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.

Internal (blue) water footprint of municipal consumption: a case study for Turkey.

This study aimed to develop a common approach to investigate (blue) water footprint of consumption of municipalities. Analysis framework consists of two distinct phases as: water abstraction profile and water distribution and water use profile. In the proposed approach municipal water footprint (WFmunicipal) comprises three components: domestic water footprint (WFdomestic), industrial/commercial water footprint (WFindustrial/commercial), and public water footprint (WFpublic). The application of the methodology was demonstrated in Turkey. The overall objective was to identify water consumption profile regarding model components and assess spatial and temporal distributions in the country scale. In this scope, each component was determined for 81 cities. After the investigation of spatial differences, an answer to the question of, "whether water use is increasing or decreasing over time" was found. Results investigated that WFmunicipal was 140 L/ca.day in average and reached up to 300 L/ca.day in some cities. WFdomestic was about 100 L/ca.day and cities having lower values mostly located on north-west, south-east of the country. Furthermore, few spots with high values were observed for WFindustrial/commercial (with 10 L/ca.day average), and relatively lower values belonged to the cities in south-eastern region. WFpublic having 30 L/ca.day mean value had extremes in eastern part. Based on water consumption characteristics, cities were grouped using factor analysis and results created four groups of cities. Although eastern and western cities had no trends in water abstraction rate, other regions had decreasing trend in last 20 years. Investigation of (blue) water footprint of consumption of municipalities is believed to assist water managers to identify water use profiles and assess spatial and temporal distributions. This is important because water resources are becoming increasingly stretched to accommodate continued population and economic growth and to restore environmental flows.

Investigation of priorities in water quality management based on correlations and variations.

The development of water quality assessment strategies investigating spatial and temporal changes caused by natural and anthropogenic phenomena is an important tool in management practices. This paper used cluster analysis, water quality index method, sensitivity analysis and canonical correlation analysis to investigate priorities in pollution control activities. Data sets representing 22 surface water quality parameters were subject to analysis. Results revealed that organic pollution was serious threat for overall water quality in the region. Besides, oil and grease, lead and mercury were the critical variables violating the standard. In contrast to inorganic variables, organic and physical-inorganic chemical parameters were influenced by variations in physical conditions (discharge, temperature). This study showed that information produced based on the variations and correlations in water quality data sets can be helpful to investigate priorities in water management activities. Moreover statistical techniques and index methods are useful tools in data - information transformation process.

Utilization of the water quality index method as a classification tool.

The study comprised modification of the Canadian Council of Ministers of the Environment (CCME) Water Quality Index (CCMEWQI) to obtain a tool in classification of surface waters according to quality defined by the European Legislation-75/440/EEC. Three categories were proposed, and the category ranges of CCMEWQI have been modified depending on the objective chosen. The application of the CCMEWQI with modified categorization scheme was demonstrated to assess overall water quality by integrating observed water quality determinants in the Kucuk Menderes Basin, Turkey. In this scope, the samples analyzed for pH, total dissolved solids (TDS), chlorides (Cl), nitrate-nitrogen (NO3-N), dissolved oxygen (DO), biochemical oxygen demand (BOD5), sulfate (SO4), and boron (B), variables taken monthly over 2 years from the five monitoring sites, were processed. Results revealed that the overall surface water mainly fell within the A2 water class. The CCMEWQI with modified categorization scheme is believed to assist water managers to integrate and interpret the picture of overall water quality based on the European legislation concerning the quality required of surface water intended for the abstraction of drinking water in the Member States (75/440/EEC).

Detection of seasonal variations in surface water quality using discriminant analysis.

In the study, discriminant analysis (DA) was applied to water quality data set monitored in winter and summer months along 3 years to investigate seasonal variations of Tahtali Reservoir water quality. The variables were divided into two categories as "parameters naturally found in surface waters--Al, Fe, Mn, F, Ba, Cl, and SO(4)" and "pollutants-biochemical oxygen demand, chemical oxygen demand, and NO(3)". Linear discriminant functions were calculated to distinguish between winter and summer samples. Results revealed that water quality variables (naturally found in surface water and also pollutants) were distinctly different between two seasons. Seasonal changes of water quality caused by anthropogenic activities should be taken into consideration by the water managers especially in summer seasons in which higher concentrations were observed. The study showed that DA can be applied successfully to establish the seasonal variation in surface water quality and make it possible to design a future temporal sampling strategy in an optimal manner.

Utilization of statistics based classification approach to investigate water supply profile of Turkey.

In the paper water supply profile of Turkey was examined. In this scope, the questionnaire survey conducted by Turkish Statistical Institute in 2004 to investigate annual amount of water abstracted to drinking water networks by type of resources in 81 provinces was evaluated. In the questionnaire, sources were grouped under five categories as spring, (artificial) lake, river, reservoir and well. Due to the complex and multivariate characteristics of the data sets, to replace a large collection of variables with a smaller number of factors the statistical method "factor analysis" was performed. Results revealed that, water supply systems in the country were mainly governed by groundwater sources (well and/or spring). However, in the northeastern part of the country, rivers were allocated for drinking water supply. On the other hand, reservoir dependent cities were densely located in Marmara, Central Anatolia and Southeast Anatolia Regions. This study showed that statistics based classification methods assist decision makers to extract information from multidimensional complex data sets representing environmental conditions.

Investigation of temporal trends in hydrochemical quality of surface water in Western Turkey.

This study comprises application of non-parametric trend analysis (Mann-Kendall test and Sen's Slope estimator techniques) and multidimensional scaling method to water quality data sets. Water samples analyzed (for chloride, nitrate-nitrogen, sodium, sulfate and total dissolved solid parameters) semi-monthly at seven river monitoring stations in Tahtali Basin, Turkey for 6 years were evaluated. The results revealed that agricultural discharges caused spatial differences in terms of water quality in the basin. Moreover, variable concentrations generally decreased or did not change over time. This study showed that, trend detection and data grouping methods help decision makers to judge effectiveness of management programs.

Total maximum daily load (TMDL) based sustainable basin growth and management strategy.

This study focused on the development and application of the new approach 'Total Maximum Daily Load (TMDL) based sustainable basin growth and management strategy' to give better insight for the management of surface waters. The establishment of the proposed decision process mainly comprised: beneficial use designations-targets, interrogation of the ambient water quality, selection of variable(s) for TMDL analysis, water quality modeling, basin growth scenarios development and decision on the basin growth plan. The approach was validated through a systematic application study in a field case in Turkey, known as Tahtali Basin. Results revealed that decision process assists policy makers to develop realistic strategies that take into account the basin specific conditions.

Surface water quality assessment by environmetric methods.

This environmetric study deals with the interpretation of river water monitoring data from the basin of the Buyuk Menderes River and its tributaries in Turkey. Eleven variables were measured to estimate water quality at 17 sampling sites. Factor analysis was applied to explain the correlations between the observations in terms of underlying factors. Results revealed that, water quality was strongly affected from agricultural uses. Cluster analysis was used to classify stations with similar properties and results distinguished three groups of stations. Water quality at downstream of the river was quite different from the other part. It is recommended to involve the environmetric data treatment as a substantial procedure in assessment of water quality data.