consideration spatial dependence function (SDF) for the scenario precipitation projections at a set of available meteorology stations. Temporal adjustment between the climate scenarios and precipitation record time series is achieved by the white Markov (WM) stochastic process. Although various climate research center scenario data are considered, herein, only the general circulation model (GCM) A2 scenario data are adapted from the Hadley Center, England. The precipitation and runoff results are presented in decadal groups starting from 2001 to 2050 as cumulative monthly precipitation (CMP) and cumulative monthly runoff (CMR) graphs. It is observed that after 2021, precipitation decreases at about 12.5% and after 2030, it is 26%. Runoff projections indicate that they may decrease at about 30% especial after 2040. [ABSTRACT FROM AUTHOR]

This paper studied hydrological drought identified by the Streamflow Drought Index (SDI) at eight river-gauging stations in the Eastern Mediterranean part of Turkey for a roughly 43-year period covering from 1972 to 2014 (4 stations), from 1973 to 2015 (2 stations), and from 1969 to 2011 (2 stations). Results of SDI analyses indicate that the number of drought years was highest during the 3-month October–December period. A considerable part of the drought years was determined to be mild drought. Although moderate drought conditions were observed in all stations, moderate drought conditions were determined especially at Göksu-H in the Seyhan River Basin and Söğütlü and Savrun in the Ceyhan River Basin. Short-term fluctuations of dry and wet conditions are the dominant pattern for most of the stations; however, long-term persistent drought conditions are also prominent, especially at Tacin and Körkün in Seyhan Basin and Göksun in Ceyhan Basin. The starting point for the negative trend in the 12-month series was the years 1996, 1999, and 2000. [ABSTRACT FROM AUTHOR]

Drought has devastating effects, and its frequency has increased due to climate change. Therefore, it is important to specifically identify and evaluate the drought-sensitive areas for taking early measures against drought and controlling its effects. The purpose of this study is to evaluate the hydrological drought of the Orontes River Basin within the borders of Turkey in the Eastern Mediterranean using streamflow drought index (SDI) method. The historical droughts of the region are examined in three periods: first period (1954–1976), second period (1976–1998), and third period (1998–2020). The return periods of the drought parameters (duration, severity, peak) are evaluated by univariate and bivariate analysis (duration-severity and duration-peak) using copula functions. Among Ali-Mikhail-Haq, Clayton, Frank, Gumbel-Hougaard, Joe, and Galambos copulas, the Galambos copula function is found to be the best to represent the drought parameters according to the Akaike's information criterion (AIC) and Bayesian information criterion (BIC). As a result of the study, it is found that all parameters of drought (duration, severity, and peak) are considerably higher in the third period than in other periods. The severity of drought in the region is found to increase significantly in the third period. Moreover, the univariate return periods of the drought parameters and their bivariate return periods calculated using the Galambos copula are compared. [ABSTRACT FROM AUTHOR]

Knowledge of the historical changes in streamflow is essential for operating and planning water structures. Hence, the monthly mean streamflow trends of 20 streamflow gauge stations in Turkey's Mediterranean basins, which are sensitive to climate change, are examined using the Mann–Kendall test, and trend slopes are calculated using Sen's slope method. Furthermore, the innovative trend significance test (ITST) and recently proposed innovative polygon trend analysis (IPTA) method are used to analyse the historical changes in streamflow values at the stations. The trend analysis results of a total of 240-time series between 1977 and 2015 are evaluated and compared with three different trend methods. As a result of the study, the MK method determined significant trends in only 24% (3 increasing, 55 decreasing), ITST in 83% (41 increasing, 158 decreasing), and IPTA in 82% (38 increasing, 158 decreasing) of the 240-time series. The IPTA and ITST methods are more sensitive to determining significant monthly streamflow trends than the MK method. In addition, there is a more significant decrease in the streamflow values of the stations located east of the basin, and the trend slope value reaches − 26%/decade. Therefore, the results of the streamflow trend in the Mediterranean basins will benefit decision-makers in planning the efficient use of water resources in the region. [ABSTRACT FROM AUTHOR]

Meteorological drought is analyzed both in time and space by using drought indices based on site-specific precipitation and temperature data. Departure of precipitation from its normal called in this study as the Dimensionless Precipitation Anomaly Index (DPAI) is used at annual scale, while the Standardized Precipitation Index (SPI) using precipitation and the Standardized Precipitation Evapotranspiration Index (SPEI) using precipitation and temperature are considered at monthly time scale. Five meteorological stations over Kucuk Menderes River Basin in the western part of Turkey are selected for the case study. Results are presented in the forms of drought index time series, drought risk graphs, and drought severity maps. The prolonged severe historical dry periods of the river basin are correctly identified by the drought indices. It is seen that simple tools such as the drought indices used in this study based on easily available meteorological data could explain temporal variability at a site or spatial variability over a river basin. They are therefore important not only for the scientific community dealing with drought as a research problem but also for decision-makers, stakeholders, and end-users making practice about the drought through water allocation studies and drought management plans. [ABSTRACT FROM AUTHOR]

Prior to hydrological assessment of climate change at catchment scale, an applied methodology is necessary to evaluate the performance of climate models available for a given catchment. This study presents a grid-based performance evaluation approach as well as an intercomparison framework to evaluate the uncertainty of climate models for rainfall reproduction. For this purpose, we used outputs of two general circulation models (GCMs), namely ECHAM5 and CCSM3, downscaled by a regional climate model (RCM), namely RegCM3, over ten small to mid-size catchments in Rize Province, Turkey. To this end, five rainfall-borne climatic statistics are computed from the outputs of ECHAM5-RegCM3 and CCSM3-RegCM3 combinations in order to compare with those of observations in the province for the reference period 1961-1990. Performance of each combination is tested by means of scatter diagram, bias, mean absolute bias, root mean squared error, and model performance index (MPI) measures. Our results indicated that ECHAM5-RegCM3 overestimates the total monthly rainfall observations whereas CCSM3-RegCM3 tends to underestimate. In terms of maximum monthly and annual maximum rainfall reproduction, ECHAM5-RegCM3 shows higher performance than CCSM3-RegCM3, particularly in the coastland areas. In contrast, CCSM3-RegCM3 outperforms ECHAM5-RegCM3 in reproducing the number of rainy days, especially in the inland areas. The results also revealed that if a GCM-RCM combination performs well for a portion (statistic) of a catchment, it is not necessarily appropriate for the other portions (statistics). Moreover, the MPI measure demonstrated the superiority of ECHAM5-RegCM3 to CCSM3-RegCM3 up to 33 % excelling for annual rainfall reproduction in Rize Province. [ABSTRACT FROM AUTHOR]

In this study, meteorological time series from five meteorological stations in and around a watershed in Turkey were used in the statistical downscaling of global climate model results to be used for future projections. Two general circulation models (GCMs), Canadian Climate Center (CGCM3.1(T63)) and Met Office Hadley Centre (2012) (HadCM3) models, were used with three Special Report Emission Scenarios, A1B, A2, and B2. The statistical downscaling model SDSM was used for the downscaling. The downscaled ensembles were put to validation with GCM predictors against observations using nonparametric statistical tests. The two most important meteorological variables, temperature and precipitation, passed validation statistics, and partial validation was achieved with other time series relevant in hydrological studies, namely, cloudiness, relative humidity, and wind velocity. Heat waves, number of dry days, length of dry and wet spells, and maximum precipitation were derived from the primary time series as annual series. The change in monthly predictor sets used in constructing the multiple regression equations for downscaling was examined over the watershed and over the months in a year. Projections between 1962 and 2100 showed that temperatures and dryness indicators show increasing trends while precipitation, relative humidity, and cloudiness tend to decrease. The spatial changes over the watershed and monthly temporal changes revealed that the western parts of the watershed where water is produced for subsequent downstream use will get drier than the rest and the precipitation distribution over the year will shift. Temperatures showed increasing trends over the whole watershed unparalleled with another period in history. The results emphasize the necessity of mitigation efforts to combat climate change on local and global scales and the introduction of adaptation strategies for the region under study which was shown to be vulnerable to climate change. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to evaluate the impacts of climate change on Izmir-Tahtali freshwater basin, which is located in the Aegean Region of Turkey. For this purpose, a developed strategy involving statistical downscaling and hydrological modeling is illustrated through its application to the basin. Prior to statistical downscaling of precipitation and temperature, the explanatory variables are obtained from National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data set. All possible regression approach is used to establish the most parsimonious relationship between precipitation, temperature, and climatic variables. Selected predictors have been used in training of artificial neural networks-based downscaling models and the trained models with the obtained relationships have been operated to produce scenario precipitation and temperature from the simulations of third Generation Coupled Climate Model. Biases from downscaled outputs have been reduced after downscaling process. Finally, the corrected downscaled outputs have been transformed to runoff by means of a monthly parametric hydrological model GR2M to assess the probable impacts of temperature and precipitation changes on runoff. According to the A1B climate scenario results, statistically significant trends are foreseen for precipitation, temperature, and runoff in the study basin. [ABSTRACT FROM AUTHOR]