Basin Turkey Research Articles

Multiscale investigations on RDI-SPI teleconnections of Çoruh and Aras Basins, Türkiye using Time Dependent Intrinsic Correlation

This paper proposes a multiscale dynamic correlation framework based on time-dependent intrinsic correlation (TDIC) to investigate the teleconnections between reconnaissance drought index (RDI) and standardized precipitation index (SPI). The SPI and RDI indices were calculated at 3-, 6-, and 12-month time scales using data from six stations in the Çoruh and Aras (CA) basins in Turkey for the 1969 - 2020 period. The spatial variability of the evaluation of the drought class demonstrated that, with the exception of the northwestern region (Bayburt station), the correlation between RDI and SPI exceeded 97% and the difference in occurrence between drought classes is found to be marginal. In the multiscale analysis of the two indices, firstly, the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (I-CEEMDAN) was employed to decompose the series. The modes of RDI and SPI at different process scales exhibited a strong positive linear correlation, however, the association in their long-term trends may not be of the same nature. The TDIC analysis captured the long-range correlations between the modes of RDI and SPI at diverse process scales, and the newly proposed average significant correlation (ASC) measure could quantify their strength. Within the basin, there exists strong interconnections between SPI and RDI, with the exception of the observed alterations in their nature and strength at short time spells in some inter-annual scales. The proposed TDIC based framework is a generic and robust alternative for multiscale investigation studies while ASC can quantify the strength of non-linear associations at distinct process scales.

Meteorological Drought Analysis and Regional Frequency Analysis in the Kızılırmak Basin: Creating a Framework for Sustainable Water Resources Management

Drought research is needed to understand the complex nature of drought phenomena and to develop effective management and mitigation strategies accordingly. This study presents a comprehensive regional frequency analysis (RFA) of 12-month meteorological droughts in the Kızılırmak Basin of Turkey using the L-moments approach. For this purpose, monthly precipitation data from 1960 to 2020 obtained from 22 meteorological stations in the basin are used. In the drought analysis, the Standard Precipitation Index (SPI), Z-Score Index (ZSI), China-Z Index (CZI) and Modified China-Z Index (MCZI), which are widely used precipitation-based indices in the literature, are employed. Here, the main objectives of this study are (i) to determine homogeneous regions based on drought, (ii) to identify the best-fit regional frequency distributions, (iii) to estimate the maximum drought intensities for return periods ranging from 5 to 1000 years, and (iv) to obtain drought maps for the selected return periods. The homogeneity test results show that the basin consists of a single homogeneous region according to the drought indices considered here. The best-fit regional frequency distributions for the selected drought indices are identified using L-moment ratio diagrams and ZDIST goodness-of-fit tests. According to the results, the best-fit regional distributions are the Pearson-Type 3 (PE3) for the SPI and ZSI, generalized extreme value (GEV) for the CZI, and generalized logistic distribution (GLO) for the MCZI. The drought maps obtained here can be utilized as a useful tool for estimating the probability of drought at any location across the basin, even without enough data for hydrological research.

Formative drought rate to quantify propagation from meteorological to hydrological drought

AbstractIn this study, we propose a probabilistic metric, the formative drought rate (FDR), to quantify drought propagation. It is the probability that a meteorological drought in precipitation forms a hydrological drought in streamflow. Drought events were identified based on the standardized precipitation index and streamflow drought index, respectively, at 1‐, 3‐, 6‐ and 12‐month timescales. The method was tested in three river basins in Turkey (Kucuk Menderes, Gediz and Ergene). In each river basin, meteorological stations were coupled with streamflow gauging stations to form pairs of stations depending on their distance from each other and the length of their common record periods. The FDR was calculated across all timescales for each pair of stations. It was found capable to describe the river basin‐specific spatial and temporal variability of drought propagation. As the FDR is defined in the form of probability, it is expected to be a useful metric for quantifying propagation from meteorological to hydrological drought. Thus, it carries a potential for scientific research and practice in water resources management.

Exploring the Spatial Distribution of Coastal Drainage Basins in Turkey

Coastal regions are vital areas globally, serving as hubs for human habitation and economic activities. Water, being the fundamental resource for life, plays a crucial role in sustaining ecosystems and shaping coastal landscapes. The convergence of river systems in coastal zones underscores their significance in the hydrological cycle and aquatic biodiversity. However, managing these valuable yet vulnerable regions presents multifaceted challenges, necessitating robust management frameworks supported by monitoring and assessment tools. In Türkiye, a country with limited freshwater resources, the management of coastal zones is particularly complex due to increasing pressure on resources and land. This study examines the distribution and characteristics of river and coastal basins in Türkiye. Through spatial analyses on Geographical Information System and basin delineations with watershed modelling program, the study clarifies the regional differences and obstacles encountered by coastal provinces spanning the entirety of Türkiye's coastal borders. The results offer valuable understanding regarding the spatial dynamics of Türkiye's coastal areas with particular emphasis on the significance of Black Sea coastal basins and all coastal provinces. Firstly, river basin systems draining into the Black Sea constitute the majority of Türkiye's surface area. Although the Black Sea region covers only 14% of the total area, more than half of the country's surface area, excluding transboundary and endorheic basins, drains into the Black Sea. Similarly, the analysis of basin types reveals that coastal basins constitute approximately 18% of the drainage areas associated with our coastal waters, nearly one-fifth. This distinction between coastal basin and river basin boundaries differs from the traditional zoning approach in river basin management and coastal area management plans in Türkiye. Consequently, it is anticipated that this spatial evaluation, which has brought a new perspective, will significantly contribute to addressing management challenges, especially the studies that will be evaluated together with population and resource use.

Investigation of the variability applying classical (MK-SR) and modern (ITTA-TPSC) trend methods to meteorological parameters of Marmara Basin in Turkey

Scientific studies for countries experiencing climate change have accelerated recently. Turkey is among the countries experiencing climate change. Studies carried out for this country or its basins are of great importance both for the basin and the country. Therefore, Marmara Basin, where Turkey's population density is highest and industrialization is at the most advanced level, is selected in this study. The length of meteorological data is 45 years. The analysis of these data is made with Mann-Kendall (MK) and Spearman Rho (SR), which are classical trend methods, and Innovative Triangle Trend Analysis (ITTA) and Trend Polygon Star Concept (TPSC), which are modern trend methods. When the studies on Marmara basin are examined, there is no study that includes these four methods. Therefore, this study stands out in this respect. Because these analysis methods will reveal a new idea by applying them to hydro-meteorological data within the basin area. Before applying MK method, serial correlation method is applied to the meteorological parameter data of all stations. When the analysis results are examined; a general increasing trend is observed in precipitation data for ITTA and TPSC methods. No trend is observed in precipitation data for MK and SR methods. A general increasing trend is observed in temperature data for ITTA, MK and SR methods. However, a generally decreasing trend is observed in temperature data for TPSC method. While there is generally no trend in relative humidity data for MK and SR methods, an increasing trend is observed for ITTA and TPSC methods.

A novel metaheuristic optimization and soft computing techniques for improved hydrological drought forecasting

Drought is one of the costliest natural disasters worldwide and weakens countries economically by causing negative impacts on hydropower and agricultural production. Therefore, it is necessary to create drought risk management plans by monitoring and predicting droughts. Various drought indicators have been developed to monitor droughts. This study aims to forecast Streamflow Drought Index (SDI) values with various novel metaheuristic optimization-based Artificial Neural Network (ANN) and deep learning models to predict 1-month lead-time hydrological droughts on 1, 3, and 12-month time scales in the Konya closed basin, one of the driest basins in Turkey. To achieve this goal, the ANN model was integrated with the Firefly Algorithm (FFA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) techniques and compared against long short-term memory (LSTM) networks. While establishing the SDI prediction model, lag values exceeding the 95% confidence intervals in the partial autocorrelation function graphs were used. Model performance was evaluated according to scatter matrix, radar, time series, bee swarm graphs, and statistical performance metrics. As a result of the analysis, the PSO-ANN hybrid model with (R2:0.468–0.931) at station 1611 and the FFA-ANN hybrid model with (R2:0.443–0.916) at station 1612 generally have the highest accuracy.

Rapid identification of flood-prone settlements in the Eastern Mediterranean Basin in Turkey

Territories and settlements in low plains are at risk of flooding. Therefore, determining the areas at risk of flooding before preparing city plans or country development plans is essential. The number of hydrological models is increasing day by day; on the other hand, the solution of these models requires too many parameters. Long-term measurements are required to perform flood analysis with these models. However, in some regions, data from previous years may not always be available. Therefore, a method that enables the determination of flood-prone areas in a short time based on historical records is proposed in the current study. In the current study, the Eastern Mediterranean basin has an area of 21,682 km2 was examined. Using geographic information system (GIS) and the current population information (growth trend) as well as evaluating the historical process and archival records, 157 flood-prone settlement areas were identified. Different flood scenarios were examined and settlement areas that needed to be further examined by modeling were digitized. We aimed to create a base for basin-based flood modeling and to provide information about flood-prone areas to local administrators for national and local plans.

A Review on the 3D Cartographic and Spatiotemporal GIS Models for Safety of Accidents in Deep Underground Coal Mines

The aim of this study was the safety risk assessment of accidents that occur because of production dynamics in deep coal mining, one of the highly dangerous business class, with spatiotemporal GIS. In this study, accidents that occur at certain times during production in underground mining workplaces are discussed based on evaluations of spatial and temporal dimensions. Accordingly, various analyses have been handled using criminology science tactics and strategies such as 80–20, kernel density, space–time cube, and hot spot, which have been adapted to GIS tools. Implementations have been realized on 3D underground cartographic models covering accident data from deep coal mine workplaces in the Zonguldak-Kozlu basin in Turkey between 2019 and 2021, at an average elevation of – 400 m. Space–time cube, kernel density, and time series analyses suggest that the Annual Bonus Incentives, which are repeated every year and given before the new year, increase the psychosocial risks for employees. It has been determined that this situation can lead to problems such as poor concentration among miners and loss of focus in some shifts. Additionally, significant relationships were found between the number of accidents and monthly production progress rates as a temporal parameter. The results demonstrate that applying a reactive approach with spatiotemporal GIS to accidents in deep coal mines is becoming increasingly important.

Spatial characterization of drought through CHIRPS and a station-based dataset in the Eastern Mediterranean

Abstract. Drought is a natural hazard which occurs in all climatic zones and affects different sectors, such as irrigation, energy, water supply, and ecology. Monitoring and predicting drought are pressing challenges, as drought is becoming more common and severe owing to the impacts of climate change and increased climatic variability. However, in many areas of the globe, the temporal and spatial characterization of droughts and drought severities are hindered by a lack of reliable, locally-measured long-term data and unevenly distributed, erratic meteorological stations. In this situation, remote sensing datasets such as Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) can offer valuable insights into long-term developments and the spatial characteristics of droughts. Nonetheless, it is often uncertain to which extent data such as CHIRPS succeeds in representing local dynamics and how this varies between geographical regions and climate zones. In this analysis, we aim to evaluate spatial drought conditions over the Seyhan River basin in Turkey in the Eastern Mediterranean. Using the Standardized Precipitation Index (SPI) as a drought index, the applicability of CHIRPS as a long-term satellite precipitation product for drought monitoring is investigated. We compare two spatial representations of the SPI: one derived on a per-pixel basis from CHIRPS data since 1981, the other based on data from 19 meteorological stations scattered across the basin, which was spatialized using inverse distance weighted interpolation (IDW). Our results offer insights into the relative accuracy of CHIRPS data and avenues towards optimizing the quality of spatial drought characterization.

Drought Assessment of Yeşilırmak Basin Using Long-term Data

Drought is a prolonged period of inadequate rainfall, such as one season, one year or several years, on a statistical multi-year average for a region. Drought is a natural disaster effective on several socio-economic activities from agriculture to public health and leads to deterioration of the environment sustainability. The drought starts with meteorological drought, continues with agricultural and hydrological drought, and when it is in the socioeconomic dimension, the effects begin to be observed. Generally, drought studies are based on drought indices in the literature. This study applied long-term precipitation, temperature, and evaporation data from Samsun, Tokat, Merzifon, Çorum and Amasya meteorological stations from 1961 to 2022 to investigate the drought in the Yeşilırmak basin of Turkey. The present study applied Standardized Precipitation Index (SPI), and Effective Drought Index (EDI), China Z- Index (CZI) and Standardized Precipitation Evapotranspiration Index (SPEI) based on daily, monthly, seasonal, and annual time periods to evaluate drought. The Sen slope and Mann-Kendall test were employed for data analysis. The results revealed that the monthly drought indices for the study area were almost identical for the study area. Although dry and wet periods were observed.

Disaster Risk Assessment of Fluvial and Pluvial Flood Using the Google Earth Engine Platform: a Case Study for the Filyos River Basin

The aim of this study is to conduct a risk analysis of fluvial and pluvial flood disasters, focusing on the vulnerability of those residing in the river basin in coastal regions. However, there are numerous factors and indicators that need to be considered for this type of analysis. Swift and precise acquisition and evaluation of such data is an arduous task, necessitating significant public investment. Remote sensing offers unique data and information flow solutions in areas where access to information is restricted. The Google Earth Engine (GEE), a remote sensing platform, offers strong support to users and researchers in this context. A data-based and informative case study has been conducted to evaluate the disaster risk analysis capacity of the platform. Data on three factors and 17 indicators for assessing disaster risk were determined using coding techniques and web geographic information system (web GIS) applications. The study focused on the Filyos River basin in Turkey. Various satellite images and datasets were utilized to identify indicators, while land use was determined using classification studies employing machine learning algorithms on the GEE platform. Using various applications, we obtained information on ecological vulnerability, fluvial and pluvial flooding analyses, and the value of indicators related to construction and population density. Within the scope of the analysis, it has been determined that the disaster risk index (DRI) value for the basin is 4. This DRI value indicates that an unacceptable risk level exists for the 807,889 individuals residing in the basin.

Determination of Effective Parameters for Hydropower Plants’ Energy Generation: A Case Study

The current study aims to conduct a comprehensive analysis of the key parameters that affect the energy output of the Bagisli Hydropower Plant, located on the Zap River in the Dicle (Tigris) basin of Turkey. It considers the daily data for the time interval of 2016–2019 related to flow rate, precipitation, and temperature in relation to the generation of electricity. The relationship between energy output and flow rate is evident; however, the energy production is limited by the design flow rate. The largest flow rates were seen during the spring season after the occurrence of peak precipitation, which exhibited a shifting pattern. Similarly, energy generation also reaches its highest level during this time period. Another outcome of this study is that there is no apparent association between daily precipitation and daily energy generation. Moreover, a novel correlation with an R2 value of 0.89 has been proposed, in the deviation band of ±20%, to estimate energy generation when only flow rate data are available.

Spatiotemporal analysis of precipitation variability in an endorheic basin of Turkey with coordinated regional climate downscaling experiment data

Understanding how temporal precipitation variability will behave in the future is crucial. Change point detection and sub-trend analysis were done on monthly total precipitation data acquired from the Coordinated Regional Climate Downscaling Experiment project in this study. Sub-periods have been determined based on the natural structure of the data set, as opposed to standard sub-period determination approaches. For the period 1971–2100, six different time series were used under three global climate models (CNRM-CERFACS-CNRM-CM5, ICHEC-EC-EARTH, MPI-M-MPI-ESM-LR) and two emission scenarios (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5). The study area has been selected to be the Konya Endorheic Basin in Turkey, which has been significantly influenced by climate change and human impacts. For change point detection, the Pruned Exact Linear Time method (PELT) and Binary Segmentation (BS) were employed, for trend analysis, Mann Kendall (MK) and Şen-Innovative Trend Analysis (Şen-ITA), and for both change point detection and sub-trend analysis, the Onyutha Trend Test (OTT) was utilized. The findings revealed four change points and five sub-periods. Summer precipitation has reduced considerably at a 95% significance level. There is strong evidence that precipitation has decreased between 1981 and 2070. Precipitation decreases similarly in the middle basin for the 1981–2000 and 2041–2070 years.

Impact of climate change and land cover dynamics on nitrate transport to surface waters.

The study investigated the impact of climate and land cover change on water quality. The novel contribution of the study was to investigate the individual and combined impacts of climate and land cover change on water quality with high spatial and temporal resolution in a basin in Turkey. The global circulation model MPI-ESM-MR was dynamically downscaled to 10-km resolution under the RCP8.5 emission scenario. The Soil and Water Assessment Tool (SWAT) was used to model stream flow and nitrate loads. The land cover model outputs that were produced by the Land Change Modeler (LCM) were used for these simulation studies. Results revealed that decreasing precipitation intensity driven by climate change could significantly reduce nitrate transport to surface waters. In the 2075-2100 period, nitrate-nitrogen (NO3-N) loads transported to surface water decreased by more than 75%. Furthermore, the transition predominantly from forestry to pastoral farming systems increased loads by about 6%. The study results indicated that fine-resolution land use and climate data lead to better model performance. Environmental managers can also benefit greatly from the LCM-based forecast of land use changes and the SWAT model's attribution of changes in water quality to land use changes.

The effect of climate change on energy generated at hydroelectric power plants: A case of Sakarya river basin in Turkey

In this study, the effect of climate change on energy data produced in HEPPs in Sakarya River basin of Turkey was investigated. Data were analysis by using classical and modern analysis methods. Before applying these methods, serial correlation coefficients of the data were calculated and it was decided whether trend methods would be applied or not. As a result of the study, while a decreasing trend was observed in Mann-Kendall (50 % of data) and Innovative Trend Analysis (ITA) (90 % of data) methods in energy and streamflow data, unstable trends were observed in Three-Dimensional Innovative Trend Analysis (3D-ITA) method (70 % of data). However, a stable decreasing trend was observed in the middle region in energy and streamflow data of Pamukova HEPP. No trend was generally observed in all methods in precipitation data of Sakarya province. Stable trends were observed in the 3D-ITA method (In 67 % of the region). A generally increasing trend was observed in all methods in temperature data of Sakarya province. Stable trends were observed in the 3D-ITA method (In 67 % of the region). The beginning of the trend in Mann-Kendall Rank Correlation method in both energy-streamflow data and precipitation-temperature data showed the second half of 2016.

Screening of Bean Genotypes Against Bean Common Mosaic Virus (BCMV) by Artificial Inoculation and Molecular Confirmation

Bean mosaic virus (BCMV) is a widespread plant pathogen that causes significant bean yield losses in several bean-growing regions worldwide. The use of resistant common bean varieties to BCMV is considered the most efficient and feasible approach to control its effects. Numerous genes and molecular markers associated with resistance to these pathogens have been discovered and used extensively in breeding studies around the world. Screening bean genotypes for resistance to these viruses is a critical step in developing resistant varieties. The goals of the study are to identify virus sources in the region and artificially inoculate Lake Van basin bean genotypes with BCMV. The recovered BCMV strain NL-4 was inoculated with 45 bean cultivars, most of which originated from the Lake Van basin in Turkey. Differentiation between resistant and susceptible was based on visual symptoms, and of the 45 genotypes, 29 were found to be resistant to NL-4, while 16 genotypes were susceptible (8 of them moderately susceptible and 8 of them highly susceptible).

Eutrophication Status of the Berdan and Göksu River Basins in Turkey

Eutrophication Status of the Berdan and Göksu River Basins in Turkey

Evaluation of the seroprevalence and the demographic and clinical findings of fascioliasis patients in the Dicle River Basin in Turkey: a nine-year experience at a university hospital.

Fasciola hepatica and Fasciola gigantica are liver trematodes that cause fascioliasis in humans and animals. In Turkey, the medical importance of fascioliasis has been increasing in humans, and it continues to cause great economic loss in the field of animal husbandry. Therefore, it is important to diagnose fascioliasis quickly and reliably. The aim of this study is to show that the ELISA test is a reliable and specific method for diagnosing fascioliasis both in the early stage and in the acute stage. In this study, 640 individuals aged 7-75 years who showed one or more symptoms of fascioliasis, such as abdominal pain, fever, weight loss, weakness, fatigue, headache, sweating, nausea, vomiting, allergic urticaria, liver mass, hypereosinophilia, or liver enzyme elevation, were recruited from the Dicle University Research and Application Hospital in southeastern Turkey. Serum and fecal samples were taken from them to investigate if the Fasciola hepatica IgG antibody was present in the serum and if eggs were present in the feces. To detect the IgG antibodies, an enzyme-linked immunosorbent assay (ELISA) kit was used. The stool samples were analyzed for three consecutive days in mini Parasep fecal parasite concentrator tubes using the native-lugol and sedimentation methods. Abdominal ultrasonography and computed tomography were performed in all the patients. Among the subjects of this study, 90 (14%) were positive for fascioliasis, of whom 85 (94.4%) were adults and 5 (5.5%), children; 73 (81.1%) were women and 17 (18.8%), men; 57 (63.3%) lived in the rural areas and 33 (36.6%), in the city center; 90 (14%) were positive for Fasciola hepatica IgG antibodies; (20%) had helminth eggs in their stools; and 85 (94.4%) had a history of eating watercress. According to the epidemiological classification for fascioliasis by Mas-Coma, the Dicle Basin, which is the setting of this study, is indeed a hyperendemic region. Thus, ELISA is a reliable and specific method of diagnosing fascioliasis, both in the early phase and in the acute phase, when the eggs are no longer seen in the stool.

Crustal thicknesses on Thrace Basin via receiver function

The Thrace Basin which is a geological and geographical feature located in southeastern Europe, is the largest and thickest Cenozoic sedimentary basin in Turkey. Various geophysical methods have been used to investigate the basin's properties, tectonic evolution and gain insights into its formation. Within the contexts we applied receiver function method to provide insights on the crustal thicknesses and Vp/Vs ratio beneath Thrace Basin. More than 100 events with magnitudes greater than 6.3 recorded between 2007 and 2022 are evaluated and crustal thickness and Vp/Vs ratio are inferred from H-k analysis. Due to a thick sedimentary fill the average Moho depth is ∼30 km and the average Vp/Vs ratio is ∼1.77 in the Thrace basin which are consistent with the previous studies.

Understanding water characteristics and arsenic contamination of Lower Bakırçay Basin (LBB) and its coastal wetland (Western Turkiye): from Bergama (Pergamum) to Çandarlı (Elaia) by hydrogeochemical tools and stable isotope signatures.

Bakırçay Basin is one of the largest and most productive basins in Turkey in terms of geothermal energy, history, mining, agriculture, and tourism. In this study, the lower part of the Bakırçay Basin was extensively examined using hydrogeochemical tools, encompassing 27 different water sample points in the basin, in alignment with the United Nations' 2030 sustainable development goals that focus on access to safe drinking water for all and climate action for carbon emissions. From the higher zones of the basin towards the coastal wetland, EC values increase from 212 to 26500 µS/cm. Again in the same direction, water types are Ca-Mg-HCO3 in hilly areas and Na-Cl at the coastal wetland. Salt marshes, which are the silent heroes of carbon sequestration, are the most important element of the Bakırçay coastal wetland. Irrigation water evaluation has also been made for agriculture, which is widespread in the basin. Except for the salty waters in the wetland, waters are suitable for irrigation. A contamination investigation was conducted in the waters with the aim of clean drinking water. As and Mn contamination, which exceeds the standard values, has been detected in the Bakırçay river and its tributaries, especially from the mining sites in LBB. The arsenic content of water in the study area varies between 2 and 62.2 ppb. Additionally, the study identified As(III) species, which is 60 times more toxic than As(V), in the study area. Stable isotope values (δ18O and δD) of waters in the basin are from - 6.66 to 1.43‰ and - 36.4 to 5.8‰, respectively, and all waters are of meteoric origin. It is essential to emphasize the importance of controlling mining activities in the basin, halting the construction of the port that will destroy the carbon sequestration coastal wetland, and instead, transforming it into a recreation area, the significance of which is now understood during the COVID-19 pandemic.