HEC-RAS Model Research Articles

Current and Modified Flood Discharge Capacity of a Reach of Tigris River between Kut and Amarah Barrages

This study was conducted to examine the discharge capacity of the reach of the Tigris River between Kut and Amarah Barrages of 250km in length. The examination includes simulation the current capacity of the reach by using HEC-RAS model. 247cross sections surveyed in 2012 were used in the simulation. The model was calibrated using observed discharges of 533, 800, 1025 and 3000m3/s discharged at Kut Barrage during 2013, 1995, 1995 and 1988, respectively, and its related water level at three gauge stations located along the reach. The result of calibration process indicated that the lowest Root Mean Square Error of 0.095 can be obtained when using Manning’s n coefficient of 0.026, 0.03 for the Kut- Ali Al Garbi and Ali Al Garbi- Amarah reaches respectively, and 0.03 for the flood plain of the whole reach under study. The reach under study has two lateral inflow streams, UmAljury, which joins Tigris River at station 51km, and Aljabab, which joins Tigris River at station 57km. The discharge of Aljabab varies between 0 and 400m3/s and the discharge of UmAljury varies between 0 and 50m3/s. The results showed that the current capacity of the main channel of the reach of the Tigris River between Kut and Amarah Barrages is 400m3/s. The water levels kept less 1m than both levees in case of discharging 1800m3/s from Kut Barrage, with no lateral inflows, and 1700m3/s with lateral inflow. The reach of Tigris River fails to accommodate the flood discharge of 3300m3/s which is the discharge of the flood of 1988 measured at Kut Barage. It can be concluded that the reach had large amount of sediment for the period from 1988 to 2012 and the reach capacity reduced to about half its capacity of 1988 during this period. The results of removing 12 islands and 2 sidebars by reshaping the current condition into trapezoidal cross-section will decrease the surface water levels by 20cm and flow of 1900m3/s can be discharged safely at Kut Barrage without any lateral inflow and 1800m3/s with lateral inflow from the tributaries. While, expand 58 narrow cross-sections that choking the flow, the water levels along the reach are lowered by an average of 20cm in addition to that 20cm when modifying the cross-sections at the islands and sidebars. In this case, flow of 2100m3/s can safely be discharged from Kut Barrage without any lateral inflow and 1900m3/s with lateral inflow. The result when modifying additional 111 cross-sections showed that the reach can safely accommodate a flood wave of 3300m3/s from Kut Barrage without any lateral inflow and 3000m3/s with lateral inflow.

Floodplain response to varied flows in a large coastal plain river

The natural flood pulse maintains river-floodplain ecosystems through the exchange of freshwater resources between the main-stem and floodplain habitats. Few prior studies have quantified the relationship between flows and floodplain response including estimating inundation area, floodwater volumes, and slough connectivity. Floodplain modeling typically uses the flow-stage height relationship at river gauge stations. In this study, we compared a relative elevation model (REM) and the Hydrologic Engineering Center River Analysis System (HEC-RAS 1D) model using events from 2015 and 2016 covering a range of flows from the 1st to the 99th percentile for the Apalachicola River, Florida. Because digital elevation models (DEM) from LiDAR (light detection and ranging) data lack details of riverbed topography, we compared a LiDAR-alone and LiDAR-sonar combined DEM to assess their differences. Estimates from the REM and HEC-RAS models were compared to maps based on Landsat imagery-derived water and vegetation indices. In this river, we found a non-linear relationship between the inundated area and flow, increasing markedly through the 90th flow percentile after which increases are minimal. Inundated areas from both REM and HEC-RAS models were similar for all selected flow levels except at the 74th percentile (708 m3/s) flow at which the REM produced 11% higher inundated area than HEC-RAS. Near the median flows, major sloughs were fully connected with backswamps and low-lying patches being inundated. At the higher flows, only a few anthropogenic features were exposed. Floodplain inundation estimates from Landsat performed poorly, detecting 9% with the modified normalized difference water index (mNDWI) and 41% with the open water likelihood index (OWL). These estimates were much lower than the HEC-RAS model (96% flooded), largely because the satellite is unable to penetrate dense forests and examine the floodplain surface, and the Landsat pixel size is twice the width of floodplain sloughs. The LiDAR-sonar combined DEM produced a higher floodwater volume estimate with the HEC-RAS model than using LiDAR-alone. The difference of 1,368,000 m3 at the 1st percentile (142 m3/s) and 2,825,000 m3 at the 89th percentile (1133 m3/s) demonstrate the limitation of using a LiDAR-alone DEM, which cannot penetrate the water surface, and the importance of surveying floodplains using sonar. Modeling results under predict historical wetting of the floodplain because Corps dredging made the main channel approximately 13% wider from its historical width in 1941. Further, in the past few decades, droughts and low flows have become more common because of varied upstream water uses, resulting in less inundation than in the past. Frequent high flows are required to maintain river-floodplain connectivity, floodplain forests, and other hydroecological functions in the Apalachicola River floodplain. Our findings present a basis to assess the legacy of past and ongoing disturbances, inform potential policy decisions for water and floodplain management, and provide a baseline for further research.

Development of algorithms for evaluating performance of flood simulation models with satellite-derived flood

Abstract Flood inundation simulation models are widely used for simulating severe events of flood, generating hazard maps, risk assessment, and to identify flood vulnerable locations. It is important to assess the degree of accuracy of flood model results as these results may be one of the triggering parameters considered in developing flood hazard maps, flood mitigation policies, and land using planning where multi-criteria analysis is approached. In the present study, an algorithm is developed in order to know the performance of flood models by validating it with flood footprints extracted from synthetic aperture radar (SAR) images using multi-segmentation and Otsu's thresholding technique. Evaluation of the performance of the model is based on two best fit criteria called F1 and F2. For this, HEC-RAS model is used for simulating the severe event of flood witnessed in Mahanadi River in Odisha stretching between Tikarpara and Mundali during September 2008. Three simulations were made by considering three different Manning's roughness for river and floodplain. The model gives appreciable results and best fit F1 = 0.85 and F2 = 0.74 was found for Manning's roughness 0.020.

DELINEATION OF FLOOD PLAIN EXTENSION

Floodplain delineation is an effective approach in either avoiding of water crisis or making pragmatic decisions in terms of water management strategies. In this study a flood plain extension has been developed in ArcGIS and HE-CRAS models and a comparison has been made within three different scenarios of discharge. The results showed in low and medium discharge scenarios the buffer zone acts as a safety factor zone to adjacent infrastructure either agricultural or residential, but in high discharge condition buffer zone is entirely filled with stream water hence yet more safety regulation should be considered in order to avoid human and resource loss or damage within adjacent areas. Keywords: Flood plain delineation, Water depth profile, HE-CRAS, F. Sakhaee. Parks College of Engineering, Aviation and Technology, Civil Engineering Dept., Saint Louis University, USA

استخدام نظم المعلومات الجغرافية لدراسة تحليل فيضان مناطق جنوب سد حمرين إلى شمال قضاء بعقوبة/ العراق

تصف هذه الدراسة تحليل فيضان مناطق جنوب سد حمرين إلى شمال قضاء بعقوبة, وتهدف الدراسة إلى قياسات مختلفة للفيضان بطريقة المحاكاة, وذلك لتقليل حجم الخسائر التي من الممكن أن تتعرض لها هذه المناطق عند الفيضان الفعلي, فقياسات المجرى والتوقع تعد الأساس لفهم ميكانيكية الفيضان, وتحديده في كل محطة نهرية لفترة زمنية معينة. في هذه الدراسة تم استخدام مناهج مختلفة وصفية وتحليلية وكمية, وقد استخدم نموذج (HEC-RAS) مع برنامج (ArcGIS) لتصميم وتحليل الفيضان, واستنادا إلى البيانات المتوفرة اختيرت مناطق جنوب سد حمرين إلى شمال قضاء بعقوبة كمنطقة دراسة, إذ تبلغ سعة خزان حمرين نحو 347كم², وطاقته التخزينية تصل2. 06مليارمتر مكعب في الظروف الاعتيادية, ويؤمن المياه لنحو300ألف هكتار من الأراضي, وتبلغ اقصى سعة خزان حمرين نحو 450كم², واقصى طاقة تخزينية تصل3. 95مليار متر مكعب, في ظروف الفيضان. أن المعلومات في برنامج (HEC-RAS) تتم بإعادة إنشاء ملفات الإدخال والإخراج, إلى جانب تنظيم الوقت في نموذج بيانات قاعدة البيانات الجغرافية, لتعزيز واجهة النموذج والاستفادة من التحليل المكاني لنظم المعلومات الجغرافية, وتصور القدرات وفقا للحركة المرسومة.

Assessing Flow Pattern of Sabarmati River Portion at Hirpura Barrage Site Gujarat , India Using HEC-RAS Hydrodynamic Models and Physical Models

A barrage is proposed to be constructed across river Sabarmati, 60 km downstream of Daroi dam to create reservoir within the bank for recharging and meeting water demand of nearby areas. For analyzing the flow pattern and assessing the hydraulic parameters of Hipura barrage on Sabarmati river near Hirpura village of Mehsana District of Gujarat, a 3D physical model with geometrically similar scale 1:80 for river reach 3 km (1 km upstream and 2 km downstream) and for assessing the adequate energy dissipating arrangement a sectional model with scale 1:40 are used. These experimental observations on physical models are carried out at GERI and have been used to calibrate HEC-RAS based model for Manning’s roughness (n). The calibrated parameters of model are used to compute the hydraulic parameters in HEC-RAS model in the steady state condition of flow in the river reach for 25, 50, 75 and 100% of design discharge 16785

Simulación de calidad del agua en un tramo de la sub-cuenca río alto Bogotá en el periodo 2014-2016 a partir del modelo HEC-RAS

Simulación de calidad del agua en un tramo de la sub-cuenca río alto Bogotá en el periodo 2014-2016 a partir del modelo HEC-RAS

A Prediction–Correction Solver for Real-Time Simulation of Free-Surface Flows in River Networks

A prediction–correction solver is presented here for rapid simulation of free-surface flows in dendritic and looped river networks. Rather than solving a large global algebraic system over the entire domain of river networks, the model solves subsystems for subdomains of branches in two steps: prediction and correction. With the help of the prediction–correction method (PCM), the partial linearization technique, the semi-implicit method, and the Eulerian–Lagrangian method (ELM), the model only needs to solve tridiagonal linear systems for branches and is free of any iteration. The new model was tested using a hypothetical looped river network with regular cross sections, the Three Gorges Reservoir (TGR) dendritic river network, and the Jing-south looped river system (with seasonally flooding branches). In the first test, a time-step sensitivity study was conducted and the model was revealed to produce accurate simulations at large time steps when the condition for application of the PCM to river networks was satisfied. In the TGR test, the PCM model provided almost the same histories of water levels and discharges as those simulated by the HEC-RAS model. In the Jing-south test, the mean absolute error in simulated water levels was 0.07–0.24 m, and the relative error in simulated cross-section water flux was 0.5–4.9% compared with field data; the conservation error was generally 2 × 10−4 to 3 × 10−4. The PCM model was revealed to be 2–4 times as fast as a reported model, which solves local nonlinear subsystems using two-layer iterations, and 1.2–1.4 times as fast as the HEC-RAS. Using a time step of 1200 s, it took the sequential code 26.8 and 23.1 s to complete a simulation of a one-year unsteady flow process, respectively, in the TGR river networks (with 588 cells) and the Jing-south river system (with 662 cells).

Sustainable sediment management in a reservoir through flushing using HEC-RAS model: case study of Thakot Hydropower Project (D-3) on the Indus river

Abstract To increase the life of small storage reservoirs, sediment flushing is found to be a very useful technique throughout the world. A sediment flushing study of the Thakot D-3 Hydropower Project reservoir after construction of the Dasu dam on the Indus river is presented in this paper. HEC-RAS 5.0.6 numerical model has been employed to check the sediment removal during flushing and to assess the model's applicability and limitations. Dasu reservoir sediment discharge data of 20 years were used to evaluate the sediment load with different transport functions under no-flushing (FSL 656 m asl) and flushing conditions. Without flushing, the river bed would be raised 56.1 m at the dam site and the low-level spillway and power intake would be filled in 2–5 years' time. It was observed that reservoir sediment flushing is economically realistic for this dam and the HEC-RAS sediment simulation model is encouraged for reservoir flushing modeling. If the Thakot D-3 HPP is commissioned a number of years after Dasu, a coarser sediment load will also be reached in the reservoir which could pose a serious challenge for the Thakot D-3 reservoir life. It is recommended that without construction of the Bhasha-Diamer storage dam, sedimentation not only is a complicated issue for Dasu HPP and Thakot D-3 HPP, but will also have drastic impacts on other downstream run-of-river energy projects.

Spatio-temporal flood trends & settlement choice in flood-prone areas. A case study of Lubiji micro-catchment, Kampala City

ABSTRACT This study was conducted to establish the spatio-temporal distribution of flash floods and to learn why people prefer to settle in flood-prone areas of Lubiji micro-catchment in Kampala City. Rainfall data were analysed to ascertain Peak Runoff expected for the given flood event based on Soil Conservation Service Curve Numbers. The micro-catchment was delineated in the Arc GIS 10.0 programme, from the Digital Elevation Model. Feature classes were created to obtain the reach extents and river banks. HEC-RAS model was then used to create flood inundation maps in Arc GIS 10.0 between 1983 and 2014. High magnitude flash floods occurred almost after every three years and the spatial extent varied from 4.4 to 6.8 km2. The choice of settlement location in flood-prone areas was influenced by socio-economic ties. The flood hazard maps produced will aid land-use planning, resettlement of the people and setting up a flood forecasting system.

Sensitivity Analysis of Input Data in Surface Water Quality Models

Abstract The article is focused on analysis of input data impact on outputs of water quality models. The authors examined the impact of roughness coefficient, both boundary and initial conditions setup on changes of outputs generated by HEC-RAS model. Simulation results have shown a various response rate of input data on simulated results. The strong impact shows roughness coefficient setup that through the value of longitudinal dispersion coefficient affects pollution transport process. Changes in boundary conditions have had less influence on outputs. Relatively strong impact shows the setup of initial state of pollution concentration along the reach mainly for the case of low gradient rivers.

Analysis of Impact of Exposures and Hydrological Modelling of Flood Peak Zones in Adamawa Catchment, Nigeria

During the wet season, the Benue River overflows its banks and sometimes, extreme floods also occur in Adamawa catchment. Intensification of agriculture in some areas and urban growth in other areas has exposed a large population to flood risk. Little is known about localities or areas liable to flood at various peak flows and how land use and soil permeability affects the severity of flood in Adamawa catchment. This study seeks to analyse the exposures of land use/land cover and soil permeability to flood and model flood peak zones for three flow rates (2 years, 5 years and 10 years) using geospatial techniques and HEC-RAS model. Results of 2 years flood show that at least eight localities in the study area are highly prone to flood. This means that the probability of a flood of this calibre to occur and affect those localities in a given year is 50%. The number of localities prone to flood increases for Annual Exceedance Probability of 20% and 10%. The probability of 10% flood to occur and affect those localities in a given year is relatively low compared to both the 2yr and 5yr flood. Modelling results generated a curve number grid map which shows the permeability levels within the study area. Areas with more infiltration capacity recorded 50% (very high) and 20% (high). Moderate permeability score 16%. Very low and low levels account for 7.6% and 5.2% respectively. The implication is that 70% of the total area experience reduced surface runoff whereas 12.9% are more prone to water logging.

Developing Sukh-Beas as a potential recharge site during wet years for Bari Doab

Bari Doab is depleting the most in groundwater and therefore needs to be recharged. This paper presents a possibility of recharging Bari Doab through the abandoned Sukh-Beas channel. For this purpose, 25 cross sections were taken and ten infiltration tests were performed. Three different HEC-RAS models were run to find its channel capacity at different reaches. The infiltration capacity of the Sukh-Beas Nallah was found to be a total of about 808 cfs, which can be used to recharge the groundwater, after some necessary steps have been taken to improve the infrastructure.

Effect of Sediment Load Boundary Conditions in Predicting Sediment Delta of Tarbela Reservoir in Pakistan

Setting precise sediment load boundary conditions plays a central role in robust modeling of sedimentation in reservoirs. In the presented study, we modeled sediment transport in Tarbela Reservoir using sediment rating curves (SRC) and wavelet artificial neural networks (WA-ANNs) for setting sediment load boundary conditions in the HEC-RAS 1D numerical model. The reconstruction performance of SRC for finding the missing sediment sampling data was at R2 = 0.655 and NSE = 0.635. The same performance using WA-ANNs was at R2 = 0.771 and NSE = 0.771. As the WA-ANNs have better ability to model non-linear sediment transport behavior in the Upper Indus River, the reconstructed missing suspended sediment load data were more accurate. Therefore, using more accurately-reconstructed sediment load boundary conditions in HEC-RAS, the model was better morphodynamically calibrated with R2 = 0.980 and NSE = 0.979. Using SRC-based sediment load boundary conditions, the HEC-RAS model was calibrated with R2 = 0.959 and NSE = 0.943. Both models validated the delta movement in the Tarbela Reservoir with R2 = 0.968, NSE = 0.959 and R2 = 0.950, NSE = 0.893 using WA-ANN and SRC estimates, respectively. Unlike SRC, WA-ANN-based boundary conditions provided stable simulations in HEC-RAS. In addition, WA-ANN-predicted sediment load also suggested a decrease in supply of sediment significantly to the Tarbela Reservoir in the future due to intra-annual shifting of flows from summer to pre- and post-winter. Therefore, our future predictions also suggested the stability of the sediment delta. As the WA-ANN-based sediment load boundary conditions precisely represented the physics of sediment transport, the modeling concept could very likely be used to study bed level changes in reservoirs/rivers elsewhere in the world.

2D Flood Simulation and Development of Flood Hazard Map by using Hydraulic Model

A flood is an overtopping of water from channel banks which submerges land which is usually dry. In India, floods in Godavari and Sabari River are observed several times but 2006 flood was one of the severe event which affected Khammam district extensively. The present paper demonstrates the analysis of severe flood of Khammam using hydraulic modeling. For this purposeHEC-RAS 2D a Hydraulic model was used to simulate the behavior of study area which covers part of Godavari river and Sabari River in Telangana and Andhra Pradesh states. Model provides detail temporal simulated parameters like depth of water, water elevation with respect to M.S.L and Velocity of flowing water. SRTM 30m posting, river discharge data, LULC for assigning Roughness coefficient was used as input to the model. HEC-RAS Simulated flood results were validated with remotely sensed Radarsat satellite observations. Performance of HEC-RAS model was evaluated according to the criteria of measure of fitting raster cells with satellite data. Validation results showed that performance of HEC-RAS model is very effective and can be used by hydrologist or water resources engineers for planning and development. , , , ,

The role of river channel roughness for water level modeling during the 2005 year flood on Siret river using HEC-RAS model

At present, the value of channel roughness represents the most important parameter of hydraulic model calibration for flood mapping and flood forecasting. In practice, the roughness coefficient (Manning’s “n” value) cannot be determined from in situ surveying, but it can be automatically extracted from alternative sources, like pedological maps, ortophotomaps by digitizing each polygon associated with “n” value or using satellite images LANDSAT. For calibration of Manning’s “n” values, it was used the data from 2005, when a major flood occurred in this study area. To verify the performance of the calibrated HEC-RAS model, it was analyzed the flood peaks of observed and simulated values, and computation of root mean square error for the used hydrograph station on the lower Siret River. The study aims to present an efficient calibration method for flood mapping using HEC-RAS model.

Flood Analysis at Ramghat, Pokhara, Nepal Using HEC-RAS

Flooding in Ramghat area of Pokhara, Nepal is the major problem that has to be faced every year by the people residing nearby the area. Main goal of this study was to conduct the flood analysis of Seti River in Ramghat. Catchment area of the Ramghat was calculated to be 574.56 sq. km. using ArcGIS where the area above 5000 m elevation was 52 sq. km. and area below 3000 m elevation was 356 sq. km. Precipitation data of two meteorological stations, Pokhara airport and Lumle, were used in this research for the calculation of peak discharge. PCJ method (1996) was used to estimate the peak flood and also compared with the peak flood calculated using Modified Dicken's formula, WECS/DHM method, Rational method and Sharma and Adhikari (2004) method. Peak flood values were found to be 1918 m3/s and 2336 m3/s by PCJ method for return period of 50 years and 100 years respectively. The HEC-RAS modelling was performed for these flooding situations to determine the water surface profile along the eight cross-sections of the Ramghat. Finally, the floodplain map was prepared using the topographic map and the Google Earth Map. It was found that 50 years flood in Ramghat could inundate three cemetery shades situated along the river banks. Most importantly, 100 years’ peak flood was found more vulnerable for residential buildings too. The flood plain maps prepared in this study can be used by government authorities for planning, decision making, early warning system and disaster risk management. Additionally, the rating curve was prepared for the outlet section of Ramghat that can be used to estimate the river discharge during flooding in future.

Improving Practice of Flood Shelter Implementation in Alluvial River Floodplain With Hydro-Morphological Analysis

Flood shelter is widely used as a flood-proofing measure in floodplain areas. However, the practice of flood shelter implementation lacks proper planning, design, and construction. This study was undertaken to identify such gaps and bridge them through a case study and pilot of selected shelters in Bangladesh. An interdisciplinary approach comprising both quantitative hydrologic-hydraulic analysis and qualitative participatory social appraisal was followed in the study. The findings revealed that design flood levels were under-estimated, macro-stability of shelter sites were not assessed, and water velocity was not considered in shelter implementation. Based on an assessment of macro-stability of the chars, flood frequency and flow velocity through hydro-dynamic simulation with the HEC-RAS model, two shelters were redesigned and promoted as model shelters which performed well in a subsequent flood. The approach followed in this study can be replicated for shelter implementation in any riverine char environment for better outcome.

ANALYZING THE IMPACTS OF LAND COVER CHANGE TO THE HYDROLOGIC AND HYDRAULIC BEHAVIOURS OF THE PHILIPPINES' THIRD LARGEST RIVER BASIN

Abstract. Changes in land cover can have negative impacts on the hydrological and hydraulic processes in river basins and watersheds such as increase in surface runoff and peak flows, and greater incidence, risk and vulnerability of flooding. In this study, the impacts of land-cover changes to the hydrologic and hydraulic behaviours of the Agusan River Basin (ARB), the third largest river basin in the Philippines, was analysed using an integrated approach involving Remote Sensing (RS), Geographic Information System (GIS), and hydrologic and hydraulic models. Different land-cover classes in the ARB for the years 1995 and 2017 were mapped using Landsat 5 TM and Landsat 8 OLI images. Using a post-classification change detection approach, changes in land-cover were then determined. The impacts of these changes in land-cover to the to the basin discharge were then estimated using a calibrated hydrologic model based on the Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS) under different extreme rainfall conditions. The impact of the changes in land-cover to flood depth and extent was also determined using a hydraulic model based on the HEC-RAS (River Analysis System). Land cover classification results revealed that the ARB is 67.7% forest in 1995 but have decreased to 62.8% in 2017. Agricultural areas in the basin were also found to have increased from 12.2% to 15.5% in the same period. Other notable land cover changes detected include the increase in built-up lands and range lands, and decrease in barren lands. HEC HMS and HEC RAS model simulation results showed that there was an increase in discharge, flood depth, and flood extents between 1995 and 2017, implying that that the detected changes in land cover have negative impacts to hydrologic and hydraulic behaviours of the ARB.

Analysis of extreme flow uncertainty impact on size of flood hazard zones for the Wronki gauge station in the Warta river

In this paper, the impact of maximum flow uncertainty on flood hazard zone is analyzed. Two factors are taken into account: (1) the method for determination of maximum flows and (2) the limited length of the data series available for calculations. The importance of this problem is a consequence of the implementation of the EU Flood Directive in all EU member states. The factors mentioned seem to be among the most important elements responsible for potential uncertainty and inaccuracy of the developed flood hazard maps. Two methods are analyzed, namely the quantiles method and the maximum likelihood method. The maximum flows are estimated for the Wronki gauge station located in the reach of the Warta river. This simple river system is located in the central part of Poland. The length of the available data is 44 years. Hence, the series of the lengths 40, 30 and 20 years are tested and compared with reference calculations for 44 years. The hydrodynamic model HEC-RAS is used to calculate water surface profiles in steady state flow. The Python scripting language is applied for automation of HEC-RAS calculations and processing of final results in the form of inundation maps. The number of trials for each factor is not huge to keep the presented methodology useful in practice. The chosen measure of uncertainty is the range of variability for maximum flow values as well as inundation areas. The estimated values stressed the great importance of the factors analyzed for the uncertainty of the maximum flows as well as inundation areas. The impact of the data series length on the maximum flows is straightforward; a shorter data series gives a wider range of variability. However, the dependencies between other factors are more complex. Hence, the application of methodology based on the simulation and GIS data processing for assessment of this problem seems to be quite a good approach.