14 research outputs found
Spatial Distribution of Groundwater Availability for Various Pumping Scenarios in Savannah Region
No full textOptimum daily operation of a wind-hydro hybrid system
No full text© 2022 Elsevier LtdDue to the negative effects of fossil fuels on the environment and health, energy supply is shifting towards renewables. The integration of renewable energy systems is challenging due to the intermittent nature of renewables, however this can be mitigated through storage. Uncertainty in electricity prices in spot markets further complicates the operation of these systems. Pumped storage hydropower is currently the most viable form of large-scale energy storage, and operation of renewable energy systems together with pumped storage hydropower plants is highly efficient. In this study, optimum daily operation strategies are developed for a wind-hydro hybrid system. A long short-term memory network to forecast electricity prices in the day-ahead spot electricity market is coupled with an optimization model to maximize daily revenue. Various scenarios are considered to investigate the benefits of future electricity price estimations. For the wind-hydro hybrid system with 25 MW wind turbine, the net revenue for one-year test period increased 3.5% when forecasted electricity prices with the proposed long short-term memory network is used instead of electricity prices of the previous day. It is observed that increasing the installed capacity of wind turbines compensates for the loss resulting from the poor forecasting of electricity prices; however, the operation schedules of the pump and the hydro turbine do not change when the optimization model uses a simulation duration of one day with hourly time steps
Determination of unit nutrient loads for different land uses in wet periods through modelling and optimization for a semi-arid region
No full textDiffuse pollution abatement has been a challenge for decision-makers because of the intermittent nature and difficulty of identifying impacts of non-point sources. Depending on the degree of complexity of the system processes and constraints related to time, budget and human resources, variety of tools are used in diffuse pollution management. Decision-makers prefer to use rough estimates that require limited time and budget, in the preliminary assessment of diffuse pollution. The unit pollution load method which is based on the pollution generation rate per unit area and time for a given land use can aid decision-makers in the preliminary assessment of diffuse pollution. In this study, a deterministic distributed watershed model, SWAT is used together with nonlinear optimization models to estimate unit nutrient pollution loads during wet periods for different land use classes for the semi-arid Lake Mogan watershed that is dominated by agricultural activities. Extensive data sets including in-stream water quality and flowrate measurements, meteorological data, land use/land cover (LULC) map developed using remote sensing algorithms, information about agricultural activities, and soil data are used to calibrate and verify the hydraulic and water quality components of SWAT model. Results show that the unit total nitrogen (TN) and total phosphorus (TP) loads (0.46 kg TN/ha/yr and 0.07 kg TP/ha/yr) generated from the watershed during wet periods are very close to the minimum values of the loads specified in the literature and highly depend on the variations in rainfall. Estimated unit nutrient loads both at watershed scale and for different land use classes can be used to assess diffuse pollution control measures for similar regions with semi-arid conditions and heavy agricultural activity
A GIS Tool to Estimate Flow at Ungaged Basins Using the Map Correlation Method
No full textWater resources management has been a critical component of sustainable resources planning. One of the most commonly used data in water resources management is streamflow measurements. Daily streamflow time series collected at a stream gage provide information on the temporal variation in water quantity where the gage is located. However, streamflow information is often needed at ungaged catchments especially when the stream gage network is not dense. One conventional approach to estimate streamflow at an ungaged catchment is to transfer streamflow measurements from the spatially closest stream gage, commonly referred to as the donor or reference gage using the drainage-area ratio method. Recently, the correlation between daily streamflow time series is proposed as an alternative to distance for reference stream gage selection. The Map Correlation Method (MCM) enables development of a map that demonstrates the spatial distribution of correlation coefficients between daily streamflow time series at a selected stream gage and all other locations within a selected study area. Although utility of the map correlation method has been demonstrated in various studies, due to its geostatistical analysis procedure it is time-consuming and hard to implement for practical purposes such as installed capacity selection of run-of-river hydropower plants during their feasibility studies. In this study, an easy-to-use GIS-based tool, called MCM_GIS is developed to apply the MCM in estimating daily time series of streamflow. MCM_GIS provides a user-friendly working environment and flexibility in choosing between two types of interpolation models, kriging and inverse distance weighting. The main motivation of this study is to increase practical application of the MCM by integrating it to the GIS environment. MCM_GIS can also carry out the leave-one-out cross-validation scheme to monitor the overall performance of the estimation. The tool is demonstrated on a case study carried out in Western Black Sea Region, Turkey. ESRI's ArcGIS for Desktop product along with a Python script is utilized. The outcomes of inverse distance weighting and ordinary kriging are compared. Results of GIS-based MCM are in good agreement with the observed hydrographs
Model Selection Challenges in Non-Stationary Precipitation Estimation: The Role of AIC, BIC, and Covariate Choice
No full textGIS-based environmental assessment of wind energy systems for spatial planning: A case study from Western Turkey
No full textIncreasing population and life standards causes fossil fuel consumption to increase. Due to this increasing consumption, fossil fuels are being depleted rapidly. In addition to rapid exhaustion, another important problem associated with fossil fuels is that their consumption has major negative impacts on the environment. Therefore, many countries around the world have included renewable energy systems (RES) in their future energy plans so that they can produce reliable and environmentally friendly energy. Parallel to this trend, various RES have been identified and recently integrated into the current energy network of Turkey as well. However, it should be recognized that renewable energy resources are not fully environmentally safe. Different RES are associated with different environmental impacts. In planning the future energy development of a country, evaluation of renewable energy resources potentials together with their associated environmental impacts is critical. The aim of this study is to create a decision support system for site selection of wind turbines using Geographic Information System (GIS) tools. Wind energy potential and environmental fitness/acceptability are used as decision criteria for the site selection process. Potential environmental impacts of wind generation are identified in accordance with Turkish legislations and previous studies; and represented as fuzzy objectives of the decision problem. Wind potential map of Turkey generated by General Directorate of Electrical Power Resources Survey and Development is used to identify economically feasible locations in terms of wind energy generation. A study area composed of Usak, Aydin, Denizli, Mugla, and Burdur provinces in Turkey is selected and divided into 250 m x 250 m grids. Each grid represents an alternative location for a wind turbine or group of wind turbines. Fuzzy environmental objectives such as "Acceptable in terms of noise level", "Acceptable in terms of bird habitat", "Acceptable in terms of safety and aesthetics" and "Safe in terms of natural reserves" associated with wind turbines are identified based on previous research and each of these objectives are represented by a fuzzy set. Individual satisfaction degree of each of these environmental objectives for each grid is calculated. Then these individual satisfactions are aggregated into an overall satisfaction degree using various aggregator operators such as "and", "or", and "order weighted averaging." Thus, an overall satisfaction degree of all the environmental objectives is obtained for each grid in the study area. A map of environmental fitness is developed in GIS environment by using these overall satisfaction degrees. Then this map is utilized together with the wind potential map of Turkey to identify both potentially and environmentally feasible wind turbine locations within the study area.Wind energy Ordered weight average aggregator Environmental impacts GIS Decision support tool
Improving precipitation estimates for Turkey with multimodel ensemble: a comparison of nonlinear artificial neural network method with linear methods
No full textEnsemble analysis is proven to provide advantages in climate change impact assessment based on outputs from climate models. Ensembled series are shown to outperform single-model assessments through increased consistency and stability. This study aims to test the improvement of precipitation estimates through the use of ensemble analysis for south and southwestern Turkey which is known to have complex climatic features due to varying topography and interacting climate forcings. The analysis covers an evaluation of the performance of eight regional climate models (RCMs) from the EUR-11 domain available from the CORDEX database. The historical outputs are evaluated for their representativeness of the current climate of the Mediterranean region and its surroundings in Turkey through a comparison with long-term monthly precipitation time series obtained from ground-based precipitation observations by the use of statistical performance indicators and Taylor diagrams. This is followed by a comparative evaluation of three ensemble methodologies, simple average of the models, multiple linear regression for superensemble, and artificial neural networks (ANN). The analysis results show that the overall performance of ensembled time series is better compared to individual RCMs. ANN generally provided the best performance when all RCMs are used as inputs. Improvement in the performance of ensembling due to the use of nonlinear models is further confirmed by fuzzy inference systems (FIS). Both ANN and FIS generated monthly precipitation time series with higher correlations with those of observations. However, extreme events are poorly represented in the ensembled time series, and this may result in inefficiency in the design of various water structures such as spillways and storm water drainage systems that are based on high return period events
Climate Change Risk Evaluation of Tsunami Hazards in the Eastern Mediterranean Sea
No full textClimate change impacts on social and economic assets and activities are expected to be devastating. What is as important as the analysis of climate change triggered events is the analysis of a combination of climate change related events and other natural hazards not related to climate change. Given this observation, the purpose of this study is to present a coastal risk analysis for potential earthquake triggered tsunamis (ETTs) coupled with the sea level rise (SLR) in the Eastern Mediterranean Sea. For this purpose, extensive stochastic analysis of ETTs, which are not related to climate change, are conducted considering the effects of climate change related SLR projections for this century. For the combined analysis, economic and social risks are evaluated for two regions in the Eastern Mediterranean Coastline, namely the Fethiye City Center at the Turkish Coastline and the Cairo Agricultural Area near Egypt. It is observed that ignoring SLR will hinder realistic evaluation of ETT risks in the region. Moreover, spatial evaluations of economic and social risks are necessary since topography and proximity to the earthquake zones affect inundation levels due to ETTs in the presence of SLR
Ensemble Precipitation Estimation Using a Fuzzy Rule-Based Model
No full textIn this study, a Takagi-Sugeno (TS) fuzzy rule-based (FRB) model is used for ensembling precipitation time series. The TS FRB model takes precipitation predictions of grid-based regional climate models (RCMs) from the EUR11 domain, available from the CORDEX database, as inputs to generate ensembled precipitation time series for two meteorological stations (MSs) in the Mediterranean region of Turkey. For each MS, RCM data that are available at the closest grid to the corresponding MSs are used. To generate the fuzzy rules of the TS FRB model, the subtractive clustering algorithm (SC) is utilized. Together with the TS FRB, the simple ensemble mean approach is also applied, and the performances of these two model results and individual RCM predictions are compared. The results show that ensembled models outperform individual RCMs, for monthly precipitation, for both MSs. On the other hand, although ensemble models capture the general trend in the observations, they underestimate the peak precipitation events
