Abstract
Introduction: Despite being helpful to explore and analyze large multidimensional datasets, visualization Techniques have been rarely considered in hydrology. One of the techniques is Pixel-Based (Raster-Based) graphs. Pixel-based graph is a graphing technique that maximizes displayed information using ...
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Introduction: Despite being helpful to explore and analyze large multidimensional datasets, visualization Techniques have been rarely considered in hydrology. One of the techniques is Pixel-Based (Raster-Based) graphs. Pixel-based graph is a graphing technique that maximizes displayed information using a pixel or raster-based approach.
Materials and Methods: This study two types of raster-based graphs, including Raster-Hydrograph and Raster Hyetograph were evaluated, for Gamasiyab Karstic Spring located in Nahavand. The graphs were drawn by applying discharge and rainfall daily information of gamasiyab spring in 1969-2018. The MATLAB was employed to draw the graphs. To calculate the spring discharge, recorded data from Sang Sorakh and Variane Canal station were used. The data gathered for Sang Sorakh and Variane were recorded from 1969 and 2005, respectively. Thus, the spring discharge was the summation of both stations. The maximum, minimum and average discharge was, respectively, 37.97, 0.3 and 4 m3/s. It is important to note that the basin area is about 60 Km2.
Results and Discussion: By applying the graphs, six different phenomena were investigated:
Snowmelt: According to the raster hydrograph of the Gamasiyab spring, snowmelt occurs in the first 200 to 300 days of year (e.g. early April to late July). According to this graph, during the recent years, snowmelt period shortened. As of 2004, that the number of snowmelt days showed a considerable reduction as compared to the previous years. This issue has become more intense for the years after 2013 indicating a change in the spring discharge regime.
Drought: According to the raster hydrograph of the Gamasiyab spring, droughts were observed in 1998 and 1999.
Storm Flow: According to the raster hydrograph of the Gamasiyab spring, a storm flow was observed in the middle of April,1986. Storm flows were also observed in late February of 1986 and 2005, and the late March of 2016.
Dry Year: Dry Year is a year that the discharge is less than the average. 2008 and 2009 were the examples of dry years. In addition, 2014 was one-year low water.
Dry Month: Determine dry months are used for baseflow separation. In dry months, discharge is due to baseflow, and rainfall and snowmelt play a very small role in the discharge.
Monthly changes: Monthly changes happen when rapid changes in discharge are observed from one month to another. For example, the discharge regime suddenly changes from a dry to wet condition. According to the raster hydrograph of the Gamasiyab spring, the monthly changes in April and May, 2014 were observed. It was observed that the rainfall was almost equal to 0 in June to September. In the other words, rainfall period is from early November to early June. Maximum rainfall is in April and May.
Better results can be achieved by using both Raster Hydrograph and Raster Hyetograph. Discharge of Gamasiyab spring is affected by snowmelt and groundwater flow since late May to late September, and rainfall has no effect on spring discharge in this period. According to these graphs, it can be also concluded that springtime rainfall was impacted with one-month lag time. According to raster hydrograph, the minimum discharge occurs in October, however, the area receives rainfall during October based on raster Hyetograph. Therefore, the discharge increase in the November can be attributed to the precipitation falling during October.
Conclusion: Main benefits of this graphs are: 1. a way to view large datasets. 2. Quickly review and interpret. 3. Develop new types of products. 4. Cost and time efficiency. This method is able to show systematic error, missing data, outliers, comparison different places, potential new products. Results show that the snowmelt period in Gamasiyab spring decreased from 1969 to 2018. This period shortened from 100 to 30 days per year. The year of 2008 was the driest year during the statistical period of the spring, and a drought was also observed in 1998. According to raster hydrograph, the driest month was found to be October. Determining this month is very useful for base flow separation. One can conclude that these graphs including large amount of information, accelerate the processes of scanning and interpretation.
hadi ansari; safar marofi
Abstract
Introduction: Snow water equivalent (SWE) provides important information for water resources management and recently has attracted the attention of many researchers using remote sensing. Remote sensing presents a possibility for observation of snow characteristics, like water equivalent, over larger ...
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Introduction: Snow water equivalent (SWE) provides important information for water resources management and recently has attracted the attention of many researchers using remote sensing. Remote sensing presents a possibility for observation of snow characteristics, like water equivalent, over larger areas. Validation of remote sensing data of snow water equivalent (SWE) has always been an important issue for the researchers. Previous studies have assessed the global SWE data. Although it has been tried by using large-scale models of the world to estimate SWE, but regional effects such as snow density, topography and local meteorological conditions may lead to uncertainty.
Materials and Methods: The Northwestern Iran was selected as the study area in this research. Reasons for choosing this area are being mountainous with much snowfall. Also this region compared to the other parts of Iran, has more dense snow survey stations. In this study the AMSR-E sensor data and Global Land Data Assimilation System (GLDAS) was used to estimate SWE in the basins of the northwestern Iran. After processing AMSR-E sensor data and GLDAS model with related software, SWE was estimated in the snow survey stations and evaluated with observed data. To specify the snow density effect on SWE data in AMSR-E sensor from the snow density data, the stations were used. To determine the accuracy of estimation of SWE at different heights, snow survey stations is arranged by considering height and were divided into four height classes that contain enough observational data to evaluate computational data in each height class. To verify SWE obtained estimations in the stations, Root Mean Square Error (RMSE) and Pearson correlation coefficient (r) assessment criteria were used. After evaluating, the SWE data of AMSR-E sensor and GLDAS model for the GLDAS model monthly data to estimate SWE was used for the period 2000 to 2015. With calculating average annual SWE from monthly data, SWE trend changes in mentioned period, the moving averages graphs 3, 5 and 7-year-old was drawn.
Results and Discussion: According to the obtained results, SWE computational data with observational data had significant correlation at the 1% level. Using in situ snow densities, the correlation coefficient between AMSR-E and situ SWE increased from 0.27 to 0.55. The results showed that the best estimation of SWE is in the stations, which have the height of 1,350 to 1600 meters. Also with increasing altitude, the estimation accuracy is significantly reduced. In most years maximum of the SWE was obtained in January and February and in the period of June to September, the area was out of snow storage. According to the average annual SWE and moving averages graphs 3, 5 and 7-years old, the SWE of Northwestern Iran basins in period 2015-2001 has a reducing trend.
Conclusions: In the regions like the Northwestern Iran mountainous where snowfall constitutes a significant fraction of total precipitation, the snowpack delays the resulting runoff into the time of year where water demand is greater. So measurement of snow on the ground has been an important component of hydrologic forecasting for a century. Various remotely sensed snow data have been widely utilized for cold regions to explore the relationships between snow distribution, river discharge, and climate change. The accuracy of remotely sensed snow products should be well understood and incorporated in any investigations using such data. The main objective of the present study was to quantitatively compare the AMSR-E and GLDAS model for an understudied region of the earth. AMSR-E global SWE data and GLDAS data were compared by situ SWE measurements performed in the snow courses. The results showed that the snow density is an effective factor in derived algorithm for the SWE AMSR-E data. Also with increasing height, precision of the estimation significantly decreased. The determination of SWE from satellite imagery in progress updated with new learning. The obtained results from passive microwave in smooth terrain are promising, but involvement of different mechanisms become more complicated as the terrain gets more complex. Nevertheless, it is believed that if the above discussions are taken into account, AMSR-E would provide valuable SWE information even for a mountainous region like Northwestern Iran. It is also hoped that this study would be a starting point in the water scarce, developing Iran to plan and use the limited supply in a suitable manner.
Omid Nasiri-Gheidari; Safar Marofi
Abstract
Introduction: Due to the rapid rate of population growth, water resource topics wasmainly affected by the economic and social components, however, the importance of environmental issues in such projects has gained more attention. As pollution loads are increasing, it has become more essential to incorporate ...
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Introduction: Due to the rapid rate of population growth, water resource topics wasmainly affected by the economic and social components, however, the importance of environmental issues in such projects has gained more attention. As pollution loads are increasing, it has become more essential to incorporate water quality in water resource management issues. Under this condition, optimal water allocation by considering multiple objectives of water quality and quantity issues can lead to sustainable and optimal benefit of stakeholders. This study was done in order to balance environmental and economic concerns in water resource allocation.
Materials and Methods: Based on game theory concepts and fuzzy programming procedure, two new methodologies were developed for sustainable water resource allocation in river systems. The proposed methods which include a multi-objective bargaining and fuzzy programming approaches were utilized to analysis strategies of interaction between environmental protection and economical income. Two groups of players, consists of player 1 for environmental and player 2 for economic issues were considered in order to apply the developed models. As players will not be satisfied with the outcome of each other, they will begin the bargaining process. Throughout the bargaining rounds, players will reduce their expectations. After several negotiations, the interval between the reset goal values and outcomes will be decreased. The bargaining process will be finished if final solutions reach to the determined goals. In the study, the Total Dissolved Solids (TDS) were considered as water quality indicators of environmental objective function, since salinity is the important problem of the study area. Using crop production function in economic income objective function makes it possible to incorporate deficit irrigation in different crop growth stages. Since allocation problems include many decision variables, conventional (non-linear) crop production function will have high computational costs and linear form of it can reduce the complexity of the optimization model. Therefore,additive (linear) form of crop production function was taken into consideration instead of multiplicative form. Total pollution load discharged into the river (ton per year) and economical income of the system (thousand dollars per year) wasconsidered as environmental and economic values, respectively. During the fuzzy programming procedure, the purpose is to achieve a compromise solution. In this approach, the individual maximum and minimum values of objectives is used to define the membership function. This procedure will maximize the satisfaction degree of the constructed membership functions of the objectives. The presented methodology was illustrated in a part of Karoon-Dez river system between Gotvand dam, Dez dam and Ahvaz city, as a case study. The area of Karoon-Dez river basin is about 67000 square kilometers and it is located in the southwestern part of Iran. The selected area includes 8 agro-industrial and 3 traditional agricultural sub-sectors.
Results and Discussion: Using a linear form of crop production function for calculating the total benefit of the system leads to significant reduction in run-time of the optimization model and make irrigation programming possible by regarding crop growth stages and the available water amount. The results of this study showed that Nash equilibrium, which provides a base for decision makers to choose a strategy, was reached at the fourth round of bargaining process. Moreover, balance between economic and environmental objectives is available by reducing economical expectation and environmental concerns from 553636 to 496216 thousand dollars per year and from 68264 to 87251 tons per year, respectively. In these cases, the annual allocated water to environmental and economical player will be 6123 MCM (5318 to agro-industrial sub-sectors and 805 to agricultural sub-sectors) and 6453 MCM (5730 to agro-industrial sub-sectors and 723 to agricultural sub-sectors) respectively. The results of the fuzzy programming approach demonstrated that at optimal condition, environmental and economic objective function was 85999 tons per year 500422 thousand dollars per year, respectively and allocated water to water users are 6354 MCM per year (agricultural and agro-industrial sub-sectors of the system will be (763 and 5591 MCM per year). Agro-Industrial sub-sector 3 will take the maximum allocated annual water (1789 MCM per year) and Agro-Industrial sub-sector 5 will receive the minimum annual allocated water (151 MCM per year). Comparison of two investigated approaches showed that their results are in agreement with each other.
Conclusions: Results of applying the developed methodology to the Karoon-Dez river system demonstrated that it is effective and applicable to determine sustainable water allocation policies. Finding of this study reveals that the proposed framework can facilitate decision-making process and optimize allocated water to different water users under conflicting objectives. Therefore, the developed procedure can be used as a managerial tool for optimal water allocation strategies, which is in accordance with sustainable development approach. It is easy to apply the presented methodology to other river systems with high pollution loads of agricultural return flows.
M. Shakarami; S. Marofi; Gh. Rahimi
Abstract
Introduction: Arid and semi-arid areas are confronting increasing water shortages. In these regions of the world, planners are being forced to consider other water sources that could be used economically and effectively to promote further development. Wastewater is the only potential water source, which ...
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Introduction: Arid and semi-arid areas are confronting increasing water shortages. In these regions of the world, planners are being forced to consider other water sources that could be used economically and effectively to promote further development. Wastewater is the only potential water source, which will increase as the population grows and the demand on freshwater increases. Composting municipal solid wastes (MSW) and sewage sludge is a good way to reduce the amount of wastes generated in densely populated areas. Municipal solid waste production in Asia in 1998 was 0.76 million tons per day, with an annual growth rate of 2- 3% in developing countries and 3.2- 4.5% in developed countries. (MSW) compost is increasingly used in agriculture not only as a soil conditioner but also as a fertilizer. Despite the growing interest in wastewater and compost usage, excessive application of them may have some harmful effects such as human health problems, runoff and leaching of nutrients to surface and groundwater, undesirable chemical constituents, pathogens, accumulations of heavy metals in plants and soils, negative environmental and health impacts. So, using of wastewater and compost application should be under controlled conditions that minimize health risks of agricultural products.
Materials and Methods: This study was conducted in greenhouse of Bu-Ali Sina as a factorial completely randomized design to evaluate the effects of wastewater and compost on physical and chemical properties of soil. The factors included four types of watering: raw wastewater (W1), treated wastewater (W2) combined 50% of raw wastewater and fresh water (W3) and tap water (W4) and also four compost levels: 0 (C1), 40 (C2), 80 (C3) and 120 tha-1 (C4). Therefore, 16 treatments (W1C1 to W4C4) were considered for investigation. It is noted that Compost added and mixed just with top layer of the soil. 48 volumetric lysimeters were applied as Cultivation beds (26 × 30 × 30 cm). The soil had three layers: the upper layer (Clay texture), the middle layer (clay loam) and the bottom layer (sandy clay loam). After beds preparation, basil (Ocimum Basilicum) was planted in them. Due to the lack of an active wastewater treatment plant in the region, raw and treated wastewaters were transported from Kermanshah, the nearest city to Hamedan. Also, municipal compost was prepared from Kermanshah Compost Company.At the end of cultivation period, the soil samples (from 0-15 cm) were collected and the amount of physical (hydraulic conductivity, bulk and particle density and porosity)and chemical (nitrogen, phosphorus and potassium) properties were measured.
Results and Discussion: The results showed that the water quality has a significant effect on all parameters and the amount of compost has significant effect on all parameters except bulk density. But, the amount of all parameters (except hydraulic conductivity) was not influenced by interaction between water quality and compost levels. In all treatments, the range of hydraulic conductivity, bulk density, particle density and total porosity were varied between 23.82 to 35.61 mmh-1, 1.41 to 1.43 grcm-3, 2.51 to 2.57 grcm-3 and 42.88 to 45.19 %, respectively. Also the range of nitrogen, phosphorus, and potassium were varied between 0.06 to0.08 %, 14.64 to232.28mgkg-1,and 393.22 to519.84mgkg-1,respectively.Overall, the results indicated that using compost and wastewater increased hydraulic conductivity, porosity, nitrogen, phosphorus, and potassium of the soil in comparison to the control. Whereasbulk and particle density of soil decresed by using compost and wastewater (as a mixed material).
Conclusion: In this study, we investigated the effect of wastewater and compost on some of soil physical properties (hydraulic conductivity, bulk density, particle density and total porosity) and also some of chemical properties of soil nitrogen, phosphorus and potassium).The results showed that the use of wastewater and compost on soil physical condition has a positive effect.Wastewater and compost by improving the soil pore size distribution, decreased the bulk and particle density and increased porosity and hydraulic conductivity of the soil. The impact of wastewater and compost to improve the physical properties, commensurate with the level of wastewater treatment and composting rate in the soil. Also using the wastewater (raw wastewater, treated wastewater and combined 50% of raw wastewater and fresh water) and compost (40, 80 and 120 tha-1), compared to the control (fresh water and soil without compost), increased total of nitrogen, phosphorus and potassium of soil. But, due to the risks of soil salinity and nitrogen leaching, it is suggested that longterm exposure to wastewater and compost needs a careful practical management.
H. Zreabyaneh; M. Bayat; S. Marofi; R. Amiri Chayjan
Abstract
Abstract
The present study is attempted to present the minimum required meteorological parameters for reference evapotranspiration estimation at Hamedan region of Iran from 1997 to 1998. Employing Pierson test, six meteorological parameters which are used by Penman-Montieth FAO-56 method including maximum ...
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Abstract
The present study is attempted to present the minimum required meteorological parameters for reference evapotranspiration estimation at Hamedan region of Iran from 1997 to 1998. Employing Pierson test, six meteorological parameters which are used by Penman-Montieth FAO-56 method including maximum and minimum air temperature, maximum and minimum relative humidity, wind speed and daily sunshine were composed and considered as 4 difference scenarios (called 1, 2, 3 and 4). These scenarios were applied to artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for reference evapotranspiration estimation of the area using the Matlab software. The results of the scenarios were evaluated using the actual reference evapotranspiration (lysimeter data). The results showed that increasing of number of input layers data could not be based as obtaining the more exact results. Using the scenario 2, which was based on minimum and maximum temperature as well as daily sunshine, showed more reliable results using the ANN and ANFIS methods. The root mean square error (RMSE), mean absolute error (MAE) and R2 of examination step of this scenario were 0.09, 0.07 mm/day and 0.9, respectively. Overall, the statistic performances revealed that ANN and ANFIS had the same results and similar input layer sensitivity. The iteration times of the ANN and ANFIS methods to reach the best results were 26 and 40, respectively. Comparison between ANN (RMSE= 0.09 mm/day) and standard Penman-Montieth method (RMSE= 0.34 mm/day) confirmed that the intelligence approaches such as ANN are more accurate for reference evapotranspiration estimation.
Keywords: Reference evapotranspiration, Pierson test, Intelligence methods, Hamedan
H. Zreabyaneh; A. Ghasemi; M. Bayat; S. Marofi
Abstract
Abstract
Evapotranspiration as one of the important elements in agriculture has a considerable role in water resource management. Therefore, using a more exact estimation method is an essential step of agricultural development, especially in arid semi-arid area. In this research, in order to exact estimate ...
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Abstract
Evapotranspiration as one of the important elements in agriculture has a considerable role in water resource management. Therefore, using a more exact estimation method is an essential step of agricultural development, especially in arid semi-arid area. In this research, in order to exact estimate of garlic evapotranspiration using lysimeteric data, an artificial neural network (ANN) model was developed. Maximum and minimum air temperatures, maximum and minimum relative humidity values, wind speed and sunshine hours were used as the input layer data. The crop evapotranspiration was measured using 4 lysimetres of 2×2×2m of the Bu-Ali Sina agriculture collage’s meteorology station during 2006-2008. Statistic indicators RMSE, MAE, STDMAE R2 were used for performance evaluation of the models. The results showed the more exact method concerned to the multilayer perceptron (MLP) model with the back propagation algorithm. The 6-6-1 layout with Levenberg-Marquat rule and sigmoid function had the best topology of the model. The evaluation criteria were 0.088, 0.07 and 0.061 mm/day as well as 0.88, respectively. The results also showed that the average daily garlic evapotranspiration were 8.3 and 6.5 mm based on the lysimeter ANN methods, respectively. Overall, evaluation of ANN results showed that the errors of ANN were negligible. The ANN showed high and low sensitivity to maximum air temperature and minimum relative humidity, respectively.
Key words: Artificial Neural Networks, Evapotranspiration, Lysimeter, Garlic, Hamedan
