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https://hdl.handle.net/20.500.12511/4519

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A new innovative method for model efficiency performance
(IWA Publishing, 2022) Şen, Zekai; Şişman, Eyüp; Kızılöz, Burak
In every aspect of scientific research, model predictions need calibration and validation as their representativity of the record measurement. In the literature, there are a myriad of formulations, empirical expressions, algorithms and software for model efficiency assessment. In general, model predictions are curve fitting procedures with a set of assumptions that are not cared for sensitively in many studies, but only a single value comparison between the measurements and predictions is taken into consideration, and then the researcher makes the decision as for the model efficiency. Among the classical statistical efficiency formulations, the most widely used ones are bias (BI), mean square error (MSE), correlation coefficient (CC) and Nash-Sutcliffe efficiency (NSE) procedures all of which are embedded within the visual inspection and numerical analysis (VINAM) square graph as measurements versus predictions scatter diagram. The VINAM provides a set of verbal interpretations and then numerical improvements embracing all the previous statistical efficiency formulations. The fundamental criterion in the VINAM is 1:1 (45 degrees) main diagonal along which all visual, science philosophical, logical, rational and mathematical procedures boil down for model validation. The application of the VINAM approach is presented for artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS) model predictions.
Predicting a water infrastructure leakage index via machine learning
(Elsevier Ltd, 2022) Kızılöz, Burak; Şişman, Eyüp; Oruç, Halil Nurullah
In this study, the infrastructure leakage index (ILI) indicator that is preferred frequently by the water utilities with sufficient data to determine the performances of water distribution systems is modeled for the first time through the three different methodologies using different input data. In addition to the variables in the literature used for the classical ILI calculations, the age parameter is also included in the models. In the first step, the ILI values have been estimated via multiple linear regression (MLR) using water supply quantity, water accrual quantity, network length, service connection length, number of service connections, and pressure variables. Secondly, the Artificial Neural Network (ANN) approach has been applied with raw data to improve the ILI prediction performance. Finally, the data set has been standardized with the Z-Score method for increasing the learning power of the ANN models, and then the ANN predictions have been made by converting the data through the principal component analysis (PCA) method to minimize complexity by reducing the data set size. The model predictions have been evaluated via mean square error, G-value, mean absolute error, mean bias error, and adjusted-R2 model performance scale. When the model outputs obtained at the end of the study are evaluated together with the classical ILI calculations, it is seen that the successful ILI predictions with three and four variables, including the age parameter, rather than six variables, have been made through the PC-ANN method. Water utilities with insufficient physical and operational data for ILI indicator calculation can make network performance evaluations by predicting the ILI through the models suggested in this study with high accuracy in a reliable way.
Non-Revenue water ratio prediction with serial triple diagram model
(IWA Publishing, 2021) Kızılöz, Burak; Şişman, Eyüp
Water administrations attempt to control the Non-Revenue Water Ratio (NRWR) values in sustainable and well-performing water distribution infrastructures. In this respect, the NRWR value prediction through appropriate models over a small number of controllable variables is significant. The collection, monitoring, and predictions of data on variables that are used in the NRWR calculations are not practical and required significant time besides financial resources. In this study, the NRWR predictions have been made through the suggested method over three parameters. The model prediction accuracies, in the literature obtained by using the Triple Diagram Model (TDM) over two parameters, have been increased through the Serial Triple Diagram Model (STDM) suggested in this study. This method shows that better predictions are possible in the NRWR modeling. Thanks to the model applications developed in this study, water administrations can make predictions with the least error (less than 10% relative error) and certain variables, according to the characteristics of each water distribution network.
A new performance analysis model for urban water supply systems evaluation
(Desalination Publications, 2021) Kızılöz, Burak; Şişman, Eyüp
Non-revenue water (NRW) is among the performance indicators that have a great importance in urban water distribution systems. In this study, the probability statistical approach used to compare the temporal variations of the non-revenue water rate (NRWR) and a new performance evaluation chart have been suggested for practical use of the NRWR. The NRWR's probabilistic occurrence frequency and the statistical analysis provide a criterion for the performance evaluation and improvement of operating conditions. The NRWR performance indicator evaluation has been made for three periods of 12 districts in Kocaeli by considering the risk level. According to the study results, in the 2013-2015 periods, the performance of the Dilovasi, Gebze, and Kartepe districts has improved significantly compared to the 2010-2012 periods. Basiskele and Izmit have the highest performance level in the last period following Kandira. It will be possible to ameliorate the NRWR of districts in the future periods through the suggested site-specific model analysis and prioritize the plans by sampling the good district practices.
Wind quality designation concept and application
(Wiley, 2021) Şen, Zekai; Serencam, Uğur
Generally, wind energy production is based on the average wind speed without any classification. This article proposes a classification system on the basis of wind speed durations greater than a given threshold value. For this purpose, the wind quality designation (WQD) concept is defined based on the wind potential duration, amount, and intensity on a threshold level. Its classifications are depicted on five risk percentage classes as "excellent," "very good," "good," "fair," and "weak. Apart from the classification, the change of WQD with wind speed threshold provides qualitative and quantitative wind speed energy production assessment. The specific objective of the article is to present theoretical WQD explanations on the basis of the most frequently employed two-parameter Weibull probability distribution function (PDF). The application is provided for Adiyaman City, Kahta meteorology station wind speed records from the Southeastern province of Turkey. It is noticed that there is no "Weak" category at this station and the most effective quality class is "Excellent" from 14 m/s to almost 27 m/s wind speeds. The average wind speed corresponds to about 62% WQD. Finally, the wind speed potential durations PDF abides by the logarithmic-normal PDF, whereas amount and intensity accord with the Weibull PDFs.
The application of piecewise ITA method in Oxford, 1870-2019
(Springer Wien, 2021) Şişman, Eyüp; Kızılöz, Burak
In this study, the trends, stabilities of temperature, and rainfall data have been analyzed in detail for hydrometeorology time series recorded since 1870 in Oxford city in England. The innovative trend analysis (ITA) method has been used to identify and analyze the piecewise trends and stabilities of the selected time series. To compare the results, the modified Mann-Kendall (MMK) and Sen's slope (SS) methods have been applied to each series as a piecewise ITA application. To obtain reliable and objective conclusions, +/- 5% and +/- 10% trend percentage lines have been considered in the application of the ITA method. The piecewise ITA method provides more detailed information in this study, compared to the studies in the literature such as the MMK. Identification of trends that implies climate change is taken into consideration by the ITA approach for future design purposes. In this study, the available time series with a record length of 150 years has been divided into sub-series of 30 years considering the last 30-year period in which climate change began to be discussed due to its significant effects. As a result, when the trends of 150 years are examined for the different partial series, it is seen that the temperature increase in the 1990-2019 period is much higher than the past 120 years. The highest average rainfall occurred in the 1990-2019 and 1900-1929 periods, and their amounts are nearly similar.
Power law characteristics of trend analysis in Turkey
(Springer Wien, 2021) Şişman, Eyüp
Trend identification analyses in any hydrometeorological data are necessary and critical for predictions and planning in many disciplines such as atmospheric, environmental, and oceanographic sciences; water engineering; global warming; and climate change applications. In the literature, many researches have employed trend analyses by Mann-Kendall (MK) and innovative trend analysis (ITA) methods. Especially in recent years, the ITA method is preferred in trend identification methodological applications, because it can present trend graphs with visual inspection, verbal inferences, and objective quantitative calculations. In this paper, the trends of sea surface temperature (SST) data are identified by the MK and ITA methods on double logarithmic graphs, which provide fractal geometrical appearances with power law features. The SST data trends are evaluated at 22 coastal area stations of Turkey with monthly records from 1969 to 2014. According to the MK trend test, only 6 of the 22 stations had a significant upward trend at 5% significant level and 4 of these stations are in the Mediterranean Sea coastal area. At 10% significance level increasing trend numbers become 14 stations. According to the MK test results, the data records have been grouped into two parts as warming and cooling periods considering the physical conditions of the SST data. On the other hand, the results of ITA application provide average behavioral form according to the mathematical power law equations.
Exceedance probabilities of non-revenue water and performance analysis
(Springer, 2021) Kızılöz, Burak; Şişman, Eyüp
Water utilities evaluate the water distribution system performances by taking various performance indicators into consideration. However, it is necessary to digitize the current network characteristics and to provide hydraulic models, district metered area and pressure management system besides monitoring the water distribution systems by SCADA in order to identify an important part of these indicators. On the other hand, these studies are quite costly for underdeveloped countries including Turkey, so they are projected and applied partially in accordance with the budget of water utilities. Nevertheless, the utilities should control the network performance and make investments by taking the income and expenditure accounts into consideration. In this study, the network performances have been evaluated simply on the basis of the probabilities of exceedance determined with the help of innovative models based on risk calculations of non-revenue water volumes determined by using water supply and accrual amounts of the previous year held by water utilities. As a result, it is seen that the non-revenue water reduction performances of Izmit and Kandira have the highest levels in the evaluation years (2017 and 2018) based on 2010-2016 time period. Korfez has also the highest performance after the above-mentioned districts. On the other hand, the lowest performance occurred in Derince for analysis years. Thanks to the approach suggested in this study, the network performances can be analyzed easily through the data on the previous year water supply and accrual, and thus, future strategies and plans can be identified considering the improvements made.
Climate change impacts on sea surface temperature (SST) trend around Turkey seashores
(Springer International Publishing AG, 2021) Dabanlı, İsmail; Şişman, Eyüp; Güçlü, Yavuz Selim; Birpınar, Mehmet Emin; Şen, Zekai
This paper focuses on sea surface temperature (SST) trends due to the importance of temperature difference in climate change impact research. These trends are not only essential for climate, but they are also important for marine ecosystem. Immigration of fish population due to the temperature changes is expected to cause unexpected economical results. For this purpose, both classical Mann-Kendall, (MK) (Mann in Econom: J Econom Soc 13:245-259, 1945; Kendall in Rank Correlation Methods, Charless Griffin, London, 1975) and innovative trend analysis (ITA) (Sen in J Hydrol Eng 17(9):1042-1046, 2012) methodologies are applied for the SST data records. Monthly SST data are considered along the Black, Marmara, Aegean, and Mediterranean coastal areas in Turkey. SST data are categorized into five clusters considering fish life as "hot," "warm-hot," "warm," "cold," and "very cold." According to ITA, SST in all coastal areas tends to increase except for winter season during "very cold" (0-10 degrees C) temperatures. The temperature changes in both winter and summer seasons are expected to change the marine life, fish population, tourism habit, precipitation regime, and drought feature.
Gelir getirmeyen su oranı tahmin modelleri
(Niğde Ömer Halisdemir Üniversitesi, 2021) Kızılöz, Burak; Şişman, Eyüp
Bu araştırmada Gelir Getirmeyen Su Oranı (GGSO) tahminleri, Kocaeli’nin en fazla su kaybı yaşanan altı ilçesinin 2018 ve2019 yıllarına ait iki yıllık verisi dikkate alınarak ve tüketilen su miktarı, şebeke uzunluğu, servis bağlantı uzunluğu, toplam şebeke uzunluğu, şebeke yaşı ve şebeke basıncı ana parametreleri kullanılarak gerçekleştirilmiştir. Model tahminleri iki girdi ve tek çıktılı Yapay Sinir Ağı (YSA) modelleri ve Kriging yöntemi ile gerçekleştirilmiştir. Modellerde toplam şebeke uzunluğu ve iki girdili YSA model kombinasyonlarında ise, servis bağlantı uzunluğu ilk kez bu araştırmada model girdisi olarak kullanılmıştır. Yöntemlerin model çıktı performansları R2 ve HKOK performans ölçütleri üzerinden değerlendirilmiştir. Sonuç olarak; Kriging yöntemi ile gerçekleştirilen modellerin tahmin performansları YSA yöntemine göre oldukça iyidir. Kriging tekniği ile oluşturulan GGSO tahmin model çıktılarının değerlendirilmesi ve yorumlanması elde edilen tahmin haritaları sayesinde daha kolay yapılabilirken, kapalı model yapısına sahip olan YSA model sonuçlarında bu durum nitelikli uzmanlık gerektirmektedir.
Climate change impact on rainfall in north-eastern Algeria using innovative trend analyses (ITA)
(Springer Science and Business Media Deutschland GmbH, 2021) Boudiaf, Besma; Şen, Zekai; Boutaghane, Hamouda
Climate change impacts affect the hydrological cycle and hence the availability of water resources and their management. Rainfall, the most important hydro-meteorological event and as the main source of water, may have increasing or decreasing trends depending on geography and location, general air circulation, proximity to coastal areas, and geomorphology. There are many studies using monotonic trend analysis in the literature, but it is important to assess these trends at different levels for proper recording. For this purpose, in this paper, instead of using monotonic trend analysis, partial trends will be sought at “Low,” “Medium,” and “High” rainfall records groups, which is possible through the innovative trend analysis (ITA) methodology. Algeria being adjacent to the Mediterranean Sea is impacted by variations in rainfall. The application of the ITA methodology is presented for 16 different Algerian annual rainfall records from 1982 to 2019 in the north-eastern region of the country which is in proximity to the Mediterranean basin. Partially increasing, decreasing, or no trend pieces are identified at each station. It is concluded as the future unfolds some stations will record dry spell or drought dangers for “Low” data groups, and significant flood danger for the “High” rainfall amount data group. In general, the study area is known to be subject to an increasing rainfall trend. This is due to the mountainous terrain in the study area and makes for confrontation with cold air movements from the European continent during winter periods.
Extreme rain trend analysis in Macta watershed North West Algeria
(Springer, 2021) Benzater, Benali; Elouissi, Abdelkader; Dabanlı, İsmail; Benaricha, Boumediene; Hamimed, Abderrahmane
The north of Algeria is subject to floods generated directly by extreme rains. Detecting their trends, at different spatial and temporal scales, is a crucial step in the context of climate change. In this article, the Mann-Kendall method was used to detect the trends of maximum daily rains in 41 rainfall stations in the Macta watershed (North West Algeria) for a period of 41 years (1970-2010). The results show contrasting monthly trends; a significant increase, at the 5% (10%) confidence level, was detected in March, May, June, November, and December months, with 29% (7%), 24% (32%), 17% (24%), 12% (0%), and 10% (20%) of stations respectively. In terms of rain intensity, an increase was detected in April, July, August, September, October, and November. It is obvious that the months of August and September, representing the beginning of the autumn season, are marked by the greatest increases in the intensity of the rains justifying the catastrophic floods that hit our basin each year. The same significant upward trends are detected for autumn and winter, accompanied by an increase in quantities in the first season (autumn). Annually, a trend towards a significant increase trend, at 5% (10%) confidence level, in extreme rains with 20% (15%) of stations, was detected. Furthermore, a slight decrease in quantities was observed.
Trend-risk model for predicting non-revenue water: An application in Turkey
(Elsevier Science Ltd, 2020) Şişman, Eyüp; Kızılöz, Burak
Reducing non-revenue water (NRW) is one of the most significant strategies for the effective management of water resources. Efforts to reduce NRW and losses are also critical for planning the future budgets of water utilities. In this study, NRW prediction are made by a new approach based on trend and risk calculations based on historical data. Prediction, monitoring, and evaluation of NRW amounts according to specific risk values provide objective planning support for successful and sustainable water management. The relationship between specific risk levels and NRW loss amounts is explained through the model charts. Possible NRW losses for specific risk levels are predicted through 2023. NRW prediction provides advantages for budget balances and sound water utility decision-making, planning, and investment.
Artificial neural network system analysis and Kriging methodology for estimation of non-revenue water ratio
(IWA Publishing, 2020) Şişman, Eyüp; Kızılöz, Burak
The non-revenue water (NRW) ratio parameter is significantly important for performance evaluation of water distribution systems. In order to evaluate the NRW ratio, the variables influencing this parameter should be determined. Therefore, the first aim of the paper is to define the variables which are influential on the estimation of the NRW ratio and then analyze these variables by using artificial neural networks (ANNs) methodology by means of 50 models with one, two, three, and four-variable input. Secondly, in this study, the NRW ratios have been predicted for the first time by using the Kriging methodology through only two variables. By using the data measured in 12 district meter areas (DMA) in Kocaeli, 60 models in total have been established for NRW ratio prediction through the ANN and Kriging methodologies. The ANN models are closed-box models and therefore the interpretation of the ANN model results requires higher expert opinion. As a consequence, the results show that Kriging model graphs produce much more useful information than ANN models in terms of application and interpretation.
Wet and dry spell feature charts for practical uses
(Springer, 2020) Şen, Zekai; Şişman, Eyüp; Dabanlı, İsmail
Water resources management is dependent on wet and dry spells occurrences in an alternative manner. Therefore, information about their probabilistic occurrence frequencies and statistical parameters are the most required quantities for optimum and well-balanced operations for water demand. Among the most important dry spells are the meteorological (precipitation) and hydrological (runoff, stream flow, reservoir level, ground water level, etc.) drought occurrences and their future expectations under a certain level of risk (exceedance probability) or return period, which is the inverse of the risk. Firstly, this paper presents detection of wet and dry spell parameters among which are the duration, maximum surplus or deficit, magnitude, and intensity. Secondly, a set ofbeneficialcharts is presented in the new graphical form for each dry (wet) spell characteristic versus different risk levels (0.50, 0.20, 0.10, 0.04 0.02, 0.01, 0.004 and 0.002) corresponding to return periods (2-year, 5-year, 10-year, 25-year, 50-year, 100-year, 250-year and 500-year). These applications of the methodology are presented for New Jersey Statewide annual precipitation and Danube River annual discharge records each with more than 100 years records. Finally, it is found that the mathematical relationship between each wet and dry spell parameter and the return periods abide with exponential function, which appears on semi-logarithmic papers as straight lines. Consequently, it can be generalized for the study area that any drought (wet) parameters variation with the return period appears as exponential function for hydro-meteorological records.
Temperature and precipitation risk assessment under climate change effect in northeast algeria
(Springer International Publishing AG, 2020) Boudiaf, Besma; Dabanlı, İsmail; Boutaghane, Hamouda; Şen, Zekai
Climate change impacts on social, economic, industrial, agricultural, and water resource systems tend to increase incrementally with each passing day. Therefore, it is necessary to plan to control its effects, especially with regard to temperature and rainfall events impacting future water resource operation, maintenance and management works. Climate change has a direct influence at the trend of both components temperature and precipitation in increasing or decreasing manner depending on the study area. This paper presents and interprets temperature and rainfall trends for Northeast Algeria. A trend analysis technique was employed along with risk assessment. The modified risks associated with 2-, 5-, 10-, 25-, 50-, 100-, 250, and 500-year return periods are then calculated for each station. This methodology has been applied to precipitation and temperature records for six different meteorological stations in Northeast Algeria. This study confirms that climate change has and will continue to have an impact on temperature and precipitation that should be considered for all infrastructure planning, design, construction, operation, maintenance and optimum management studies in future.
Physical and practical hydrograph recession modeling in karstic sinkholes
(IWA Publishing, 2020) Şen, Zekai; Dabanlı, İsmail; Şişman, Eyüp
Karstic spring discharge is related to the hydraulic head recession through a power function with an exponent <1. In the literature, analytical solutions are available for exponential and non-exponential models based on a set of restrictive physical and mathematical assumptions. The models search for a holistic and deductive solution without basic physical and practical interpretations, simple logical inferences leading to mathematical analytical or empirical formulations. In this paper, an inductive, logical, practical, and instead of holistic modeling, physically plausible piecewise solutions are proposed with detailed inferences and interpretations. In the proposed methodology, the discharge and hydraulic head records are decomposed first into a set of verbal classes and, subsequently, physical meaning for each class is explained leading to simple general but empirical models. For this purpose, Wakula and St. Marks River (Florida) hydrograph records are used for the general solution sinkhole discharge and hydraulic head variations. The solution methodology presented in this paper does not make any distinction between relatively small or large sinkhole heads. The calibration and verification of the methodology is shown with a comparison of the available record values to partial power models. Finally, it is concluded that the proposed methodology is reliable and can be applied to hydraulic head availability with discharge records in any part of the world for karstic aquifer domains.
Self-similar characteristics of drought duration, total deficit, and intensity curves
(Springer, 2020) Şişman, Eyüp
Droughts are among the creeping extreme events with meteorological, hydrological, agricultural, and even social impacts. Due to their complex occurrences, drought identification and prediction need simple, effective, conceptual, logical, and rational innovative approaches that can help for practical applications. A new approach is being suggested at a set of threshold (or demand) levels to identify drought features such as duration, total deficit, and intensity relations, which depend on the run analysis and standardized precipitation index (SPI) methodology. This concept is applicable to identify mathematical relationships between the threshold values and the drought features. Exponential and power laws appear as straight lines on semi-logarithmic and double-logarithmic papers, respectively. In addition, power law implies self-similarity property with fractal geometrical patterns. As the threshold level increases, so does each one of the drought descriptors. Graphical representations help to identify climate change implications as well as practical design quantity determination. The applications of the suggested methodology are presented for monthly meteorological time series records. This methodology is also considered for the SPI over 6-month and 12-month moving average time scales at seven meteorology stations from different geographical parts of Turkey. The empirical mathematical expressions are obtained between the threshold values and the drought durations, total deficits, and drought intensities, which provide future drought characteristic predictions.
Innovative flow risk assessment with climate change perspective in Yesilirmak Basin
(Parlar Scientific Publications, 2020) Serancam, Uğur; Dabanlı, İsmail
Surface temperature increase due to global warming results in polar ice melting, snow cover thinning, changes in precipitation anomaly. All these phenological effects alert engineers, planners and administrators to be more sensitive against climate change-based risk effects on water structures. Vulnerability to natural disasters such as floods and droughts are expected to occur more frequent than past. Therefore, design and potential evaluation of water structures such as transmission channels, water wells, dams and hydraulic power generation facilities need to be re-evaluation. This re-evaluations procedure must be updated by taking into consideration climate change impacts with their risk assessments. For this purpose, the climate change-based risk levels are calculated from historically available records through possible trend tendencies, which are expressed in terms of trend slope. It has been observed that, in general, the climate change impacts are not significant on precipitation and runoff This is due to the low trend slopes in the standardized hydro-meteorological time series. This point has been documented for Yesilirmak basin, where the climate change impact is very limited.
Innovative triangular trend analysis
(Springer, 2020) Güçlü, Yavuz Selim; Şişman, Eyüp; Dabanlı, İsmail
In this study, based on the Sen innovative trend analysis (ITA) method, another approach has been developed as innovative triangular trend analysis (ITTA), which helps to identify partial trends within a given time series comparatively with each other. The basis of this methodology is to divide a given time series into a set of equal length sub-series and then to compare them pairwise in the form of a triangular array. In this manner, the trends within the whole series can be identified separately in detail. Consequently, it is possible to make much more realistic assessments depending on these trends. The application of the proposed method is carried out by considering the longest annual rainfall measurement records from 1966 to 2015, inclusive for stanbul, Rize, and Ankara provinces in Turkey. As a result, generally monotonically a negative trend in Ankara, no trend in Florya, and positive trend in Rize are determined by ITA methodology. On the other hand, instability of trends in time series is presented for these stations. Ankara has negative and no trend to the first 10 years and the last 20 years, respectively. Florya has successively positive and negative trends from the first to fifth part. As for Rize, according to ITTA, it has generally positive trends.

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