DRYNESS CHARACTERIZATION: A CLIMATIC WATER DEFICIT APPROACH IN TURKEY

Drought has several negative impacts on economy, society and ecology. The drought duration, magnitude and severity is of great importance and can be expressed by using different indexes which could give different information for the drought analysis. In this study, drought is analyzed using the concept of standardized precipitation index (SPI) and run analysis.This paper is to assess the temporal and spatial characteristics of meteorological droughts in the Aegean and Central Anatolian regions of Turkey for providing a guide for sustainable water resources management. Long-term precipitation and temperature data observed in 77 raingauge stations in these regions of Turkey are evaluated for the period of 1973-2006.Water deficit (WD) was calculated as difference between precipitation and evapotranspiration. SPI was calculated from precipitation values. There is a clear difference between drought and aridity. The dryness analysis by run analysis is based on water deficit (WD) data and identifies various aridity properties. Frequencies present a small reduction moving from north to south and from west to east within a region. In this study, through scatter diagrams between dryness magnitude and length are provided, and the link between SPI and WD run analysis is assessed. In addition, kriging is used as a spatial aridity analysis for mapping. Dryness period, magnitude and standardized precipitation index values are presented to depict the relationships between dryness duration and magnitude

Trend analysis of precipitation and drought in the Aegean region, Turkey

Trend analysis of precipitation and drought will play a significant role in the future development and sustainable management of water resources. It is the main purpose of this paper to analyse meteorological droughts and trends. The variability of the standardized precipitation index (SPI) was investigated at 1, 3, 6, 9, 12 and 24 monthly intervals. The trends of 1, 3, 6, 9, 12 and 24 monthly SPI results were analysed by applying linear regression and the Mann-Kendall and Spearman's rho tests at the 5% significance level. The linear slopes of the trends were calculated with a technique proposed by Sen. Meteorological data from eight meteorological stations in the Aegean region of Turkey were used for the period 1960-2013.The monthly precipitation trend decreases in December, January, February and March in all regions according to the linear regression analysis results. Annual precipitation decreased at five stations. In drought analysis by the SPI, in a short time period (such as 3months) drought is more frequent but shorter, and as the period increases the duration of drought also increases but frequency decreases. Winter droughts are beginning to occur in the class of severe' in recent years. In this study carried out for different time periods according to SPI values in all stations, the highest ranges are in the normal and mild drought degrees. In addition, severe and extreme droughts are also seen intensely frequently. Trend analysis of precipitation and drought is compared. The trend analyses of precipitation are in parallel with the results of drought analyses

DRYNESS CHARACTERIZATION: A CLIMATIC WATER DEFICIT APPROACH IN TURKEY

Drought has several negative impacts on economy, society and ecology. The drought duration, magnitude and severity is of great importance and can be expressed by using different indexes which could give different information for the drought analysis. In this study, drought is analyzed using the concept of standardized precipitation index (SPI) and run analysis.This paper is to assess the temporal and spatial characteristics of meteorological droughts in the Aegean and Central Anatolian regions of Turkey for providing a guide for sustainable water resources management. Long-term precipitation and temperature data observed in 77 raingauge stations in these regions of Turkey are evaluated for the period of 1973-2006.Water deficit (WD) was calculated as difference between precipitation and evapotranspiration. SPI was calculated from precipitation values. There is a clear difference between drought and aridity. The dryness analysis by run analysis is based on water deficit (WD) data and identifies various aridity properties. Frequencies present a small reduction moving from north to south and from west to east within a region. In this study, through scatter diagrams between dryness magnitude and length are provided, and the link between SPI and WD run analysis is assessed. In addition, kriging is used as a spatial aridity analysis for mapping. Dryness period, magnitude and standardized precipitation index values are presented to depict the relationships between dryness duration and magnitude

Public Health Rep

4965442PMCnul

concentrations in the Aegean Region of Turkey

Air pollution has temporal and spatial variability. Time series analysis is commonly used to evolution of air pollutants in time. The sulphur dioxide (SO2) and particulate matter (PM10) concentrations in the cities of the Aegean Region for the period of 1990-2009 have been modelled by using autoregressive (AR) and autoregressive moving average (ARMA) models for the yearly, monthly, and winter season pattern. The AR(2) model was generally observed for the yearly SO2 data in the Aegean Region according to the all investigated and AR(p) models. The AR(1), AR(2) and ARMA(1,2) models could provide reliable and satisfactory predictions for the yearly PM10 data according to the all analysed models. The most suitable model was predominantly determined as ARMA(1,2) model according to the all investigated models, while the best fitted model was mainly determined as AR(1) model according to the AR(p) type models for the monthly SO2 and PM10 data. The AR and ARMA models could be used for reliable and satisfactory predictions for the winter season SO2 and PM10 data to all analysed models

Adaptive Neuro-Fuzzy Inference System for drought forecasting

Drought causes huge losses in agriculture and has many negative influences on natural ecosystems. In this study, the applicability of Adaptive Neuro-Fuzzy Inference System (ANFIS) for drought forecasting and quantitative value of drought indices, the Standardized Precipitation Index (SPI), is investigated. For this aim, 10 rainfall gauging stations located in Central Anatolia, Turkey are selected as study area. Monthly mean rainfall and SPI values are used for constructing the ANFIS forecasting models. For all stations, data sets include a total of 516 data records measured between in 1964 and 2006 years and data sets are divided into two subsets, training and testing. Different ANFIS forecasting models for SPI at time scales 1-12 months were trained and tested. The results of ANFIS forecasting models and observed values are compared and performances of models were evaluated. Moreover, the best fit models have been also trained and tested by Feed Forward Neural Networks (FFNN). The results demonstrate that ANFIS can be successfully applied and provide high accuracy and reliability for drought forecasting

Applicability of apportionment entropy as a drought index

Drought is one of the most important natural disasters. The main aim of the present study is to investigate the applicability of the Apportionment Entropy (AE) as a drought index. For this purpose, the Standard Precipitation Index (SPI) and the AE method as a drought indices were investigated and compared for monthly precipitation data in Northern Aegean Region. In the presented study, 29 gauging stations with long term observations are evaluated in Northern Aegean Region. The results of the study showed that PE method can be used as a drought index and the analysis of drought results contributed to the identification of drought periods for the Northern Aegean Region

Meteorological drought analysis case study: Central Anatolia

Drought is one of the major disasters which might have consequences like hunger and poverty. The droughts depend on many factors including climatic and regional properties, soil type, population increase and environmental degradation. The complex character of drought makes it difficult to define. Hence, various specific criteria must be defined and used for the evaluated basin, region or territory to determine drought. In this study, several drought analysis methods are performed on the Central Anatolian Region in Turkey where has survived a severe drought. In comparative analysis, Palmer Drought Severity Index (PDSI), Erinc and De Martonne methods were used. The evaluated data consist of the observed monthly mean precipitation and temperature data of 13 selected meteorology stations in the region. The observed data in between 1965-2006 periods were evaluated for all stations. Thus, the distribution of dry and wet periods is investigated at monthly time scale. The comparative results show that PDSI index indicates more humid conditions than Erinc and De Martonne indices. Nevertheless, the results verify that the region is still in danger of severe drought