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Evaluation of the One and Two-Dimensional HEC-RAS Models' Performance in Determining Flood Zone of Rivers
M.a. Mohammadi, H. Ebrahimnezhadian, M. Asgarkhan Maskan, V. Vaziri,
Volume 26, Issue 2 (9-2022)
Abstract
The study of annual damage statistics due to floods in Iran and the world shows the extent of flood damage to natural and human resources in different regions. Determining the flood zone of rivers in order to protect national resources and reduce flood damage provides the possibility of protecting the river from encroachment and the construction of any unauthorized facilities in it. Therefore, in the present study, the capability of numerical models in simulating the flood zone of rivers was evaluated in the range of Azarshahr Qushqura river and the two-dimensional hydraulic model HEC-RAS 5.0.7 and one-dimensional HEC-RAS model were compared. Changes in the hydraulic characteristics of the flood flow including depth and velocity of the flow at different cross sections of the models were evaluated. The results showed that the water surface level (flow depth) of the two-dimensional model HEC-RAS compared to the one-dimensional model had the lowest error as compared to other hydraulic parameters of flood flow. The two-dimensional HEC-RAS model showed the highest error rate in the flow velocity parameter in comparison to the one-dimensional model. The results indicated that two-dimensional HEC-RAS model V5.0.7 determined the surface of the flood zone 12.46 % more than the one-dimensional HEC-RAS model. The confirmation of the resulting zones on the current state of the river and comparison with the river aerial photo of 1346 indicated the higher accuracy of the two-dimensional HEC-RAS model in estimating the flood zone of the river.

Ardabil Plain Flood Vulnerability Rating Using the Combined BWM and TOPSIS Methods
A. Esmali Ouri1, P. Farzi, S. Choubeh,
Volume 26, Issue 3 (12-2022)
Abstract

Planning and providing appropriate tools to reduce the adverse effects of natural hazards including floods is inevitable. Achieving the above goal depends on having sufficient and accurate knowledge and information about the vulnerability of different ecosystems (watersheds) to various destructive factors. Vulnerability assessment by identifying potential stresses and disturbances (natural and man-made) as well as estimating the sensitivity of watersheds allows for predicting the effects and selecting appropriate solutions for the sustainable management of these ecosystems. Therefore, this study has been designed to identify and rank vulnerable sub-watersheds to floods in the Ardabil plain, taking into account social, economic, infrastructural, and ecological dimensions. First, the indicators and criteria of each dimension were identified taking into account the conditions prevailing in Ardabil plain. Then, information and data on climatic, hydrological, demographic, economic, infrastructure, and land use were obtained from relevant authorities. Then, the mentioned criteria were standardized and the weight according to their importance was calculated based on the BWM method the data obtained from this stage were performed using the TOPSIS technique to rank flood vulnerability for different sub-watersheds in Ardabil plain for the period 2007-2017. Finally, a map of Ardabil's plain vulnerability to floods was prepared and presented. According to the results, the criteria of building density, rainfall, population density, and the unemployment rate were the most important criteria of vulnerability and among the studied dimensions, the infrastructure dimension is too significant in flood vulnerability in Ardabil plain. Based on the comprehensive vulnerability map, sub-watershed 7 in Ardabil plain was identified as the most vulnerable sub-watershed in the study area.


Simulation of Design Flood Hydrographs in Aydooghmush Basin with HEC-HMS Model
F. Naeimi Hoshmand, F. Ahmadzadeh Kaleybar,
Volume 26, Issue 3 (12-2022)
Abstract
Hydrological models for evaluating and predicting the amount of available water in basins, flood frequency analysis, and developing strategies to deal with destructive floods are expanding daily. In this study, HEC-GeoHMS and Arc Hydro extensions in ArcGIS software and the HEC-HMS model were used to simulate design flood hydrographs in the Aydooghmush basin in the northwest of Iran. SCS-CN, SCS-UH, Maskingham, and monthly fixed methods were used to calculate rainfall losses, rainfall-runoff transformation, flood routing, and base flow, respectively. In model calibration with two real flood events, the average of absolute values of the residuals, the sum of the remaining squares, and the weight of the peak mean the error squares for the flood volume were 2.75, 5.91, and 5.32, respectively and for peak discharge were 8.9, 8.0, and 8.0, respectively. Model validation was evaluated as acceptable with a one percent error rate in the peak of discharge and a 19 percent in the flood volume. For maximum 24-hour precipitation, the log-Pearson type 3 was determined as the most suitable distribution in the SMADA model and design precipitation was extracted in different return periods. Thus, for the return period of 2 to 1000 years, the peak discharge and volume of the design flood were simulated equally to 18.8 to 415.6 m3 s-1 and 5.7 to 87.9 MCM, respectively.

Flood Risk Assessment using Multi-Criteria Decision-Making Models (MCDM) and Data Mining Methods (Case Study: Shiraz District 4)
S. Ayoubi Ayoublu, M. Vafakhah, H.r. Pourghasemi,
Volume 26, Issue 3 (12-2022)
Abstract
Population growth, urbanization, and land use change have increased disastrous floods. Iran is also among the countries at high risk of floods. The latest examples of flood damage are the devastating floods of the spring of 2019 with significant mortality and financial losses in more than ten provinces of the country. The purpose of this study is to prepare an urban flood risk map of District 4 City Shiraz. The vulnerability of the region was made using PROMETHEE Ⅱ and COPRAS multi-criteria decision-making models and urban flood hazard zones were prepared by partial least squares regression (PLSR) and ridge regression (RR) models and a risk map was obtained by multiplying the vulnerability and hazard in ArcGIS software. The highest percentage of the study area in the PROMETHEE Ⅱ and COPRAS models belongs to the moderate class of vulnerability. The evaluation of the vulnerability models using Boolean logic and RMSE and MAPE statistics, showed that the COPRAS model provided better results than the PROMETHEE model. The results of partial least square regression (PLSR) and ridge regression (RR) models in flood risk modeling were analyzed by the Taylor diagram, which showed the superiority of the ridge regression (RR) model and the accuracy of this model in preparing urban flood hazard maps. The risk map of the study area indicated that 34% of the area (973 ha) is in the range of high and very high flood risk.

Providing Regional Models for Maximum Daily Discharges of Iran’s Western Sub-Basins Using Generalized Linear Models (GLMs)
P. Mohit-Isfahanii, V. Chitsaz,
Volume 27, Issue 1 (5-2023)
Abstract
Introducing reliable regional models to predict the maximum discharge of floods using characteristics of sub-basins has special importance in terms of flood management and designing hydraulic structures in basins that have no hydrometric station. The present study has tried to provide appropriate regional flood models using generalized linear models (GLMs) to estimate 2-, 10-, 50-, and 100-year maximum daily discharges of 62 sub-basins in Great-Karoon and Karkhe basins. According to the results, the sub-basins were categorized into four sub-regions based on some physiographic and climatic characteristics of the study sub-basins. The results showed that regional flood modeling was successful in all sub-regions except sub-region II, which includes very large basins (A̅≈17300 km2). The adjusted R2 of the best models in sub-regions I, III, and IV were estimated at around 82.4, 91.3, and 90.6 percent, and these models have a relative error (RRMSE) of around 9.5, 9.23, and 6.7 percent, respectively. Also, it was found that more frequent floods with 2- and 10-year return periods are influenced by properties such as basin’s length, perimeter, and area, while rare floods with 50- and 100-year return periods are mostly influenced by the river systems characteristics such as the main river length, total lengths of the river system, and slope of the main river. According to the research, it can be stated that the behavior of maximum daily discharges in the study area is extremely influenced by the different climatic and physiographic characteristics of the watersheds. Therefore, the maximum daily discharges can be estimated accurately at ungauged sites by appropriate modeling in gauged catchments.

Determining the Most Susceptible Areas of Flood Occurrence Using MaxEnt Model in Marzdaran Watershed, Tehran Province
Y. Esmaeli, F. Yosefvand, S. Shabanlou, M.a. Izadbakhsh,
Volume 27, Issue 2 (9-2023)
Abstract
The objective of the current study was to zone flood probability in the Marzdaran watershed. Since the allocated budget for management work is limited and it is not possible to carry out operations in the whole area, having a map that has prioritized different areas in terms of the probability of flood occurrence will be very useful and necessary. A well-known data mining model namely MaxEnt (ME) is applied due to its robust computational algorithm. Flood inventories are gathered through several field surveys using local information and available organizational resources, and the corresponding map is created in the geographic information system. The twelve predisposing variables are selected and the corresponding maps are generated in the geographic information system by reviewing several studies. The area under the curve (ROC) is used to evaluate the modeling results. Then, the most prone areas of flood occurrence which are prioritized for management operations are identified based on the prepared map. Based on the results, about 100 km2 of the study area is identified as the most prone area for management operations. The results showed that the accuracy of the maximum entropy model is 98% in the training phase and 95% in the validation phase. The distance from the river, drainage density, and topographic wetness index are identified as the most effective factors in the occurrence of floods, respectively.

Bio-Retention Cells Performance in Restoring the Hydrologic Cycle of Highly Urbanized Catchments
M. Mehri, M. Hashemy, S. Javadi, M. Movahedinia,
Volume 27, Issue 3 (12-2023)
Abstract
Rapid urbanization is responsible for impervious area increases and more runoff generation in urbanized catchments. Higher runoff volume in urbanized catchments leads to higher flood risk. One of the methods of runoff management is low impact development (LID). Bio-retention cell (BRC) is one of the infiltration-based LID practices that allows restoring the pre-development hydrologic cycle. However, the overall hydrologic performance of BRCs can vary depending on different urban environments. In this study, the hydrologic performance of BRC in terms of runoff and flood reduction was investigated in a highly urbanized area in the east of Tehran, Iran. The SWMM model was used to evaluate the performance of BRC. The results showed that BRC for rainfall with a return period of 2 to 50 years reduced the total runoff volume by 76.2% to 70.2% and the peak discharge by 65.9% to 36.4%, respectively. Also, for rainfall with a return period of 2 to 50 years, BRC resulted in 15.2% to 27.5% infiltration of rainfall in the study area, respectively. This study demonstrates that BRC can help restore the natural hydrologic cycle of urbanized catchments by reducing runoff and increasing infiltration.

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