murat çobaner | Erciyes University (original) (raw)

Papers by murat çobaner

Hydrological Processes, 2010

The parameter estimation methods of (1) moments, (2) maximum-likelihood, (3) probability-weighted... more The parameter estimation methods of (1) moments, (2) maximum-likelihood, (3) probability-weighted moments (PWM) and (4) self-determined PWM are applied to the probability distributions of Gumbel, general extreme values, three-parameter log-normal (LN3), Pearson-3 and log-Pearson-3. The special method of computing parameters so as to make the sample skewness coefficient zero is also applied to LN3, and hence, altogether 21 candidate distributions resulted. The parameters of these distributions are computed first by original sample series of 14 successive-duration annual extreme rainfalls recorded at a rain-gauging station. Next, the parameters are scaled by first-degree semi-log or log-log polynomial regressions versus rainfall durations from 5 to 1440 min (24 h). Those distributions satisfying the divergence criterion for frequency curves are selected as potential distributions, whose better-fit ones are determined by a conjunctive evaluation of three goodness-of-fit tests. Frequency tables, frequency curves and intensity-duration-frequency curves are the outcome.

Water SA

There are many environmental concerns relating to the quality and quantity of surface and groundw... more There are many environmental concerns relating to the quality and quantity of surface and groundwater. It is very important to estimate the quantity of water by using readily available climate data for managing water resources of the natural environment. As a case study an artificial neural network (ANN) methodology is developed for estimating the groundwater levels (upper Floridan aquifer levels) as a function of monthly averaged precipitation, evaporation, and measured levels of Magnolia and Brooklyn Lakes in north-central Florida. Groundwater and surface water are highly interactive in the region due to the characteristics of the geological structure, which consists of a sandy surficial aquifer, and a highly transmissive limestoneconfined aquifer known as the Floridan aquifer system (FAS), which are separated by a leaky clayey confining unit. In a lake groundwater system that is typical of many karst lakes in Florida, a large part of the groundwater outflow occurs by means of vertical leakage through the underlying confining unit to a deeper highly transmissive upper Floridan aquifer. This provides a direct hydraulic connection between the lakes and the aquifer, which creates fast and dynamic surface water/groundwater interaction. Relationships among lake levels, groundwater levels, rainfall, and evapotranspiration were determined using ANN-based models and multiple-linear regression (MLR) and multiple-nonlinear regression (MNLR) models. All the models were fitted to the monthly data series and their performances were compared. ANN-based models performed better than MLR and MNLR models in predicting groundwater levels.

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi

Computers and Electronics in Agriculture, 2014

ABSTRACT One of the most important climatic factors influencing growth, development and yield of ... more ABSTRACT One of the most important climatic factors influencing growth, development and yield of crops, which involve a countless number of biochemical reactions, is temperature. It is also one of the most effective explanatory variables of the evapotranspiration estimation models such as Hargreaves, Rich and Thornthwaite needed for irrigation scheduling policies. Using artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models, means of maximum, minimum, and average monthly temperatures are estimated as a function of geographical coordinates and month number for any location in Turkey. The monthly data measured by the General Directorate of State Meteorological Works at 275 stations having records of at least 20 years are used in developing the models. The latitude, longitude, and altitude of the location, and the month number are used as the input variables, and each of the mean monthly maximum, minimum, and average air temperatures is computed as the output variable. The observed values are compared versus those predicted by the ANN, ANFIS, and MLR models by evaluating their errors, and as a result the ANFIS model turns out to be the best.

Water Resources Management, 2013

A regional flood frequency analysis based on the index flood method is applied using probability ... more A regional flood frequency analysis based on the index flood method is applied using probability distributions commonly utilized for this purpose. The distribution parameters are calculated by the method of L-moments with the data of the annual flood peaks series recorded at gauging sections of 13 unregulated natural streams in the East Mediterranean River Basin in Turkey. The artificial neural networks (ANNs) models of (1) the multi-layer perceptrons (MLP) neural networks, (2) radial basis function based neural networks (RBNN), and (3) generalized regression neural networks (GRNN) are developed as alternatives to the L-moments method. Multiple-linear and multiple-nonlinear regression models (MLR and MNLR) are also used in the study. The L-moments analysis on these 13 annual flood peaks series indicates that the East Mediterranean River Basin is hydrologically homogeneous as a whole. Among the tried distributions which are the Generalized Logistic, Generalized Extreme Vaules, Generalized Normal, Pearson Type III, Wakeby, and Generalized Pareto, the Generalized Logistic and Generalized Extreme Values distributions pass the Z statistic goodness-of-fit test of the L-moments method for the East Mediterranean River Basin, the former performing yet better than the latter. Hence, as the outcome of the L-moments method applied by the Generalized Logistic distribution, two equations are developed to estimate flood peaks of any return periods for any un-gauged site in the study region. The ANNs, MLR and MNLR models are trained and tested using the data of these 13 gauged sites. The results show that the predicting performance of the MLP model is superior to the others. The application of the MLP model is performed by a special Matlab code, which yields logarithm of the flood peak, Ln(Q T), versus a desired return period, T.

Water Resources Management, 2014

ABSTRACT Monthly mean reference evapotranspiration (ET 0 ) is estimated using adaptive network ba... more ABSTRACT Monthly mean reference evapotranspiration (ET 0 ) is estimated using adaptive network based fuzzy inference system (ANFIS) and artificial neural network (ANN) models. Various combinations of long-term average monthly climatic data of wind speed, air temperature, relative humidity, and solar radiation, recorded at stations in Turkey, are used as inputs to the ANFIS and ANN models so as to calculate ET 0 given by the FAO-56 PM (Penman-Monteith) equation. First, a comparison is made among the estimates provided by the ANFIS and ANN models and those by the empirical methods of Hargreaves and Ritchie. Next, the empirical models are calibrated using the ET 0 values given by FAO-56 PM, and the estimates by the ANFIS and ANN techniques are compared with those of the calibrated models. Mean square error, mean absolute error, and determination coefficient statistics are used as comparison criteria for evaluation of performances of all the models considered. Based on these evaluations, it is found that the ANFIS and ANN schemes can be employed successfully in modeling the monthly mean ET 0 , because both approaches yield better estimates than the classical methods, and yet ANFIS being slightly more successful than ANN.

Soil Dynamics and Earthquake Engineering, 2012

The risk formula, expressing the probability of at least one occurrence of earthquakes of greater... more The risk formula, expressing the probability of at least one occurrence of earthquakes of greater-thandesign-value magnitudes over the economic life of a structure, is modified taking into consideration the probability of no-earthquake years. The annual maximum earthquake magnitudes of three scales: Richter magnitude, also known as local magnitude (M L), body-wave magnitude (M b), and moment magnitude (M M) in a geographical area encompassing the Bingöl Province in Turkey are taken from two sources: (1) report by Kalafat et al. (2007) [14] and (2) the web site reporting data by Kandilli Observatory which has been recording earthquakes occurring in and around Turkey since 1900. Statistical frequency analyses are applied on the three sample series using various probability distribution models, and magnitude versus average return period relationships are determined. The values of the M L , M b , and M M series for 10% and 2% risk are computed to be around 7.2 and 8.3. The tectonic structure and seismic properties of the Bingöl region are also given briefly.

Proceedings of the ICE - Water Management, 2011

Journal of Hydrology, 2012

ABSTRACT Unplanned exploitation of groundwater from coastal aquifers may cause salt water intrusi... more ABSTRACT Unplanned exploitation of groundwater from coastal aquifers may cause salt water intrusion in coastal aquifers. Coastal areas are generally overpopulated with fertile agricultural lands and diversified irrigated farming activities. The objective of this study was to develop a model to control/prevent seawater intrusion into the coastal aquifer with a case study of the Silifke-Goksu Deltaic Plain. A computer program for the simulation of three-dimensional variable density groundwater flow, SEAWAT, is used to model the seawater intrusion mechanism of the Goksu Deltaic Plain along the Mediterranean coast of Turkey. The calibration analysis of the developed seawater intrusion model is performed using field measured data in the water-year of 2008 including static groundwater head, electrical conductivity, total dissolved solid (TDS), and chloride concentration values collected from 23 observation wells and the existing data which were compiled and reviewed. The main objectives for applying the seawater intrusion model to the Goksu Deltaic Plain were (1) to determine the hydraulic and hydrogeologic parameters of the aquifer, (2) to estimate the spatial variation of the salt concentration in the aquifer and (3) to investigate the impact of the increase and decrease in groundwater extractions. The simulation results show that the Goksu Deltaic Plain aquifer is especially sensitive to the increase in groundwater extraction.

Scientific Research and Essay, 2009

In this study, vertical and lateral velocity distribution in a compound channel cross section was... more In this study, vertical and lateral velocity distribution in a compound channel cross section was measured to investigate kinetic energy and momentum correction coefficients for nine different test discharges. Experiments were carried out for subcritical flow conditions and the Froude number (Fr) and depth ratio (Dr) varied between 0.87 and 0.95, and 0.17 and 0.48 respectively. Kinetic energy and momentum correction coefficients, α α α α and β β β β were computed for each experimental test condition. Results wer Yuan SY, Xiao Ch, Li ZY, Zhu JY (2003). A study on laboratory rearing techniques for Bactrocera dorsalis (Hendal). Acta Agr. Univ. Jiangx. 25: 577-580.e compared with findings taken from the experimental work of other researchers carried out in flumes with different cross-sectional shapes. For 37 different experimental test cases, the average values of kinetic energy and momentum correction coefficients, α α α α and β β β β were obtained as 1.094 and 1.034 respectively. An attempt also was made to determine the relation between α α α α and β β β β.

Journal of Hydrology, 2009

ABSTRACT So far, various models have been developed to identify the relation between discharge an... more ABSTRACT So far, various models have been developed to identify the relation between discharge and suspended sediment load. Empirical relations such as sediment rating curves are often applied to determine the average relationship between discharge and suspended sediment load. This type of model generally underestimate when sediment load are estimated from water discharge using least squares regression of log-transformed variables. To avoid that drawback, it is proposed to employ HBMO algorithm as a new tool for optimization of this relation. Results of this model are compared with two different sediment rating curves (SRC). The daily streamflow and suspended sediment concentration data from Mad River Catchment near Arcata, USA are used as a case study. Statistics and graphs present that the HBMO algorithm performs better than the other models in estimation of suspended sediment concentration in the particular data sets used in this study.

Canadian Journal of Civil Engineering, 2008

ABSTRACT The assessment of backwater resulting from extra energy losses on flood flows caused by ... more ABSTRACT The assessment of backwater resulting from extra energy losses on flood flows caused by bridge constrictions is of vital interest in hydraulic engineering due to its importance in the design of waterways and management of flooding. Although many detailed methods for estimating bridge backwater have been developed, an initial estimate of the magnitude of bridge backwater using a practical model, such as the multiple linear regression (MLR) technique, has a crucial importance for rapid evaluation of flood damages upstream of the bridge structure. In the current study, first, two artificial neural network (ANN) models using the same amount of input data as that of an MLR approach were developed, and then the ability of these ANN models versus the MLR models was investigated for the initial assessment of bridge backwater, both models having been based on the comprehensive laboratory data of the Hydraulic Research Wallingford in UK. The comparison of the results by the MLR and the ANN approaches revealed that the ANN model gave better predictions than those of the MLR model when applied to these laboratory data. United States Geological Survey (USGS) field data were also used for the validation and comparison of these methods. The results showed that ANN approaches yielded more accurate results than those of the MLR models when applied to these field data including actual flood profiles through many bridges.