Showing 193 results for Ssi
M. Kyanpoor Kal Khajeh, Me. Pajouhesh, S. Emamgolizadeh,
Volume 26, Issue 3 (12-2022)
Abstract
Humans are always trying to change land to use natural resources to meet their needs. One of the land use changes that take place in order to benefit from sustainable water resources is dam construction. Dam construction has many positive and negative consequences for the environment from the beginning to use. The objective of this study was to investigate the effect of Gotvand Dam on the problem of collision of water flow path with salt domes and large volume accumulation of salt behind the dam lake. Images of the Landsat 5 satellite TM sensor for 1991, Landsat 7 satellite ETM+ sensor for 2008, and Landsat 8 satellite OLI sensor for 2020 were used to classify images, and prepare land use maps of the studied basin. Reviewing and evaluating the land use maps of the study area showed that agricultural lands are being developed after the operation of the dam. Also, barren lands were decreasing as well as the area's water content was increasing during the study period. In the second period of study (2008-2020), the population of the regions with an increasing area has been increasing. Also, the rangeland and meadows had a decreasing trend during the first and second periods. The results of classification accuracy using the object-oriented method for three periods of 1991, 2008, and 2020 were obtained as 0.92, 0.97, and 0.93, respectively. In general, it can be stated that the construction of the dam has increased the area under cultivation of land and by increasing population and urbanization in the construction area of the dam, destruction and reduction of rangelands occurred.
E. Masoumi, R. Ajalloeian, A.a. Nourbakhsh, M. Bayat,
Volume 26, Issue 3 (12-2022)
Abstract
Since clay is widely used in most construction projects, the issue of improving clay soils has considerable importance. This study aimed to optimize the variables affecting the properties of geopolymer and improve their mechanical properties using Isfahan blast furnace slag. Taguchi's statistical design method was used to model three process variables (blast furnace slag, water, and alkali sodium hydroxide agent) with four different values in the mixing design. Geopolymer was used to optimize the uniaxial compressive strength. Sixteen geopolymer compositions determined by mini-tab software were prepared and their uniaxial compressive strength was measured. The obtained results were modeled by analysis of variance, and then the interactions of the three variables on the uniaxial compressive strength of geopolymer were investigated using two and 3D diagrams. Then, the variables were optimized and the proposed values for the optimal sample were examined at temperatures of 25, 50, and 70°C and at times of 3, 7, 14, and 28 days of operation. A comparison of the results predicted by the models and the results of the experiments confirmed the validity of the models. Also, the scanning electron microscopy (SEM) images showed that the porosity will reduce from 7 to 28 days. It indicated that the use of the geopolymerization method has a significant role in stabilizing weak clay soils with low plasticity. The effect of fibers and geopolymer to reinforce was also investigated and for better evaluation, it was compared with soil stabilization with Portland cement. The results showed that in the most optimal geopolymer composition, the bearing resistance of clay has increased by more than 3400%. Meanwhile, fibers along with geopolymer with optimal percentage and length (0.1% by weight of geopolymer composition and length of 12 mm) were able to increase the uniaxial compressive strength of clay by nearly 4000%, which shows the excellent effect of using cellular fibers parameter whit the geopolymer in this research.
B. Shahinejad, A. Parsaei, A. Haghizadeh, A. Arshia, Z. Shamsi,
Volume 26, Issue 3 (12-2022)
Abstract
In this research, soft computational models including multiple adaptive spline regression model (MARS) and data group classification model (GMDH) were used to estimate the geometric dimensions of stable alluvial channels including channel surface width (w), flow depth (h), and longitudinal slope (S) and the results of the developed models were compared with the multilayer neural network (MLP) model. To develop the models, the flow rate parameters (Q), the average particle size in the floor and body (d50) as well as the shear stress (t) as input and the parameters of water surface width (w), flow depth (h), and longitudinal slope (S) were used as output parameters. Soft computing models were developed in two scenarios based on raw parameters and dimensionless form independent and dependent parameters. The results showed that the statistical characteristics in estimating w, the best performance is related to the MARS model, whose statistical indicators of accuracy in the training stage are R2 = 0.902, RMSE=1.666 and in the test phase is R2 = 0.844, RMSE=2.317. In estimating the channel depth, the performance of both GMDH and MARS models is approximately equal, both of which were developed based on the dimensionless form of flow rate as the input variable. The statistical indicators of both models in the training stage are R2 » 0.90, RMSE » 8.15 and in the test phase is R2 » 0.90, RMSE = 7.40. The best performance of the developed models in estimating the longitudinal slope of the channel was related to both MARS and GMDH models, although, in part, the accuracy of the GMDH model with statistical indicators R2 = 0.942, RMSE = 0.0011 in the training phase and R2 = 0.925, RMSE = 0.0014 in the experimental stage is more than the MARS model.
H. Noury Hasanabady, M.r. Kavianpour, A. Khosrojerdi, H. Babazadeh,
Volume 26, Issue 3 (12-2022)
Abstract
Using a rough bed for spillway compare to common dissipation methods such as stilling basins, stepped spillways, ski jumps, and bed elements may be more efficient to boost energy dissipation. In this research, the impact of spillway continuous bed roughness on energy dissipation was investigated. For this purpose, a non-dimensional relationship was developed, and by calibrating the numerical model based on the present experimental study, energy dissipation over the spillway for three slopes of 15, 22.5, and 30 (degree) with six roughness sizes of 0.0, 0.005, 0.0072, 0.0111, 0.016, and 0.022 (m) and three discharges of 170, 110, and 90 (lit/s) was investigated. Based on the present results, using a rough bed spillway will increase energy dissipation. Also, the ratio of energy lost per meter length of rough bed spillway to that of smooth spillway increases by chute slope. The results showed that the highest amount of relative energy consumption in the presence of roughness was related to the slope of 22.5 degrees and 22.2 mm for roughness (85%), and the lowest relative energy consumption was observed in the control state (25%). As a result of the present study, a natural rough bed without concrete coating has befitted in terms of environmental aspects, construction cost, and energy loss.
S. Ayoubi Ayoublu, M. Vafakhah, H.r. Pourghasemi,
Volume 26, Issue 3 (12-2022)
Abstract
Population growth, urbanization, and land use change have increased disastrous floods. Iran is also among the countries at high risk of floods. The latest examples of flood damage are the devastating floods of the spring of 2019 with significant mortality and financial losses in more than ten provinces of the country. The purpose of this study is to prepare an urban flood risk map of District 4 City Shiraz. The vulnerability of the region was made using PROMETHEE Ⅱ and COPRAS multi-criteria decision-making models and urban flood hazard zones were prepared by partial least squares regression (PLSR) and ridge regression (RR) models and a risk map was obtained by multiplying the vulnerability and hazard in ArcGIS software. The highest percentage of the study area in the PROMETHEE Ⅱ and COPRAS models belongs to the moderate class of vulnerability. The evaluation of the vulnerability models using Boolean logic and RMSE and MAPE statistics, showed that the COPRAS model provided better results than the PROMETHEE model. The results of partial least square regression (PLSR) and ridge regression (RR) models in flood risk modeling were analyzed by the Taylor diagram, which showed the superiority of the ridge regression (RR) model and the accuracy of this model in preparing urban flood hazard maps. The risk map of the study area indicated that 34% of the area (973 ha) is in the range of high and very high flood risk.
N. Dalvand, S. Sobhan Ardakani, M. Kiani Sadr, M. Cheraghi, B. Lorestani,
Volume 26, Issue 3 (12-2022)
Abstract
Individuals spend a lot of time indoors, thus they can generally be exposed to polycyclic aromatic hydrocarbons (PAHs) as a teratogen, mutagen, and carcinogen pollutants with the potential for environmental and also human health risks. Therefore, the current study was performed to analyze PAHs in household dust samples of the city of Khorramabad, Iran in 2019. A total of 50 indoor dust samples were collected from 10 sampling sites. After the extraction of analytes, the gas chromatography/mass spectrometry (GC–MS) method was used to determine PAHs in the studied samples. All statistical analyses were performed by SPSS software. The results showed that 16 priority PAHs were detected in the samples with the minimum, maximum, and mean values of 14.0, 23.3, and 19.2 µg/kg. Also, based on the results the mean contents of detected PAHs were lower than the maximum permissible concentration (MPC) established by MHWS and Iran DOE. In conclusion, due to exposure risks of PAHs, regular and periodic analysis of these pollutants in different environmental samples including soil, sediment, dust, particulate matter, air, water, and tissues of living organisms for environmental and human health maintenance is recommended.
A. Balvaieh, L. Gholami, F. Shokrian, A, Kavian,
Volume 26, Issue 4 (12-2022)
Abstract
Changes in nutrient concentrations of soil can specify optimal management of manure and prevent environmental and water resources pollution. The present study was conducted with the objective of changing macronutrients concentrations of Nitrogen, Phosphorus, and Potassium with amendments application of polyvinyl acetate, bean residual, and a combination of polyvinyl acetate + bean residual for time periods of one, two, and four months. The results showed that the application of soil amendments had various effects on changing Nitrogen, Phosphorus, and Potassium. The maximum amount of Nitrogen related to the treatment of bean residual at the time period of four months before simulation (with a rate of 44.62 percent) and minimum amount of nitrogen related to Polyvinyl acetate treatment at the time period of one month (with a rate of -1.92 percent). The minimum rate of Phosphorus was measured at the treatment of bean residual at the time period of one month before simulation (with a rate of 0.95 percent). The maximum amount of Potassium related to the treatment of Polyvinyl acetate at the time period of four months before simulation (with a rate of 189.35 percent) and the minimum amount of Potassium related to the combination of bean residual + Polyvinyl acetate at the time period of one month after simulation (with a rate of 40.66 percent). Therefore, the application of amendments has various effects on changing soil macronutrients at different time periods.
R. Daneshfaraz, M. Bagherzadeh, M. Jafari,
Volume 26, Issue 4 (12-2022)
Abstract
The present study aimed to investigate and compare the laboratory results of energy dissipation and length of vertical Drops equipped with horizontal Screens with the results of standard stilling basins of type one, two, three and four simple vertical Drops. For this purpose, 64 different experiments were performed on vertical Drops equipped with a horizontal Screen at relative distances of 0, 0.25, 0.5, and 0.75 from the edge of Drops, with a porosity of 40 and 50% of the Screen and a height of 20 cm .The results showed that in all experiments and at a constant flow, increasing the distance of the Screen from the edge of Drops does not have much affect the energy dissipation of the current. On average, the downstream energy dissipation for the present study has increased by more than 20% compared to the simple vertical Drop, which can be an excellent alternative to the downstream stilling basin. Among the models of the present study, the most significant reduction in the relative length of the Drops was achieved by the vertical Drops model with a horizontal Screen with a relative distance of 0.75. On average, when using horizontal Screen at four relative distances from the edge of Drops, the relative length of the Drops is reduced by more than 73% compared to the vertical Drops equipped with a standard stilling basin.
N. Salamati, M. Moayeri, F. Abbasi,
Volume 27, Issue 2 (9-2023)
Abstract
The objective of the present study was to conduct field studies for direct measurement of canola under farmers' management in one crop season (2019-2020) in 27 farms in Behbahan, Khuzestan province. Water requirement was calculated based on the FAO Penman-Monteith model using the daily statistics of the Behbahan synoptic meteorological station. A T-test was used to statistically compare the results such as the depth of irrigation and applied water productivity in the field in different irrigation systems. Linear multivariate regression analysis was used to investigate the effects of the independent variable on the dependent parameter of water productivity. The volume of applied water in the fields ranged from 4085.5 to 7865.3 m3/ha. The results of comparing the average yield of two irrigation systems in the t-test showed that the two sprinkler and surface irrigation systems with yields of 2614 and 2330 kg/ha, respectively, were not significantly different. Applied water productivity in traditional and modern irrigation systems was calculated to be 0.386 and 0.486 kg/m3, respectively, which had significant differences. The results of the analysis of variance in the regression model showed that among the independent variables, yield with t-statistic (23.997) and equivalent beta coefficient (0.880) had the most significant positive effect at a 1% level on applied water productivity. After that, the volume of applied water (irrigation water + effective rainfall) with a t-statistic of (-11.702) and a beta coefficient of equivalent (-0.793) had the most negative and significant effect at the level of 1% on the applied water productivity. The results of the Pearson correlation coefficient showed that irrigation events had a positive and significant correlation at a 5% level with applied water and yield. These correlations were 0.455 and 0.380, respectively. By increasing irrigation events, the volume of applied water has practically decreased and has become as close as the plant needs, and has increased water productivity.
S. Jalali, K. Nosrati, Z. Fathi,
Volume 27, Issue 2 (9-2023)
Abstract
The geomorphic characteristics of the watersheds are interrelated and the temporal and spatial scale in the form of season and sub-basins affect the concentration of suspended sediment. One of the objectives of this study was to investigate the relationship between suspended sediment concentration and watershed characteristics of Kan River using principal components regression and to recognize the effect of seasons and sub-basins on sediment concentration. The concentration of suspended sediment during four rainfall-runoff events in three seasons and in sub-basins was measured and calculated. The sixteen physiographic and land use characteristics were determined in the sub-basins and the main factors were identified and the scores of each factor for each feature were calculated using principal component analysis (PCA). The results of variance analysis showed that the concentration of suspended sediment was significant in terms of time scale and spring had the highest rate of sedimentation. Redundancy analysis and canonical analysis on the properties that participate in the first factor (PC1) showed the characteristics of the percentage of erodible formation, relatively erodible formation, and percentage of free construction activity, respectively. Road (slope leveling) and stream length are the most essential attributes of sub-basins in the production and concentration of suspended sediment in the study area.
Z. Feizi, A. Ranjbar Fordoee, A.r. Shakeri,
Volume 27, Issue 2 (9-2023)
Abstract
Maintaining soil structure and stability is essential, especially in arid and semi-arid regions with poor soil structural stability. Destruction of soil and its crust can cause wind erosion and desertification. The objective of this study was to investigate the effect of using hydrogel nanocomposite mulch on the stabilization of sand surfaces. A wind tunnel test was used to evaluate the erodibility of samples treated with different amounts of hydrogel nanocomposite. The compressive strength of the samples was measured by a manual penetrometer. The prepared nanocomposites were examined using scanning electron microscopy (FE-SEM), infrared spectroscopy (FTIR), and X-ray diffraction (XRD) images. The results of the wind tunnel showed that the addition of hydrogel nanocomposite to the samples improved the soil erosion rate by 100% at a speed of 15 m/s compared to the control sample. Bonding between sand particles by spraying hydrogel nanocomposites improves the erodibility of sand. Measurement of mechanical strength of treated samples after 30 days showed that the resistance of the crust increased with increasing the amount of nanocellulose in the composite, which can be expressed due to the increased surface area of the nanoparticle and the possibility of further bonding of the nanocomposite polymer bed with sand particles. While the crust diameter showed no significant difference with increasing concentration and the sample treated with nanocomposites containing 3% nanoparticles was thicker compared to other samples.
A.r. Tavakoli, M. Basirat,
Volume 27, Issue 2 (9-2023)
Abstract
Shifting of surface irrigation to drip system is key tool to reduce water saving. Due to the soil moisture profile variation of the drip irrigation; water distributed of the root zone is not uniform. Moreover, moisture deficit and inefficient fertilizing in drip system due to unavailability in deeper layers of soils is one of the disadvantages of drip system in pistachio orchards with depth root systems. An experiment was carried out by adjusted subsurface drip irrigation (SSDIadj) system in pistachio of Damghan region (Semnan province) in a randomized complete block design with split plot arrangement in three replications for three years. The potassium fertilizer amounts (Fertigation) at three levels (50, 70, and 100% of requirement) were considered as the main plot and the design of conductor tubes of the SSDIadj system in seven levels as sub plots. The irrigation guide tubes were arranged for sand tube irrigation in (control), 40-40-40-40, 40-40- 50-50, 40-40-60-60, 40-40-50-60, 40-40-50-70, and 40-40-50-80. Meteorological data from the nearest meteorological station was collected and analyzed. Yield, water consumption, irrigation water productivity index and growth conditions of ShahPasand pistachio cultivar were determined in different treatments. Data were analyzed using Genstat-12 software and based on the analysis of surplus costs and aerial data, the best treatment including combination of potassium fertilizer and arranged tubes of SSDIadj system was determined. The recommended treatments are including of full irrigation, full potassium fertilizer and guide tubes 40-40-50-70 and or 40-40-50-80. The treatments with stratified conductive tubes in the optimal distribution of water, improving productivity and reducing inefficient consumption water. In addition, there are no restrictions on subsurface irrigation such as root accumulation, root penetration into pores of drippers and as well as accumulation of salts.
Miss S. Bandak, A.r. Movhedei Naeani, Ch.b. Komaki, M. Kakooei, J. Verrlest,
Volume 27, Issue 3 (12-2023)
Abstract
Soil organic carbon (SOC) is one of the most important components of soil physical and chemical properties that have an important role in sustainable production in agriculture and preventing soil degradation and erosion. Data mining approaches and spatial modeling besides machine learning techniques to investigate the amount of soil organic carbon using remote sensing data have been widely considered. The objective of the present study was the evaluation of SOC using the remote sensing technique compared with field methods in some areas of the Gonbad Kavous and Neli forests of Azadshar. The soil samples were collected from the soil surface (0-10 cm depth) to estimate the SOC. Data were categorized into two categories: 70% for training and 30% for validation. Three machine learning algorithms including Random forest (RF), support vector machine, extra tree decision, and XGBoost were used to prepare the organic soil carbon map. In the present study, auxiliary variables for predicting SOC included bands related to Lands 8 OLI and sentinel 2 measurement images, topography, and climate. The results showed that the extraction of the components related to the bands along with the calculation of indicators such as normalized vegetation difference, wetness index, and the MrVBF index as auxiliary variables play an important role in more correct estimation of the amount of soil organic matter. Comparison of different estimation regressions showed that the Sentinel 2 random forest model and in Landsat8 with the values of coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MEA) of 0.64, 0.05, and 0.17, respectively, was the best performance ratio compared to other approaches used in the study to estimate the organic carbon content of surface soil in the study area. In general, the results of this study indicated the ability of remote sensing techniques and learning models in the spatial estimation of soil organic carbon. So, this method can be used as an alternative to laboratory methods in determining soil organic carbon.
M. Majedi Asl, T. Omidpour Alavian, M. Kouhdaragh, V. Shamsi,
Volume 27, Issue 3 (12-2023)
Abstract
Non-linear weirs meanwhile economic advantages, have more passing flow capacity than linear weirs. These weirs have higher discharge efficiency with less free height upstream compared to linear weirs by increasing the length of the crown at a certain width. Intelligent algorithms have found a valuable place among researchers due to their great ability to discover complex and hidden relationships between effective independent parameters and dependent parameters, as well as saving money and time. In this research, the performance of support vector machine (SVM) and gene expression programming algorithm (GEP) in predicting the discharge coefficient of arched non-linear weirs was investigated using 243 laboratory data series for the first scenario and 247 laboratory data series for the second scenario. The geometric and hydraulic parameters were used in this research including the water load (HT), weir height (P), total water load ratio (HT/p), arc cycle angle (Ɵ), cycle wall angle (α), and discharge coefficient (Cd). The results of artificial intelligence showed that the combination of parameters (Cd, H_T/p, α, Ɵ) respectively in GEP and SVM algorithms in the training phase related to the first scenario (Labyrinth weir with cycle wall angle 6 degrees) were respectively equal to (R2=0.9811), (RMSE=0.02120), (DC=0.9807), and (R2=0.9896), (RMSE=0.0189), (DC=0.9871) in the second scenario (Labyrinth weir with a cycle wall angle of 12 degrees) it was equal to (R2=0.9770), (RMSE=0.0193), (RMSE=0.9768), and (R2 = 0.9908), (RMSE = 0.0128), (DC = 0.9905), which compared to other combinations has led to the most optimal output that shows the very favorable accuracy of both algorithms in predicting the coefficient the Weir discharge is arched non-linear. The results of the sensitivity analysis indicated that the effective parameter in determining the discharge coefficient of the arched non-linear Weir in GEP and in SVM is the total water load ratio parameter (HT/p). Comparing the results of this research with other researchers revealed that the evaluation indices for GEP and SVM algorithms of this research had better estimates than other researchers.
A.r. Hossienpur, M. Barati, M.h. Salehi,
Volume 27, Issue 4 (12-2023)
Abstract
The kinetics of potassium release may be affected by P When phosphorus (P) fertilizer is applied to soils. The objective of this study was to the effect of Ca(H2Po4)2 fertilizer on the kinetics of non-exchangeable potassium (NEK) release in 10 calcareous soils. The amount of 100 mg kg-1 of P as Ca(H2Po4)2 was added to the soils. Treated and untreated soils were incubated at 70% of field capacity and 25±1°C for 90 days. After that, the NEK release was studied by 0.01 M CaCl2 extractant in 2017 hours by successive extraction methods in the treated and untreated soils. The results showed the NEK released in treated soils less than in untreated soils. The mean cumulative NEK released after 2017 h in the treated and untreated soils was 260.6 and 303.3 mg kg-1, respectively. The release of NEK in all soils was fast in the initial stages and continued at a lower speed in the later stages until the end of the experiment. The kinetics of NEK release was evaluated using kinetic equations. Based on the highest coefficients of determination (R2) and the lowest standard error (SE), the kinetics of NEK release in treated and untreated soils were described by the power function equation. The results of this research could be helpful for the precise fertilizer recommendation for the study in calcareous soils.
M. R. Taghizadeh, A. Motamedi, M. Galoie, F. Kilanehei,
Volume 27, Issue 4 (12-2023)
Abstract
Understanding flow behavior over bedforms is one of the most complex topics in sedimentary engineering. Despite numerous studies that have been conducted on river beds, the understanding of the interaction between flow and bed in turbid and clear waters is still impoverished. The present study mainly focused on simulating clear and turbid flows using SSIIM software. This study modeled the flow through a 12-meter channel with nine consecutive dunes of 1-meter length and 4 cm height. Nine simulations were performed to investigate the effects of flow velocity and flow separation zone in clear and turbid water. Finally, the results were compared with the experimental results of previous researchers using the PIV. The modeling results showed that the length of the flow separation zone increases with increasing velocity, and the highest probability of flow separation occurs at the highest velocity. In turbid flow, flow separation is less than the same flow condition in clear flow, and as fluid density increases, the length of the flow separation zone decreases. This study demonstrates the acceptable functionality of the SSIIM software and its accuracy in estimating flow behavior with and without sediment.
A. Salar, M. Shahriari, V. Rahdari, S. Maleki,
Volume 28, Issue 2 (8-2024)
Abstract
Unbalanced development of different land use/cover in basins without considering the contribution of all components, can cause serious damage to the stability of the entire basin. The development of agricultural areas by increasing the amount of water use and creating dams upstream of rivers are the most important threats to wetlands in many places. Jazmorian wetland is one of the seasonal wetlands in the south-east of Iran. The most important source of water supply for this wetland is the Halil-Rood River. To investigate the land use/cover changes of Jazmurian wetland and
Halil-Rood River, the time series of Landsat satellite data for the years 1354, 1374, 1387, and 1401 were used in the present research. The Landsat satellite images were classified using a hybrid classification method and the land use/cover of the study area maps were prepared. The accuracy of the prepared maps for the latest image was calculated by preparing the error matrix, calculating the kappa index, and the overall accuracy of more than 0.8 and 9%, respectively. The investigation of the prepared maps showed that the area of land under water increased from 1354 to 1374 and then decreased from 119,552 hectares in 1374 to 723 hectares in 1401. The area of agricultural land increased from 2131 hectares in 1354 to 133913 hectares in 1387 and declined to 105795 hectares in 1401. The results of this study show that in this period, with the construction of a dam upstream of the Halil-Rood River, and the development of agricultural lands, the water volume level of the wetland decreased, and the wetland completely dried up in 1401. The present study indicates the necessity of considering different components of a watershed in development planning to achieve sustainable development.
Sh. Kiyani, T. Rajaee, M. Karamdokht Behbahani,
Volume 28, Issue 3 (10-2024)
Abstract
In this research, the hydraulic parameters of flow have been investigated on SMBF flumes in two simple and multiple modes. In this research, Flow3D software was used for the numerical simulation of SMBF flow. The simulations have been performed in three flow rates (5, 15, and 30 liters per second) and three opening rates (0.075, 0.1, and 0.15 meters). The results showed that when multiple SMBF flumes are used instead of simple SMBF flumes, the maximum velocity increased by 12% on average at a flow rate of 5 L/s, 19% at a flow rate of 15 L/s, and 10% at a flow rate of 30 L/s. The energy consumption of multiple SMBF flumes has been reduced on average by 21% at a flow rate of 5 L/s, by 66% at a flow rate of 15 L/s, and by 122% at a flow rate of 30 L/s compared to simple SMBF flumes. Finally, the observations showed that during the productivity of multiple SMBF flumes compared to simple SMBF flumes, the size of eddies has decreased and the number of eddies and the area of flow turbulence have increased.
A. Keshavarz, R. Modarres, S.a.r. Gohari,
Volume 28, Issue 4 (12-2024)
Abstract
This study was conducted to present rangeland bioclimatic zoning for Iran based on the changes in the power spectrum of the average monthly Net Primary Production (NPP) of the rangelands of Iran. Fluctuations of the mean monthly power spectrum of the NPP signal of rangelands of Iran from 2000 to 2022 were analyzed using the Power Spectrum Density (PSD) method in the frequency band between 0-100 Hz. In 24 bioclimatic subzones, there are four common periods in all sites at frequencies of 0 (no change is repeated), 8.34 (3.59 days), 16.66 (1.80 days), and 25 (1.2 days) Hz observed, which shows that the major data changes occur in those periods and that the NPP changes of Iranian rangeland are more influenced by global and regional effects than local effects. The maximum power of these spectra is concentrated in high time scales. Therefore, cycles with lower frequency (higher time scale) are more important than cycles with higher frequency (shorter time scale) and show that the changes of NPP in Iranian rangelands have long-duration cycles under climate fluctuations. In the present research, Iran was classified into 5+1 rangeland bioclimatic zones using the results of the monthly mean power spectrum of the NPP signal of rangelands, the Wards clustering method, and the Euclidean square distance. It seems that this method provides a proper match between biological boundaries and climate. Pearson correlation coefficient was used to investigate the coherence of rangeland bioclimatic regions within each homogeneous group. Correlation results showed a significant spectral density similarity within groups at the significance level of 0.01% between rangeland bioclimatic regions, especially in the second and fifth clusters.
H. Ramezani Etedali, M. Ahmadi,
Volume 29, Issue 2 (7-2025)
Abstract
change, accurately predicting wheat production is essential for developing precision agriculture. Remote sensing enables the indirect prediction of crop production before harvest. This research investigates the application of the random forest method and support vector regression for simulating wheat production across ten selected farms in Qazvin Plain from 2019 to 2020, employing NDVI, MSAVI, and EVI vegetation indices. Sentinel 2 satellite data was utilized for the vegetation indices. Production data for the ten wheat fields was obtained from the Agricultural Jihad Organization of Qazvin Province. Evaluation of support vector regression and random forest to assess both the observed and simulated wheat production data was conducted using R2, MBE, RMSE, and MAE statistics. To explore the simulation of wheat production using vegetation indices, seven methods were defined: methods 1 to 3 examine each index separately; methods 4 to 6 focus on binary combinations of the indices; and method 7 considers the combined effects of all three indices. The support vector regression model provided good estimates of wheat production in all methods, except methods one and four, in the test phase, with a coefficient of determination of more than 0.98 and a low RMSE. The random forest model showed significant results in all methods except methods two and six during the test phase, achieving a 95% probability (P-value=0.00) with a coefficient of determination greater than 0.8. Overall, this research highlights the importance and potential of machine learning techniques for timely crop production prediction as a strong foundation for regional food security.
