mohammad bashirgonbad

Depending on rainfall systems and conditions influenced by unprincipled human activities, floods cause a lot of damage to natural resources, settlements, and projects every year. Hydrometric stations are often destroyed during floods or small watersheds lack hydrometric stations, which means that the estimation of runoff and maximum flood discharges requires a suitable method to calculate runoff and flood values in these basins. Prevention of this damage is doubly important when the study area overlooks places with a high density of settlements and urban facilities that can threaten the lives of many residents. The amount of runoff in each sub-basin of the watershed overlooking Malayer City was estimated in this study.

The watershed overlooking the city of Malayer with an area of 14,700 hectares is stretched from the north to the northeast of the city. The processing of digital elevation models identified five sub-basins overlooking the city and field visits. The curve number method was used to estimate runoff height and flood volume in each sub-basin. The most intense rainfall event (88 mm per day) with a return period of 30 years was designed as rainfall, considering the amount of previous rainfall 5 days before this event with a cumulative value of 45.2 mm. To calculate the physical parameters of the watershed in this study, topography, geology, vegetation, soil, and land use maps were digitized using a geographic information system. Simultaneous maps of land use and rainfall were provided using Sentinel-2 images, containing 13 spectral bands and a spatial resolution of 10 meters. Utilizing the SCS method, the layers of land use, vegetation, and soil hydrological groups were combined to produce a curve number map. The value of the curve number was corrected for the wet condition based on the rainfall 5 days before and the location of the basin in the previous wet conditions. A weighted curve number approach for each sub-basin was compared with another approach based on the arithmetic mean of the curve number for each sub-basin, as well as a weighted runoff height approach for each curve number. Kirpich's method was used to calculate the concentration time of each sub-basin. In the next step, using the maximum daily rainfall data from the Malayer synoptic station in the statistical period from 1991 to 2021, the rainfall height values were converted to runoff height using the SCS relationship, and then the peak flood discharge was calculated for each sub-basin.

The lack of permanent vegetation and the presence of annual grasses are among the reasons for the high potential of the sub-basins in runoff production. As a result, the average curve numbers of arithmetic and weighted average methods are 79.09 and 81.46, respectively, which shows the high capacity of the basin in producing runoff. Converting curve number values to peak flood height and flow using two commonly used methods of curve number calculation and comparing it with the results of the weighted runoff height calculation approach for each curve number in the working units of the study area showed no significant difference. Finally, the runoff height maps and the peak discharge of each sub-basin were drawn. The northern sub-basin of the basin with an average runoff height of 44.32 mm and a peak discharge of 168 m3/s has the highest participation in flood discharge toward the city of Malayer, and sub-basin 4 in the south-eastern part of the basin has the least participation in flood generation. The results of the relationship between the area and runoff height showed that the basins with a larger area did not necessarily contribute the most to the occurrence of floods in all three calculation methods of the curve number and runoff height. Other factors also play a role in these results, such as the extent of rocky outcrops and reduction time of concentration due to the high slope as one of the reasons for this problem. The formation of the longest watercourse in the basin with a length of 16314 meters under Sub-basin 3, which has the highest peak flood flow after Sub-basin 2, is one of the discussed technical points that can handle the rapid discharge of the peak flow of about 100 m3/s. However, the study of its longitudinal slope of about 2% indicates the high risk of flooding caused by the lack of evacuation in rains with a high return period, which in turn is a serious risk for the threats caused by floods in the southeastern part of the city. The intersection of the end part of the main waterway with the exit of other sub-basins and the collection of runoff under the upstream basins are other problems that increase the risk of flooding in the downstream areas.

It is suitable to use the curve number method to estimate the amount of runoff produced in the basins overlooking the settlements that do not usually have hydrometric stations. Because of its low-density pastures and rain-fed agriculture, the watershed overlooking Malayer has a high potential for runoff production.

Due to the large volume of human and commercial activities, one of the most important goals of infrastructure is to collect and transfer urban runoff, control floods and prevent flooding in cities. To correctly estimate the runoff and characteristics of hydrological units and channels, it is important to use appropriate hydrological and water models. Considering the importance of this topic, this research was conducted with the aim of estimating the urban runoff of the Malayer to determine the potential flooding points using a storm water management model (SWMM).

On the basis of available technical reports, the area of the sub-watersheds, nodes and main channels of the city were first determined. Flow direction and slope of the area was determined using a digital elevation model and 11 sub-watersheds were identified. In addition, 11 nodes were determined, regardless of the initial water depth and water level. Using the daily rainfall data of the Malayer synoptic station during the 1992–2020 statistical period, a nine-hour rainfall with a return period of 2 years was calculated and entered into the model. The geometrical shape of the channels was an open rectangle and the flow trend in the channels was determined using the kinetic wave method. The size of the maximum flow of water through the channels was calculated using the relationship between the cross-section of the flow and the speed of the flow a 9-hour the rainfall with a return period of 2 years. To calibrate the model, the variables of percentage of impervious areas, pond storage and roughness coefficient of impervious areas were used in the change range of the allowed modification range. In order to evaluate the model, Nash-Sutcliffe efficiency coefficient and the root mean square error were used.

The results showed that after optimizing the sizes of the variables, the Nash-Sutcliffe efficiency coefficient and the root mean square error were 0.73 and 0.02, respectively. Of the total rainfall of 14.54 mm, 5.53 mm was related to infiltration losses, 7.55 mm was related to surface runoff, and 1.45 mm was related to pond storage. The results showed that the sub-watersheds that were in the north of the city and overlooking the heights and leading to node number 10 had more volume and drainage and it is necessary to revise the design and expansion of the channels in this area. In addition, the sub-watersheds of the western part of the city (sub-watersheds no. 4) and the southwestern part (sub-watersheds no. 8) had the highest and lowest flood potential of 0.651 and 0.547, respectively.

In this research, the results showed that almost half of the city would be affected by flood risks in the event of rains. Therefore, the current drainage network does not have the necessary efficiency to discharge urban runoff in the northern part of the city, and it is necessary to determine the optimal dimensions of the channels. Because the eastern elevations of the studied area are snow-covered and considering the geology of the area, in future research, models capable of calculating the runoff caused by snow melting should be used.

In recent years, river flow forecasting is one of the most important issues for water resources management in Iran. This prediction requires statistics and information, unfortunately, most of the basins of the country lack data of the desired quantity and quality.

Therefore, hydrological modelling and the use of artificial intelligence are examples of solutions that are used to solve this challenge in hydrology. The criteria for selecting the appropriate model for this process are to evaluate the performance of the models according to the hydrological conditions of each region. In this research, IHACRES model and Artificial Neural Network (ANN) were used to predict the streamflow in Bakhtiary basin. The data from 1984 to 1994 were used as calibration period and the data from 1995 to 2006 were used for validation.

The evaluation results of the hydrological model and the artificial neural network were evaluated using Kling-Gupta, Nash-Sutcliffe indices, coefficient of determination, mean squared error and absolute mean error. Results showed that the artificial neural network had better results in the simulation in all the evaluated evaluation criteria.

According to the results of the methods used in the research, the artificial neural network method has a more accurate prediction of the Bakhtiary river flow than the hydrological model.

One of the most important challenges in recent years is the issue of climate change and its effects on water resources, which is considered one of the main areas of research around the world. Two obvious signs of climate change are changes in the mean and extreme values of climate variables that can increase the Probability of flood occurrence. Therefore, it is necessary to study the effect of climate change on floods in the future.

In this study, using the observed daily data of precipitation and temperature in the period 1961-2005 synoptic and climatological stations inside and around the Bakhtiary catchment, the effect of climate change was investigated. To predict future precipitation and temperature, the data of the canESM2 general circulation model under RC 2.6 and RCP 8.5 scenarios for climate variables for the period 2006 to 2100 were used. The effective criteria in downscaling were selected according to the correlation between the predictor and predictands variables from the NCEP-NCAR reanalysis database. Then the MORDOR-SD semi-distributed models were used to evaluate the effects of climate change on runoff. This model was calibrated and validated using daily rainfall, temperature, and observation data at Tang-e-Panj Bakhtiary station for the period 1976-2006. Applying the results of changes in precipitation and temperature data obtained from the SDSM model under the two scenarios mentioned and reproducing them in large numbers by nonparametric bootstrap method and replacing the resulting maximum daily events in the hydrological model to achieve maximum daily flood and probability made it possible. At the end of the simulation and calculation of the cumulative distribution function (CDF) of the simulated events, the maximum daily discharge values in different return periods were calculated.

The results showed that, temperature and precipitation parameters under RCP 2.6 and RCP 8.5 scenarios with average evaluation criteria MAE = 1.29, RMSE = 1.96 and NASH = 0.56 for precipitation decreased by an average of 5.4 to 11% compared to the base period for temperature with evaluation criteria of MAE= 2.27, RMSE= 2.71 and NASH 0.92 = from 6.5 to 10.4% increase compared to the base period. The results of the Nash-Sutcliffe and Kling-Gupta evaluation criteria are 0.76 and 0.83, respectively, which shows the acceptable ability of the hydrological model in the simulation. The results of the study showed that the maximum daily discharges simulated using scenario 8.5 in different return periods show higher values than the maximum daily discharges in scenario 2.6 but there is no significant change compared to the maximum daily data in the base period.

In general, it can be said that the use of climate data in the future for planning in the field of integrated water resources management and prevention of natural hazards such as extreme floods and droughts can be a useful tool for planning managers.

There are many methods for estimating the maximum flood discharge including frequency analysis methods and risk study of hydraulic structures based on flood frequency analysis is often sensitive to the observations and selected statistical distribution that cause errors in design. Since heavy rainfalls are the main cause of floods and the rainfall records are longer than flow records, hence long-term records of rainfall at rain gauge stations of Bakhtiary basin in a 66-year period and the 58-year records of daily maximum discharge were used in this study. In this research, peak and maximum daily flows were estimated by using hydro-climatic methods of Agregee and Gradex. Then, the results obtained from the simulation based on hydro-climatic approach for the different return periods were compared with those of classical statistical techniques of Gumbel and Generalized Extreme Values (GEV). The results showed that using additional information like rainfall data plus hydrometric data in hydro-climatic methods gives better estimates rather than frequency analysis methods. Because each three evaluation criteria of Root Mean Squared Error (RMSE), Nash–Sutcliffe efficiency (NSE) coefficient, Kling-Gupta efficiency (KGE) coefficient confirm performance of hydro-climatic methods in comparison with Gumbel and Generalized Extreme Values (GEV) distributions. Finally, a peak to volume ratio extracted from the 26 major flood events detected at Tang-e panj hydrometric station within the hourly discharge records was used to transform the cumulative distribution function of daily discharge into peak discharge.