Saeid Okhravi; Saeid Eslamian; nader fathianpour
Abstract
Introduction: Horizontal subsurface flow constructed wetlands have long been applied to improve water or wastewater quality. Previous studies on wetland systems have focused on trying to comprehend the processes leading to the removal of pollutants. Comparatively, there have been fewer studies dedicated ...
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Introduction: Horizontal subsurface flow constructed wetlands have long been applied to improve water or wastewater quality. Previous studies on wetland systems have focused on trying to comprehend the processes leading to the removal of pollutants. Comparatively, there have been fewer studies dedicated to the assessment of flow distribution on hydraulic behavior through the wetland. Researchers declared the aspect ratio (length to width ratio), inlet-outlet configuration, the size of the porous media and the loading rate of constructed wetland could influence hydraulic retention time (HRT). Su et al. (2009) have stated that in free water surface constructed wetlands, when the aspect ratio is greater than 5, the hydraulic efficiency will reach 0.9, or even higher. If the project site or field area cannot meet the theoretical standard, the recommended aspect ratio is higher than 1.88 to ensure some hydraulic efficiency greater than 0.7. The present study was an attempt to analyse, with the aid of 3D numerical simulation and tracer study, how flow distribution affected hydraulic behavior by using 3 different input flow layouts.
Materials and Methods: The treatment system consisted of a horizontal subsurface flow in a constructed wetland having an aspect ratio of 6.5 and the bed slope of one percent. The geometry of this system, which was 4 m wide × 26 m long × 1 m deep, was planted with Phragmites australis. Inlet configurations were selected as a variable parameter. Three different inlet flow configurations including midpoint-midpoint (A), corner- midpoint (B) and uniform-midpoint (C), with the same fixed outlet configurations, were studied. The average flow discharge in each configuration was 6.58, 6.52 and 6.4 m3/day, respectively. Dye tracer was used to draw retention time distribution curves in each configuration for assessing the internal dispersion, short-circuiting and hydraulic parameters such as effective volume rate which is derived by division of mean retention time per nominal retention time. The 3D model presented, which was built on the Comsol Multiphysics platform, was implemented for fluid flow to show internal hydraulic patterns in the system. Hence, the hydraulic model used the Darcy equation to simulate a stationary water flow through the bed. The simulations were verified by using real data obtained from the existing constructed wetland. It was mostly used to show pressure throughout the system for each configuration of the inlet and the outlet.
Results and Discussion: The mean retention time for each configuration was found to be 4.53, 3.24 and 4.65 days, respectively. A marked reduction of the mean hydraulic retention time signified leaving tracer concentration from the outlet rapidly, high short-circuiting and dead volume and finally defective treatment process influenced by changing the inlet to the corner. According to tracer breakthrough curve, the effective volumes for configurations A and C were 87.5%, as compared to 62.1% for the configuration B. The two-day difference of tpeak between configurations 2 and 1, and 3 was probably due to the establishment of preferential streamlines resulting in short-circuiting and areas of dead volume in the system. The value of tpeakis related to dispersion, in the sense that a retention time distribution curve with a small peak time generally contains low dispersion. Simulation results showed the pressure difference from the inlet to the outlet ranged from 12-14, 14-15 and 10-13 cm H2O for A, B and C layouts, respectively. It was shown that the maximum pressure gradient occurred at the outset of the influent wastewater at the inlet, and it was gradually reduced to the lowest values at the outlet ports. Consequence of surface pressure demonstrated uniform pressure from inlet toward outlet at configuration C. Simulated streamlines approved this result, while range of high and low pressure area at configuration B was the most. There was a strong association between tracer experiments and simulation works. One of the major findings of this study was the significant shorter hydraulic mean retention time of the corner inlet setup. There are many that may cause these effects, although short-circuiting may be the primary one. A large low-pressure zone appeared at the opposite corner that was neither inlet nor outlet in this configuration.
Conclusions: This paper investigated the hydraulic performance and short-circuiting effects on water flow due to three different inlet patterns (i.e. midpoint, corner, and uniform) in horizontal subsurface flow wetlands based on dye tracer measurements and numerical modeling. The results showed that the uniform inlet could provide the highest hydraulic efficiency (i.e. longest hydraulic retention time, HRT), in comparison to other two setups. The performance of the three different layouts was also investigated in terms of hydraulic parameters. Short-circuiting was influenced by lower hydraulic retention time, leading to inadequate treatment. Uniform-midpoint and midpoint-midpoint yielded the best effective volume as compared to the corner-midpoint. It was demonstrated that these two cases increased dispersion and used the whole capacity of the constructed wetland for the treatment process. The most important result of this paper was the evaluation of internal hydraulic pattern thorough the wetland, something not investigated in previous research works. Based on the simulation results, the spatial pressure distribution in wetland cells was depicted. Finally, it can be concluded that the best configuration of inlet-outlet layout based on both numerical simulations and physical experiments is uniform-midpoint. Meanwhile, midpoint-midpoint is preferable to corner-corner by all performance criteria.
farshad kiani; Behroz Behtari nejad; Ali Najafi nejad; Abdolreza Kaboli4
Abstract
Introduction: population growth, urbanization and land use changes cause negative effects in natural ecosystems and water resources. Soil erosion is one of the most important problems in agriculture and natural resources of Golestan province. Using low cost and accurate methods for planning and proper ...
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Introduction: population growth, urbanization and land use changes cause negative effects in natural ecosystems and water resources. Soil erosion is one of the most important problems in agriculture and natural resources of Golestan province. Using low cost and accurate methods for planning and proper management of land and water resources are essential for estimating consequences of soil erosion and providing appropriate solutions to reduce soil losses.
Materials and Methods: The study area is located in eastern part of Golestan province with an area of 1524 square Kilometers. The average annual precipitation of the region is 496 millimeters. In this watershed, rainfall decreases from south and south west to north and north east (due to the remoteness from the Caspian Sea), while evapotranspiration, temperature and the number of dry months increase in the same direction. Also the average annual temperature of the watershed and its relative humidity and evaporation are 17.8°C, 68.5 % and 1398.34 millimeters, respectively. Tamer watershed was divided into 15 sub-watersheds by adding an outlet in the site of Tamar gauging station. In this study, the SWAT model was used to simulate erosion and sedimentation. To compare the measured and simulated data and evaluation of the SWAT performance in terms of simulating flow and sediments, daily flow (cubic meters per second) and sediment (tons per day) data at the Tamar gauging station located in Tamar’s watershed outlet was collected from the studies of water resources organization (Tamab). Simulated values were generally consistent with the data observed during calibration and validation period. At this stage of calibration, the SUFI-2 model was used to optimize the parameter values. In this study, daily rainfall and temperature data recorded during an 8-year period by the stations within the watershed were imported into the model. The daily discharge data and daily sediment data of Tamar station recorded during 1999- 2006 were selected. Then model was run using runoff and sediment parameters, and ranges of parameters were adjusted at each iterations, and therefore SWAT model was calibrated using SUFI-2 model. After calibration, model must be validated and its ability to predict future events must be determined. Validation was performed using the runoff and sediment data recorded in Tamar gauging station from 2007 to 2010.
Results and Discussion: NS, R2, R-factor and P-factor were estimated for runoff calibration about 0.76, 0.77, 0.06 and 69 and for runoff evaluation 0.72, 0.75, 0.05 and 69 respectively. The same parameters were also measured for sediment calibration about 0.54, 0.62, 0.15, and 16 and sediment evaluation 0.55, 0.61, 0.35, and 12 respectively. The results showed that irrigated agriculture 24.95 and 15.56 t ha -1y-1 respectively, with average erosion and sediment ha of agriculture by an average of 20.23 and 12.33 t ha -1y-1 respectively erosion and sediment erosion and deposition are tons per hectare maximum value. Results also showed that the soil loss caused by erosion in this watershed is average 6.49 t ha -1y-1 in sediment and 10.28 t ha -1y-1 in erosion.
Conclusion: The assessment factors showed that model has successfully simulated the daily runoff discharge during calibration and validation phases with a Nash-Sutcliffe coefficient of 0.76 and 0.72. A Nash-Sutcliffe coefficient above 0.5 could be acceptable for sediment simulation. However, sediment load simulated for rainy seasons has been lower than actual value while this value has been higher than actual value during dry seasons. In most months of the year, model results are higher than measured values and this issue is more pronounced in the peak runoffs. This issue is due to limitations in spatial distribution of rainfall, so when a small area in watershed experience a severe rainfall, model considers the impact for the entire watershed and therefore overestimates the total runoff. The results showed that SWAT model can be a useful tool for the simulation of flow and sediment basins in the loess land.
Simulation results showed that land use changes have resulted in corresponding increases in surface runoff and sediment. Rates were highly variable both spatially and temporally, and the agricultural lands were most significantly affected. These land use changes have negative implications for the ecological health of the river system as and local communities.
Ali Barikloo; Parisa Alamdari; kamran Moravej; Moslem Servati
Abstract
Introduction: In recent decades, the most important issue for agricultural activities is maximizing the productions. Today, wheat is grown on more lands than any other commercial crops and continues to be the most important food grain source for humans. Sustainable agriculture is a scientific activity ...
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Introduction: In recent decades, the most important issue for agricultural activities is maximizing the productions. Today, wheat is grown on more lands than any other commercial crops and continues to be the most important food grain source for humans. Sustainable agriculture is a scientific activity based on ecological principles with focus on achieving sustainable production. It requires a full understanding of the relationships between crop production with soil and land characteristics. Furthermore, one of the objectives of sustainable agriculture is enhancing the agricultural production efficiency through applying proper management, which requires a deep understanding of relationships between production rate, soil and environment characteristics. Hence, the first step in this process is finding appropriate methods which are able to determine the correct relationships between measured characteristics of soil and environment with performance rate. The aim of this study was evaluating the performance of neuro-genetic hybrid model in predicting wheat yield by using land characteristics in the west of Herris City.
Materials and Methods: The study area was located in the northwest of east Azarbaijan province, Heris region. In this study, 80 soil profiles were surveyed in irrigated wheat farms and soil samples were taken from each genetic horizon for physical and chemical analyses. In this region, soil moisture and temperature regimes are Aridic border to Xeric and Mesic, respectively. The soils were classified as Entisols and Aridisols. We used 1×1 m woody square plots in each profile to determine the amounts of yield. Because of nonlinear trend of yield, a nonlinear algorithm hybrid technique (neural-genetics) was used for modeling. At first step, the average weight of soil characteristics (from depth of 100 cm) and landscape parameters of selected profiles were measured for modeling according to the annual growing season of wheat. Then, land components and wheat yield were considered as inputs and output of model, respectively. For this reason, genetic algorithm was investigated to train neural network. Finally, estimated wheat yield was obtained using input data. Root mean square error (RMSE) and Coefficient of determination (r2), Nash-Sutcliffe Coefficient (NES) indices were used for assessing the method performance.
Results and Discussion: The sensitivity analysis of model showed that soil and land parameters such as total nitrogen, available phosphorus, slope percentage, content of gravel, soil reaction and organic matter percentage played an important role in determining wheat yield in the studied area. The soil organic matter and total nitrogen had the highest and lowest correlation with wheat yield quantity and quality, respectively, indicating the total nitrogen was the most important soil property for determination of wheat yield in our studied area. We found that network learning process based on genetic algorithms in the learning process had lower error. The findings showed that beside of confirming the desired results in the case of using sigmoid activation function in the hidden layer and linear activation function in the output layer of all neural networks, it is demonstrated that the proposed hybrid technique had much better results. These findings also confirm better prediction ability of neural network based on error back propagation algorithm or Levenberg-Marquardt training algorithm compared to other types of neural network confirms.
Conclusion: Using nonlinear techniques in modeling and forecasting wheat yield due to its nonlinear trend and influencing variables is inevitable. Recently, genetic algorithms and neural network techniques is considered as the most important tools to model nonlinear and complex processes. Despite the advantages of these techniques there are a lot of weaknesses. Imposing specific conditioned form by researchers in the techniques of genetic algorithms and stopping neural network learning at the optimal points are the main weaknesses of these techniques, while searching for global optimal point and not imposing a specific functional forms are the robustness of genetic algorithm techniques and neural networks, respectively. Results of this study indicated that the proposed hybrid technique had much better results. Correlation coefficient (0.87) and average deviation square error (473.5) were high and low, respectively. It can be concluded that the surveyed soil properties have very strong relationship with the yield. Implementation of appropriate land management practices is thus necessary for improving soil and land characteristics to maintain high yield, preventing land degradation and preserving it for future generations required for sustainable development.
azam gholamnia; mohammadhosein mobin; atefe jebali; hamid alipor
Abstract
Introduction: Solar radiation (Rs) energy received at the Earth's surface is measured usingclimatological variables in horizontal surface and is widely used in various fields. Domination of hot and dry climates especially in the central regions of Iran results from decreasing cloudiness and precipitation ...
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Introduction: Solar radiation (Rs) energy received at the Earth's surface is measured usingclimatological variables in horizontal surface and is widely used in various fields. Domination of hot and dry climates especially in the central regions of Iran results from decreasing cloudiness and precipitation and increasing sunshine hours, which shows the high potential of solar energy in Iran. There is a reasonable climatic field and solar radiation in most of regions and seasons which have provided an essential and suitable field to use and extend new and pure energy.
Materials and Methods: One of the common methods to estimate the solar energy received by the earthis usingtemperature variables in any place . An empirical model is proposed to estimate the solar energy as a function of other climatic variables (maximum temperature) recorded in 50 climatological, conventional stations; this model is helpful inextending the climatological solar-energy estimation in the study area. The mean values of both measured and estimated solar energy wereobjectively mapped to fill the observation gaps and reduce the noise associated with inhomogeneous statistics and estimation errors. This analysis and the solar irradiation estimation method wereapplied to 50 different climatologicalstations in Iran for monthly data during1980–2005. The main aim of this study wasto map and estimate the solar energy received in four provinces of Yazd, Esfahan, Kerman and Khorasan-e-Jonoubi.The data used in this analysis and its processing, as well as the formulation of an empirical model to estimate the climatological incident of solar energy as a function of other climatic variables, which is complemented with an objective mapping to obtain continuous solar-energy maps. Therefore, firstly the Rswasestimated using a valid model for 50 meteorological stations in which the amounts of solar radiation weren't recorded for arid and semi-arid areas in Iran. Then, the appropriate method was selected to interpolate by GS+ software and after that, the seasonal maps of the received solar energy over the ground surface were produced by GIS software. The best fitof the Gaussian model was determined in winter with the lowest residual error and the highest correlation 1.87 and 0.913respectively, in spring with the lowest RSS and highest R23.87 and 0.86 respectively and during summer with RSS and R2, 5.9 and 0.851 and the exponential model in autumn withthe RSS and R2, 3.61 and 0.88..
Results and Discussion: Naturally, some of the differences in the mean solar energy among the stations may be related to inter annual variability rather than to differences in the climatic, radiative regimes. If different periods for the climatological estimations are used, the resulting mean values can be representative of the regional climatic regime of solar energy. The results showed that 53% of Yazd province Received 26 Mj / m2.day, in summer.In winter, more than 80% of Yazd province received 15 Mj / m2.day radiation. Kerman compared to other provinces received high solar radiation, especially this feature wasmore pronounced in winter because in this season compared to Yazd, Kerman radiation didnot only showed greater range, but also about 40% of the province's total area received 16 Mj / m2.day radiation, whereas Yazd no radiation was received during this season. Because Kerman is located in the southeast of region and itreceived more solar radiation than other provinces.In this study, the amount of solar energy in surface of 4 provinces including Yazd, Esfahan, Kerman and South Khorasan in arid and semiarid regions of Iran was estimated by the geostatistic. Seasonal mean values of solar energy absorbed at the surface of 4 stationswascalculated. The results showed that Kerman with receiving 27.25 (Mj m-2. D-1) averagely has the most received solar energy and Esfahan with 21.54 (Mj m-2. D-1) during the summer has received the least solar energy. The limited records of solar energy used in thisanalysis madethe analysis of long-term variations impossible. This paper wasthe first stage of a more extensive study which involvedmonitoring the behavior of photocells under real environmental conditions, which allowedto obtain efficiency curves used in the mapping of actual photovoltaic potential inarid and semiarid regions of Central Iran. This analysis must be complemented by better, higher resolution estimates of the incident solar energy; a viable alternative for such a task is the use of satellite observations. However, a better photovoltaic prospection, with high quality data, is necessary.
H. Kashi; H. Ghorbani; S. Emamgholizadeh; S.A.A. Hashemi
Abstract
With respect to the problem of direct measurement of soil parameters in recent year using indirect method such as artificial neural networks has been considered. In the present study, 200 soil samples were collected from Ghoshe location in Semnan province. Half of samples were collected from disturbed ...
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With respect to the problem of direct measurement of soil parameters in recent year using indirect method such as artificial neural networks has been considered. In the present study, 200 soil samples were collected from Ghoshe location in Semnan province. Half of samples were collected from disturbed agricultural lands and the other half were collected from undisturbed nearby lands. Some soil chemical as well as physical properties such as electrical conductivity (EC), soil texture, lime percentage, sodium adsorption ration (SAR) and bulk density were considered as easy and fast obtainable features and soil cation exchange capacity as difficult and time consuming feature. The collected data randomly divided in two categories of training (70%) and testing (30%) and they used for train and test of two artificial neural networks, multi-layer perception using back-propagation algorithm (MLP/BP) and Radial basis functions (RBF) and nonlinear regression model. Results of this research show high efficiency of artificial neural network compared with nonlinear regression and also MLP network was better than RBF network. Sensitivity analysis was also performed for all parameters to find out the relationship between soil mentioned parameters and soil cation exchange capacity for both disturbed and undisturbed soils. At last, the correlation between soil parameters and soil cation exchange capacity was determined and most important parameters which could influence the soil cation exchange capacity were described.
