Iranian Water Research Journal

Abstract Extended Abstract

Introduction:

Accurate measurement of the rainfall, as one of the essential meteorological variables in hydrological and agricultural studies, has a significant impact on the optimal management of water resources, cultivation of agricultural products, urban management, and identification and classification of areas in terms of the occurrence of floods risk or the ability to extract water. The inappropriate distribution of rainfall measurement stations in different regions has caused researchers to seek to create models that can estimate the amount of rainfall in areas that lack rain gauge stations or have Insufficient of them.

Methods:

In the current research, the data from Era5, the newest product of the ECMWF, has been used. Era5 data is the fifth generation of ECMWF reanalysis data for climate over the past several decades. These data provide hourly estimates of important atmospheric variables at the surface of the earth and other pressure levels. Era5 data is updated with a delay of 5 days and is available in a gridded form with an accuracy of 0.25 degrees (equivalent to 31 km). In the present study, hourly data in NetCDF format were used during the period from 1997 to 2018. The accuracy of Era5 in the Middle East and Iran has yet to be investigated much. In order to evaluate the accuracy of Era5 model data, the data of 51 rain gauge stations of Iran Water Resources Management Company in Razavi Khorasan province from 1997 to 2017 were used were used. The mentioned stations have a suitable distribution and length of statistical period compared to other types of stations. To evaluate the data of Era5 model, first using Python programming and the nearest neighbor method, NetCDF data was processed and rainfall values for each station were extracted. Then the hourly data were converted to daily. The modeled values compared to the observed values were evaluated using two groups of quantitative and qualitative indicators. The first group of indicators that were used for quantitative evaluation of observed and modeled rainfall values include root mean square error (RMSE), coefficient of explanation (R2) and Nash‐Sutcliffe Efficiency (NSE). The second group of indicators was used to evaluate the quality of Era5 model outputs. Using these indicators, the occurrence or non-occurrence of precipitation (regardless of the amount of recorded precipitation) was investigated in both data groups. The indicators of the second group include probability of detection (POD), false alarm ratio (FAR) and critical success index (CSI). In this group of indicators, the occurrence or non-occurrence of recorded precipitation is recorded as yes or no by observational data and modeling. Using these indicators, it is possible to determine the occurrence or non-occurrence of precipitation by the model.

Results:

According to the quality indicators of Era5 rainfall data on a daily scale, the results showed that the said data have a high ability to identify the days that rainfall occurred at the station. It is worth noting that qualitative indicators can only be calculated and evaluated for the daily scale. The results of the investigations show that the Era5 model recorded the maximum rainfall values on a daily scale with a relatively large difference lower than the observed values. The results of the statistical evaluation of the monthly rainfall of the stations in comparison with the estimated values of the model show that unlike the low coefficient of explanation of the observed and modeled data on a daily scale, the coefficient of explanation has increased significantly on a monthly scale so that the range Its fluctuation ranges from 0.45 in Ferizi station to 0.86 in Sarakhs station. As the time scale increases, the accuracy of Era5 model estimates also increases. The results show that the dynamic and numerical methods used in the Era5 model have the ability to provide estimates that are close to reality with the least error and have the ability to improve in providing more optimal results in other areas. These results show that Era5 model estimates have performed best on monthly and seasonal scales in regions with a warmer climate and less rainfall in Razavi Khorasan province. These results show that Era5 model estimates performed best in monthly and seasonal scales in areas with warmer climate and less rainfall in Razavi Khorasan Province. Therefore, if the skew error is fixed, the data of this model can be used as input data to agricultural and hydrological models.

Abstract Drought is a natural phenomenon that occurs as a result of a decrease in the amount of precipitation in a period of time, compared to the normal or expected amount in the same period of time. Irregularity of meteorological variables, including the precipitation with a long periodicity, is affected by the phenomena that occur all over the earth with different periodicity and are known as meteorological signals. Teleconnections are a category of meteorological signals. Teleconnection refers to two regions on the surface of the earth that have a high correlation with each other in terms of climate. In addition, some low-frequency events (with long periodicity) in tropical regions also affect atmospheric patterns in higher latitudes. Since the amount of precipitation has a direct effect on recharging the aquifers, the prolongation of the drought period due to teleconnection patterns can also affect the groundwater level. Investigating the effects of the teleconnection patterns and predicting them, especially during drought periods, will be a great help for more accurate planning and management of the watershed. Since teleconnection patterns are in the category of large-scale phenomena, it is expected that the areas affected by them will be very vast. In most of the conducted studies, the relationship between drought indices and these phenomena has been done at station points. Considering the effect of local factors on the phenomenon of precipitation, point analysis can increase the uncertainty in the results. In this study, the regional average of precipitation in Chaharmahal and Bakhtiari provinces was used to calculate the drought index and to investigate its relationship with the groundwater level. Also, in order to study the role of teleconnection phenomena in creating meteorological and hydrological (groundwater) droughts in Faradonbeh and Sefiddasht plains, the relationship between the indicators of several well-known teleconnection patterns and meteorological and hydrological (groundwater) droughts has been investigated.

Methods:

In order to study the meteorological drought, the monthly precipitation data of the synoptic stations of Chaharmahal and Bakhtiari province from 2000 to 2020 were used. Also, the water level measured at 19 observation wells were used to investigate the groundwater drought of the Faradonbeh and Sefiddasht plains. The Standardized Precipitation Index (SPI) and the Groundwater Resource Index (GRI) were applied to monitor the meteorological and groundwater droughts of the Faradonbeh and Sefiddasht plains, respectively. Since the stations in the study area do not have the same distribution and each station has a different effect area, the average precipitation of the Chaharmahal and Bakhtiari province was calculated by weighted average method (based on area and distance) and the regional monthly precipitation time series was used to calculate the SPI index. Also, the values of teleconnection indicators including Madden-Julian Oscillation (MJO), El Nino-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) for the period of 1991-2021 were downloaded from the website of The National Center for Atmospheric Research and the National Center for Environmental Prediction (NCEP/NCAR). Since teleconnection phenomena have two positive and negative phases, to investigate the relationship between meteorological and groundwater drought indices with these phenomena, the correlation between SPI and GRI with teleconnection indicators has been done in several cases: Simultaneous correlation of data (correlation between all data), correlation in positive and negative phases of each teleconnection pattern (only positive phases or negative phase of teleconnection indicators were considered), calculation of correlation in each season (based on the solar calendar) separately, removing 5 dry months of the year (June to October) and calculating the correlation with a delay of one month.

Results:

The results showed that the NAO and IOD indices have the highest correlation with precipitation and SPI index, and have had the greatest impact on precipitation and drought in the study area. Also, the IOD and ENSO indices have a negative and inverse correlation with the GRI index. In general, it can be concluded that the difference in the response time of meteorological and groundwater droughts has a direct role in the extent of its influence from teleconnection events. So that the NAO phenomenon, which has a shorter periodicity than El Nino and IOD, is more significantly related to meteorological drought, which has a shorter response time, and hydrological drought, which has a longer response time, is more affected by El Nino teleconnection, which has a longer periodicity. The MJO phenomenon, which has the shortest periodicity among the studied teleconnection phenomena, had no significant relationship with the droughts of these plains.

Abstract A lack of adaptive capacities for climate change prevents poor farmers from diversifying agricultural production. Climate change adaptation strategies can reduce the production risk relating to unforeseen climatic shocks and increase farmers’ food, income, and livelihood security. This paper investigates date palm farmers’ adaptive capacities to adapt climate change strategies to reduce the date production risk. The study collected 300 farm-level micro-data of date palm farmers with the direct cooperation. The survey was conducted during periods between July and September of 2022. Date palm farmers’ adaptive capacities were estimated quantitatively by categorizing the farmers as high, moderate, and low-level adapters to climate change adaptation strategies. In this study, a Cobb–Douglas production function was used to measure the effects of farmers’ adaptive capacities on date production. The obtained results show that farmers are moderately adaptive in terms of adaptation strategies on climate change and the degree of adaptation capacities. Agronomic practices such as the quantity of fertilizer used, the amount of labor, the farm’s size, and extension contacts have a substantial impact on date production. This study recommends that a farmer more significantly adjusts to adaptation strategies on climate change to reduce date production. These strategies will help farmers to reduce the risk and produce higher quality date fruit. Consequently, date palm farmers should facilitate better extension services and change the present agronomic practice to attain a higher adaptation status. It can be very clearly seen that low adaptability results in lower date yields

Abstract Introduction:

As it has been for several years, drought conditions in various regions of Iran, including the central part of Marvdasht city in Fars province, have been very noticeable and have led to a severe decrease in the quantity and quality of groundwater, resulting in severe restrictions on agricultural production. Therefore, the farmers in the region have spontaneously turned to planting drought-resistant trees such as olives and pistachios. On the other hand, due to the significant reduction in the quantity and quality of groundwater in the study area, the quantitative and qualitative parameters of the fruit of the region's agricultural products, especially olive trees, which are irrigated under these conditions, are effective. It can be said that the quality parameters of olives increase with low irrigation and high salinity (to a tolerable extent). On the other hand, water and salinity stresses will have different effects on the performance of the mentioned plants. In this region, olives are used in two forms, canned and oil production. The amount of olive oil is often dependent on the growing conditions and fruit ripeness, and how the oil accumulates. The amount of oil in the dry matter of the fruit during the fruit ripening period (second fruit growth period) and its accumulation increases until the onset of dark purple. The quantity and quality of irrigation water affect the time and amount of oil accumulation, as well as the quality of olive oil. Also, the shelf life of olives in canned conditions and the shelf life of the aroma and taste of extra virgin olive oil are important features that will be controlled and examined by studying the density of olives during the fruit growth period. Therefore, the main purpose of this study is to investigate the changes in the density of olives during the fruit growth period under conditions of low irrigation and salinity stress.



Methods:

The study area is located in the central part of Marvdasht city in Fars province, Iran, at geographical coordinates '693196;3303288' with an elevation of 1620 meters above sea level. According to the De Martonne method, the climate of the region is semi-arid and the dominant wind direction is eastern. Two years (2020-2021) of field experiments were conducted to study olive fruit density in a 20-year-old olive orchard (Roghani variety). The experiment utilized a factorial layout in a randomized complete blocks design with three replications. Five irrigation levels (I1-I5) were tested, ranging from 25% to 125% of olive water requirement. Three saline water levels (S1-S3) were also included, with S1 being saline well water with an electrical conductivity of 3.5-7.5 dS/m, S2 being a combination of 50% well water and fresh water, and S3 being fresh water. The weight and volume characteristics of olive fruits were examined and measured at seven different periods, starting from the fruit's appearance in June until its harvest in December for oil production. The I5S3 represented the control treatment.



Results:

Despite the fact that poor quality and quantity of irrigation water (S1, I1, and I2) will result in a decrease in the weight and volume of olive fruit, it is beneficial for improving the quality of suitable oil and will have an impact on the density of olive fruit. Oil production in olive fruit, which occurs during the second period of fruit growth, has a significant role in the density of the fruit. If the volume of fruit does not change (in the case of low-quality and low-quantity irrigation water), due to the increase in oil in a specific volume, it will lead to an increase in fruit weight and consequently an increase in olive density. The increase in density during the first growth period is accompanied by the production of dry matter in the fruit. A decreasing trend in the density of olive fruit can be observed in all irrigation treatments and different salinity levels in both consecutive years. The study found that normal irrigation water (I4 and I5) and appropriate quality (S2 and S3) increase the weight and volume of olive fruit and alter the density of olive fruit. The interaction effect of salinity and irrigation on the density of olive fruit was significant (5%) in both years. In 2020, changes in fruit density during the second period of fruit growth at salinity level (S1) were more pronounced in different irrigation treatments from I2 to I5 compared to other salinity levels (S2 and S3). The highest and lowest density values in 2020 were I2 and I3, respectively. The highest fruit density (1.1356 gr/cm3) was observed in the high salinity level (S1) and low irrigation treatment (I2). In 2021, the highest fruit density (1.1105 gr/cm3) in the first period of growth is related to S1, and in the second period of growth, it decreases compared to S2 and S3. In the same year, I1S3 had the highest value (1.0753 gr/cm3) and I5S3 had the lowest value (0.9899 gr/cm3) in the second stage of olive fruit growth. Although low quality and quantity of irrigation water (S1, I1 and I2) reduces the weight and volume of olive fruit, it is suitable for improving the quality of oil and will affect the density of olive fruit.

Abstract Introduction: One of the destructive consequences of the earthquake was the failure of the infrastructure structures and facilities of each region, such as the fuel transmission system. In general, the fuel transmission system in cities consists of pipes buried in the ground for fuel transfer and various tanks on the ground for the storage and storage of petroleum materials. With the occurrence of earthquakes and the movement of the earth's tectonic plates, we have witnessed two main destructive phenomena: 1- failure of fuel transfer pipes 2- creating cracks in the pipes (leakage of oil materials). Based on the position of the fuel networks system, which consists of pipes buried in the soil, it is expected that after the pipe breaks and leaks, the contents inside the pipes of the fuel transmission system will move in the soil as a pollutant, and in addition to soil pollution based on the coefficient hydraulic transmission, has entered the groundwater resources and caused the pollution of these valuable resources. Considering the nature of the earthquake, which is classified as a random phenomenon, an accurate prediction of its time, place, and intensity cannot be provided, and also based on the numerous parameters involved in the performance of the fuel transmission system under seismic loading, which has wide uncertainties. There is a need to carry out extensive studies (vulnerability analysis, risk analysis) on the fuel network under different earthquake scenarios and consider getting the conditions of uncertainty assessment on the pollution of groundwater resources by the leakage of oil pollutants resulting from the failure of the fuel transmission system should be implemented.
Methods: In this research, a comprehensive model has been presented to evaluate the pollution of underground water resources based on the vulnerability of the fuel transmission pipeline under the conditions of an earthquake. In the research model, the seismic vulnerability of the buried pipeline has been developed by considering the conditions of uncertainty and using the machine learning method. The results of the validation of the developed numerical models have shown acceptable performance and high accuracy in predicting the seismic vulnerability of the pipe. Also, the aquifer pollution assessment using the DRASTIC model has been implemented. In this research, 5 main machine learning algorithms, each of which has different computational branches, have been used to develop a model for predicting the seismic vulnerability of a buried pipeline.In order to consider the conditions of uncertainty in the input data of stress prediction models and the possibility of seismic damage that directly affects the results, the conditions of uncertainty in the input data of the model have been taken into account regarding the main goal of assessing the probability of seismic vulnerability in the line The buried pipe is under different earthquake scenarios, taking into account the uncertainty in the input data values of the model, the most critical conditions for the possibility of pipe vulnerability are extracted. Based on this, 4 main parameters: 1- Depth of working, 2- Modulus of elasticity, 3- Soil density, 4- Magnitude of earthquake in numerical models based on the conditions of uncertainty in the initial input values and using the probability distribution function and the coefficient of variation. The Monte Carlo method is used for simulating critical conditions (the highest probability of pipe seismic failure) have been extracted. In this research, the number of Monte Carlo simulation repetitions is considered equivalent to 100,000 repetitions.
Results: The results of the performance of the machine learning model based on different algorithms indicate the amount of error in predicting the stress on the buried pipe compared to the exact values based on the initial data set. Based on the results, it is clear that the GPR models have a better performance than other computational models of machine learning. Based on the results, it is clear that among the algorithms of the GPR method, the Exponential GPR algorithm has the minimum error rate, so the machine learning model developed based on this algorithm has an MSE error equal to 0.00329 and the correlation R equal to 0.999. The results of the performance of the machine learning model for predicting seismic vulnerability based on different algorithms showed that GPR models (Gaussian Process Regression Models) had better performance than other computational models of machine learning and had a minimum error rate, so the machine learning model developed based on this algorithm has an MSE error equal to 0.00329 and a correlation value R equal to 0.999. Based on the results of the drastic model, the pollution of the Tehran aquifer based on the first seismic scenario (earthquake event with magnitude Mw = 5) showed that the pollution zoning of the aquifer has changed and the area of the area with moderate pollution has increased by about 9% based on the ML prediction model. According to the results of the forecasting models, which indicate the number of failures 2 and the number of leaks 15 under the first seismic scenario in the pipeline, the amount of 10% changes in the medium vulnerability level can be investigated.
Based on the results of the implementation of the second seismic scenario (earthquake with a magnitude of 6 on the Richter scale) based on the seismic damage prediction model, the ML prediction model showed an increase in the level of moderate pollution by 35% and an increase in the level of high pollution by 5%. The zoning of Tehran aquifer pollution based on the third seismic scenario (earthquake event with magnitude Mw = 7) showed that the underground water sources of Tehran city have been heavily polluted due to the leakage of fuel products from the fuel pipeline in such a way that according to the model ML, the area of low pollution level is 18%, medium pollution level is 45% and high pollution level is 37%. Based on the results obtained in the event of an earthquake with a magnitude of 7 on the Richter scale, the amount of aquifer pollution based on the ML prediction model indicates an increase of 25% in the medium pollution level and 19% in the level of high pollution. There has been a lot of pollution.

Abstract Abstract

The use of isotopes, especially stable environmental isotopes, is very important in investigating the water cycle and water resources studies. Preparation of the local meteoric water line and its equation in a region is used to determine the origin of the air mass affecting the region and is used as a basis for a more detailed study of water resources, because by maintaining the initial characteristics of precipitation as an input to the groundwater aquifer, the subsequent changes that occur in the groundwater aquifer will be traceable.



Methods

The studied area is located in Chaharmahal and Bakhtiari province and in Chelgerd, Farsan and Ardal cities, and in terms of structure, it is a part of high Zagros (shredded or eroded). The major part of the study area is located in the large Karun basin and part of it is located in the Gavkhouni basin.

In this research, in order to investigate the isotopic composition of precipitation, a total of 38 rain samples and 7 snow samples were collected from 9 stations at different altitudes with monthly frequency in the 2017-2018 in the form of cumulative and precipitation event in the rainy season. In order to determine the isotopic values of the collected samples, they were sent to Mesbah Energy laboratory and the isotopic composition of oxygen and hydrogen of all samples was determined by a laser spectroscopy.

By examining the composition of oxygen 18 and deuterium isotopes of precipitation samples in hydrological year 2017-2018, the local meteoric water line for the middle Zagros study area in the Zardkoh Bakhtiari area has been drawn and compared with the global meteoric water line and the Meditrranean meteoric water line. In addition, in order to establish a relationship between precipitation isotopes and regional weather conditions, the correlation of altitude, temperature and precipitation parameters on stable isotopes of oxygen 18 and deuterium of event precipitation samples from different altitudes has been investigated. Also, in order to do more detailed studies and determine the origin of moisture masses, the correlation between the amounts of oxygen 18 and deuterium isotopes with deuterium excess and electrical conductivity was also investigated.



Results

By examining the isotopic results obtained from the collected precipitation samples, for the first time, the atmospheric water isotopic line of the middle Zagros region in the Zardkoh Bakhtiari was obtained with the equation δD =7.1068 δ18O+12.364. The local meteoric water line of the region had differences with global and Meditrranean meteoric water line due to the occurrence of evaporation and transpiration from precipitation. The changes of δ18O value in meteoric precipitation in the region are from -12.92‰ to -1.07‰ (average -6.38‰) and δD value is from -80.16‰ to 7.51‰ (average -33.58‰).

Comparing the isotopic content of precipitation in the range with altitude and amount of precipitation indicates that precipitation with richer isotopic composition occurred in areas with lower altitude and amount of precipitation. For every 100 meters change in altitude in this area, about 0.49 and 2.16 permil decrease in δ18O and δD isotopic values, respectively, and for every 20 mm increase in precipitation, about 1.3 permil decreases in δ18O isotopic value and about 10.1 of a permil decrease in the amount of deuterium occurs.

Also, the increase in temperature has led to the enrichment of oxygen 18 and deuterium isotopes in the study area. So that the changes of δ18O and δD of the precipitation samples of the middle Zagros range are about 0.9 and 0.4 permil per 5 degrees centigrade of temperature change, respectively

Also, the amount of electrical conductivity (EC) of precipitation samples has a direct relationship with the amount of oxygen 18 and deuterium isotopes of these samples, so that with an increase of 20 microsiemens per centimeter of electrical conductivity, the amount of oxygen 18 and deuterium isotopes of precipitation samples increase by about 1.45 and 9.40 permil, respectively.

In the conducted studies, the relationship between deuterium excess and isotopic values of precipitation samples was also investigated. deuterium excess of precipitation is usually affected by relative humidity and atmospheric temperature of the source of moisture, which is why it is considered an important indicator in determining the source of moisture. If the cloud humidity drops below 100%, deuterium excess occurs. The increase in the amount of deuterium excess and the decrease in isotopic values of δ18O and δD of precipitation in the study area also indicate the main origin of moisture masses from Mediterranean regions.

Abstract Weirs are among the structures used in water transfer channels, hydraulic structures, irrigation and drainage channels, and they are used to regulate the water level and control the flow. Weirs are flow diversion tools that are widely used in irrigation and drainage systems and urban sewage systems. Increasing the capacity of each weirs in a certain width is one of the important issues. These changes cannot be implemented in all structures because limiting factors such as topographical conditions and construction materials may not allow. The use of weirs with non-linear crests is one of the ways to increase the capacity of each weir. During the construction of dam structures, due to the high cost, they are looking for a solution to optimize costs, and one of the best ways to build a dam is to use a weir with a non-linear crest. One of the advantages of non-linear weir is to increase the flow rate capacity. Simulation using various software including Flow3d to investigate the flow pattern has become very popular in recent years. The most important reason for using simulation software, in addition to cost reduction, is the possibility of creating different forms of labyrinth weirs in the software. Meanwhile, in the laboratory, it is not possible to investigate the labyrinth weirs of different shapes and dimensions.

In this research, the hydraulic model was tested inside a glass flume with a length of 10 meters, a height of 80 cm and a width of 80 cm. This flume has a pump with a maximum flow rate of 90 lit/s. The flow rate is measured using an ultrasonic flow meter. To measure the water level, several rail gauges points that can move along the flume are used. The labyrinth weir is triangular with 4 mm thick and height of 15 cm. The length of the model is 126 cm and the L/W ratio is 1.58. At first, the laboratory model was compared with the simulated model with the same magnification ratio. For this purpose, 9 discharges with a head ratio of 0.2 to 0.7 were investigated in the laboratory. The purpose was to check the accuracy of the model used in the simulation compared to the laboratory model. Then, three triangular and three arched labyrinth weirs models were simulated with 2, 3 and 4 magnifications. K-Ɛ RNG turbulence model was used to solve the turbulence flow. This model has an additional term compared to other turbulence equations, which will give us a more accurate solution for solving and discretizing the turbulence equations. In the current research, the flow depth boundary conditions were used in the flow entry, the exit flow boundary conditions were used in the exit sections, the wall boundary conditions were used in the walls and the floor, and the symmetry boundary conditions were used in the water surface.

In order to validate the model, comparison of numerical and laboratory of discharge coefficient (Cd) was used. The results showed that RMSE is equal to 3.9% and MSE is equal to 0.16%. Therefore, the error is acceptable and the model will be used in the simulation of triangular and arched labyrinth weirs. The results showed that the discharge coefficient increased at first and then decreased. At first, gradually increasing the flow over the weirs, the amount of air trapped under the nappe decreases. This has caused a decrease in the amount of momentum introduced by the rotating air under the nappe, as well as a decrease in the negative pressure in that area, and as a result, it has resulted in an increase in the discharge coefficient. Investigations showed that with the increase of the water head ratio (HT⁄P) and magnification ratio (L/W), the nappe interference and local submergence increased and caused a decrease in the discharge coefficient. Thus, in the triangular and arched labyrinth weir, the discharge coefficient decreases up to 38% and 39% with the increase of the water head ratio from 0.1 to 1 and up to 29% and 37% with the increase of the magnification ratio from 2 to 4. On the other hand, arched labyrinth weirs have a lower discharge coefficient of up to 14% at a same magnification ratio than triangular labyrinth weirs. The reason for this problem is the smaller angle of the arched labyrinth weir with the channel wall compared to the triangular labyrinth weir, which causes the nappe interference to hit the channel wall and also cause more local submergence in the arched weir. Also, the impact angle of the flow jets at the top of the arched weir is higher than that of the triangular weir, which will cause more disturbance of the flow and decrease the flow coefficient.

Abstract Evaporation is a physical phenomenon by which water particles enter the atmosphere in the form of vapor from the surface of water or the surface of wet soil through receiving solar energy. Evaporation process is an essential part of the hydrological cycle and it takes place continuously in nature. The importance of evaporation estimation in water resources and agriculture studies is undeniable. The evaporation pan is used as an indicator to determine the evaporation from the water level of lakes and reservoirs all over the world due to the ease of interpreting its data. Evaporation prediction is one of the important variables in planning and managing water resources. Various models are used to predict evaporation, such as stochastic time series models, experimental models, data mining models. Due to the fact that evaporation is affected by many parameters that are non-linear, non-stationary and random and occurs in a dynamic and complex manner, the use of experimental methods to predict evaporation that is based only on weather information such as temperature, relative humidity, wind speed and solar radiation are used, the accuracy is not enough. So far, various methods have been presented to calculate and estimate evaporation, such as the water balance method and experimental methods. These methods have flaws such as the inability to generalize to other places and different climatic conditions. Therefore, researchers tried to find a way to reduce the error as much as possible. The use of machine learning models are among these methods.

Materials and Methods

In this research, two techniques of support vector machine and network with long short-term memory will be used to estimate the amount of evaporation from the pan in Kohgiluyeh and Boyer-Ahmad Province, and the results will be compared with the actual evaporation values recorded in evapotranspiration stations and some experimental methods of evaporation estimation. In order to model and estimate the amount of evaporation, daily data of parameters of pan evaporation, rainfall, wind speed, maximum and minimum temperature, cloudiness, soil temperature, maximum and minimum relative humidity, average dew point temperature, sea level pressure and actual vapor pressure has been prepared from the regional water organization for 6 stations including Yasouj, Imamzadeh Jafar, Dehdasht, Dogonbadan, Siskhet and Likk. The length of the statistical data period varies from 39 years in Dogonbadan to 14 years in Likk. In this research, two SVM and LSTM models, as well as three experimental methods of Mayer, US Civil Engineering Organization (USBR) and Ivanov were used to estimate evaporation from pans. To use the models to estimate evaporation, first the data were randomly divided into training and testing stage. 70% of the data were considered as training data and 30% of the data were considered as test data. Finally, in order to evaluate the models, the statistical indices of explanation coefficient (R2), root mean square error (RMSE) and mean absolute value of error (MAE), model efficiency index or Nash Sutcliffe coefficient (N.S) and residual mass index (CRM) were used.

Results and Discussion

The results of the SVM model show that the error values of daily pan evaporation estimation in the SVM model in the training stage vary between 1.6 and 1.2 mm per day. The efficiency coefficient also shows that the model is in a satisfactory condition in terms of estimation and forecasting ability in the Siskhet station, in a good condition in the Yasouj station, and in a very good condition in other stations. LSTM model has weaker results than SVM model. The error values in this model are higher than the SVM model and vary between 2.2 and 3 mm per day. Also, the results of the efficiency coefficient of the model (N.S) also show that this model has not provided acceptable results for estimating pan evaporation in the two stations of Sisakht and Yasouj. In part of the models test, the LSTM model also showed a weaker ability than the SVM model in most of the stations. The LSTM model has provided better results than the SVM model only in Imamzadeh Jafar station. The best result among all the stations and the two investigated models was obtained at the Dehdasht station with an error of 1.6 mm per day and a Nash coefficient of 0.87 for the SVM model. Comparison of the results of the models with 3 experimental methods of Mayer, Ivanov and USBR also showed that, except for Ivanov's method and at Doganbadan station, none of the experimental methods could simulate the daily evaporation values well.

Conclusion

In summary, the results of this research show that the SVM model has estimated the northern and central regions of the province with an error between 15 and 18 percent, while the LSTM model estimates the same regions with a greater error and about 22 to 26 percent. In the south of the province, the results is almost reversed and the SVM model has an error of about 19 to 21 percent and the LSTM model has an error of between 13 to 21 percent. In the east of the province, the amount of error in the estimation of pan evaporation in the LSTM model is also higher than in the SVM model. In total, the comparison of the results of two models and three experimental methods of estimating evaporation from pans in Kohgiluyeh and Boyer-Ahmad provinces showed that LSTM model is the best model for Imamzadeh Jafar station and SVM model is the best model for the other 5 investigated stations. None of the three experimental models, provided acceptable results for the province. The results of this research show that, despite the emergence of powerful models that are capable of detecting complex and non-linear behaviors of variables based on mathematical relationships that can well recognize and simulate the pattern of data variability, the use of experimental methods to estimate pans evaporation is not recommended.

Abstract Introduction:

Weirs are a type of water structures that are used to pass floods, control water levels and measure flow rates. The accurate and appropriate design of the weir is of particular importance, and the existence of weirs with inappropriate discharge capacity is one of the most important factors of channel inefficiency. Circular crest weirs are reliable weirs for use in channels that are built perpendicular to the flow or at an angle (oblique) to the direction of the flow. Oblique weirs are used to increase the effective length of the weir and increase the water-passing capacity and hydraulic parameters such as the discharge coefficient. On the other hand, the study of the flow in the unsteady state, in which the flow variables in the channel vary with time, is of special importance in hydraulic science. In this research, the calibration of the discharge coefficient of the oblique circular crest weir under unsteady flow condition has been discussed. Also, the effect of changing the height of the weir and changing the flow pattern on the discharge coefficient of the unsteady flow in this type of weir has been investigated.



Methods:

In this research, three oblique circular crest weirs with a height of 15, 10 and 20 cm and other identical geometric parameters under free and unsteady flow conditions in the flow range of 25 to 51 liters per second under the range of flow rate changes of 1, 3 and 5 liters per second and the range of time changes of 5, 10 and 15 seconds have been tested. Therefore, the total number of tests was equal to 27. Experiments were carried out in the research flume of Islamic Azad University, Isfahan (Khorasgan) branch with a rectangular cross-section of 10 meters in length and 0.6 meters in width, and weirs were installed at 2.5 meters from the entrance of the channel The flume has no slope of the floor and the height of the flume is the same without change and its walls are made of tempered glass and completely sealed. The mentioned flume is equipped with a closed water circulation system and can provide a maximum flow rate of up to 55 liters per second. The tank of this flume is made of fiberglass and has a cylindrical shape with a volume of 10 cubic meters and is placed underground at a height of about 2 meters. Flow can be regulated by PLC device. The depth gauge of the device without contacting the free surface of the flow, by sending and receiving ultrasonic waves, measures the distance with very high speed and accuracy, and in this way the depth of the flow is recorded in the PLC device. In fact, the most important part of this test set is the PLC device connected to the flume, which controls all flow settings, including the flow rate, maximum flow rate, relevant hydrographs, and records the flow depth data. In this study, the governing relations were first extracted and then the genetic algorithm was used for optimization. The optimization process in the genetic algorithm is based on a guided random process. This method is based on the theory of gradual evolution and Darwin's fundamental ideas. Genetic Algorithm is a non-algebraic optimization method that is suitable for functions whose optimization with algebraic methods is exhausting. This algorithm and other evolutionary algorithms examine the response space in parallel and cluster by cluster and not member by member and for this reason, the possibility of occurrence of local maxima or minima is eliminated. Also, these methods do not need information about the derivatives of the target function and only the main form of the function is required. In this research, the solver available in Excel software was used for optimization with evolutionary algorithm method. After specifying the target variable, which is the discharge coefficient in this research, the evolutionary algorithm option is selected, and the software performs its analysis to calculate the best discharge coefficient with the lowest value for total errors.



Results:

The results obtained in this research show that in all patterns of flow changes, increasing the ratio of water height relative to the weir crest to the weir height (H/P) causes a decrease in the discharge coefficient of unsteady flow. Also, in all patterns of flow rate change, increasing the height of the weir causes a decrease in the discharge coefficient of the unsteady flow, that is, the discharge coefficient of the unsteady flow in the oblique circular crest weir is a function of the upstream flow conditions and the height of the weir. Also, the unsteady flow rate coefficient in this type of weir is a function of the flow rate change pattern. As can be seen from the graphs obtained in this research, the flow rate change pattern does not have much effect on the slope of the flow coefficient changes compared to the H/P changes, but it is effective on the degree of influence of the weir height changes for a fixed H/P value. On the other hand, the graphs show that the discharge coefficient of unsteady flow for oblique circular crest weir varies between 0.5 and 1.5, which previous researchers had also concluded that the discharge coefficient of unsteady flow for other weirs is not constant and is a function of the geometry of the weir and the pattern of changes in flow rate.

Abstract Nowadays, resources management in the watersheds is a vital task for the managers and planners due to the necessity of handling challenging issues existed between supply and demand sector. Water, energy and food are necessary for human comfort, poverty reduction, sustainable development and are inseparable part of human life. Iran is located in arid and semi-arid climate and the average rainfall is very low. So, it is very important to apply the proper management of water resource with considering the conditions of water shortage and crisis, to provide people’s food in the future. In this study, which was conducted two regions in the west of Iran (Miandarband & Oshtorinan plain), with purpose to evaluate and compare the difference farmer’s performances in the same crops with similar weather, it was investigated for the sustainable agriculture by Water, Food and Energy Nexus Index (WEFNI). WEFNI includes six indicators of water consumption, energy consumption, water efficiency, energy efficiency, water economic efficiency and energy economic efficiency. The final results obtained by the weighting and averaging of these indicators. The data has been collected by interviews with 43 farmers, field observations, related organizations and NETWAT software. Three crops tomato, potato, and cucumber were evaluated, which are prevailing cultivation in two regions. WEFNI of tomato, cucumber and potato was 0.87, 0.49 & 0.24 in Miandarband plain and 0.96, 0.48 & 0.33 in Oshtorinan plain Respectively. In both regions, based on WEFNI, tomato has the best conditions. So recommended to use WEFNI as a management tool to improve cropping pattern, which consider aspects of water and energy consumption and food security.