نشریه دانش آب و خاک
سال سی و سوم شماره 3 (پاییز 1402)

Evapotranspiration is one of the main components of water balance in agriculture and is one of the effective and efficient factors for accurate irrigation planning and management. Direct measurement of evapotranspiration values is time consuming and costly. On the other hand, modeling such a complex process in which many parameters interact with each other is so difficult that it is not possible to simplify the issue without multiple assumptions. Therefore, accurate estimation of this parameter has always been considered by the researchers. In the other point of view, the FAO-56 method was used as the accurate and accepted method for calculating reference evapotranspiration. One of the weaknesses of this model is its dependence on various meteorological variables. Therefore, it is necessary to use methods which need low number of meteorological variables and estimate the reference evapotranspiration with high accuracy. Additionally, due to the use of many meteorological variables and the complexity of the calculations, it is difficult to use FAO-56 method in all regions. Therefore, in the recent years, many researchers implemented machine learning methods to estimate reference evapotranspiration. Most studies in the field of reference evapotranspiration estimation use experimental models that require all the effective reference evapotranspiration parameters to provide an acceptable estimate. Hence, the aim of the current study was to present a superior model from three machine learning models, including random forest (RF), gradient boosted tree (GBT) and generalized linear model (GLM) for estimating reference evapotranspiration in three synoptic stations located at arid, semi-arid and wet climates of Iran. To the best of our knowledge, the proposed GBT and GLM methods have not been used for estimating reference evapotranspiration in the mentioned stations.

In this research, the FAO-56 method was used to estimate the reference evapotranspiration. Also, three machine learning methods including GBT, GLM and RF were implemented to estimate the amount of reference evapotranspiration. Daily parameters of some fundamental and effective meteorological variables on evapotranspiration during 21-years statistical period (2000-2020) were collected in three stations located at different climates including Yazd station (arid), Birjand station (semi-arid) and Sari station (wet). In order to investigate the possibility of using different combinations of meteorological parameters to estimate the reference evapotranspiration as accurately as possible, seven different combinations of meteorological parameters were defined. The accuracy of the utilized methods was evaluated using three criteria such as correlation coefficient, scattering index and Nash-Sutcliffe coefficient. Additionally, Taylor diagrams were implemented for evaluating the accuracy of the used methods. It should be noted that the Taylor diagram shows the three parameters of root mean square error, correlation coefficient and standard deviation simultaneously in one figure. Also, the most suitable combination of meteorological parameters that had good accuracy for estimating reference evapotranspiration, was suggested.

The results showed that in the best model at Birjand Station, and Yazd stations scenario number three by two meteorological variables of temperature and wind speed and in Sari station the scenario number two with temperature and relative humidity, the gradient boosted tree model was reinforced with Nash-Sutcliffe coefficient of 0.804, 0.826 and 0.733, with correlation coefficient of 0.997, 0.997 and 919 and scatter index of 0.249, 0.218 and 0.361 and the generalized linear model with Nash-Sutcliffe coefficient of 0.892, 0.931 and 0.869 correlation coefficient of 0.952, 0.966 and 0.933 and scatter index of 0.185, 0.137 and 0.252, respectively. Finally, the RF method with Nash-Sutcliffe coefficient of 0.954, 0.956 and 0.929, correlation coefficient of 0.978, 0.978 and 0.965 and scatter index of 0.121, 0.110 and 0.186 had good performance for estimating the reference evapotranspiration. On the other hand, in all methods, the scenario number seven using the meteorological parameters of temperature, relative humidity of sunny hours and wind speed in all three stations, presented the most accurate performance. Therefore, all three methods may be proposed as models with high degree of accuracy for estimating reference evapotranspiration.

Reference evapotranspiration is one of the main components of water balance in agriculture and is one of the effective and influential factors for accurate irrigation planning. Therefore, accurate estimation of this parameter has a significant role on reducing excessive water consumption. In this study, three data-driven models of RF, GBT and GLM were used in three stations of Yazd, Birjand and Sari stations. The obtained results indicated that the seventh scenario using all four meteorological parameters in all stations with the highest correlation coefficient, the lowest scatter index and the highest Nash-Sutcliffe coefficient provided most accurate estimates of the reference evapotranspiration and may be recommended for proper estimation of reference evapotranspiration.

Accurate estimation of crop water requirement is important especially in arid and semiarid climates. The rate of evapotranspiration can be measured by a lysimeter, however, it is expensive and its measurement is a cumbersome practice and time consuming. Therefore, many researchers use empirical models instead of direct measurements. Evapotranspiration of every crop is related directly to reference crop evapotranspiration (ET0). There are many empirical models for estimation of ET0. Among them the FAO-56 Penman-Monteith (FAO56PM) is known as the standard method in every climate. However, this method needs more climatic parameters which are not available everywhere. Therefore, identification of the model which needs less parameters and easily available climatic parameters will be useful. In this study three candidate models which had such conditions considered. These three models are i) Blaney-Criddle (BC), ii) Doorenbos and Pruitt (DP), and iii) Turk. The suitability of the candidate models compared with the output of the FAO56PM method. The main objective of this study is finding the most suitable model among the three candidate methods in Urmia Lake basin.

The region under study is the Urmia Lake basin located in North West of Iran. Nine stations selected across the basin. Meteorological data gathered from the Islamic Republic of Iran Meteorological Office (IRIMO). The method used here as a bench mark for evaluation of other empirical models is FAO-56 Penman-Monteith (FAO56PM). Three empirical models for ET0 estimation which need less climatic parameters are i) Blaney-Criddle, ii) Doorenbos and Pruit, and iii) Turk. These three models need climatidata that are easily available at least in the region. The recommended form of the FAO56PM method is as follows:ET_0=(0.484×Δ(R_(n-) G)+ϒ 900/(T+273) u_2 (e_s-e_a))/(Δ+ϒ(1+0.34u_2)) (mm day-1) [1] Where Rn is the net solar radiation (MJ/m2/day), G is the ground heat flux (MJ/m2/day), T is mean daily air temperature (℃), u2 is the wind speed at two- meter height (m/s), es is the saturated vapor pressure (kPa), ea actual vapor pressure (kPa). Other parameters explained in Allen et al. (1998).The first empirical candidate model for estimation of ET0 is the Turk model (Shuttleworth 1993) which reads:ET0 =0.31 T/(T+15)(S_n+2.09)(1+(50-RH)/70 ) ( 〖mm day〗^(-1) ) ,if RH<50% [2] Where Sn is the net solar radiation in (MJ/m2/day), RH is the relative humidity (%). If the average RH of a station is great or equal to 50%, then the second parenthesis will be removed from the equation, i.e. its value will be unity. The second empirical candidate model for estimation of ET0 is the Doorenbos and Pruitt (DP) model (Shuttleworth 1993) which reads:ET0 =-0.3+b_dp Δ/(Δ+γ) S_n 〖(mm day〗^(-1)) [3] where bdp calculated from the following relationship:b_dp= 1.066-0.0013 (〖RH〗_mean)+0.045 (U_d)-0.0002 (〖RH〗_mean)(U_d)-0.000315〖(〖RH〗_mean)〗^2-0.0011(〖U_d)〗^2 [4] The third empirical candidate model for estimation of ET0 is the Blaney-Criddle (BC) model (Fooladmand and Ahmadi 2009) which reads:ET0=(a_BC+b_BC f) ) 〖mm day〗^(-1)) [5] Where f=P(0.46T+8.13) [6] and a_BC= 0.0043〖RH〗_min - (n/N)- 1.41 [7] b_BC= 0.82-0.0041 (〖RH〗_min) + 1.07(n/N) + 0.066(U_d) -0.006(〖RH〗_min) (n/N) - 0.0006 (〖RH〗_min) (〖RH〗_min) (U_d [8] In [7] and [8] n is the actual sunshine hours and N is the maximum daily sunshine hours.In order to evaluate the models performances three criteria were used in this study which are i) coefficient of determination (R2), ii) root mean square error (RMSE), and mean absolute error (MAE). The output of models compared with that of the FAO56PM output in each of the selected stations.

Results showed that the median of R2 values of the Turk and BC were great than DP. The median of R2 values of both the Turk and BC were about 0.9. However, this measure for DP was about 0.75. The variance of R2 values in the case of BC was less than DP. The lowest value of RMSE belonged to the BC model which was about 2 mm/day. This value for other two models were more than 2 mm/day. The variance of RMSE obtained for all the nine stations was minimum comparing the three models. Therefore, according to Fig. 3, it can be suggested that when the RMSE was used for selection of the best model then the TURK model was superior than the others. However, when we considered all the three criteria for model selection, then the TURK model was superior than the others. According to Fig. 6 it can be concluded that in summer hot days the DP model overestimate the ET0 comparing the FAo56PM at Tabriz station. However, in the winter cold days DP underestimated the ET0 comparing the FAo56PM at the same station.

In this study three candidate models compared with the base model i.e. FAO56PM. Nine stations around the Urmia lake selected. Results indicated that the TURK model was suitable for ET0 estimation in Urmia Lake basin. This model only need three weather parameters which are i) Tmean, ii) actual sunshine hours (n), and relative humidity (RH). Logical use of fresh water in this basin is recommended.

Pre-sedimentation basins are considered as the major and important components in water treatment process through conventional method. Because of the high cost of constructing these basins, which is approximately 30% of the total costs of water treatment plants, modeling and optimum performance of pre-sedimentation basins are very important. In pre-sedimentation basins, because of the existence of velocity gradients, secondary and rotational flows occur. In order to increase the performance of a pre-sedimentation basin (clarifier), it is essential to have a uniform and calm flow field. The use of suitable baffle configurations may help forming favorable flow field and increase the efficiency of the pre-sedimentation basins. In order to find the proper position of a baffle in a rectangular sedimentation basin, computational investigations are performed. The first step to optimize pre-sedimentation basin is accurate calculation of the velocity field and the volume of rotation zones. Flow guiding blades can also be used to depreciate the inlet jet and reduce turbulent kinetic energy. Because of the flow complexity and also the effects of scale, physical models can not solely provide a clear understanding of the physics governing the flow field and it is necessary to study this phenomenon numerically along with field and experimental studies. The first step to optimize pre-sedimentation basins is accurate simulation of the velocity field and the volume of rotation zones. In the present study, numerical simulation of flow was investigated in a pre-sedimentation basin using SSIIM and Fluent models. Continuity and momentum equations were solved using finite volume method. Flow analysis was done steady by the SIMPLE algorithm for velocity and pressure coupling. Discrete method of continuity equations, momentum, turbulent kinetic energy, Reynolds stress drop and discretion of pressure equation are standard. The numerical results were calibrated with experimental results of Shahrokhi et al. (2011) and Imam et al. (1984). Flow simulation was performed in 3D and flow velocity profiles were compared with the experimental results in different sections of a pre-sedimentation basin. Then, in order to sedimentation investigation in the pre-sedimentation basin, advection and dispersion equation of sediment concentration was solved simultaneously with the governing equations of flow. The results of the vertical distribution of sediment concentration profiles in different sections of the basin were compared with the experimental and numerical results of other researchers. Finally, the effect of flow guiding blades on the flow pattern and the efficiency of sedimentation in the pre-sedimentation ponds were investigated. The comparison showed that there is a good agreement between numerical and experimental study with an average error of 6%. Flow rate is one of the effective parameters on creating a rotational zone inside the basins. With increasing the inlet flow rate from 0.002 to 0.01 cubic meters per second, the length of the rotational zone has increased 25% and the width of the rotating zone has increased 45%. The secondary and rotational currents formed at the entrance of the basin are two small rotational zones and approaching the middle of the basin and formation of flow separation zones, the number of rotating areas and their dimensions have increased. From the beginning to the middle of the basin, the shear stress is increased. In the sections x = 0.46 m and x = 0.82 m, the amount of shear stress is maximum. Amount of energy in the middle of the depth has decreased by 40% compared to the water level and about 60% compared to the floor of the sedimentation basin. It showed that there is a good agreement between the numerical and experimental results. It also indicated high ability of SSIIM in predicting distribution of sediment concentration profiles in pre-sedimentation basins. With increasing flow depth, the sediment concentration decreases. In the section x = 1.58 m, the sediment concentration near the free surface is 44 mg L-1, which decreased by 57.48% compared to the concentration of sediment in the basin bed. In the case without the guide blade, near the free surface of the stream, the sediment concentration was decreased. Also, in the middle of the basin, due to the turbulence of the flow and the rotational areas, the secondary current strength was maximal and decreased as it approached the end of the basin.

A large part of Iran is located in arid and semi-arid climates. Despite the existing shortcomings, Iranian agriculture is highly dependent on irrigation water. As water is considered as the most important and limiting input of agricultural production in Iran (Zibaie, 2007). Rapeseed (Brassica napus L.) is the third annual oil crop in the world after palm oil and soybeans, which is cultivated for its edible oil and is easily replaced by cereals (FAO, 2013). The main goal in improving agricultural water productivity in the world is to increase agricultural products with less water consumption, thus reducing the share of water in the agricultural sector and allocating more water to other uses and, most importantly, the water needs of the environment (Heydari, 2014). So far, no report has been presented on the evaluation of different irrigation systems in rapeseed cultivation in East Khuzestan. The main purpose of this article was to measure the irrigation water of rapeseed fields in Behbahan city and compare their physical and economic water productivity. In this way, the physical and economic productivity of water under different agricultural management and in irrigation systems can be compared and evaluated.

This project was implemented in the field to determine canola irrigation water under the management of farmers in Behbahan city. In 26 farms, the volume of canola irrigation water (without interfering with their irrigation program) was measured. To determine the volume of irrigation water, first the amount of inflow from the selected water source was measured with a suitable device (WSC flume, meter or ultrasonic flow meter). Linear multivariate regression analysis was used to investigate the effects of the independent variable on the above dependent parameters. Water requirement was calculated based on the FAO Penman-Monteith model using the daily statistics of Behbahan Synoptic Meteorological Station (minimum and maximum daily temperature, minimum and maximum daily humidity, wind speed and maximum sunny hours) and using ETCalculator software. One-way analysis of variance was used to show a statistically significant difference between the means of two or more independent groups. To compare physical and economic productivity indicators of irrigation water, there was a need to resolve the difference. Therefore, the standard Z-Score standardization method was used to resolve the scale difference. SPSS16 software was used for statistical analysis.

The average irrigation water productivity in 26 farms ranged from 0.351 to 1.545 kg per cubic meter and economic water productivity ranged from 6940 to 3719660 Rials per cubic meter. Irrigation water volume with t-statistic (-11.193) and equivalent beta coefficient (-0.056) had a significant negative effect at the level of 1% on the irrigation water productivity and a significant negative effect at level 5% had on the economic water productivity. The method of irrigation of selected farms (surface or sprinkler) had a significant effect at the level of 5% on the physical and economic irrigation water productivity. The calculated scores according to Z-Score showed that 31% of the farms that had sprinkler irrigation system were in good condition in terms of physical and economic productivity of irrigation water and none of the farms in the surface irrigation system were ranked well in terms of irrigation water productivity, but 8% of the irrigation farms had good economic productivity. The results of Pearson correlation coefficient showed that rapeseed yield had a positive and significant correlation at the level of 1% and 0.608 with irrigation water productivity, while yield had no significant correlation with economic water productivity.

Comparison of the results of average traits showed that the implementation of sprinkler irrigation system in the studied farms has increased the physical and economic productivity of irrigation water. The high cost of implementing the irrigation system in agricultural lands has not caused these farms to have lower physical and economic productivity than surface irrigation farms, but instead the cost of implementing the irrigation system during ten years of using this system has led to better management use of irrigation water, increase the physical and economic productivity of irrigation water. This management is mainly implemented by irrigation and drainage companies by shortening the irrigation period and increasing irrigation times. Prevents grain filling and by adjusting the irrigation hour at each irrigation time by moving the sprinklers by irrigation workers, prevents water wastage and deep percolation of water from the root zone and compared to surface irrigation from water losses prevents the end of irrigation furrows. This management, along with reducing labor costs while keeping the canola crop, has reduced costs and increased the physical and economic productivity of irrigation water.

Many countries around the world are currently facing a major challenge of producing food from limited water resources. Water scarcity, coupled with the misuse of valuable water resources, does not meet the current growing demand for food by the population. Therefore, in the current situation and in order to alleviate poverty and hunger, the most important challenge for the agricultural sector is the strategy of using water more efficiently. In the long run, increasing water productivity to expand irrigated lands and increasing rainfall productivity to produce more food is a key factor in combating hunger and reducing poverty (Kiani and Sedaghat Doost, 2016). Water scarcity in Iran is also an undeniable climatic reality. The total volume of water resources by rainfall is 403 billion cubic meters in the country, of which a significant amount becomes unavailable in the form of evaporation. The volume of renewable water resources is about 100 billion cubic meters, which is a water consumptionin the agricultural sector of about 80% (Naseri et al., 2017). Moreover, the rapid increase in population along with the expansion of urbanization has increased water consumption; whaich has led to the consumption of about 69% of the country's total renewable water that is very high compared to other countries. Meanwhile, agriculture in Iran is in dire need of water. According to the studies, identifying the factors affecting water productivity is of great importance due to the existing conditions (water scarcity) and factor analysis can be used in this regard. Therefore, the present study was planned and conducted to investigate the factors acting water productivity by means of factor analysis.

The study area is located in the central latitude and longitude of Qazvin province between 48 degrees and 44 minutes to 50 degrees and 51 minutes in the east of Greenwich meridian and 35 degrees and 24 minutes to 36 degrees and 48 minutes in the north latitude relative to the equator. The total area under cultivation of crops and horticulture in Qazvin province is 334.7 thousand hectares on average, of which about 2323.4 thousand hectares (equivalent to 66.5%) are irrigated and about 1112.3 thousand hectares are (equivalent to 33.5%) rainfed (Anonymous 2019a, Anonymous 2019b). In this study, three methods including documentary and library study, searching through electronic sources, and field study have been used to collect the required information. The data collection tool was a questionnaire that consists of two parts: personal profile and variables affecting water productivity. The sampling method in this study was completely random. In this study 317 questionnaires were completed. The percentage of variance and eigenvalues of different factors were used to determine the maximum effect of factors in explaining the variance of the data.

Examining the age and education level of farmers showed that farmers are more in the age range of 40- 61 years and older and their education is mostly Middle School Diploma and lower. The first factor among the nine extraction factors, with a specific value of 4.55, explained 14.67% of the variance of the whole analyzed set. Then the second factor, with a specific value of 3.84, was able to explained 12.39% of the variance of the set. The third factor, with a specific value of 3.22, explained 10.39% of the variance of the whole set under analysis. The fourth, fifth, sixth, seventh, eighth, and ninth factors, with special values ​​of 2.56, 1.65, 1.60, 1.50, 1.40, and 1.16, explained about 8.25, 31. 5, 16.5, 4.84, 4.50, and 3.74 the total variances, respectively. Overall, the nine extracted factors were able to explain about 69.25% of the total variance, which indicates the appropriate variance explained by the extracted factors. Among the nine factors obtained in this study, the components of agricultural-managerial measures and technical-infrastructure measures were recognized as the most important ones. The former factor explained 14.67% of the variance of the whole set under analysis and the lattar factor was able to explain 12.39% of the variance of the set.

In this research, nine extracted factors were included in the order of "agricultural-managerial measures", "technical-infrastructural measures", "irrigation management", "extension factors", "fertilizer recommendations", "field time management", "mechanization", "farmer's education level" and "principled control of pests and weeds". The results of this study can be used by managers and researchers in planning to improve water productivity in the agricultural sector.

In arid and semi-arid regions, meeting the environmental need of rivers and natural lakes is drastically diminished due to the climate changes, drought, and mismanagement of the water supply and distribution in agricultural activities. The closed basins, like Lake Urmia, are more sensitive to reducing the environmental need, climate change and drought. In Lake Urmia basin with arid and semi-arid climate, water shortage and high demand for water consumption in agricultural activities have caused to increase the free accessibility of the extraction of the surface water and groundwater resources. Therefore, in arid and semi-arid regions, it is necessary to implement an integrated dynamic system (IDS) for water consumption management in all sectors of water consumption, including drinking, industrial, and agriculture needs to stabilize the groundwater resources; hence, the optimal use of water resources to increase production capacity per unit of water consumption is a fundamental solution to meet the nutritional needs of humans and improve the economic conditions of operators. The multiplication of greenhouse agricultural products compared to the open-field cultivation for the same water consumption is one of the crucial solutions in the optimal use of water resources.

The Ajichay basin with an area of 12600 km2 is one of the greatest sub-basins of Lake Urmia. The average annual temperature of this basin is 11.3oC and the average annual precipitation is 320 mm. The soil and water assessment tool (SWAT) model was used to evaluate the impacts of the implementation of development scenarios of greenhouse towns. The Soil and Water Assessment Tool (SWAT) is considered as a comprehensive hydrological model to evaluate the impacts of different factors such as climate changes, land use variations, changes in irrigation methods, agricultural management, and greenhouse development on runoff volume and groundwater level fluctuations. In this study, the SWAT model has been calibrated and verified using a 30 m digital elevation model (DEM), a soil map with 217 homogeneous zones, 5 land use maps from 1987 to 2016, data gathered from 10 hydrometric stations and more than 50 meteorological stations, hydrological studies and field measurements. In the present study, two scenarios were adopted according to the current policies of greenhouse towns development in Iran and an ideal scenario (third scenario) was also considered for the development of greenhouse towns. The first scenario for the development of greenhouse settlements was adjusted using new water resources with the aim of increasing the production of agricultural products in the region. The second scenario is based on the removal of part of the arable lands of each aquifer and the use of harvested water from the removed lands in the development of greenhouse settlements. The third scenario was based on the average production statistics in open and closed environment in Ajichay catchment, in order to maintain the current production per hectare. In modelling the Ajichay basin, the time periods of 1987-1991, 1992-2009, and 2010-2016 have been assigned to the model adaptation to the basin conditions, calibration, and verification, respectively. The statistical criteria comprising correlation coefficient (CC), Nash-Sutcliffe efficiency (NSE), and root mean square error (RMSE) have been utilized to evaluate model performance for stream flow simulation in hydrometric stations.

Statistical criteria indicated the high accuracy of simulation for all ten hydrometric stations. At Akhula station (watershed outlet), the statistics including correlation coefficient (R), Nash-Sutcliffe efficiency (NSE), and root mean square error (RMSE) were 0.92, 0.83 and 6.48 m3 s-1, respectively, during calibration, and 0.86, 0.73 and 3.23 m3 s-1, respectively, during verification periods. Development of 1875 hectares of greenhouse towns in the Ajichay watershed caused an average depletion of 11.68 m and 4.41 m within the first and second scenarios, respectively; in contrast, for the third scenario, an increase of 3.86 m for the average groundwater level of the aquifers of the Ajichay watershed was acquired rather than the initial condition. At the end of the simulation period of the third scenario, the flow volume increase of 28.5 MCM y-1 was observed at the Akhula hydrometric station. The results revealed that the development of greenhouse towns using new water resources can increase agricultural crop production and also intensify the downward trend in groundwater levels. The second scenario has caused a negative balance in the aquifers due to the eliminating the water withdrawal under the traditional irrigation system from the hydrological cycle. Only in the third scenario, the removal of nearly ten hectares of farmlands for the development of one hectare of greenhouse has caused the aquifers of Ajichay basin to have an increasing trend of groundwater level. The results of the third scenario revealed that 24% of the total reduced volume of groundwater abstraction, was discharged into Lake Urmia through rivers, and 38% was related to the water withdrawal of the traditional irrigation, and the other part was spent on increasing the water abstraction from groundwater and rivers for the agricultural purposes.

The results of the implementation of the scenarios to develop greenhouse towns revealed that the type of policies and how to implement the development of greenhouse towns can enhance agricultural production capacity as well as decrease/increase the flow of rivers in the Ajichay basin. The adverse effect on the groundwater resources occurs when the administrative institutions' approach is focused only on the increasing production capacity. Furthermore, when the ratio of replacing traditional farmlands with greenhouse towns is not commensurate with the corresponding irrigation efficiencies, it applies more stress to the groundwater resources to meet the evapotranspiration need of the greenhouse plants. The positive effect on aquifers and increased river flow occurs when the actual evapotranspiration of the plants cultivated in greenhouse towns is less than the eliminated traditional farmland.

One of the main priorities of the agriculture section is the proper use of water and soil resources. Limitation of the cultivated lands, the increasing population and human need for natural resources have led to the use of soil so that in addition to achieving maximum crop, this source is protected for the future. In this regard, it seems that land suitability studies are necessary. There are several methods for assessing land suitability, among which Sys et al. (1991) method is most widely used due to the use of simple and classic models. In many land suitability studies, the uncorrected land index has been used. This has led to many differences in the results of different approaches of land suitability evaluation. The present study was conducted for assessing of accuracy and validity of the corrected indices of land suitability based on the determined relations by Sys et al. (1991) and Bagheri Bodaghabadi (2021).

In this research, field studies were conducted, then several profiles were drilled and described in Khanouk-Zarand, Bam and Rabor districts in Kerman province. Land suitability classes were determined by the four methods including 1-simple limitation, 2- number and intensity of limitations, 3- Khidir.

Daily precipitation, which is completely stochastic, is one of the basic components of the water cycle and has an important role in the management of surface and ground water resources in terms of quantity and quality. Indispensable element of drought analysis and flood control research is precipitation. The efficient management of surface water resources directly depends on precipitation. The lack of long-term and reliable data has made it difficult to determine precipitation behavior. In this study, we tried to determine the behavior and pattern of precipitation through human-data interaction called visual data mining approach. One of the new approaches that focuses on the use of visualization and graphics in the analysis of complexities in data is visual data mining. Visual data mining can be thought of as a combination of two disciplines, visualization and data mining. Visual data mining is also closely related to computer graphics, multimedia systems, human-computer interaction, pattern recognition, and high-performance computing. The aim of this study is to analyze Tabriz daily precipitation data and discover the patterns in this data with the help of visual data mining approaches. Discovering these patterns and identifying rainfall behavior will help to manage floods on the one hand and droughts on the other.

In this study, daily precipitation and temperature data of Tabriz Synoptic Station for the last seventy one years (1951-2021) were used to determine precipitation patterns. Tabriz has a generally cold climate as the center of the eastern Azerbaijan province and is surrounded by mountains. Recently, with the increase in data and software, data mining techniques have also started to attract attention. Data alone cannot mean anything. However, graphs consisting of data can give very meaningful information and messages. Visual data mining approach is an effort to bring data to life with different graphics. In this research, various softwares such as R, ArcGIS and Tableau were used for visualization. In addition, ExcelStat was used to check the accuracy of the data and for statistical tests. R statistical language was used to create the data mining structure and to display the data graphically. Then, different diagrams were drawn using the Tableau program. Finally, the drawn diagrams were evaluated and the final graphics were selected. ArcGIS software was used for spatial analysis and map drawing. Also, multiple linear regression method was used to predict precipitation amount and probability of occurrence.

According to the temperature histogram, the long-term average annual temperature in Tabriz varies between 12 and 13 degrees Celsius. Also, according to the precipitation histogram, precipitation over 5 mm in Tabriz varies between 10 and 20 days per year on average. The results obtained showed that there has been a change in precipitation patterns in the last 5 years (2017-2021). Although annual precipitation during these five years is above the 71-year average, it is still below the golden precipitation period (1961 to 1970). The results showed that the intensity of spring rains decreased significantly in Tabriz during the period 2006-2021. However, from 1971 to 1980 and from 2001 to 2010, it was observed that the spring rains were more in terms of both precipitation values and precipitation intensity. However, in the following periods from 2011 to 2021, both precipitation intensity and precipitation values decreased. The results showed that most of the spring precipitation in 1981 was 276.3 mm, making up 73.26% of the total precipitation for that year. According to the findings, precipitation has started to decrease in the spring season in recent periods. Decreased dry grain yield in the Azerbaijan region may be affected by decreased spring precipitation. As a result of this decrease, it is expected that the agricultural economy in the study area will be negatively affected.

In this study, as a first, daily precipitation in Tabriz was investigated with visualized data mining techniques. Thus, interesting findings were obtained with the help of different graphics. The results showed an increase in precipitation in the last 5-6 years. It has also been proven that the temperature behavior during this period shows an increase in average temperature, a confirmation of the increase in global temperature. Although the results of this research showed that visualized data mining is successful in precipitation analysis, it is recommended to conduct more comprehensive studies in this field in the future.

Traditionally, most researches on artificial wetlands focuses only on two phases, i.e., water and soil, ignoring or underestimating the importance of the microbial aggregates between them, the third phase in artificial wetlands. Filamentous algae grow substantially by attaching themselves to the soil/sediment surface and form aggregates with bacteria, fungi, and other micro- and meso-organisms (e.g., protozoa and metazoa), known as periphytic biofilms. Actually, periphytic biofilms are ubiquitous in wetlands (including paddy fields) and play a major role in regulating nutrient cycling in these ecosystems. However, their effects on rice plant growth indices have been rarely reported. Therefore, the aim of this study was to investigate the effect of natural periphyton and enriched periphyton with plant growth-promoting microorganisms on germination and rice growth indices.

To achieve the objectives of this study, first three periphyton samples were collected from paddy fields of Guilan province and grown in BG11 medium in the laboratory. Then, the superior bacteria and fungi that stimulated plant growth were isolated from the periphyton mass and the periphyton samples were enriched with these microorganisms. The greenhouse experiment was conducted in 1399 in the research greenhouse of the Department of Soil Science and Engineering, University of Tehran. For this purpose, 2.5 kg pots with a length of 25 cm and a diameter of 15 cm were selected for greenhouse experiments. Twenty rice seeds (Oryza Sativa: cultivar Hashemi) were placed directly in pots in three replications for each treatment. About 100 mL of natural periphyton suspension grown in BG11 medium (equivalent to 2 g/kg dry weight) and periphyton enriched with superior bacteria and fungi and a mixture of bacteria + fungi was added to the pots. Experimental treatments included WP treatment:  without periphyton, PN1 epipelon 13, PN2 epiphyton 8 and PN3 epipelon 6, PN1 + Bacillus cereus, PN2 + Talaromyces stipitatus and PN3 +Acinetobacter calcoaceticus + Talaromyces minioluteus. Also, phosphorus fertilizer treatment at four levels (F0: without phosphorus fertilizer, F1: supply of 50% of phosphorus fertilizer from mono calcium phosphate source, F2: supply of 100% of mono calcium phosphate and F3: supply of 100% of rock phosphate source) was added to the pots. The treatments were grown in three replications in a greenhouse with a temperature between 25–35 °C for 30 days in 80 percent humidity.

The results showed that the presence of natural and enriched periphyton in the soil increased the germination index of rice seeds compared to the control by about 1.4 and 1.9 times, respectively. The rice seedlings decreased by about 10 percent with the presence of natural periphyton, but this negative effect was lowered by enrichment of plant growth promoting microorganisms. Measurement of rice seedling height index showed that the highest measured height was related to the treatment of periphyton enriched with Bacillus cereus (PSB) at F2 level of 39 cm. In general, in natural periphyton treatments, about 15 percent of the height of rice shoots was lower than the control treatment and periphyton treatments enriched with superior microorganisms. The maximum measured root length was related to the treatment of recombinant periphyton with Bacillus cereu (PSB) with 16.95 cm. The lowest root length was measured in natural periphyton treatment (PN3) with 11.5 cm. The highest shoot to root ratio was related to periphyton treatment enriched with Bacillus cereus at F2 and F3 fertilizer levels with 0.7 and 0.68, respectively, with a statistically significant difference at level 95 percentage (p˂ 0.05) compared to other treatments. The maximum weight of rice biomass in periphyton enriched with Bacillus cereus (PSB) treatment, which was the enriched with plant growth promoting bacterium, was measured at F2 and F3 fertilizer levels with 8.7 and 8.3 g, respectively. In general, measurement of rice seedling height, root length, biomass weight and phosphorus in shoots showed that treatment of enriched periphyton with Bacillus cereus at different levels of phosphorus fertilizer had a positive effect and led to an increase of 3.5, 9.4, 6.1, and 35.8 percent compared to the control treatment, respectively.

Finally, it can be concluded that periphyton enriched with superior plant growth microorganisms can be used as a multi-functional biofertilizer in paddy fields, it increases plant growth and efficiency of fertilizer, and it can also control weeds in paddy fields.

Pore water pressure, stress and settlement are the most important geotechnical parameters that must be constantly monitored during the construction of earth dams. Since measuring dam settlement directly at the time of dam construction requires cost and time, the development of artificial intelligence methods can be very effective. Most studies have been done in the field of modeling earth dams during construction with a numerical model; therefore the need for artificial intelligence modeling in this field seems to be necessary. Artificial intelligence models, including neural networks, are used for study and modeling many engineering sciences. Also, with the development of meta-heuristic algorithms, their combination with neural networks has become very wide-spreading due to more accurate results. So, The purpose of this study is to determine the most effective features in modeling settlement in the body of earthen dams at the time of construction as a case study (Kaboud-val dam) using the hybrid algorithm Dragonfly - artificial neural network in different points of the body of earthen dam at the time of construction. Therefore, in this research, new inputs in artificial intelligence modeling have been proposed for this purpose and their importance in different levels of installation has been investigated.

Kaboud-val Dam is located in Golestan province of Gorgan and around the city of Aliabad. This dam is homogeneous and has a filter and inclined drainage. In order to obtain the deformations of the body and the foundation of Kaboud-val dam, settlement plates have been installed in different sections of the body and its foundation during the construction. In this study, instrumental data related to the section of 19 Kaboud-val dam were used. Also, out of 17 pages, 4 pages named M1, M5, M9 and M13 (installed in the body and Kabudwal dam at levels 140, 152, 164 and 180 meter, respectively) have been used for modeling. By analyzing the data of section 19 pages, fill level (F), reservoir level (RL), dam construction time (T), fill rate (FR) and impounding rate (RV) for inlet and landing (P) on terms of (kp), was selected as the output of the hybrid model in the feature selection method. In this study, in order to select the best combination of input features in the artificial neural network, the dragonfly algorithm was used. Feature selection is a method of selecting a subset of related attributes (the best combination of them) that is relevant to a particular goal. The most important principle is to choose stable features and remove extra data. The combination of dragonfly algorithm with artificial neural network as DA-ANN is shown, Therefore, the dragonfly algorithm (DA) models a variety of different combinations of features with an artificial neural network and selects the best least error combination (RMSE) as the optimal artificial neural network model.

By performing a hybrid algorithm, sensitivity analysis and feature selection method, combining the four features on pages M1, M5,M9 and M13 with error values (RMSE) of 0.0023(kPa), 0.0024(kPa), 0.0026(kPa), respectively, and combining the three features on the M13 page with the value Error (RMSE) equal to 0.0035(kPa) was the best input combination. The three features of construction time, fill level and reservoir level as common features in all plates are the most effective features in modeling the settlement on selected plates. On plates mounted at higher levels, the modeling error increases, because during the test period and for plate M13 (with the highest mounting level), according to the statistical indices R^2, SI, NSE and NRMSE are equal to the values of 0.9998, 0.0062, 0.9998 and 0.0062 respectively, have poorer performance than other pages. The effect of reservoir level feature on the plates installed at higher levels due to the high sensitivity coefficient is more than other points and the fill level feature has the least effect on subsidence modeling.

The results are very important considering the cost of installing the measuring equipment and the significance of estimating the actual values in the future. The present study shows that the DA-ANN hybrid model is an important tool in predicting and selecting the best input combination for the intelligent model of the target variable of the settlement at the time of construction of earth dams. However, assessment of this model using the input data studied in different dams is necessary to ensure the application of these models in different conditions.

The analysis of transient flows in closed ducts has always been one of the most important and favorite topics of hydraulic engineers. On the other hand, with operation of water supply facilities during the time, water leakage may occur anywhere in the transmission pipeline system. Haghighi and Ramos (2012) performed leak detection in pipelines using inverse transient analysis and CFO optimization method. Mohammadi and Fathi-moghadam (2013) analyzed the fast transient flow in pipelines by the unsteady friction model. Akbari et al. (2021) investigated the detection of leaks in polyethylene transmission pipelines using pressure wave reflection of transient flow. Therefore, using laboratory modeling, fast unsteady flow in leaking pipelines was investigated, and then, a computer model was coded by Visual Basic programming language, with the ability to simulate transient flow in pipelines in presence of leakage. Then the parameters of temporal and spatial acceleration coefficients kut and kux and discharge coefficient of leak orifice cd were calculated.

In this research, a 47m long pipe that made of polyethylene with 10bar nominal pressure and diameter of 63mm was used in experiments. The transient flow was generated in it by very fast closure of the end valve. A computer numerical program was developed to simulate the hydraulic conditions in pipeline. The coded model analyzer motor analyzes the basic unsteady flow equations in pressurized ducts, and the inverse analyzer is an optimization algorithm using a defined goal function to find the best fit of the recorded pressure waves and those simulated with the least error. Also, the boundary conditions for simulating the leak in the pipeline were included in the numerical model.

The values of kut and kux coefficients related to the wave simulations was calculated. The values of kut for leakage and non-leakage state were approximately the same, and the coefficient of kux for leak state would be less than non-leakge state. In the case of leaks with different diameters, the coefficient of kut were generally the same as in the case of non-leakage. However, the values of kux coefficients for leakage with a diameter of 4 mm were greater than those for leakage with a diameter of 10 mm, and both of these values were less than non-leaking. The reason is that as the diameter of the leak increases, the damping rate of the pressure waves increases, therefore the value of the kux coefficient decreases.The change in the leak location had almost no effect on the values of kut and kux. The coefficient of kux in the presence of leak, either at a distance of 27 m or 39 m, were less than its values in non-leak state, and both values were also approximately equal to each other. Leak orifice with a larger diameter (10 mm) had a higher discharge coefficient than leak with a smaller diameter (4 mm), due to their lower resistance and lower energy dissipation against the increase in pressure produce in the system by the transient pressure wave. The performance of the two-coefficient unsteady friction model was evaluated by statistical indexes. Also, the numerically simulated waves and the laboratory samples was compared to each other. The two-coefficient unsteady friction model had a good ability to simulate a transient pressure wave in presence of a leak.

The values of kut for leak and no-leak state were almost constant and the values of kux for leak state was less than the kux for the no-leak state. Changes in leak location had almost no effect on the values of kut and kux. Selecting a steady or unsteady type of friction model to simulate the transient flow in the presence of leakage had almost no effect on the orifice discharge coefficient. Two coefficient unsteady friction model had a good ability to simulate the pressure wave of transient flow in the presence of leakage.

Generally, Iran has an arid and semi-arid climate with a high population. In recent years, the shortages of surface water and groundwater have become a main national challenge in Iran. The optimum operation of reservoirs is one of the most critical challenges in water resources management. In a situation where the drying crisis of the Urmia Lake is serious, comprehensive management of water resources in this basin, allocation of environmental water rights, and the optimal operation of dam reservoirs are the most principled methods of allocation to combat the drying crisis of this lake. The choice of management policies and optimization method depends on the system specification, availability of data, type of objective function, constraints, and variables. The Eleviyan dam is located on the Sufi-Chay River and is one of the main existing dams in the Urmia Lake basin. Therefore, in this research, the performance of the Teaching Learning Based Optimization algorithm (TLBO) is compared with Improved Harmony Search (IHS) and Particle Swarm Optimization (PSO) algorithms in order to optimize the Eleviyan reservoir operation, located across the Sufi-Chay River.

Considering the vital importance of environmental flow to prevent the death of Urmia Lake, the minimum environmental flow of the Sufi-Chay River was estimated by two hydrological methods Tennant (first scenario) and Flow Duration Curve analysis (second scenario). The Teaching Learning Based Optimization algorithm, Improved Harmony Search, and Particle Swarm Optimization algorithms were used for optimization. The optimization models were written in the form of two scenarios, taking into account the complete provision of the minimum environmental flow, the municipal demands, and industry, and minimizing the severity of agricultural shortages. In order to check the performance of the studied algorithms in the optimal exploitation of the reservoir, the performance indicators of the reservoir including reliability, vulnerability, and stability index of the reservoir were used.

The results in this study showed better performance of the TLBO algorithm method compared with both scenarios. In TLBO algorithm, the objective function values for both scenarios are calculated, respectively 2.43 and 7.54. While with Improved Harmony Search algorithm objective function values are calculated respectively 2.81 and 8, and with the Particle Swarm Optimization algorithm objective function values are calculated 3.34 and 8.45 with both Tenant and Flow Duration Curve (FDC) methods. Based on the obtained results, the TLBO algorithm has been able to supply the downstream demand of the dam. So, for the first scenario, it will provide 81.40% and for the second scenario, 62.55% of the demands. The release of observation has been able to provide about 70% of the total demand and according to the situation of Urmia Lake, the current policy of the dam is not suitable and should be revised. Taking place according to the second scenario (flow duration curve method), in case of reducing about 8% of agricultural expenses and allocating it to the environmental flow, the problem of water rights of Urmia Lake from the Sufi-Chay River will also be solved to some extent.

One of the main causes of drying of the Urmia Lake is the reduction of inflow to the Lake due to the development of agricultural lands, allocation of irregular water resources to the agricultural sector regardless of the environmental right of water, and irregular yields of surface and groundwater resources. Regarding the scenarios, it seems that if the downstream agricultural demand is reduced by about 8% in methods such as lessened irrigation of gardens, changes to crop cultivation, and revising the curve of dams around the Lake, it would aid the recovery of Urmia Lake and play an important role in adequately supplying the downstream needs. The results show that managing the Eleviyan dam is required to reduce the agricultural demand through the methods such as reducing the crop area and changing the cropping patterns such as low consumption plant cultivation or changing the type of irrigation method in order to optimize the operation of water resources in the basin. Otherwise, water stress will increase in the basin. The results in this study showed a higher performance of the Teaching algorithm compared with the other methods employed in the optimum release from the Eleviyan reservoir with considering environmental flow.

Although a dam’s structure has an important role in suppressing floods and providing water for activities such as agriculture, human consumption, industrial use, electricity generation and pisciculture, its break has an immense damage and loss of life when it occurs. In order to reduce the damaging effects of the dam break on the downstream places, it is necessary to provide the flood hazard map.There are few studies on applying HEC-RAS two-dimensional model in the field of dam break analysis. For example, Hassanzadeh et al. (2019b) computed the output breach hydrograph of the Alavian dam by the BREACH model under the overtopping scenario. Also, the breach hydrograph was routed through the downstream of the river by using HEC-RAS two-dimensional model. Finally, the ArcGIS software was utilized to prepare the flood mapping. The results of their study illustrated that the Alavian dam is breached with the time of failure of 46 min and the peak discharge of about 66000 m3 s-1. Furthermore, according to the flood hazard map, most of the downstream inundation zones due to Alavian failure dam have been considered as the high hazard area.

Two-dimensional (2D) numerical simulation proved to be an important tool for understanding flood events. The HEC-RAS model is one of the most popular hydraulic models. In 2016 a new version of HEC-RAS (HEC-RAS-v5) was released including 2D capabilities. HEC-RAS software supports special capability to correct waterway and computing necessary ground-related operations. The capabilities of HEC-RAS are: 1) Developing a 2D unsteady flow model; 2) Modeling the 2D shallow water equations or the 2D diffusion wave equations; 3) Solving implicit finite volume algorithm; 4) Developing a terrain model and geospatial layers. The HEC-RAS software also enjoys connect-ability to ArcGIS software via an adaptor called HEC-GeoRAS to perform pre- and post-processing in geographical information system (GIS).The threat to personal safety and to gross structural damage caused by floods depends largely upon the speed and depth of floodwaters. The greater these factors become, the greater the danger to people and property. The depth-velocity hazard classification diagram considered in this study is based on the Garcia and Lopez (2005), in which hazard categories are broken down into high, medium and low hazard for each hydraulic category. These can be defined as: 1) High hazard: possible danger to personal safety; evacuation by trucks difficult; able-bodied adults would have difficulty in wading to safety, potential significant structural damage to buildings; 2) Low hazard: should it be necessary, truck can evacuate people and their possessions; able-bodied adults would have little difficulty in wading to safety; 3) Medium hazard: In the transition zone highlight by the median color, the degree of hazard is dependent on site conditions and the nature of the proposed development.

In this research, the dam break problem has been presented from the viewpoints of importance, mechanism, spatial and temporal analyses as well as governing mathematical equations. For this purpose, the output hydrographs of the Bafrajard dam site have been computed by breach model under a fictitious dam break scenario (overtopping) as the first step. In the next step, the output hydrographs have been routed through the downstream river by using HEC-RAS model. Then water levels and wave front arrival times have been computed at all cross sections. Finally, the obtained results have been imposed to Geographic Information Systems in order to obtain the presentation of the results to develop floodplain maps.

The results of the present study demonstrated that the Bafrajard dam is breached with the time of failure of 80 min after the upstream erosion and the peak discharge of about 4000 m3 s-1. Also, Khanghah-e Bafrajard village, Aznav tourist area and Khalkhal city are affected by floods with inundation percentages of about 35, 10 and 20%, respectively. Furthermore, the wave front arrival time at the mentioned areas is about 10, 30 and 40 minutes, respectively, so there will be very short time available for various emergency actions.

Scour around bridge piers is an important challenging issue in hydraulic engineering and one of the primary causes of bridge failures (Singh et al., 2022). To date, a large number of empirical equations have been proposed by researches for estimating local scour depth at bridge piers. However, their applicability and results are very different from each other, in such a way, calculated local scour depths using these equations, for a 1 m diameter pier in fine and coarse sand beds, could vary almost from 0.2 m to 3 m, and 0.25 m to 5 m, respectively (Sheppard et al. 2014). In these conditions, evaluation of the performance and accuracy of pier scour empirical equations is very important. In fact, it is necessary to assess the effect of errors in measurements of input properties on estimation of local scour at piers in order to specify the equations that are mostly affected by propagation of input data errors. Sensitivity analysis of these equations and determining the effect of data uncertainties on them could result in precise computation of pier scour that leads in safe designs and reduction in further damages. Variables that are used in local scour equations at bridge piers, are flow and sediment properties, such as flow velocity and depth, and sediment grain sizes. Computation of local scour depth at bridge piers using empirical equations is based on the measurements of these properties. Errors in these measurements, that are common in engineering applications, affect the accuracy of estimations of pier scour. In the present research, propagation of input data errors and its effect on the pier scour estimation analyzed by Monte Carlo numerical method, that determines the sensitivity level, and relative strengths and weaknesses of the equations. In this research, sensitivity analysis carried out for four empirical equations of local scour depth around cylindrical piers in non-cohesive sediment beds and in both clear-water and live-bed scour conditions. Evaluated equations are: Froehlich (1991), Gao et al. (1993), S/M (2014), and HEC-18 (2016) equations. Monte Carlo method is based on generation of random numbers. The goal of the Monte Carlo method is to simulate an existing model (in the present study, an empirical equation to estimate the local scour at bridge piers) by randomly sampling from the input physical properties distribution using a large number of samples and finally predicting the output response (Pinto et al., 2006). The physical properties selected for the error analysis include the depth-averaged flow velocity (v ̅_1), flow depth (y_1), and sediment median grain diameter (d_50). Bridge pier width (w) is a property in the equations that is supposed to be known precisely, therefore it is excluded from the analysis. In this research, pier’s reference width is supposed to be constant in the value of 1 m. The densities of water (ρ) and sediment (ρ_s) are variables that could be the error source in the computation of pier scour. However, they are both excluded from sensitivity analysis of pier scour equations, because their values are usually known and supposed to be constant. In order to analyze the results, four output quantities are defined: 1- local scour depth around bridge pier that is computed based on the mean values of physical properties (z_mp=z(v ̅_1,y ̅_1,d ̅_50)), 2- pier scour depths in each Monte Carlo simulation (z_i=z(v_1i,y_1i,d_50i );i=1,…,N), the number of computations (N) set to 10 000 in all simulations, 3- Mean pier scour depth (z_m=z ̅_i), and 4- standard deviation of pier scour depths (σ_z). The error analysis is based on the ratio between fourth and first quantities, that is defined as r ratio (r=σ_z/z_mp). In evaluating velocity errors on local scour depth at piers, in all velocities, except in v ̅_1=0.5 m/s acceptable values of r (r≤0.3) obtained for all equations. In relative comparison of the equations, two equations, Gao et al. and HEC-18 show most and least sensitivity to the velocity variations, respectively. For flow depth (y_1) variations, small values of r obtained for all equations. In all cases, values of r were below 0.1. comparison of equations reveals that HEC-18 and S/M equations are the most and least sensitive to the flow depth errors, respectively. In analysis of sediment median grain size errors on pier scour depth, acceptable values of r observed for all the cases simulated. In all simulations, values of r were smaller than 0.07, except for Gao et al. equation, with d_50 = 0.2 mm and 0.5 mm and with α = 0.4, that values of r reached to 1.3 and 0.17, respectively.Among four evaluated equations, Gao et al. and HEC-18 equations show most and least sensitivity to the sediment grain size variation, respectively. Therefore, Gao et al. equation is more sensitive to physical properties than the other equations analyzed. Results also show that among three input variables, errors in the measurements of flow depth and velocity have minimum and maximum effect on the estimation of pier scour depth, respectively.

Stepped spillways are convenient and economical options for high dams compared to other types of spillways because of their special abilities such as construction procedure compatibility with the Roller Compacted Concrete Dams (RCC Dam) technology, the ability of self-aeration of flow and reduction the stilling basin dimensions at the downstream dam toe due to significant energy dissipation. Depending on the discharge rate, step height and slope, three flow regimes can be identified on stepped spillways: nappe, transition, and skimming flow. Nappe flow occurs for relatively low discharge rates and lower slopes. Transition flow with a range of intermediate flow rates has a chaotic flow motion with intense splashing. Skimming flow occurs for relatively higher discharge rates and steeper slopes, is characterized by a flow over the pseudo-bottom formed by small vortices between steps. On a stepped spillway, the steps act as macro roughness elements, contributing to enhanced energy dissipation and significant aeration. In a skimming flow, the upstream flow motion is nonaerated, and the free surface appears smooth and glossy up to the inception point of free-surface aeration. In this developing flow region, a turbulent boundary layer grows until the outer edge of the boundary layer interacts with the free surface and air entrainment takes place. In recent decades, much research has been done on various flow regimes over the stepped spillway, the way they dissipate energy and the impact of the geometry of the steps on flow structure. In this research, hydraulic performance of skimming flow over Zhaveh stepped spillway has been studied and qualitative and quantitative comparison of flow between stepped and chute spillways has been presented.

Methodology:

 A 2D numerical models of spillway has prepared using FLUENT 6.3.26 software, k-e RNG turbulence model and Mixture multiphase flow method to simulate and calculate the hydraulic characteristics of the energy dissipation of spillways. The softwares to create the spillways geometry and mesh were SOLIDWORKS and GAMBIT respectively. The meshes in the tank section were quadrilateral and due to irregular geometry and the presence of stairs, meshes in the spillway and chute section were tri / pave. The boundary conditions were velocity inlet for inlet flow, free pressure inlet for free surface flow, outlet pressure for outflow and wall for floor and stairs. The numerical model has been calibrated applying experimental data extracted from the physical model of the Zhaveh spillway. It is stepped spillway with a height of 85 m and located on the Zaveh river at the junction of the Gavrood and Gheshlagh rivers at 35 km south of Sanandaj city. The spillway with a crest length of 55 m and a side slope of 1.2V:1H (50.19 degrees) located on the body of the Zhaveh dam.

Findings:

 The results indicated in addition to agreement between laboratory and numerical data, having steps alongside the chute spillway can reduce significantly the length of the boundary layer which is developed from the spillway crest and encountered with the flow surface from where the flow air entrainment is initiated. So the inception point related to air entrainment is located further upstream. Analysing the flow pattern indicated that due to aeration after the inception point, the flow depth and velocity in stepped spillway increases and decreases respectively compared to a chute spillway. Flow aeration causes the cavitation index to become much higher than the critical value (0.2) in the entire stepped spillway thus the risk of cavitation occurrence and the relevant damages are reduced considerably. While it was observed that the possibility of cavitation occurrence was high on the chute spillway (without steps) starting from 56 m downstream of the spillway crest. As a result, cavitation erosion was more likely expected on the chute spillway surface. Also for design discharge, the flow energy was effectively dissipated alongside the stepped spillway in comparison to chute spillway with a discrepancy of 46%.

Conclusion:

 The application of the stepped spillway would be more appropriate and economical than the chute spillway due to the various advantages mentioned above and also there is no risk of cavitation on the Zaveh stepped spillway, while in the end of the chute spillway Corresponding to it, we may encounter cavitation erosion.