Research Article
Hossein Behzadi Karimi; Gholam Ali Mozaffari; Kamal Omidvar; Ahmad Mazidi
Abstract
The excessive emission of greenhouse gases in recent decades and the ongoing changes in the climate have changed the meteorological parameters and, accordingly, the climatic zones. In this study, the future prospect of climatic zones and the risk of desertification in the watershed of Karun basin was ...
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The excessive emission of greenhouse gases in recent decades and the ongoing changes in the climate have changed the meteorological parameters and, accordingly, the climatic zones. In this study, the future prospect of climatic zones and the risk of desertification in the watershed of Karun basin was investigated using UNEP index and LARS-WG6 microdirection model and HadGEM2-ES model under the RCPs emission scenarios for three periods 2021-2040, 2041-2060, and 2061-2080. The results pertaining to all three future periods and RCPs release scenarios showed that the long-term average annual precipitation will decrease between 1.9 and 14.6% compared to the base period, but the annual average minimum temperature will be between 1.2 and 3.4 °C, maximum temperature between 1.3 and 3.7 °C and the annual average of evaporation and transpiration will increase between 4.7 and 12.3% compared to the observation period. In the upcoming period and based on the emission scenarios, dry climate (the risk of very severe desertification) and semi-arid climate (the danger of severe desertification) increase 3.5% and 4.4%, respectively, and semi-humid (moderate desertification) and humid (no desertification) and very humid (moisture and wet climate) decrease 4% and 4.7%, respectively. However, semi-humid climate zones (low risk of desertification) with 0.8% will be less severe. Under the pessimistic scenario, the semi-arid climate region will reach its maximum level among the publishing scenarios in the near future with 12.4%. Therefore, this displacement in the boundaries of climatic classification will increase the desertification of Karun basin in the upcoming period.
Research Article
Fazlolah Ahmadi-Mirghaed; Babak Souri
Abstract
Water is one of the critical needs of human life and living things. Therefore, proper planning is important for its consumption all over the world, especially in Iran. This study was conducted to evaluate the impacts of land use change on water yield in the Teraz watershed, Khuzestan province, Iran, ...
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Water is one of the critical needs of human life and living things. Therefore, proper planning is important for its consumption all over the world, especially in Iran. This study was conducted to evaluate the impacts of land use change on water yield in the Teraz watershed, Khuzestan province, Iran, from 1990 to 2050. Water yield was evaluated using integrated valuation of ecosystem services and tradeoffs (InVEST) tool and land use was mapped using the maximum likelihood classification in the ENVI 5.3, and CA-Markov in the TerrSet environment. Moreover, the relationship between water yield and landscape metrics, including the number of patches (NP), patch density (PD), landscape shape index (LSI), and Largest Patch Index (LPI), was considered based on the Geographically Weighted Regression (GWR) method in the Arc GIS 10.5. The results showed that the area of forest and rangeland in the studied area decreased in the last 30 years, by 3199 and 1611 ha, respectively, and the area of agriculture and construction land uses increased by 4388 and 387 ha, respectively. It is predicted that in the next 30 years, 2442 ha of forests will decrease and the area of agriculture, rangeland, and construction land uses will increase by 1651, 687, and 102 ha, respectively. It was found that the total volume of available water yield in the region is equal to 26.5 Mm3 in 2020, on average of 857 m3 ha-1, and based on that, the ranking of land uses is as follows: 1. Construction, 2. Rangeland, 3. Forest, 4. agriculture. The results of GWR confirmed that water yield had a significant and negative spatial relationships with the NP, PD, and LSI metrics (R2>=0.83, p-value>0.05), while its relationship with the LPI metric was a significant and positive relationship (R2>0.84, p-value>0.05). It can be concluded that the landscape features and land use pattern can determine the production and yield of water in the study area.
Research Article
zahra Vahabzadeh Arasteh; Atabak Feizi; Leila Malekani
Abstract
In this study, the efficiency of hydrological re-analyzed models SWBM, HTESSEL, HBV-SIMREG, Ensemble, and LISFLOOD in estimating the rate of evaporation from the reservoir of Yamchi dam in Ardabil was investigated. The evaporation values obtained from the re-analyzed models were validated using the findings ...
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In this study, the efficiency of hydrological re-analyzed models SWBM, HTESSEL, HBV-SIMREG, Ensemble, and LISFLOOD in estimating the rate of evaporation from the reservoir of Yamchi dam in Ardabil was investigated. The evaporation values obtained from the re-analyzed models were validated using the findings of Penman's analytical equation and the values of eight experimental models. In addition to the methods, the accuracy of re-analyzed models was evaluated using the feed forward neural network. The resulting feed forward neural network was designed in two stages with two and three hidden layers and each was evaluated in three different combinations of network inputs. According to the findings, the values generated from the Penman analytical model had a correlation coefficient of 0.9 with the data received from studied area's evaporation pan. Among the hydrological re-analyzed models, the highest correlation with received data from study area's evaporation pan was related to LISFLOOD model with a value of 0.87 and RMSE equal to 1.37 mm per day. The obtained results showed that the mean absolute error for the LISFLOOD model with the data provided from the study area's evaporation pan was 1.14 mm per day, on a daily time scale. The results showed that in the absence of area data, re-analyzed hydrological model can readily offer the best estimate of evaporation from the reservoirs’ free surface on a monthly scale.
Research Article
Hassan Ahmadzadeh; Mostafa Davarpanah
Abstract
Floods are one of the most important natural hazards on earth. The purpose of this study was to prepare a flood hazard map in Urmia city and identify vulnerable areas. In order to prepare the flood hazard map of quantitative-explanatory study, 9 factors affecting the occurrence of this phenomenon ...
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Floods are one of the most important natural hazards on earth. The purpose of this study was to prepare a flood hazard map in Urmia city and identify vulnerable areas. In order to prepare the flood hazard map of quantitative-explanatory study, 9 factors affecting the occurrence of this phenomenon were used, including elevation, slope, aspect, distance from the river, watercourse density, lithology, land use, precipitation and Topographic Wetness Index (TWI). To prepare information layers from ArcGIS and ENVI software and to weight the factors and determine the most important factor, analytic network process (ANP) was used. The weighting results of the factors showed that the two factors of slope and distance from the river have the highest weighting coefficients of 0.219 and 0.177, respectively, in the occurrence of floods in the region. Finally, by applying the weights of each of the factors, a flood hazard map was prepared. The final map showed that about 43.7% of the total area of the studied area is in high and very high classes in terms of flood hazard. These parts mostly include the vicinity of the secondary and main waterways that flow in the city. Failure to pay attention to hydrogeomorphological considerations such as encroaching on the legal boundaries of rivers and illegal constructions in their vicinity has increased the hazard of flooding in these parts. Behdari town and Beit al-Moghadad, Saadi and Roudaki, Shahed and Shahryar town, Sad Metri Street, and Golshahr are among these areas.
Research Article
Ali Azizi; Rasoul Sadeghi
Abstract
Migration is affected by several factors, the effect of each factor is different in various parts of the world. One of these factors is drought, which can have a greater impact upon human migration in arid and semi-arid regions. Identifying the migration centers can also affect the adopted migration ...
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Migration is affected by several factors, the effect of each factor is different in various parts of the world. One of these factors is drought, which can have a greater impact upon human migration in arid and semi-arid regions. Identifying the migration centers can also affect the adopted migration policies. Standardized Precipitation Index (SPI) was used to monitor the Iran’s drought in the last three decades (1986-2016). First, using the frequency of dry months, the zoning map was obtained from the geographical information system (GIS). Then, the existence of spatial autocorrelation in the data was investigated using Global Moran's I statistics. In the next step, the Hot Spot analysis on the data of the net migration rate was done to identify the migration centers. The findings showed that the spatial pattern of occurrence of dry months during the last three decades increases from the south and southeast of Iran to the north and west. Moreover, the values of Moran's I for the net migration rate in the studied periods were between 0.17 and 0.45, which indicates clustering in the migration data. The hot spot analysis also showed that the centers of migration in the country are located in the center and west of the country. Comparing migration centers with the pattern of dry months of the year shows that migration centers, both in-migration and out-migration, are located in places with moderate to high zones of dry months, which can make complicated in identifying the relationship between drought and migration flows.
Research Article
Ata ghafari Gilandeh; Vahid Safarian Zengir
Abstract
One of the most important atmospheric challenges in recent decades in metropolitan areas is air pollution, which is caused by various natural and human factors and has harmful impacts on humans and the environment. Accordingly, investigating air pollution is important and necessary. For estimating the ...
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One of the most important atmospheric challenges in recent decades in metropolitan areas is air pollution, which is caused by various natural and human factors and has harmful impacts on humans and the environment. Accordingly, investigating air pollution is important and necessary. For estimating the amount of carbon monoxide and nitrogen dioxide, as well as water vapor in the atmosphere in southern and southwestern provinces in 2018-2019, the data of Sentinel-5 satellite images was used. The findings showed the maximum concentration of Co with the value of 0.037 mol/m^2 in April 2019, the maximum concentration of H2O with the value of 3703 mol/m^2 in August 2019 and the maximum concentration of NO2 with the value of 0.000188 mol/m^2 in November 2018. The maximum daily LST value was 324.5 degrees Kelvin in June 2019 and the maximum nighttime LST value was 302.5 degrees Kelvin in June 2019. The maximum thickness of the optical depth of aerosols with a value of 13.79 μg/m^3 at a wavelength (0.47 μm) was in July 2019 and its lowest value with a value of 1.57 μg/m^3 in a wavelength of (55 /0 μm) was in November 2018. The results of temporal and spatial monitoring of CO, NO2, H2O, LST and AOD values give the possibility of a more concrete understanding of spatial and temporal changes of the examined components on a regional macro scale.
Research Article
sayyed mohammad hosseini; farahnaz khoramabadi
Abstract
Heat waves are among the most dangerous weather threats related to global warming and climate change. Two databases were used to predict the spatial changes in the intensity of heat waves in East Azarbaijan province. The daily data of the maximum temperature in 5 synoptic stations of the province inlcuding ...
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Heat waves are among the most dangerous weather threats related to global warming and climate change. Two databases were used to predict the spatial changes in the intensity of heat waves in East Azarbaijan province. The daily data of the maximum temperature in 5 synoptic stations of the province inlcuding Tabriz, Maragheh, Jolfa, Ahar and Mianeh for the time period from 1981 to 2021 AD as the period of historical-base data were used. The output of the selected CanESM model under the dual economic-social scenario SSP1 is the result of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in the future period from 2022 to 2065. The validation of the data of the basic period with the future period was done with standard measures and with the step-by-step regression technique, the intensity of heat waves in the province was explained. The results indicate that the intensity of heat waves will increase until 2065 in all the investigated stations and it will cover a large area of the province. So, in the next half of the century, the intensity of heat waves in Tabriz will be 1.3 °C, in Maragheh will be 1 °C, in Julfa will be 0.7 °C, in Ahar will be 1 °C and in Mianeh it will be 1.4 °C. Moreover, with the warming of the earth's air due to the impact of global climate changes, smaller heat waves join together and will create more intense, bigger, and lasting heat waves. The results showed that with the decrease in latitude in this province and the proximity to low-lying and low-altitude areas, the frequency and intensity of heat waves will also increase.
Research Article
Ali Mohammadhasani; Hamidreza Kamyab; Hasan Razaei
Abstract
The relationship between air quality and the spread of Covid-19 has been proven to be sometimes positive and sometimes negative in previous studies. A research gap was seen in Iran regarding the impact of air quality on the spread of Covid-19. Thus, this study examined the relationship between the reproductive ...
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The relationship between air quality and the spread of Covid-19 has been proven to be sometimes positive and sometimes negative in previous studies. A research gap was seen in Iran regarding the impact of air quality on the spread of Covid-19. Thus, this study examined the relationship between the reproductive number of Covid-19 with the air quality index and meteorological factors. The reproductive number is an index to explain the spread of a viral disease. The air quality index related to each of the pollutants NO2, O3, CO, PM2.5, PM10, and the criterion pollutant were utilized in this study. Meteorological factors, including temperature, relative humidity, precipitation, air pressure, and wind speed were used. The data were obtained weekly and at Tehran province. The dependence of variables was determined using Pearson and Spearman correlation coefficients. The examined relationships were then estimated by regression. Each independent variable was tested in a distinct regression because of the limitations of the study. The linear and curvature regressions were performed according to the dispersion of variables and statistical assumptions. The best model was fitted based on statistical significance and regression coefficient of determination. The results of correlation tests showed the dependence of reproductive number with PM10, PM2.5, SO2 and relative humidity. Regression tests also confirmed the relationship between the reproductive number (dependent variable) and each of the independent variables PM10 (coefficient of determination 0.274), PM2.5 (coefficient of determination 0.358), SO2 (coefficient of determination 0.359), and relative humidity (determination coefficient 0.213). The results indicated that an increase in PM10, PM2.5, SO2 and decrease in relative humidity was associated with an increase in spread of Covid-19.
Research Article
Peyman Karami; Seyed Ahmad Eslaminezhad; Mobin Eftekhari; Faraz Boroumand; Mohammad Akbari
Abstract
Considering the harms of air pollution on human health and the environment, it seems necessary to reduce and solve this problem based on accurate knowledge of pollutants and criteria affecting it and identifying polluted areas. Therefore, using mathematical models in the form of machine learning is an ...
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Considering the harms of air pollution on human health and the environment, it seems necessary to reduce and solve this problem based on accurate knowledge of pollutants and criteria affecting it and identifying polluted areas. Therefore, using mathematical models in the form of machine learning is an optimal and cost-efficient approach to air pollution modeling. This research is applied in terms of purpose and its method is descriptive-analytical. The novelty of this research is presenting a new combination approach to determine the effective criteria for predicting the amount of air pollution. Therefore, the purpose of this study was to evaluate and compare the capabilities of two machine learning models, namely Support Vector Machine (SVM) and Random Forest (RF) in combination with Genetic Algorithm (GA) to predict air pollution in Tehran. The data used in this research include particulate matter and gaseous pollutants in Tehran in 2020, which was obtained from Tehran Traffic Control Company. MATLAB and ArcMap software were used to analyze the data. The value of coefficient of determination (R2) obtained from the combined RF-GA method was 0.997, which indicates the high compatibility of this model with the data of this study. Moreover, the Root Mean Square Error (RMSE) value from the combined RF-GA method was 0.153, which indicates high accuracy of this model. Based on the data obtained from Tehran Traffic Control Company, the results of the RF method indicate the appropriateness of selecting the model to estimate the amount of air pollution in Tehran.
Research Article
Ensieh Saberi Pour; Fatemeh Tabatabaei Yazdi; Morteza Kahrarian
Abstract
The increasing population, the expansion of industrial and urban wastewater, and the lack of proper treatment have significantly contributed to the existance heavy metals in the soil ecosystem. Preventing the impacts of heavy metals on the quality and health of the soil ecosystem requires selecting appropriate ...
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The increasing population, the expansion of industrial and urban wastewater, and the lack of proper treatment have significantly contributed to the existance heavy metals in the soil ecosystem. Preventing the impacts of heavy metals on the quality and health of the soil ecosystem requires selecting appropriate bioindicators. Thus, this study aims to investigate the impacts of heavy metals and the effective environmental parameters of the soil on Collembola, at genus level. For this purpose, in two stages, soil samples were taken from the stations around Charmshahr industrial wastewater treatment plant and Khin Arab and Parkandabad municipal wastewater treatment plants in Mashhad, Iran. Twenty-eight soil samples, each obtained by mixing four sub-samples, were collected from 14 stations. Statistical analysis was performed using R software. In the studied area, a total of 15 genera of Collembola were identified. All these genera were reported for the first time from Mashhad. The results of comparing the concentration of chemical parameters and the genera richness in Collembola showed that there is a significant correlation between them. The results show that the number of genera has a negative correlation with two metals, iron and chromium, and among the measured elements in soil, only total carbon has a positive correlation with the number of genera (p<0.05). The results of the canonical correspondence analysis showed that the response of the abundance of each Collembola genera to the concentrations of heavy metals and the environmental parameters is different. Thus, even if Collembola is advising as a proper bioindicator, we should mention that the response of the biodiversity to the abiotic parameters in soil is various, which must be deliberated in the ecosystem management.
Research Article
Neda Eskandari; Zahra Sadat Saeideh Zarabadi; Farah Habib
Abstract
Like any other complex system, cities fragment when they are not properly managed. Thus, the fragility conditions should be understood to calculate the effective strategies in responses. This study aims to explain the factors of fragility in the metropolitan city of Tehran using structural approach. ...
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Like any other complex system, cities fragment when they are not properly managed. Thus, the fragility conditions should be understood to calculate the effective strategies in responses. This study aims to explain the factors of fragility in the metropolitan city of Tehran using structural approach. This field study seeks to identify the factors effective in the fragility of Tehran using a descriptive-analytical approach. In order to formulate the theoretical framework, the related literature was reviewed using the documentation method. Then, experimental data were extracted based on the environmental scanning technique. The population included 14 experts and specialists in the field of urban planning, who were selected based on purposive sampling. To this aim, 91 factors were extracted as primary indicators of urban fragility based on the theoretical literature. Then, 51 factors with a lower percentage of consensuses were eliminated and 40 ones remained based on experts’ opinions taken through a questionnaire. In the next step, the answers were analyzed and evaluated applying structural mutual effects analysis in MicMac software, resulting in determining the degree of direct and indirect influence of the factors on each other and on the fragility process of Tehran. According to the results, 20 factors play a significant role in the fragility of Tehran among 40 primary influencing ones. The above-mentioned factors are rapid growth of urbanization, concentrated poverty, widespread financial corruption, social and gender inequality, unemployment rate, political instability, epidemic diseases, informal settlements, urban violence, economic security, people's participation, lack of basic urban services, exposure to natural disasters, social security, income inequality, improper distribution of security-development capacities, sanctions, global economic shocks, real insecurity, and sudden price shocks.
Applied Articale
Shadi Galehdar; Shabnam Galehdar; Mandana masoudi Rad
Abstract
Today, it is so important to investigate how to deal with natural disaster in making communities and cities resilient in all disciplines. In the natural disasters of recent years, along with government assistance, non-governmental organizations have played a very important role in bringing people back ...
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Today, it is so important to investigate how to deal with natural disaster in making communities and cities resilient in all disciplines. In the natural disasters of recent years, along with government assistance, non-governmental organizations have played a very important role in bringing people back to normal life quickly and repairing the damage. The quick impact of natural disasters leads to numerous damages, that’s why it is necessary to pay attention to the role of non-governmental organizations in effectively confronting people with floods. Therefore, this applied and descriptive-analytical research was conducted with the aim of assessing the situation of non-governmental organization in increasing social resilience after the flood crisis. The study population consists urbanism experts and non-governmental organizations. A total of 49 questionnaires were distributed between them. For data analysis, two sample independent t-test and path analysis of structural equations in SPSS and SmartPLS software were used. The results showed that social responsibility (0.890), trust (0.879), empowerment of individuals (0.879) scored the highest values, and educational spaces (0.663), emproving the quality of the environment (0.722), and providing voluntary experiences (0.746) showed lowest scores in the face of resilience. Therefore, non-governmental organizations can be effective in increasing social resilience after future crises by creating and improving educational spaces, improving the quality of the environment and providing voluntary experiences. Moreover, the results of two sample independent t-test showed that the desired dimensions are at the desired level (p<0.05). The responses of the two statistical communities of urbanism experts and non-governmental organizations in evaluating the role of non-governmental organizations in increasing social resilience after the flood crisis are the same to the variables in the response of the urbanism experts and non-governmental organizations.
Research Article
Samane Kelidari; Abolghasem Sadeghi-Niaraki; Mostafa Ghodosi
Abstract
The sustainable form of cities has been considered since the formation of first cities, but with the increasing exposure of cities to uncertainties such as natural disasters, climate change, drought crises, and energy crises, this stability is disrupted. The resilient and stable form of cities has achieved ...
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The sustainable form of cities has been considered since the formation of first cities, but with the increasing exposure of cities to uncertainties such as natural disasters, climate change, drought crises, and energy crises, this stability is disrupted. The resilient and stable form of cities has achieved a special importance and this concept has been considered by many researchers. Urban resilience is a multidimensional concept that is measured using both objective and subjective approaches. This study calculates Texas urban resilience using both objective and subjective approaches during Hurricane Harvey 2017 to provide an overview of the actual situation and public perception, respectively, and to examine the relationship between the two approaches. In the objective approach of the research, by integrating social, economic, infrastructural, organizational indicators with a certain weight, it was extracted by DANP method and cities were ranked by TOPSIS method. The DANP method used the opinions of experts, which had a high reliability. In the subjective approach, the Twitter data were used and the ratio index was used. The results of the objective approach indicated that the most resilient cities were Harris, Austin, Fort Bend, Galveston, Brazoria, Chambers, Rockwall and the least resilient cities were Moore, Presidio, Dimmit, Starr, Jasper, Camron, and Kennedy. A total of 24 cities were selected to compare resilience changes in the two approaches, as these cities had more than 50 Twitter messages and were facing direct threats from Hurricane Harvey. The results showed that the correlation coefficient between the two approaches in these cities was 0.708. There was a strong positive relationship between the two approaches, which means that cities that in terms of resilience were at a higher level, shared more Twitter messages when faced with a crisis. The knowledge gained from this study can provide valuable insights into strategies for using social media data to increase resilience to natural disasters.
Research Article
Amir Saffari; Sara Kiani; AmirAli Abbaszadeh
Abstract
Environmental hazards invariably lead to significant human and financial repercussions, underscoring the crucial need to thoroughly investigate and recognize hazardous areas. Recognizing the importance of this matter, this study focuses on identifying regions susceptible to natural hazards within Roodehen’s ...
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Environmental hazards invariably lead to significant human and financial repercussions, underscoring the crucial need to thoroughly investigate and recognize hazardous areas. Recognizing the importance of this matter, this study focuses on identifying regions susceptible to natural hazards within Roodehen’s urban area. To achieve the objectives, a variety of data sources, including a digital model with a 30-meter height resolution, a geological map at a scale of 1:100,000, a topographic map at a scale of 1:50,000, and additional information layers were harnessed as primary research tools. The research method integrated multiple analytical tools, incorporating a digital model with a 30-meter height resolution, a geological map at a scale of 1:100,000, a topographic map at a scale of 1:50,000, and various information layers. ArcGIS software served as a pivotal component in data analysis, bolstered by the fuzzy logic model and the ANP model. The approach encompassed a multi-step process commencing with the utilization of the integrated fuzzy logic and ANP model, driven by diverse parameters, to pinpoint areas susceptible to flood hazards, amplitude movements, and earthquake vulnerability. Consequently, a comprehensive hazard map of Roodehen’s urban area was formulated based on the obtained outcomes. The study underscores Roodehen's urban area as being at a heightened risk of natural hazards. Particularly, the western and northern regions exhibit elevated vulnerability due to their proximity to fault lines, earthquake centers, and steep slopes, making them susceptible to slope movements and earthquake hazards. Conversely, the central parts of the region, situated in close proximity to the river with low slopes and altitude, face a higher risk of flooding, and demonstrate significant earthquake vulnerability.
Research Article
Monir Shirzad; Hossein Namfar; Abolfazl Ghanbari
Abstract
The purpose of this study is determining the most suitable method to evaluate the vulnerability of informal settlements in Tabriz city against a possible earthquake. ELECTRE FUZZY models and the WASPAS model were used in relation to 13 criteria (passage width, building quality, materials, the number ...
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The purpose of this study is determining the most suitable method to evaluate the vulnerability of informal settlements in Tabriz city against a possible earthquake. ELECTRE FUZZY models and the WASPAS model were used in relation to 13 criteria (passage width, building quality, materials, the number of floors, distance from public open space, distance from urban facilities, distance from medical centers, population density, building density, distance from fault, geological type, plot area, land use) were compared. For this purpose, all informal settlements in Tabriz city were analyzed and the results of both models were evaluated by the authors’ field studies. Then, the most suitable method was chosen. The results of the research indicate that according to the WASPAS model, informal settlements located in Region 5 with a rank of 1 are the least vulnerable and region 10 is the most vulnerable with a rank of 6. Moreover, more than 57% of the area of informal settlements in Tabriz city are exposed to very high vulnerability, 11.05% are exposed to high vulnerability, 03.27% are exposed to moderate, and only 4.01% are exposed to low vulnerability. The results of the ELECTRE FUZZY model calculations indicated that the informal settlements located in Mentafah 3 with the rank of 1 are the least and areas 1 and 10 are the most vulnerable with the rank of 5. Moreover, more than 34% of the area of informal settlements in Tabriz city are exposed to very high vulnerability, more than 27% are exposed to high vulnerability, more than 25% are exposed to moderate vulnerability, and only 12.69% are exposed to low vulnerability. Based on the field studies of the researchers, the results of the ELECTRE FUZZY method are more accurate and realistic than the WASPAS method.
