Irrigation
M. Koohani; J. Behmanesh; V.R. Verdinejad; M. Mohammadpour
Abstract
IntroductionLand-use changes and development of irrigated agricultural lands are very important factors that affect natural resources such as the quantity and quality of water resources and the environment. Land use change is attributed to two major processes. The first process is the change in land ...
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IntroductionLand-use changes and development of irrigated agricultural lands are very important factors that affect natural resources such as the quantity and quality of water resources and the environment. Land use change is attributed to two major processes. The first process is the change in land cover, which is related to the expansion or limitation of the area of land used (such as pasture, agricultural or urban land). The second process is a change in land cover management type (for example, changes in irrigation, fertilizer use, crop type, harvesting methods or surface impermeability). Recently the Urmia lake has been accompanied by a reduction in water resources and the continuation of this process can completely cause to dry Urmia Lake. One of the approvals of the Iranian government after the formation of the National Working Group for the Lake Urmia restoration program was to prevent the development of agricultural lands in this watershed since 2014. Unfortunately, no serious and effective action has been taken in this case yet, and this process has progressed to cause conflicts in this region. Game theory is one of the most important methods used in modeling and analyzing water and environmental resources conflicts.Materials and MethodsIn the present study, using GMCR + software, the water resources conflicts arising from agricultural land development has been analyzed. In this conflict, by accurately identifying the set of decision-makers and their strategies in the conflict process (Regional Water Company, Agriculture Organization, Justice, and Profiteering Farmers), the model was executed with 4 players, 6 options, and 64 states. Players' performance was assessed once as ideal behavior (importance to the environment, sustainable development, and preference of long-term over short-term interests) and then as the use of completing a questionnaire. Then 4 states in the ideal behavior as equilibrium states and 7 states in the condition of using the questionnaire results were extracted as equilibrium states. The conflict was also examined in the coalition state of 3 government organizations (Regional Water Company, Agriculture Organization, and Justice Organization). Finally, the most probable states of equilibrium in the game results were identified.Results and DiscussionIn the discussion concerning equilibrium points, it is crucial to consider that for resolving the dispute and the proposed solution, we need to examine not only the stability of these points but also the state's priority from the perspective of stakeholders. Based on the discussions and the output results of the conflict model using the GMCR+ model, the optimal response and conflict resolution can be found in scenario 12. This scenario holds a high priority for three key players: the Agricultural Organization, the Regional Water Company, and the Justice Department. However, it doesn't share the same level of priority with the Profiteering Farmers. The reason for this divergence lies in the preference for personal gain and profit pursuit over the broader interests of the entire catchment area.ConclusionIn recent years, despite the imposed restrictions, the Urmia Lake Basin has witnessed a notable increase in the cultivation of water-intensive crops. This shift has transformed arid lands into irrigated ones and altered agricultural areas into residential zones. According to the principles of the tax evasion game, when land development carries no moral or financial consequences for profit-driven farmers, and they are aware that regulatory institutions will not commit excessive resources to prevent and effectively combat the expansion of illegal farmlands, Profiteering Farmers will consistently engage in unauthorized development under any conflict scenario. In light of the revenue potential of this situation and the opportunity to enhance one's social standing, Profiteering Farmers will persist in unauthorized development regardless of the prevailing conflict circumstances. The findings underscore the critical role of the Regional Water Company and the Agricultural Organization. These entities must proactively employ their legal capacities to impede and deter the expansion of agricultural lands. Additionally, the Justice Organization assumes primary responsibility as a crime prevention factor, while its secondary role as a judicial enforcer within this conflict situation appears fitting. Therefore, all situations are stable for Profiteering Farmers. It seems that creating a platform and conditions in which Profiteering Farmers do not develop agricultural land themselves or do not develop land due to the protection of government institutions, can be very thoughtful and effective.
B. Sarcheshmeh; J. Behmanesh; vahid Rezaverdinejad
Abstract
Introduction: Drying Urmia Lake, located in northwest of Iran, is mainly related to the reduction in rivers flowing into the lake and hydrological parameters changes. Considering the importance and critical ecological conditions of Urmia Lake, the purpose of this research is to accommodate the environmental ...
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Introduction: Drying Urmia Lake, located in northwest of Iran, is mainly related to the reduction in rivers flowing into the lake and hydrological parameters changes. Considering the importance and critical ecological conditions of Urmia Lake, the purpose of this research is to accommodate the environmental water requirement in managing rivers leading to the lake, including Zarrinehrood as the largest river to the lake. Moreover, water scarcity was assessed by QQE approach in this basin.
Materials and Methods: Tennant method is easy, rapid, inexpensive, and is based on empirical relationships between the recommended percent of the MAF. The ecological conditions of the river have been determined for use in this method. In this study, different levels of EFR were calculated to protect the relevant levels of habitat quality defined in the Tennant method. Also the fraction of Blue Water Resources (BWR) required to protect a “good” level of habitat quality was considered as the suitable EFR. If it is less than the lower limit, the habitat quality will be in degraded status.
,
SQQE is a complete index to demonstrate water scarcity by considering water quantity and quality and EFR indicator.
, ,
The Smakhtin method provided an indicator for assessing the water scarcity.
WSI =
Where WSI is the index of water scarcity, MAR is the mean annual flow and EWR is the environmental water requirement of river. If the water scarcity index is more than one, the river would suffer from water shortage and not be able to meet the environmental water requirement. When the water scarcity index is between 0.6 and 1, the river would be under stress, and if it is between 0.3 and 0.6 Harvesting conditions from the river is moderate, and if it is less than 0.3 the river is ecologically safe and has no shortage.
Results and Discussion: According to the Smakhtin method, can be noticed that the calculations of this method are the same quantitative index of the other method used in this research. Only the quantitative conditions are evaluated in the Smakhtin method. However, in addition to the quantity (blue water footprint), environmental requirement and water quality are also included in the other method used in this research. Figure 1 shows the mean annual flow (MAF) and environmental flow requirement (EFR). As shown in figure 1, the majority river flow has been conducted from January to June and the rest from July to December. The annual BWR in the Nezamabad station was equal to 1208 × 106 (m3/year). To protect the habitat health of Zarrinehrood river at a good level, 400×106 (m3) of water must be left in the river per year. Therefore EFR was equivalent to 33.11% of the annual BWR. It is about one-third of total BWR.
In this station, EFR ranged from 60×106 (m3/year) as severely degraded to 2400×106 (m3/year) as maximum habitat health situation by using the Tennant table (Fig 2).
Figure 1- Environmental flow requirement (EFR) and mean annual flow (MAF) for the (Nezamabad station) Zarrinehrood river basin
Figure 2- Different levels of total environmental flow requirement (EFR) in the (Nezamabad station) Zarrinehrood river. Habitat quality levels with the flows shown in table 3 (Tennant) have be matched
The BWF and the BWA for the studied station were calculated 830×106 and 808×106 (m3/year), respectively. The BWF is 1.02 times the BWA. Therefore, the WSI Smakhtin and S Quantity will be 1.02.
The total GWF in this station was 1.08 times the BWR. Thus, the S Quality will be 1.08.
P is a demonstrator that shows the percentage of EFR in total BWR. It is related with the EFR to protect the habitat quality in a “good” level.
As you know, the number in the bracket shows that 33.11% of the total BWR of the basin is required as EFR, for maintaining the ecological habitat condition at the ‘good’ level. Other percentages of EFR are used to represent other ecological levels of habitat condition.
The S Quantity and S Quality for the Nezamabad station in Zarrinehrood river basin were obtained 1.02 and 1.08, respectively. Both indices are above the threshold (1.0), and the basin suffer from both qualitative and quantitative deficiencies. Thus, the final water scarcity indicator, SQQE, is 1.02 (33.11%) |1.08.
Conclusion: The EFR for protecting the good ecological level is not enough in some months during a year. Water scarcity was evaluated by simultaneously considering water quantity, water quality and EFR in the Zarrinehrood river basin in Iran. Compared with the Smakhtin method as another method of water scarcity assessment, the Smakhtin Index is only quantitatively, but the SQQE Index provides a comprehensive assessment of the water scarcity. The results imply that the studied region is suffering from both water quantity, water quality problems. The water pollution has a big role in causing the water scarcity in the river basin. This shows that only aiming on reducing water consumption cannot help impressive reduce the water scarcity. It is necessary to pay attention to reduce water pollution and water conservation. Even in the areas that the hydrological and ecological data are rare, the QQE approach as a holistic method could be used.
majid montaseri; Negar Rasouli Majd; Javad Behmanesh; Hossein Rezaei
Abstract
Introduction: The water footprint index as a complete indicator represents the actual used water in agriculture based on the climate condition, the amount of crop production, the people consumption pattern, the agriculture practices and water efficiency in any region. The water footprint in agricultural ...
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Introduction: The water footprint index as a complete indicator represents the actual used water in agriculture based on the climate condition, the amount of crop production, the people consumption pattern, the agriculture practices and water efficiency in any region. The water footprint in agricultural products is divided to three components, including green, blue and gray water footprint. Green water footprint is rainwater stored in soil profile and on vegetation. Blue water refers to water in rivers, lakes and aquifers which is used for irrigation purposes. Gray water footprint refers to define as the volume of contaminated water. The water footprint in arid and semiarid regions with high water requirement for plants and limited fresh water resources has considerable importance and key role in the planning and utilization of limited water resources in these regions. On the other hand, increasing the temperature and decreasing the rainfall due to climate change, are two agents which affect arid and semiarid regions. Therefore, in this research the water footprint of agriculturalcrop production in Urmia Lake basin, with application of climate change for planning, stable operating and crop pattern optimizing, was evaluated to reduce agricultural water consumption and help supplying water rights of Urmia Lake.
Materials and Methods:Urmia Lake basin, as one of the main sextet basins in Iran, is located in the North West of Iran and includes large sections of West Azerbaijan, East Azerbaijan and Kurdistan areas. Thirteen major rivers are responsible to drain surface streams in Urmia Lake basin and these rivers after supplying agriculture and drinking water and residential areas in the flow path, are evacuated to the Lake. Today because of non-observance of sustainable development concept, increasing water use in different parts and climate change phenomena in Urmia Lake basin the hydrologic balance was perturbed, and Urmia Lake has been lost 90% of its volume and has a critical condition. Therefore, planning, managing and optimizing utilization of water resources in the basin have a high research priority and this requires the concentration on the consumption of water resources. In this study five major products including, wheat, sugar beet, tomato, alfalfa and corn, were studied. For this purpose, seven synoptic meteorological station data including,Salmas, Urmia, Mahabad, Takab, Tabriz, Maragheh and Sarab were used to calibrate the downscaling atmospheric-ocean general circulation model LARS.WG5 and forecast meteorological data in the future periods time (2011-2030) and (2046-2065) with the A2 scenario.The reason to selectA2 scenario was the most critical situation for the mentioned scenario. Then the obtained data were used to estimate the water requirement and water footprint of mentioned plants separately blue and green water footprint in the future periods.
Results and Discussion:The resultsof themeteorological data prediction showed thatall synoptic stations except for Tabriz station the average annual predicted rainfallvalues had the deviationfromhistoricalvalues.The mentioneddeviation in the south (Tekab, Mahabad) and West (Urmia, Salmas) ofUrmia lake basin will showincreaseanddecrease in theannual rainfallin the future, respectively.Moreover,the average annual of predicted temperature values for all studied stations showed that the temperature will increase about1°Cduring2011-2030 period and 2°C during 2046-2065 period. Potential evapotranspiration, as another important meteorological parameter has essentialrole in the estimation of crop water requirements which will be slightly affected by climate change phenomena and it will increase in the summer. The results of agricultural products water footprint show that the maximum amount of green water footprint in all studied stations was related to wheat and alfalfa, and this water footprint depend on the time and growth period. For corn, tomatoandsugar beetproducts the ratio of blue and green water footprint is greater 9. By comparing the water footprint of products it can be seen that in Urmia, Salmas and Tekab stations water footprint is decreased with decreasing rainfall and this decrease during 2065 – 2045 periods is higher than 2030 – 2011 periods.
Conclusions: According to the results, annual precipitation in southern and western regions of the Lake Urmia basin will be increased and decreased, respectively in the future periods. However, increasing approximately one Celsius degree in temperature is expected for each of the periods all over the basin. In addition,the results showed that the amount of potential evapotranspiration will be increased in the warm months (June to September) in the future periods, and agricultural water consumption pattern will be changed affected by evapotranspiration variations. In the future periods, the blue and green water footprint of most agricultural products will be increased and decreased, respectively.
Mohammad Nazeri Tahrudi; Keivan Khalili; Javad Behmanesh; Kamran Zeinalzadeh
Abstract
Introduction: Drought from the hydrological viewpoint is a continuation of the meteorological drought that cause of the lack of surface water such as rivers, lakes, reservoirs and groundwater resources. This analysis, which is generally on the surface streams, reservoirs, lakes and groundwater, takes ...
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Introduction: Drought from the hydrological viewpoint is a continuation of the meteorological drought that cause of the lack of surface water such as rivers, lakes, reservoirs and groundwater resources. This analysis, which is generally on the surface streams, reservoirs, lakes and groundwater, takes place as hydrological drought considered and studied. So the data on the quantity of flow of the rivers in this study is of fundamental importance. This data are included, level, flow, river flow is no term (5). Overall the hydrological drought studies are focused on annual discharges, maximum annual discharge or minimum discharge period. The most importance of this analysis is periodically during the course of the analysis remains a certain threshold and subthresholdrunoff volume fraction has created. In situations where water for irrigation or water of a river without any reservoir, is not adequate, the minimum flow analysis, the most important factor to be considered (4). The aim of this study is evaluatingthe statistical distributions of drought volume rivers data from the Urmia Lake’s rivers and its return period.
Materials and Methods: Urmia Lake is a biggest and saltiest continued lake in Iran. The Lake Urmia basin is one of the most important basins in Iran region which is located in the North West of Iran. With an extent of 52700 square kilometers and an area equivalent to 3.21% of the total area of the country, This basin is located between the circuit of 35 degrees 40 minutes to 38 degrees 29 minutes north latitude and the meridian of 44 degrees 13 minutes to 47 degrees 53 minutes east longitude. In this study used the daily discharge data (m3s-1) of Urmia Lake Rivers.
Extraction of river drought volume The drought durations were extracted from the daily discharge of 13 studied stations. The first mean year was calculated for each 365 days using the Eq 1 (14).
(1) (For i=1,2,3,…,365)
That Ki is aith mean year, Yijis ith day discharge in jth year and n is number of period years. After the extraction the 1 to ndays drought duration, the years with no data were complete with Regression or interpolation methods. After the extraction, data initial evaluation (Trend, Independence and Stationarity) and completed the drought volume data, these data were fitted by the common distribution functions and select the best function based on Kolmogorov-Sminnov test. To read more information about the data initial evaluations see the NazeriTahroudi et al (15).
Log Pearson type 3 distribution Log Pearson type 3 distribution and its parameters is (7 & 12):
(2)
After selectingthe best distribution function based on Kolmogorov - Smirnov test, estimated the selected function parameter to evaluate the return period. For this purpose, there are many methods such as moments, Sundry Average method (SAM), Logarithm of applied moments observations and maximum likelihood that in this study were compared.
Results and Discussion: In this study, using daily flow data fromstations studied; the drought volume of days 1 to 60 was extracted, corrected, and completed. Before fitting the extraction drought volume river data with distribution function, the mentioned data were investigated with Wald-Wolfowitz (Independence and Stationary), Kendall (Trend) and Wilcoxon (Homogeneity) tests and the results of these tests were accepted in two significant levels of 1 and 5 percentages. Before estimatingthe Log Pearson type III parameters, first the drought volume river data were modeled by the Easy Fit software and common distribution functions and Log Pearson type III was selected by the Kolmogorov – Smirnov test as the best function. Results of two Anderson Darling and Chi Squared tests foraccurate evaluation were added. After initial evaluation of data and statistic tests, the time series of drought Volume River data of the studyarea were fitted by log Pearson type III. To estimatethe Log Pearson type III parameters used the sundry average method and to investigatethe accuracy of this method, 3 methods (moment, maximum likelihood and Logarithm of applied moment observations) were used and 4 mentioned methods for all of rivers were calculated. The most river drought relating to Gadar-Chai river with 1742 million cubic meters low volume and the lowest of it relating to Mardoq-Chai river with 68 million cubic meters low volume in 10000 year return period. After Gadar-Chai river the most low volume of discharge relating the Zarineh-rood river. Two Zarineh-rood and Gadar-Chai rivers among other rivers have a higher average discharge. Log Normal III, Gamma, Wikeby and GEV distributions have a good fitting on river flows data and no difference in investigation models that corresponded with Mosaedi et al (13) and NazeriTahroudi et al (15). The results of Grifits (7) also introduced the Wikeby distribution has a better than Beta distribution. Lee (12) also with evaluation the rainfall frequency in the study the rainfall concentration properties in Chia-Nan (Taiwan) introduced the Log Pearson type III as the best distribution function between the common distribution function. Results of Chi-Squared test in methods of parameter estimation showed that all methods are acceptable.
Conclusion: Drought occurrence can be estimated bythe analysis of historical data for different regions and using the results of predicting problems can be reduced. In this research daily river flow of Lake Urmia basin applied to calculate drought volume of rivers. Log Pearson III distribution selected among current hydrological distribution functions for fitting drought volume of rivers. Using selected distribution function and Sundry Average Moment method for estimating parameters return period of drought from 2 to 10000 years extracted. Results showed that volume of drought for Shahar-chai , Barandoz-chai, Nazlu-Chai, Mahabad-Chai, Rozeh-Chai, Gadar-chai, Simineh-rood, Zola-chai, Aji-chai, Sofi-chai, Leilan-chai and Mardoq-chay rivers in the return period of 10000 years will be 92, 125, 228, 150, 110, 1742, 90, 77, 690, 280, 65, 68 Mm3 respectively.
F. Ahmadi; S. Ayashm; K. Khalili; J. Behmanesh
Abstract
Introduction Crop evapotranspiration modeling process mainly performs with empirical methods, aerodynamic and energy balance. In these methods, the evapotranspiration is calculated based on the average values of meteorological parameters at different time steps. The linear models didn’t have a good ...
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Introduction Crop evapotranspiration modeling process mainly performs with empirical methods, aerodynamic and energy balance. In these methods, the evapotranspiration is calculated based on the average values of meteorological parameters at different time steps. The linear models didn’t have a good performance in this field due to high variability of evapotranspiration and the researchers have turned to the use of nonlinear and intelligent models. For accurate estimation of this hydrologic variable, it should be spending much time and money to measure many data (19).
Materials and Methods Recently the new hybrid methods have been developed by combining some of methods such as artificial neural networks, fuzzy logic and evolutionary computation, that called Soft Computing and Intelligent Systems. These soft techniques are used in various fields of engineering.
A fuzzy neurosis is a hybrid system that incorporates the decision ability of fuzzy logic with the computational ability of neural network, which provides a high capability for modeling and estimating. Basically, the Fuzzy part is used to classify the input data set and determines the degree of membership (that each number can be laying between 0 and 1) and decisions for the next activity made based on a set of rules and move to the next stage. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) includes some parts of a typical fuzzy expert system which the calculations at each step is performed by the hidden layer neurons and the learning ability of the neural network has been created to increase the system information (9).
SVM is a one of supervised learning methods which used for classification and regression affairs. This method was developed by Vapink (15) based on statistical learning theory. The SVM is a method for binary classification in an arbitrary characteristic space, so it is suitable for prediction problems (12).
The SVM is originally a two-class Classifier that separates the classes by a linear boundary. In this method, the nearest samples to the decision boundary called support vectors. These vectors define the equation of the decision boundary. The classic intelligent simulation algorithms such as artificial neural network usually minimize the absolute error or sum of square errors of the training data, but the SVM models, used the structural error minimization principle (5).
Results Discussion Based on the results of performance evaluations, and RMSE and R criteria, both of the SVM and ANFIS models had a high accuracy in predicting the reference evapotranspiration of North West of Iran. From the results of Tables 6 and 8, it can be concluded that both of the models had similar performance and they can present high accuracy in modeling with different inputs. As the ANFIS model for achieving the maximum accuracy used the maximum, minimum and average temperature, sunshine (M8) and wind speed. But the SVM model in Urmia and Sanandaj stations with M8 pattern and in other stations with M9 pattern achieves the maximum performance. In all of the stations (apart from Sanandaj station) the SVM model had a high accuracy and less error than the ANFIS model but, this difference is not remarkable and the SVM model used more input parameters (than the ANFIS model) for predicting the evapotranspiration.
Conclusion In this research, in order to predict monthly reference evapotranspiration two ANFIS and SVM models employed using collected data at the six synoptic stations in the period of 38 years (1973-2010) located in the north-west of Iran. At first monthly evapotranspiration of a reference crop estimated by FAO-Penman- Monteith method for selected stations as the output of SVM and ANFIS models. Then a regression equation between effective meteorological parameters on evapotranspiration fitted and different input patterns for model determined. Results showed Relative humidity as the less effective parameter deleted from an input of the model. Also in this paper to investigate the effect of memory on predict of evapotranspiration, one, two, three and four months lag used as the input of model. Results showed both models estimated monthly evapotranspiration with the high accuracy but SVM model was better than ANFIS model. Also using the memory of evapotranspiration time series as the input of model instead of meteorological parameters showed less accuracy.
J. Behmanesh; M. Hesami Afshar
Abstract
Introduction: The frequency of floods is one of the characteristics of river flow statistics so thatanalyzing it has an important role to assess the hydrological and economical water resources projects. For determining flood frequency, the estimation of accurate skewness coefficient of annual peak discharges ...
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Introduction: The frequency of floods is one of the characteristics of river flow statistics so thatanalyzing it has an important role to assess the hydrological and economical water resources projects. For determining flood frequency, the estimation of accurate skewness coefficient of annual peak discharges is required. Estimation of population skew for different regions will be improved when it is computed from the weighted average of the sample skew and an unbiased generalized skew estimate. There are different ways to develop a generalized skewness coefficient. The goal of this study is to analyze the methods for generating unbiased generalized skew coefficient and select the best method for creating the weighted generalized skewness coefficient.
Materials and Methods: In the present study, to calculate weighted generalized skewness coefficient, initially the hurst index is calculated to analyze the adequacy of time series length. The case study of the present research (West Azerbaijan, Iran) has three basins containing different hydrologic regions. These three basins are: the Aras River, Urmia Lake and Zab River basins. Therefore, various hydrologic regions, with the help of provincial border and the borders between sub-basins, are combined to form three larger hydrologic regions.After the formation of three larger hydrologic regions, the homogeneity of skewness variance of annual peak discharge of hydrometric stations within each three hydrological groups are tested using theleuven statistical parameter. Also the Dunnett test is applied to identify areas whichare significantly differentiated with other hydrologic regions. To develop the generalized skewness coefficient of 67 hydrometric stations with different statistical periods (16 to 62 years), three methods containing statewide map of skewness in West Azerbaijan, skewness map with including three hydrologic regions, and weighted average of skewness for the three hydrologic regions were used. Finally, after calculating the errors of three methods of generalized skewness development using Mean Square Error (MSE) coefficient, a weighted technique is used to calculate the weighted generalized skewness using sample skewness and the best generalized skewness (the one which has the least error) and their corresponding errors.
Results and Discussion: The results showed that most parts of the province have negative skewness values. The Hurst test results showed that the hurst coefficient is greater than 0.5 for all 67 hydrometric stations and lengthening of time series for the analysis is not required. Also, the results of the leuven statistical parameter showed that the homogeneous assumption is true for hydrological groups. Therefore, there is no reason for the variance heterogeneity. Moreover, the results of the Dunnett test stated that statistically, skewness means within the hydrological groups are not different. An error analysis showed that the Zab river basin had the least error amongthe studied basins. Among the methods studied for developing the skewness map, the division of the province into three hydrologic regions hada higher accuracy (MSE of Generalized skew coefficient = 0.55) than the other methods. However, this difference was very marginal. According to skewness maps, it can be seen that by considering hydrologic regions, the errors can be reduced in all three hydrologic regions. As the MSE in areas A and B is lower than the provincial level and in the region C, the error rate is close to zero. However, it should be noted that the number of hydrometric stations in region C, are much lower than other parts of the study area and this can be one of the reasons for error reduction in this area.
Conclusions: Considering that the aim of this study was to evaluate the accuracy of the generalized skewness estimating methods in the calculation of weighted generalized skewness coefficients, it has been seen that a regional approach, in addition to reducing the error rate, the fracture lines on the skewness map of the annual peak discharges can be reduced. Unlike the regional approach, the averaging method has shown worse results in all three regions.We may conclude that the sample skewness coefficient alone can bring better results than the averaging approach. Also, by comparing errors in areas A, B, and C, it can be concluded that with increment in area of hydrologic regions and inadequate spatial distribution of hydrometric stations, the error rate increases.
M. Moravej; K. Khalili; J. Behmanesh
Abstract
Introduction: Studying the hydrological cycle, especially in large scales such as water catchments, is difficult and complicated despite the fact that the numbers of hydrological components are limited. This complexity rises from complex interactions between hydrological components and environment. Recognition, ...
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Introduction: Studying the hydrological cycle, especially in large scales such as water catchments, is difficult and complicated despite the fact that the numbers of hydrological components are limited. This complexity rises from complex interactions between hydrological components and environment. Recognition, determination and modeling of all interactive processes are needed to address this issue, but it's not feasible for dealing with practical engineering problems. So, it is more convenient to consider hydrological components as stochastic phenomenon, and use stochastic models for modeling them. Stochastic simulation of time series models related to water resources, particularly hydrologic time series, have been widely used in recent decades in order to solve issues pertaining planning and management of water resource systems. In this study time series models fitted to the precipitation, evaporation and stream flow series separately and the relationships between stream flow and precipitation processes are investigated. In fact, the three mentioned processes should be modeled in parallel to each other in order to acquire a comprehensive vision of hydrological conditions in the region. Moreover, the relationship between the hydrologic processes has been mostly studied with respect to their trends. It is desirable to investigate the relationship between trends of hydrological processes and climate change, while the relationship of the models has not been taken into consideration. The main objective of this study is to investigate the relationship between hydrological processes and their effects on each other and the selected models.
Material and Method: In the current study, the four sub-basins of Lake Urmia Basin namely Zolachay (A), Nazloochay (B), Shahrchay (C) and Barandoozchay (D) were considered. Precipitation, evaporation and stream flow time series were modeled by linear time series. Fundamental assumptions of time series analysis namely normalization and stationarity were considered. Skewness test applied to evaluate normalization of evaporation, precipitation and stream flow time series and logarithmic transformation function executed for in order to improve normalization. Stationarity of studied time series were evaluated by well-known powerful ADF and KPSS stationarity tests. Time series model's order was determined using modified AICC test and the portmanteau goodness of fit test was used to evaluate the adequacy of developed linear time series models. Man-Kendall trend analysis was also conducted for the precipitation amount, the number of rainy days, the maximum precipitation with 24 hours duration, the evaporation and stream flow in monthly and annual time scales.
Results and Discussion: Inferring to the physical base of ARMA models provided by Salas et al (1998), the precipitation has been considered independently and stochastically. If this assumption is not true in a given basin, it is expected that the MA component of stream flow discharge model be eliminated or washed out. This case occurred in basins A, B and C. In these basins, the behavior of precipitation and evaporation was autoregressive. It was observed that the stream flow discharge behavior also follows autoregressive models that had greater lags than precipitation and evaporation lags. This result proved that the precipitation, evaporation, and stream flow processes in the basin were regular processes. In basin D, the behavior of precipitation was stochastic and followed the MA model, which was related to the stochastic processes. In this basin, the stochastic behavior of precipitation affected the stream flow behavior, and it was observed that the stochastic term of MA also appeared in the stream flow. Thus, this leads to decrease the memory of stream flow discharge. The fact that the MA component in the stream flow discharge was greater than the MA component in precipitation indicated that during the process of producing stream flow discharge from precipitation, the stochastic factors performed an important role.
Conclusion: A comprehensive investigation on hydrological time series models of precipitation, evaporation and stream flow were investigated in this study. The framework of the study consists of trend analysis using Mann-Kendall test and time series. Trend analysis results indicate the significant changes of water resources in the studied area. It means that sustainable development in studied area is greatly threatened. The results of parallel modeling of precipitation, evaporation and stream flow time series showed that the behavior of stream flow models are greatly affected by precipitation models. In other words, this study evaluate the physical concept of ARMA models in real-world monthly time scale for three main hydrologic cycle components and suggest that considering parallel hydrological time series modeling could increase the accuracy to select a model for simulation and prediction of stream flow time series. In addition, it suggested that there is a relation between climate pattern and hydrological time series models.
Keywords: ARMA models, Stationarity, Trend analysis, Water cycle components
J. Behmanesh; E. Rezaie
Abstract
Study of soil hydraulic properties such as saturated and unsaturated hydraulic conductivity is required in the environmental investigations. Despite numerous research, measuring saturated hydraulic conductivity using by direct methods are still costly, time consuming and professional. Therefore estimating ...
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Study of soil hydraulic properties such as saturated and unsaturated hydraulic conductivity is required in the environmental investigations. Despite numerous research, measuring saturated hydraulic conductivity using by direct methods are still costly, time consuming and professional. Therefore estimating saturated hydraulic conductivity using rapid and low cost methods such as pedo-transfer functions with acceptable accuracy was developed. The purpose of this research was to compare and evaluate 11 pedo-transfer functions and Adaptive Neuro-Fuzzy Inference System (ANFIS) to estimate saturated hydraulic conductivity of soil. In this direct, saturated hydraulic conductivity and physical properties in 40 points of Urmia were calculated. The soil excavated was used in the lab to determine its easily accessible parameters. The results showed that among existing models, Aimrun et al model had the best estimation for soil saturated hydraulic conductivity. For mentioned model, the Root Mean Square Error and Mean Absolute Error parameters were 0.174 and 0.028 m/day respectively. The results of the present research, emphasises the importance of effective porosity application as an important accessible parameter in accuracy of pedo-transfer functions.
sand and silt percent, bulk density and soil particle density were selected to apply in 561 ANFIS models. In training phase of best ANFIS model, the R2 and RMSE were calculated 1 and 1.2×10-7 respectively. These amounts in the test phase were 0.98 and 0.0006 respectively. Comparison of regression and ANFIS models showed that the ANFIS model had better results than regression functions. Also Nuro-Fuzzy Inference System had capability to estimatae with high accuracy in various soil textures.
J. Behmanesh; B. Mohammadnejad
Abstract
In most civil projects, such as irrigation and drainage networks constructions, soil stabilization has an important role. Achieving maximum durability against wet-dry cycles is one of the soil stabilization objects. Therefore, depend upon project type and its importance; various hydraulic binders with ...
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In most civil projects, such as irrigation and drainage networks constructions, soil stabilization has an important role. Achieving maximum durability against wet-dry cycles is one of the soil stabilization objects. Therefore, depend upon project type and its importance; various hydraulic binders with different amounts are tested to obtain desirable results from technical and economical view. In this research, the effect of dry-wet cycles on engineering properties of clayey soils (low plasticity) was studied and lime, cement and lime-cement binders, with (2-6) percent of soil weight, were used. The results showed that with changing type and percent of binders, various sample durability against dry-wet cycles is different so that without binder samples did not have durability and the samples stabilized by 4% cement and 4% lime tolerance 12 wet-dry cycles. The results also showed that after dry-wet cycles, the mass and volume of sample were changed and its unconfined compressive strength was decreased so that the decrease of the unconfined compressive strength was between 40% and 60%. The present study showed that dry-wet cycles significantly cause to change the soil geotechnical properties.
B. Mohammadnezhad; J. Behmanesh
Abstract
Bridges are the most important structures in river engineering. One of the most causes in bridges destruction is local scouring around the bridge piers. Many bridges failed in the world because of the extreme scour around piers, which have caused to disappear a lot of investments. Then, it is essential ...
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Bridges are the most important structures in river engineering. One of the most causes in bridges destruction is local scouring around the bridge piers. Many bridges failed in the world because of the extreme scour around piers, which have caused to disappear a lot of investments. Then, it is essential to predict the scour depth around bridge piers. In this research, the Fluent three-dimensional numerical model was used to investigate the scouring around the group cylindrical pier in clear water and uniform sand bed conditions. In this model, sedimentary flow was considered as two-phase flow (water - sand) and Eulerian two-phase model was used. To estimate the parameters of flow turbulence in the water phase, the RNG K-ε model was used. To evaluate and verify the numerical model, the computational results were compared with experimental data. The maximum scour depth in front of the first pier on a numerical model equal to 12.5 cm and in experimental model equal to 12 cm have been measured. Also scour depth at the second pier less than that at the first pier and scour depth at the third pier has been less than the values of the first and second pier .The results showed that the two phase model can simulate the scour phenomena around the pier.
Mohammad Reza Nikpour; Davoud Farsadi
Abstract
Formation of shock waves has an important role in supercritical flows studies. These waves are often occurring during passage of supercritical flow in the non-prismatic channels. In the present study, the effect of length and convergence of contraction wall of open-channel was investigated on hydraulic ...
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Formation of shock waves has an important role in supercritical flows studies. These waves are often occurring during passage of supercritical flow in the non-prismatic channels. In the present study, the effect of length and convergence of contraction wall of open-channel was investigated on hydraulic parameters of shock waves using experimental model. For achieving to this goal, values of depth and instantaneous velocity were measured in various points of shock waves observed in contractions for four Froude Numbers. The results showed that for 63% decreasing the length of contraction, the values of maximum velocity and waves height averagely increased to the amount of 23.6% and 2.77×102%, respectively. Also for the fixed length of contraction, by changing the form of walls from straight-wall to convex-wall the mentioned values averagely decreased to 6.9% and 35.2%, respectively.
A. Fakheri Fard; yaghoub dinpazhoh; F. Ahmadi; J. Behmanesh
Abstract
One of the applicable ways for simulation and forecasting hydrological processes is time series modeling. An important problem in forecasting hydrological data using time series is generating stochastic data. Any changes in stochastic series will change generating data. In this study nonlinear ARCH model ...
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One of the applicable ways for simulation and forecasting hydrological processes is time series modeling. An important problem in forecasting hydrological data using time series is generating stochastic data. Any changes in stochastic series will change generating data. In this study nonlinear ARCH model presented in order to modeling and generating stochastic component of time series. After combing ARCH model with nonlinear bilinear model, BL-ARCH model suggested to forecasting river flow discharge. Daily river flow of Shahar-Chai River located in the west of Urmia Lake and West Azarbaijan province have been used for data analysis and 11 years forecasting. As results shown suggested model with 4.52 error has better than bilinear model with 6.77 error. So this model can be used for short-time river flow forecasting specially daily series.
J. Behmanesh; M. Montaseri
Abstract
Potential evapotranspiration is one of the most important and effective factors for optimizing agricultural water consumption and water resources management. One of methods for prediction of evapotranspiration is to use the time series models. In this research, application of different time series models, ...
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Potential evapotranspiration is one of the most important and effective factors for optimizing agricultural water consumption and water resources management. One of methods for prediction of evapotranspiration is to use the time series models. In this research, application of different time series models, such as AR and ARMA, in order to predicting monthly potential evapotranspiration in Urmia synoptic station were evaluated. In this process, monthly potential evapotranspiration since 1971 to 2010 was determined and the first 35 years and last 5 years were used for model calibration and validation respectively. After selecting the best model, the potential evapotranspiration were predicted for the next 5 years. The results showed that AR(11) time series model had the best results in comparing the other models and the trend of AR(11) time series model had least error. The values of R2 and RMSE in AR(11) model were 0.96 and 1.85 mm/month, respectively.
H. Rezaei; J. Behmanesh; S. Besharat
Abstract
With respect to necessity of the optimum use of water resources and existence of many various optimization methods, in this study 3 kinds of heuristic algorithms have been used including Particle Swarm Optimization, Genetic Algorithm and Simulated Annealing to optimize the operation of Shaharchai dam ...
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With respect to necessity of the optimum use of water resources and existence of many various optimization methods, in this study 3 kinds of heuristic algorithms have been used including Particle Swarm Optimization, Genetic Algorithm and Simulated Annealing to optimize the operation of Shaharchai dam reservoir as an application. The optimization was carried out considering the probability of inflow for a period of 5 years. In order to obtain the best operation of reservoir, monthly release was defined as a second order polynomial according to storage volume and inflow, and different parameters of these algorithms have beenadjusted to minimize the objective function in which supplying the required demand of downstream was defined as the target. The best state of each algorithm is selected through 10 times running of programs (due to intrinsic random behavior of algorithms) and the results comparison leads to realization of which method can perform the best. According to the results, Particle Swarm Optimization method operates more effectively and produces the best results in solving reservoir operation problems. So as an application, control curves of release and storage volume have been extracted for Shaharchai dam reservoir using this method.
H. Naveh; K. Khalili; M. T. Alami; J. Behmanesh
Abstract
One of the important tools in modeling and forecasting of hydrological processes, is using and analysis of time series. The generated river flow series by using time series models have been used in many researches such as drought, flood periods, reservoir systems design and other purposes. The use of ...
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One of the important tools in modeling and forecasting of hydrological processes, is using and analysis of time series. The generated river flow series by using time series models have been used in many researches such as drought, flood periods, reservoir systems design and other purposes. The use of nonlinear time series is very useful in river flow forecasting because of nonlinear river flow behavior in different spatial and time scales. The purpose of this study is to investigate the efficiency of bilinear nonlinear time series model in river flow forecasting. In this research monthly flow of Shahar-Chai and Barandouz-Chai rivers located in West Azarbaijan for duration of 31 and 39 years respectively were used. Despite of simplicity of bilinear nonlinear model, the results showed that this model had high efficiency in modeling and forecasting of two rivers and presented best results from ARMA model. The error of fitted model of Barandouz-Chai (1.605) was less than the model fitted for Shahar-Chai river (1.920). The reason may be due to longer data period for Barandouz-Chai river or it’s recharge from springs and ground waters.
