Showing 220 results for Model
B. Shahinejad, A. Parsaei, A. Haghizadeh, A. Arshia, Z. Shamsi,
Volume 26, Issue 3 (12-2022)
Abstract
In this research, soft computational models including multiple adaptive spline regression model (MARS) and data group classification model (GMDH) were used to estimate the geometric dimensions of stable alluvial channels including channel surface width (w), flow depth (h), and longitudinal slope (S) and the results of the developed models were compared with the multilayer neural network (MLP) model. To develop the models, the flow rate parameters (Q), the average particle size in the floor and body (d50) as well as the shear stress (t) as input and the parameters of water surface width (w), flow depth (h), and longitudinal slope (S) were used as output parameters. Soft computing models were developed in two scenarios based on raw parameters and dimensionless form independent and dependent parameters. The results showed that the statistical characteristics in estimating w, the best performance is related to the MARS model, whose statistical indicators of accuracy in the training stage are R2 = 0.902, RMSE=1.666 and in the test phase is R2 = 0.844, RMSE=2.317. In estimating the channel depth, the performance of both GMDH and MARS models is approximately equal, both of which were developed based on the dimensionless form of flow rate as the input variable. The statistical indicators of both models in the training stage are R2 » 0.90, RMSE » 8.15 and in the test phase is R2 » 0.90, RMSE = 7.40. The best performance of the developed models in estimating the longitudinal slope of the channel was related to both MARS and GMDH models, although, in part, the accuracy of the GMDH model with statistical indicators R2 = 0.942, RMSE = 0.0011 in the training phase and R2 = 0.925, RMSE = 0.0014 in the experimental stage is more than the MARS model.
H. Noury Hasanabady, M.r. Kavianpour, A. Khosrojerdi, H. Babazadeh,
Volume 26, Issue 3 (12-2022)
Abstract
Using a rough bed for spillway compare to common dissipation methods such as stilling basins, stepped spillways, ski jumps, and bed elements may be more efficient to boost energy dissipation. In this research, the impact of spillway continuous bed roughness on energy dissipation was investigated. For this purpose, a non-dimensional relationship was developed, and by calibrating the numerical model based on the present experimental study, energy dissipation over the spillway for three slopes of 15, 22.5, and 30 (degree) with six roughness sizes of 0.0, 0.005, 0.0072, 0.0111, 0.016, and 0.022 (m) and three discharges of 170, 110, and 90 (lit/s) was investigated. Based on the present results, using a rough bed spillway will increase energy dissipation. Also, the ratio of energy lost per meter length of rough bed spillway to that of smooth spillway increases by chute slope. The results showed that the highest amount of relative energy consumption in the presence of roughness was related to the slope of 22.5 degrees and 22.2 mm for roughness (85%), and the lowest relative energy consumption was observed in the control state (25%). As a result of the present study, a natural rough bed without concrete coating has befitted in terms of environmental aspects, construction cost, and energy loss.
G.m. Samadi, F. Mousavi, H. Karami,
Volume 26, Issue 3 (12-2022)
Abstract
The impact of different management options on the region and the existing conditions can be evaluated with minimal cost and time to select the most practical case using various tools including mathematical models. In this study, the SWAT hydrological model was performed from 2009 to 2019 using climatic, hydrological, and hydrometric data in the Malayer catchment, and the final model was validated by SWAT-CUP. To reduce the amount of uncertainty in the input parameters to the MODFLOW model, using the values of surface recharge from the implementation of the SWAT hydrological model, quantitative modeling of Malayer aquifer was performed more reliably in GMS software by using MODFLOW model. After modeling the study area in the 2009-2018 period and calibrating the model in the years from 2018 to 2019, the mean values of absolute error (MAE) were 0.35-0.65 m, and root means square error (RMSE) was 0.62-0.94 m, which seems acceptable considering computational and observational heads equal to 1650 m. Results of water level changes in observation wells located in the Malayer region indicate that the groundwater level in the aquifer has decreased by an average value of 9.7 m in the 10-year study period.
A. Yousefi, M. Maleki-Zadeh, A.r. Nikooie, M.s. Ebrahimi,
Volume 26, Issue 4 (3-2023)
Abstract
This study determines the amount of irrigation water saved as a result of the subsidy policy to adapt from flood to drip irrigation. We developed a positive mathematical programming model (PMP) to evaluate the effect of economic incentives on farmers’ decisions to choose the type of irrigation technology, cropping pattern, and "water use" and "water consumption" in rural Garkan Shomali district, which is part of the Najafabad aquifer. We collected data through farm surveys, desk research, and expert interviews. The results showed that a reduction in the financial costs of converting flood irrigation into drip irrigation can lead to farmers investing in this technology. In the current water allocation scenario, the subsidy policy increases the water consumption of drip-irrigated crops by 28%, of which 19% is non-consumed water before subsidy payment and the rest is related to the reduction of furrow-irrigated lands. Also, under non-volumetric water delivery conditions, the operating costs reduce and the net income of the farms increases because of the increase in efficiency and the development of the area under cultivation, which increases water consumption while the water use is constant. In the volumetric water delivery scenario, with the increase in subsidies, the net income of the farms will increase without developing the area under cultivation and only because of the increased yield. Therefore, subsidy policy increases irrigation efficiency at both the farm and regional levels and is an effective tool for dealing with drought conditions.
M. Hayatzadeh, M. Eshghizadeh, V. ,
Volume 26, Issue 4 (3-2023)
Abstract
The land use change as well as changes in climatic parameters such as temperature increase affect many natural processes such as soil erosion and sediment production, floods, and degradation of physical and chemical properties of soil. Therefore, it is necessary to pay attention to different aspects of the effect of these changes in studies and macro decisions of the country. In the present study, the SWAT conceptual model was used to test and analyze the existing scenarios in the Marvast basin. After calibrating the model, the two scenarios were tested. The first scenario is in the field of agricultural management and conversion of gardens to agricultural lands and the second scenario is a 0.5-degree increase in temperature by assuming other conditions are constant. The calibration and validation results of the model with the Nash-Sutcliffe test showed 0.66 and 0.68 respectively, which indicate the acceptable performance of the model in the study area. Then, the results of using two scenarios of land use change and heating, especially in recent years showed the effect of 30 percent of the climate scenario on the increase of flooding in the basin. The scenario of changing the use of garden lands to agriculture in two cases of 20% and 50% change of use of 10% and 12% was added to the flooding of the basin. The results indicate that in similar areas of the study area which is located in a dry climate zone, a possible increase in temperature can have a significant effect on flooding in the basin. However, the indirect impact of the human factor in increasing greenhouse gases and flooding in the basin should not be ignored.
S. Bigdeli, K. Ebrahimi, A. Hoorfar, A.a. Davudirad,
Volume 26, Issue 4 (3-2023)
Abstract
In this study, the accuracy of the Adaptive Network-Based Fuzzy Inference System (ANFIS) in integrating with the Gray Wolf Algorithm (ANFIS-GWO) in predicting groundwater level was evaluated for the first time using unpublished observational data from 1998 to 2018 in the Zarandieh aquifer, central Iran. Three observational wells were randomly selected for analysis. Assessment of evaluation criteria demonstrated that among the proposed scenarios using the hybrid model, the D scenario was selected as the optimal scenario with input data including the previous month's groundwater level, precipitation, temperature, and groundwater extraction. In the D scenario, parameters including MAPE, RMSE, and NASH were 0.29 m, 0.47 m, and 0.99, respectively for the first observational well. Also, C scenario with input data including the previous month's groundwater level, precipitation, and groundwater extraction for the second observational well, for the same parameters mentioned above equal to 0.20 m, 0.26 m, and 0.99. As well for the third observational well, the A scenario with input data including the previous month's groundwater level for the same parameters equal to 0.29 m, 0.41 m, and 0.99 as the optimal scenarios were selected using the ANFIS-GWO model. Based on the results, the Gray wolf algorithm in training the ANFIS model was able to reduce the average forecast error by equal to 0.03 (RMSE) and 0.02 (MAPE) meter and increased the average NASH value equal to 0.01 and increased the accuracy of predictions.
V. Habibi Arbatani, M. Akbari, Z. Moghaddam, A.m. Bayat,
Volume 26, Issue 4 (3-2023)
Abstract
In recent years, indirect methods such as remote sensing and data mining have been used to estimate soil salinity. In this research, the electrical conductivity of 94 soil samples from 0 to 100 cm was measured using the Hypercube technique in the Saveh plain. 23 types of input data were used in the form of topographic and spectral categories. Land area parameters such as the Topographic Wetness Index (TWI), Terrain Classification Index (TCI), Stream Power Index (STP), Digital Elevation Model (DEM), and Length of Slope (LS) were considered as topographic inputs using Arc-GIS and SAGA software. Also, salinity spatial and vegetation indices were extracted from Landsat 8 images and were considered spectral inputs. The GMDH neural network was used to model salinity with a ratio of 70% for training and 30% for validation. The results showed that the soil salinity values were between 0.1 and 18 with mean and standard deviation of 5 and 4.7 dS/m, respectively. Also, the results of modeling indicated that the statistical parameters R2, MBE, and NRMSE in the training step were 0.80, 0.06, and 42.1%, respectively. The same values in the validation step were 0.79, 0.13, and 48.7%, respectively. Therefore, the application of spectral, topographic, and GMDH neural network indices for modeling soil salinity is effective.
E. Javiz, A. Jalalian, M.r. Mosaddeghi, E. Chavoshi, N. Honarjoo,
Volume 26, Issue 4 (3-2023)
Abstract
One of the most significant environmental crises in arid, semi-arid, sub-humid, and even humid regions is the destructive phenomenon of desertification and in the arid and semi-arid regions is wind erosion. These problems exist in large areas of Iran and it is necessary to use an environmentally friendly and economic method to solve this problem. In this study, calcium bentonite clay was used for the first time in Iran and perhaps in the worlds in the critical region of Sajzi, which covers an area of 65 hectares. Experiments were performed on the crusts after one year of mulching with bentonite clay. The results showed that wind erosion has a negative and significant correlation with the mean weight diameter and geometric weight diameter of aggregate, aggregates with diameters greater than 0.25 mm, shear strength, and penetration resistance. On the other hand, the results of the permeability test using double-ring and by three models (Kostiakov, Horton, and Philip) showed that the lowest mean square error (SSE) and the highest coefficient of determination (R2) belonged to the Kostiakov model in the mulch-applied and control samples. This result indicated the superiority of the Kostiakov model compared to Horton and Philip's models. Wind erosion intensity was also measured in situ using a portable wind tunnel at 20 points in the Sajzi region. The findings showed that mulch application has controlled more than 95% of soil erosion.
H. Ghazvinian, H. Karami,
Volume 26, Issue 4 (3-2023)
Abstract
Runoff is formed by spending some time after rain and significantly depends on rainfall intensity, soil moisture, and slope. One of the fundamental questions about runoff is the time that it starts to create. In this research, the runoff start time in sandy loam soil was evaluated experimentally under different conditions using a precipitation simulator machine. The rainfall intensity parameters of (60, 80, and 100 millimeters per hour) and the slope of (0 and 5 percent) were investigated. The rainfall was created in the three soil treatment types completely dry (Sdry), the dry soil that had been saturated 24 hours before the test (S24hrlag), and the dry soil that had been saturated 48 hours before the test (S48hrlag). Eighteen tests were conducted on this soil. At the end of each test, the soil moisture was measured. The experimental results were compared with the numerical model of Green-Ampt. According to the Kendall and Spearman correlation test results, as the rainfall be intense, the start time of the runoff is lower. Also, the runoff starts at a faster time in the slope of 5 percent for every three types of soil. Also, the results of starting time of the runoff in the soil with a delay of 48 hours in the rain compared to the soil with a delay of 24 hours in the rain are closer in all of the rainfall intensity and slopes compared to the case of dry soil. Therefore, in the experiments related to a delay of 24 hours, the time of the start of runoff decreases. While in tests with a delay of 48 hours, it was not much different from completely dry soil. Also, the Green-Ampt results are close to the experimental results (R2=0.9775), and the maximum difference between the two mentioned methods is 4.8 minutes. Therefore, it can be used with the Green-Ampt method to calculate the start time of runoff in sandy loam soil in different states of rainfall intensity and bed slope.
A.r. Emadi, S. Fazeli, M. Hooshmand, S. Zamanzad-Ghavidel, R. Sobhani,
Volume 27, Issue 1 (5-2023)
Abstract
The agricultural sector as one of the most important sectors of water consumption has great importance for the sustainability of the country's water resources systems. The objective of this study was to estimate the river water abstraction (RWA) for agricultural consumption in the study area of Nobaran in the Namak Lake basin. The RWA was estimated using variables related to morphological, hydrological, and land use factors, as well as a combination of their variables collected through field sampling. Data mining methods such as adaptive-network-based fuzzy inference systems (ANFIS), group method of data handling (GMDH), radial basis function (RBF), and regression trees (Rtree) were also used to estimate the RWA variables. In the current study, the GMDH24 model with a combined scenario including the variables of river width, river depth, minimum flow, maximum flow, average flow, crop, and the garden cultivated area was adopted as the best model to estimate the RWA variable. The RMSE value for the combined scenario of the GMDH24 model was found to be 0.046 for estimating RWA in the Nobaran study area. The results showed that the performance of the GMDH24 model for estimating RWA for maximum values is very acceptable and promising. Therefore, modeling and identifying various variables that affect the optimal RWA rate for agricultural purposes fulfills the objectives of integrated water resources management (IWRM).
A. Shahbaee Kotenaee, H. Asakereh,
Volume 27, Issue 1 (5-2023)
Abstract
Precipitation is one of the main elements of the Earth's hydro-climatic cycle and its variability depends on the complex and non-linear relationships between the climate system and environmental factors. Understanding these relationships and doing environmental planning based on them is difficult. Therefore, classifying data and dividing information into homogeneous and small categories can be helpful in this regard. In the present study, an attempt was made to prepare precipitation, altitude, slope, slope direction, and station density data for 3423 synoptic, climatological, and gauge stations in Iran in the 1961-2015 years’ period. These data were entered into fuzzy (FCM), self-organizing map neural network (SOM-ANN) models and precipitation-spatial zoning. The outputs of the two models were compared in terms of accuracy and efficiency. The results obtained from the output of the models have divided the rainfall conditions of Iran into four zones concerning environmental factors. Evaluations also showed that both models had high accuracy in classifying precipitation parameters; However, the fuzzy model has a relative advantage over the neural network model in the accuracy of results.
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.
J. Abedi Koupai, A.r. Vahabi,
Volume 27, Issue 2 (9-2023)
Abstract
Awareness of water resources status is essential for the proper management of resources and planning for the future due to the occurrence of climate change in most parts of the world and its impact on different parts of the water cycle. Hence, many studies have been carried out in different regions to analyze the effects of climate change on the hydrological process in the coming periods. The present study examined the effects of climate change on surface runoff using the Atmosphere-Ocean General Circulation Model (AOGCM) in Khomeini Shahr City. The maximum and minimum temperatures and precipitation of the upcoming period (2020-2049) were simulated using a weighted average of three models for each of the minimum and maximum temperatures and precipitation parameters based on the scenario A2 and B1 (pessimistic and optimistic states, respectively) of the AOGCM-AR4 models. The LARS-WG model was also used to measure the downscaling. The HEC-HMS was used to predict runoff. The effects of climate change in the coming period (2020-2049) compared with the observation period (1971-2000), in the A2 scenario, the minimum and maximum temperatures would increase by 1.1 and 1.6 Degrees Celsius, respectively, and the precipitation would decrease 17.8 percent. In the B1 scenario, the minimum and maximum temperatures would increase by 1.1 and 1.4 degrees Celsius, respectively, and the precipitation would decrease by 13 percent. The results of runoff were different in the six scenarios in the way the most runoff reduction is related to the scenario of fixed land use and scenario A2 (22.2% reduction), and the most increase is related to the scenario of 45% urban growth and scenario B1 (5.8% increase). So, according to increase urban texture in the future and consequently enhance the volume of runoff, this volume of runoff can be used to feed groundwater, irrigate gardens, and green space in the city.
F. Ahmadzadeh Kaleibar, M. Fuladipanah,
Volume 27, Issue 2 (9-2023)
Abstract
Using transfer functions to predict soil moisture parameters has been considered strictly a scientific and economical method among researchers. In this research, field capacity (FC) and permanent wilting point (PWP) of soil were predicted using classic regression (linear and non-linear), support vector machine (SVM) algorithm, and gene programming expression (GEP) algorithm based on three performance assessment criteria as determination of coefficient (R2), root mean square error (RMSE), and standardized developed discrepancy Ratio (DDR) in the Arasbaran plain in the northwest of Iran. Independent parameters were determined as clay percent (Cl), silt percent (Si), gravel percent (Sa), organic carbon (OC), bulk density (ρb), and actual density (ρs) which (S, ρb, ρs) and (ρb, ρs) were opted to predict FC and PWP using Gamma test, respectively. The results showed that each three transfer functions are capable to simulate FC and PWP parameters but the SVM algorithm is the superior predictor among the three functions so the values of (R2, RMSE, and DDRmax) of training and testing phases for FC were obtained (0.9908, 0.5517, 17.50), (0.9785, 0.7004, 11.62) and those of PWP were calculated (0.9782, 0.5764, 2.85) and (0.8389, 1.187, 3.09), respectively.
N. Pourabdollah, M. Heidarpour, Jahangir Abedi-Koupai,
Volume 27, Issue 3 (12-2023)
Abstract
Hydraulic jump is used for dissipation of kinetic energy downstream of hydraulic structures such as spillways, chutes, and gates. In the present study, the experimental measurements and numerical simulation of the free hydraulic jump by applying Flow-3D software in six different conditions of adverse slope, roughness, and positive step were compared. It should be noted that two turbulence models including k-ε and RNG were used for numerical simulation. Based on the results, simulation accuracy using the RNG model was more than the k-ε model. The statistical indices of NRMSE, ME, NS, and R2 for comparing the water surface profile were obtained at 34.3, 0.0052, 0.995, and 983 for the application of the RNG model, respectively. Also, using the RNG model, the values of these indices for the velocity profile were obtained at 14.92, 0.127, 0.9982, and 962, respectively. In general, the error of the simulated water surface and velocity profile were obtained at 5.31 and 12.4 percent, respectively. Moreover, the maximum error of the numerical simulation results of D2/D1, Lj/D2, and Lr/D1 was ±12, ±12, and 16%, respectively. Therefore, the use of Flow-3D software with the application of the RNG turbulence model is recommended for numerical simulation of the hydraulic jump in different situations.
S. Azadi, H. Nozari, S. Marofi, B. Ghanbarian,
Volume 27, Issue 3 (12-2023)
Abstract
One of the strategies for agricultural development is the optimal use of irrigation and drainage networks, which will lead to higher productivity and environmental protection. The present study used the system dynamics approach to develop a model for simulating the cultivated area of the Shahid Chamran irrigation and drainage network located in Khuzestan province by considering environmental issues. Limit test and sensitivity analysis were used for model validation. The results showed the proper performance of the model and the logical relationship between its parameters. Also, the cropping pattern of the network was determined in two modes of non-stepwise and stepwise changes to determine the optimal cultivated area of the Shahid Chamran network with environmental objectives and minimize the amount of salt from drains. The results showed that the amount of optimized output salt from the network has decreased in both non-stepwise and stepwise changes compared to the existing situation in the region. The total output salt in the current situation, from 2013 to 2017, was obtained at 2799, 2649, 2749, 2298, and 2004 tons.day-1, respectively, in the stepwise changes, are 2739, 2546, 2644, 2223, and 1952 tons.day-1, and finally, in the non-stepwise changes, are 2363, 2309, 2481, 2151, and 1912 tons.day-1. The results showed that the non-stepwise changes due to considered limitations have been more successful in reducing output salt than the stepwise changes. The analysis of the results showed the model's success in optimizing and achieving the desired goals. The results showed that the present model has good accuracy in simulating and optimizing the irrigation network, cropping pattern, and defining other scenarios.
A. Mahdavi, S. Soltani Koopaei, R. Modares, M. Samiei,
Volume 27, Issue 4 (12-2023)
Abstract
Land use changes are one of the main factors in the amount of surface runoff changes in watersheds. Therefore, it is necessary to investigate it to reduce the damages (human and financial) caused by floods and to modify watershed management. The watershed of Nahre Azam is located in the north of Shiraz city and a lot of loss of life and money to the residents of Shiraz due to floods has occurred in previous years. The present research was conducted to investigate the relationship between land use change and runoff in the Nahre Azam watershed in Shiraz using the SWAT model in the period of 2004-2020. The model was calibrated using data from 2004 to 2014 and validated for 2015 to 2020. These images were classified into 6 main land uses using the supervised classification method after performing necessary pre-processing, and a land use map was prepared for 2040 using the Markov chain method. Then, the effect of the land use change in 2003 and 2040 on the amount of simulated runoff was evaluated with the recalibrated model. The calibration results of Nahre Azam watershed for the values of statistical parameters in the calibration step for the coefficient of determination, P-Facor and R-Facor are 0.77, 0.72, and 2.43, respectively, and for the validation step we obtained 0.69, 0.65, and 2.3 respectively. The analysis of the land use map showed that the main land use change in the region related to the conversion of pastures to agricultural land and urban land, which caused a decrease in pastures. Also, the results of the model simulation using the land use maps of 2003 and 2040 indicated that the amount of runoff decreased. The results revealed that if all the uncertainties are minimized, the calibrated SWAT model can produce acceptable hydrological simulation results for the user, which is useful for water resource and environmental managers and politicians as well as city managers of Shiraz.
A.s. Hosseini Khezrabad, A.a. Vali, A.h. Halabian, M.h. Mokhtari,
Volume 27, Issue 4 (12-2023)
Abstract
Desertification is one of the most serious ecological environmental problems in the arid regions. Quantitative assessment of the desertification process is important for the prevention and control of desertification. In this research, the IMDPA model was used to evaluate the quantitative and qualitative desertification situation in the northwest of Yazd. Three criteria of soil, vegetation, and wind erosion were considered in this model. Several indicators were defined for each criterion with a weight of 0 (low) to 4 (very severe). The geometric mean of all three criteria was used to prepare a map of sensitive areas to desertification in ArcGIS. The results indicated that more than 92% of the research area was in the extreme class of desertification, and only the dunes work unit was in a very intense class. Finally, the whole of the research area with a final score of 3.04 was placed in the extreme class of desertification intensity. Also, the soil criterion with the highest weight score of 3.26 has had the greatest impact on the desertification of the northwest region of Yazd. Therefore, it is necessary to implement remedial and revitalization operations in this region according to the expansion of the phenomenon of desertification and the high influence of the soil criteria. The results of the research showed the intensity of desertification, the potential, and the sensitivity of the region to the phenomenon of desertification can be referred to as a departure from the natural functioning of the system.
R. Sargholi, A. Bordbar, A. Asareh, M. Heidarnejad,
Volume 28, Issue 1 (5-2024)
Abstract
In the past, various methods have been proposed to control beach heel scouring. For shallow rivers (such as mountain rivers), various types of overflows are used. Therefore, the development of scour in cross-vane and w-weir structures for coastal protection was investigated in this study. The results showed that by installing a w-weir structure in a 90-degree position compared to a 30 and 60-degree position, a 37.9% and 19.7% reduction of scouring was observed, respectively. Also, by installing the cross vane structure in the 90-degree position compared to the 30 and 60-degree position, a 35.4% and 21.2% reduction of scouring was observed, respectively. With increasing width (L / B) (ratio of the width of structure to the width of flume), the w-weir structure decreased from 1.5 to 2, scour rate of 7.9%. Also, with increasing width (L / B) (ratio of the width of structure to the width of flume), the cross-vane structure has decreased from 1.3 to 1.7, and the scour rate has decreased by 4.7%. The w-weir structure had an average of 7.3% less scouring than the cross-vane structure.
I. Kazemi Roshkhari, A. Asadi Vaighan, M. Azari,
Volume 28, Issue 1 (5-2024)
Abstract
Due to climate change and human activities, the quality and quantity of water have become the most important concern of most of the countries in the world. In addition, changes in land use and climate are known as two important and influential factors in discharge. In this research, four climate change models including
HADGEM2-ES, GISS-E-R, CSIRO-M-K-3-6-0, and CNRM-CM5.0 under two extreme scenarios RCP2.6 and RCP8.5 were used as climate change scenarios in the future period of 2020-2050. The future land use scenario (2050) was prepared using the CA-Markov algorithm in IDRISI software using land use maps in 1983 and 2020. The SWAT model was calibrated to better simulate hydrological processes from 1984 to 2012 and validated from 2013 to 2019 and was used to evaluate the separate and combined effects of climate change and land use on discharge. The prediction of the climate change impact on discharge showed a decrease in most of the models under the two scenarios RCP2.6 and RCP8.5. The average maximum decrease and increase under the RCP2.6 scenario is 60 and 30 percent, respectively. This significant reduction is greater than that predicted under the RCP8.5 scenario. Examining the combined effects of climate and land use change revealed that the average decrease in discharge in the months of October, November, December, and January under two scenarios is 46.2 and 58%, respectively. The average increase in discharge is predicted to be 47% under the RCP8.5 in the months of April and May in the HadGEM2ES.
