Showing 52 results for Red
M Noruzi, A Jalalian, Sh Ayoubi, H Khademi,
Volume 12, Issue 46 (1-2009)
Abstract
Crop yield, soil properties and erosion are strongly affected by terrain parameters. Therefore, knowledge about the effects of terrain parameters on strategic crops such as wheat production will help us with sustainable management of landscape. This study was conducted in 900ha, of Ardal district, Charmahal and Bakhtiari Province to develop regression models on wheat yield components vs. terrain parameters. Wheat yield and its components were measured in 100 points. Points were distributed randomly in stratified geomorphic surfaces. Yield components were measured by harvesting of 1 m2 plots. Terrain parameters were calculated by a 3×3 m spacing from digital elevation model. The result of descriptive statistics showed that all variables followed a normal distribution. The highest and lowest coefficient of variance (CV) was related to grain yield (0.36) and thousand seeds weight (0.13), respectively. Multiple regression models were established between yield components and terrain parameters attributes. The predictive models were validated using validation data set (20% of all data). The regression analysis revealed that wetness index and curvature were the most important attributes which explained about 45-78% of total yield components variability within the study area. The overall results indicated that topographic attributes may control a significant variability of rain-fed wheat yield. The result of validation analysis confirmed the above-stated conclusion with low RMSE and ME measures.
H Morteza Por , M.h Raoufat , S Kamgar ,
Volume 13, Issue 47 (4-2009)
Abstract
Oil seed rape is an important non-cereal crop used mainly for edible oil production. Canola pods are fragile and its branches are twisted together at harvesting time. Harvesting with a conventional combine can pull off twisted branches and cause appreciable losses in the vicinity of divider at combine header. In this study, a hydraulic rotary divider was designed and developed to separate twisted pods and reduce the grain loss. The device is made up of two cylinders and a number of fingers, the cylinders rotate in opposite direction and fingers move in and out through holes on cylinder walls. The assembly was expected to separate the twisted pods and reduce grain loss. A hydraulic motor driven by combine hydraulic system was used to rotate the separating cylinders. The separating assembly was installed on righthand side of the combine harvester header. A split-plot experiment was used to evaluate the performance of the unit. Field tests were carried out at combine forward speed of 1.5 kmh-1. Variables were: cylinders rotary speed in three levels (50, 75 and 100 rpm), the number of fingers in three levels (16, 12 and 8), and the tests were conducted with and without combine reel. Two different positions of finger protrusion were also considered in field tests. The results were compared with those of a conventional combine header. The results show that the medium rotational speed (75 rpm) exhibited lowest seed loss. Furthermore, as the number of fingers increased, the seed loss tended to decrease. The seed loss also decreased in the presence of combine reel. Also, findings showed there is no significant difference between the two protrusions trajectories of fingers. A twenty percent decrease in seed loss was observed at rotary speed of 75 rpm and number of fingers of 16 in the presence of combine reel.
S.a.m Modares Sanavi, B Amiri Larijani, Sh Khalesro,
Volume 13, Issue 47 (4-2009)
Abstract
In order to study the morphological characteristics and yield of leafy corn hybrids, and comparie them with those of commercial hybrids, an experiment was conducted in the research field of Agricultural College, Tarbiat Modares University in 2005. A complete block design was used with three replications. Hybrids were obtained from crosses between leafy inbred lines and also commercial inbred lines with leafy inbred. There was a significant difference in single crosses on above and below leaf number and area, biomass, leaf length, plant height and distance between ear and tassel, internodes length, ear height (p<0.01). The most and least above ear leaf number were for b7*a4 and commercial hybrids, respectively. Most of the leafy hybrids had more above and below leaf number than commercial hybrids. Some of leafy hybrids produced the same yield as commercial hybrids and the others produced more. Considerable yield increment in the leafy corn can be attributed to the fact that the leafy gene produce twice leaf area in corn. Internodes length reduced in leafy hybrids due to increasing leaf number without plant height increment. The maximum and minimum grain yield were for b2*a4 leafy hybrid (10.22 t/ha) and SC108 non-leafy commercial corn (6.37 t/ha) respectively. Generally, b7*a4 and b2*a4 leafy hybrids produced the most biomass and leafy hybrid b2*a4 had the most grain yield.
E Dehghan, M Almasi,
Volume 13, Issue 47 (4-2009)
Abstract
Soil tillage management for various crops in different regions needs use available indices and information about condition, manual manner, defects and preferences of various tillage methods. Therefore, this experiment was conducted in summer 2003 on clay soil containing wheat residual in Shawoor agricultural research center, situated in northern Ahwaz. Experiment was conducted as a Randomized Complete Block Design (RCBD). Treatments included: conventional tillage in one pass of moldboard plowing in 20cm depth + leveler (T1), two passes of disk harrow in 8-10cm depth + leveler (T2), two passes of disk harrow in 12-15cm depth + leveler (T3), one pass of cultivator in 10cm depth + leveler (T4), one pass of cultivator in 15cm depth + leveler (T5) and one pass of rotivator in 5cm depth (T6). The results showed that fuel consumption decreased for T2-T6 57, 51, 67, 54 and 69 % as compared to T1 (49 L/ha), respectively. Total operation time decrease in T2-T6 42, 46, 42, 54 and 44 % in comparison to T1 (4.41 h/ha) respectively. Field capacity increased for T2-T6 as much as 2.4, 2.2, 2.4, 1.8 and 2.3ha/h compared to T1, respectively. Mean weight diameter (MWD) index increased in T2-T5 29, 21, 10 and 5 % than T1 (1.92cm), respectively, but decreased 6% in T6. Mean tillage costs reduced in T2-T6 as much as 40, 32, 54, 50 and 60 % compared to T1 (500000 Rial/ha), respectively.
H Shirani, M.a Hajabbasi, M Afyuni , A Hemmat ,
Volume 14, Issue 51 (4-2010)
Abstract
Tillage systems and organic manures could affect soil physical and mechanical properties. This study was conducted to investigate the impacts of two tillage systems including conventional tillage by moldboard plowing (plowing depth, 30 cm) and reduced tillage by disk plow (plowing depth, 15 cm) and three rates (0, 30 and 60 ton ha-1) of farmyard manure (FYM) on the soil penetration resistance under corn cropping in a split block design with 3 replications. The cone index (CI) decreased with increase of the tillage depth. It is attributable to soil disturbing and loosening of the deeper layers under conventional tillage compared to reduced tillage. This trend, however, was observed only in the first (after treatments’ application and before cropping) and second (the highest rate of vegetative growth) samplings. In the third sampling (after harvest), there were not significant differences between the CI values under two tillage systems in different soil depths. It might be due to soil re-compaction (approaching the pre-tillage state) as well as disappearance of the tillage effects seven month after commencement of the experiment. In fact, the soil mechanical resistance increased with the time indicating soil re-compaction over the growing season. Adding FYM to the surface layer (i.e. 0-10 cm) of ridge soil resulted in significant decrease of soil mechanical resistance compared to control treatment. The CI decreased significantly in the 30 ton ha-1 treatment up to the stage of highest rate of vegetative grow, but the effect on CI was diminished after harvest. However, the decreasing effects of the 60 ton ha-1 treatment on the CI continued to the harvesting time. There were no significant effects of FYM in the soil deeper than 10 cm from the ridge surface and in all of the layers in furrow. The CI did not decrease significantly in the furrow due to negligible effect of manure application for the inter-row position.
Afkhami, Dastorani, Malekinejad , Mobin,
Volume 14, Issue 51 (4-2010)
Abstract
Drought is a natural feature of the climate condition, and its recurrence is inevitable. The main purpose of this research is to evaluate the effects of climatic factors on prediction of drought in different areas of Yazd based on artificial neural networks technique. In most of the meteorological stations located in Yazd area, precipitation is the only measured factor while generally in synoptic meteorological stations in addition to precipitation some other variables including maximum and mean temperature, relative humidity, wind speed, dominant wind direction and the amount of evaporation are also available. In this research it was tried to evaluate the role of the type and number of meteorological factor (as inputs of ANN model) on accuracy of ANN based drought prediction. Research area is a part of Yazd province containing only one synoptic and 13 non-synoptic meteorological stations. Three-year moving average of monthly precipitation was the main input of the models in all stations. The type of ANN used in this study was time lag recurrent network (TLRN), a dynamic architecture which was selected by evaluation of different types of ANN in this research. What was predicted is the three-year moving average of monthly precipitation of the next year, which is the main factor to evaluate drought condition one year before it occurs. For the Yazd synoptic meteorological station, several combinations of input variables was evaluated and tested to find the most relevant type of input variables for prediction of drought. However, for other 13 stations precipitation data was the only variable to use in ANN models for this purpose. Results in all stations were satisfactory, even where only one input (precipitation) was used to the models, although the level prediction accuracy was different from station to station. Result taken from this research, indicates high flexibility of ANN to cope with poor data condition where it is difficult to get acceptable results by most of the methods.
F. Fathi, M. Zibaei ,
Volume 14, Issue 53 (10-2010)
Abstract
Overexploitation of groundwater resource may result in lowering groundwater table at a faster rate due to an imbalance in the total recharge and total withdrawal. In order to make a balance between groundwater exploitation and recharge, the major remedial measures suggested are to strengthen groundwater management, adopt water demand policies, raise water use efficiency, and to increase water supply. Because there is a trade off between farmers’ income and sustainability of groundwater based farming, it is essential that a mathematical model be used to study the effects of withdrawal on farmers' income and sustainability of farm. Such a model can determine optimal crop pattern, suitable irrigation strategies and irrigation methods at different levels of available irrigation water. The relationship between farmers’ income and the withdrawal was then examined using multi-objective programming. The data were obtained from a systematic random sampling method through which 112 farmers were chosen. The percentage decrease in the profit was less than that of the withdrawal for all representative farmers, based on the results obtained from multi-objective method. For example, 8% reduction of groundwater pumping could be imposed without a serious impact on the farmers' income (farmers' income falls about 4%). Finally, the results of this study can help farmers to choose crop patterns, irrigation strategies and irrigation methods in such a way that both farmers’ income and withdrawal are simultaneously optimized and lead to a decrease in extracting groundwater compared to the current status.
E. Nabizadeh, H. Beigi Harchegani,
Volume 15, Issue 57 (10-2011)
Abstract
Selecting an appropriate particle size distribution (PSD) model for a particular soil may be important for a precise estimation of soil hydraulic properties. Various models have been proposed for describing soil PSDs. The objective of this study was to compare the quality of fitting of eight PSD models (Fredlund, Gompertz, van Genuchten, Jaki, Logarithmic, Exponential, Logarithmic-Exponential and Fractal) in 71 soil samples collected from Lordegan and Saman in Charmahal-va-Bakhtiari province, Iran. Coefficient of determination ( ) and Akaike’s information criterion ( ) were used to compare the goodness-of-fit of the models to the experimental data. Results showed that Fredlund model is best for describing PSD of silt loam, silty clay loam, silty clay and sandy loam soil textures. While Fractal, Exponential and Logarithmic-Exponential models produced the poorest-fit in silt loam, silty clay loam and silty clay, they had the best performance in sandy loam texture. The performance of Fredlund and Gompertz models improved with an increase in clay and silt content from 25 and 40 percentage, respectively. The performance of Fractal, Exponential and Logarithmic-Exponential models improved by increasing the sand content. Reverse correlation was observed between silt content and the performance of the Fractal model.
A. Safadoust , A. Mahboubi, M. R. Mosaddeghi, Gh. Khodakaramian, A. Heydari,
Volume 15, Issue 57 (10-2011)
Abstract
In this study, the transport of nalidixic acid-resistant Escherichia coli (E. coli NAR) through two soils of sandy loam and clay loam was investigated. Saturated and unsaturated flow conditions were applied at two temperatures of 5 and 20ºC. Leaching was done using large repaired soil columns which had been subjected to physical weathering. A 20-cm diameter disk infiltrometer was set up to establish the steady-state flow conditions. Effluent was sampled at three depths of 15, 30 and 45 cm of soil columns. Saturated flow condition, temperature of 20 ºC and clay loam soil resulted in increasing the bacteria concentration in the leachate. Filtration coefficient and relative adsorption indices in sandy loam soil (average flow conditions, temperature and depth) were greater than those of clay loam soil with the respective values of 33% and 23%. These results may be related to the instability of soil structure and abundance of micropores in the sandy loam columns. In other words, the bacteria were physically blocked and entrapped in the fine pores of sandy loam soil. Effluent bacteria concentration decreased by depth of soil column, indicating the effect of soil on bacterial filtration as a natural filter. Leaching with cold water led to decrement of flow rate and consequently increment of bacterial filtration in the two soils of clay loam and sandy loam (average flow conditions, temperature and depth) with the respective values of 100% and 68%.
A. Vaezi, M. Abbasi,
Volume 16, Issue 61 (10-2012)
Abstract
The Soil Conservation Service Curve Number (SCS-CN) method is widely used for predicting direct runoff from rainfall events. The ratio of initial abstraction (λ=Ia/S) to maximum potential retention (S) was assumed in its original development to be equal to 0.2 (λ=Ia/S=0.2) in SCS-CN method. Application of the initial abstraction ratio equal to 0.2 out of the area where it has been developed may lead to a non logical estimation of runoff. Thus, the study was conducted to determine the initial abstraction ratio (λ=Ia/S) by analyzing measured rainfall-runoff events. The dataset consisted of 58 rainfall-runoff events during 15 years (1987-2001) of rainfall and runoff measurements from Taham-Chay watershed, northwest of Zanjan, Iran. Based on the results, the estimated runoff value on the basis of Ia= 0.2S was 26.7 times higher than the measured value, on average. There was a very low relationship between the measured and estimated runoff values (R2=0.09) and mean model error was 0.13. The Ia/S values varied from 0.004 to 0.008 with an average of 0.006. When Ia/S value was modified to 0.08, ratio of the measured to estimate runoff value was 1.4 and the determination coefficient (R2) of the relationship between the two was 0.41. When seven rainfall events that had the low rainfall intensity values (lower than 0.14 mm/h) and two events that had the high rainfall depth (bigger than 10.47 mm) during the past five days were removed from the data analysis process, ratio of the measured to estimated runoff value decreased to 1.3 and the determination coefficient (R2) of the relationship between the two enhanced to 0.90. The mean model error for the modified Ia/S value also decreased to 0.007. It also improved model efficiency coefficient (EF) to -0.089 compared with 0.91 for traditional Ia/S value (0.2).
M. Toozandehjani, M. Kashefipour,
Volume 16, Issue 62 (3-2013)
Abstract
One of the usual ways to dissipate excess energy in the dam's downstream is hydraulic jump. Hydraulic jump is a rapidly varied flow, in which the flow conditions change from supercritical to sub-critical with a large amount of energy loss. In this research, a combination of two water jets in the form of overflow dam and underflow through a slot on the body of an ogee dam with the USBR standard was established in order to decrease the length and sequent depth in a hydraulic jump. In these experiments, the underflow from the slot was designed with three out passages of 0, 45, and 90 degrees in respect horizontal line. Six different discharge ratios were used for each slot and the effect of each experiment conditions on decreasing of the length and sequent depth of hydraulic jump was investigated. The results showed that the confluence of two jets with 45 degrees from the slot had the maximum effect on the reducing of the length of hydraulic jump and sequent depth, and when 26 percent of the total discharge passed through the slot as underflow, it caused the length of hydraulic jump to be reduced by 50 percent in comparison with the classic jump. This slot not only decreases the length and sequent depth of hydraulic jump but also the sediment behind the dam can be evacuated through it. Moreover, it increases the discharge coefficient.
M. Navabian, M. Aghajani, M. Rezaei,
Volume 18, Issue 70 (3-2015)
Abstract
Water Uptake by the root under salinity and water Stress in unsaturated soils was investigated through mathematical equations in three Groups of additive, multiplicative and non-consumptive. This study was an effort to assess six water uptake functions of van Genuchten (additive and multiplicative), Dirksen et al., Van Dam et al, Skaggs et al, and Homaee, for Rasht Hashemi rice under salinity and water stress conditions. Based on field observations of Hashemi Rasht rice in 1386 and 1389, crop growth simulation model of SWAP was calibrated and validated with a correlation coefficient of 0.97 and 0.95, respectively. Water Uptake Reduction Models' parameters were determined by the simulated data using SAS statistical software. Results showed that for the anticipated reduction of Water Uptake in rice water and salinity stress conditions for Rasht Hashemi rice, Homaee model is best.
H. Nazaripour, Z. Karimi, M. Sedaghat,
Volume 20, Issue 75 (5-2016)
Abstract
Drought is a climatic anomaly that associates with a significant decrease (lack) of precipitation and water resources availability, which spreads on vast temporal and spatial scales, and significantly affects various aspects of life and environment. One of the most common methods of drought assessing and monitoring is calculating drought indices (DIs). Drought areal and temporal extent and its severity are determined by these indices. In this study, an aggregate drought index (Hydro-Meteorological) has been developed for the assessment of hydrological and meteorological droughts in Sarbaz river basin located in southeastern of Iran. The Aggregate Drought Index (ADI) comprehensively considers all physical forms of drought (meteorological, hydrological, and agricultural) through selection of variables that are related to each drought type. In this case, monthly values of Stream flow Drought Index (SDI) and Standardized Precipitation Index (SPI) indicators were used for four similar reference periods with principle component analysis and aggregate hydro-meteorological index was defined based on its first component. The study time span was set between 1981-82 to 2010-11, which begins of October in Iran. Results based on the aggregate drought index (ADI) revealed that a long period of hydro-meteorological drought occurred from 1999-2000 to 2005/06 in southeast of Iran, in which, 2003/04 water year has been extremely a drought year. The ADI methodology provides a clear, objective approach for describing the intensity of drought. This index is appropriately able to represent the behavior of Hydro-Meteorological droughts and recommended as an integrated index for assessing and monitoring of regional droughts. Finally, different states of hydro-meteorological drought have been extracted based on conventional regional thresholds, and have been modeled by Markov chain. This made the estimation of drought state transition frequency possible, and made the prediction of next drought state time more real. State transition frequency matrices, are the main instruments for predicting drought states in real time. Results of validation tests and conforming the predicted results with real data indicate that predicting hydrological drought state transitions in the study area using Markov chain method is valid.
M. Sadeghian, H. Karami, S. F. Mousavi,
Volume 21, Issue 4 (2-2018)
Abstract
Nowadays, greater recognition of drought and introducing its monitoring systems, particularly for the short-term periods, and adding predictability to these systems, could lead to presentation of more effective strategies for the management of water resources allocation. In this research, it is tried to present appropriate models to predict drought in city of Semnan, Iran, using time series, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (MLP and RBF). For these modeling processes, average monthly meteorological parameters of rainfall, temperature, minimum temperature, maximum temperature, relative humidity, minimum relative humidity, maximum relative humidity and SPI drought index were used during the period 1966 to 2013. The results showed that among the many developed models, the ANFIS model, with input data of average rainfall, maximum temperature, SPI and its last-month value, 10 rules and Gaussian membership function, showed appropriate performance at each stage of training and testing. The values of RMSE, MAE and R at training stage were 0.777, 0.593 and 0.4, respectively, and at testing stage were 0.837, 0.644 and 0.362, respectively. Then, the input parameters of this model were predicted for the next 12 months using ARIMA model, and SPI values were predicted for the next 12 months. The ANN and time series methods with low difference in error values were ranked next, respectively. The input parameters SPI and temperature had better performance and rainfall parameter had weaker performance.
R. Samiei Fard, H. Matinfar,
Volume 21, Issue 4 (2-2018)
Abstract
Reflectance spectroscopy is a fast and safe method to predict soil physicochemical and biological properties in low cost ways. Traditional methods to determine soil properties require spending a lot of time and money so that farmers are generally reluctant to use the results of laboratory measurements in soil and water management. Reflectance spectroscopy in the spectral range of 400-2500 nm (VNIR) is an alternative method for estimating the soil properties. The aim of this study was to evaluate the results of laboratory spectrometer to estimate the concentration of Lead (Pb) and Nickel (Ni) in soils irrigated with water from treatment of urban sewage sludge of Rey city and finally to compare these results with the results of measurements of atomic absorption spectrometry. In this study, the Partial Linear Square Regression (PLSR) model was used to estimate the concentration of heavy metals and Residual Mean Square Error (RMSE) was used to evaluate the performance of this model. In this research, after spectral corrections related to elimination of the water absorption bands as well as elimination of the inefficient spectrum from heavy metals estimations, the methods of estimating these elements were studied through mathematical derivation of spectral values and also the acquisition of the continuum removal spectra. The results show that the estimated values from first derivate spectra are more consistent with the results of atomic absorption spectrometers.
S. Zahedi, K. Shahedi, M. Habibnejhad Roshan, K. Solaimani, K. Dadkhah,
Volume 21, Issue 4 (2-2018)
Abstract
Soil depth is a major soil characteristic commonly used in distributed hydrological modeling in order to present watershed subsurface attributes. It strongly affects water infiltration and accordingly runoff generation, subsurface moisture storage, vertical and lateral moisture movement, saturation thickness and plant root depth in the soil. The objective of this study is to develop a statistical model that predicts the spatial pattern of soil depth over the watershed from topographic and land cover variables derived from DEM and satellite image, respectively. A 10 m resolution DEM was prepared using 1:25000 topographic maps. Landsat8 imagery, OLI sensor (May 06, 2015) was used to derive different land cover attributes. Soil depth, topographic curvature, land use and vegetation characteristics were surveyed at 426 profiles within the four sub-watersheds. Box Cox transformations were used to normalize the measured soil depth and each explanatory variable. Random Forest prediction model was used to predict soil depth using the explanatory variables. The model was run using 336 data points in the calibration dataset with all 31 explanatory variables (18 variables from DEM and 13 variables from remote sensing image), and soil depth as the response of the model. Prediction errors were computed for validation data set. Testing dataset was done with the model soil depth values at testing locations (93 points). The Nash-Sutcliffe Efficiency coefficient (NSE) for testing data set was 0.689. The results showed that land use, Specific Catchment Area (SCA), NDVI, Aspect, Slope and PCA1 are the most important explanatory variables in predicting soil depth.
A. Khorsand, M. Bazaneh, S. Besharat, K. Zeynalzadeh,
Volume 22, Issue 4 (12-2018)
Abstract
Subsurface drip irrigation systems, compared to other irrigation systems (basin and furrow), enhance the delivery of water and nutrients directly into the root zone. The purposes of this study were to determine wetting front advancement in a subsurface drip irrigation and to compare the results with the HYDRUS 2D model simulation. In this study, the irrigation using T-Tape was carried out on a sandy-loam soil by two emitters at different irrigation times. The Wet moisture meter device was used to determine the soil water content. Evaluation of the simulated and measured soil water content was performed by using the adjusted determination coefficient (R2), relative error (RE), and the normalized root mean square error (NRMSE). Based on the results, the NRMSE of soil water content prediction for the emitters at the depths of 20 and 40 cm was calculated to be in the range of 10 to 19 and 10 to 13 percent, respectively. Also, RE for the emitters at depths of 20 and 40 cm was in the range of -16 to -5 and 8 to 11 percent, respectively. The average R2 for the emitters at depths of 20 and 40 cm was calculated to be 0.87 and 0.98, respectively. Also, five scenarios (F1, F2, T1, T2 and S1) were evaluated to assess the amount of water stored in the soil profile and water mass balance. The results indicated that the model could be used to predict the soil water content subsurface drip irrigation.
S. V. Razavi Termeh, K. Shirani, M. Soltani Rabii,
Volume 23, Issue 2 (9-2019)
Abstract
Today, supplying water to meet the sustainable development goals is one of the most important concerns and challenges in most countries. Therefore, identification of the areas with groundwater potential is an important tool for conservation, management and exploitation of water resources. The purpose of this research was to prepare the potential groundwater map in Nahavand, Hamedan Province, using the weight of evidence model and combining it with logistic regression. For this purpose, the information layers of slope angle, slope aspect, slope length, altitude, plan curvature, profile curvature, TWI, SPI, distance from fault, fault density, distance from river, drainage density, lithology and land use were identified as the factors affecting groundwater potential and digitized in the ArcGIS software. After designing the groundwater potential map with these three methods, ROCs were used to evaluate the results. Of 273 springs identified in this study, 191 (70%) were used to prepare the groundwater potential map and 82 springs (30%) were used to evaluate the model. The area under curve (AUC) obtained from the ROC curve showed an accuracy of 80.4% for the weight of evidence model and 82.5% for the weight of the evidence- regression combined model
M. Boustani, F. Mousavi, H. Karami, S. Farzin,
Volume 23, Issue 4 (12-2019)
Abstract
River discharge is among the influential factors on the operation of water resources systems and the design of hydraulic structures, such as dams; so the study of it is of great importance. Several effective factors on this non-linear phenomenon have caused the discharge to be assumed as being accidental. According to the basics the chaos theory, the seemingly random and chaotic systems have regular patterns that are predictable. In this research, by using methods of phase space mapping, correlation dimension, largest Lyapunov exponent and Fourier spectrum power, a period covering 43 years of Zayandehrud River discharge (1971-2013) was evaluated and analyzed based on the chaos theory. According to the results, the non-integer value of the correlation dimension for Eskandari and Ghale Shahrokh stations (3.34 and 3.6) showed that there was a chaotic behavior in the upstream of Zayandehrud-Dam Reservoir. On the other hand, in the Tanzimi-Dam station, the correlation dimension curve was ascending with respect to the embedding dimension, showing that the studied time-series in the downstream of Zayandehrud-Dam Reservoir was random. The slope of the Lyapunov exponent curve for Eskandari, Ghale Shahrokh and Tanzimi-Dam stations was 0.0104, 0.017 and 0.0192, respectively, and the prediction horizon in the chaotic stations was 96 and 59 days. The non-periodical feature of time series was studied by using the Fourier spectrum power. The wide bandwidth, besides other indices, showed that river discharge in the upstream stations of Zayandehrud Reservoir was chaotic.
L. Cheraghpoor, M. Pajoohesh, A. Davoodyan, A. Bozorgmehr,
Volume 23, Issue 4 (12-2019)
Abstract
River discharge is among the influential factors on the operation of water resources systems and the design of hydraulic structures, such as dams; so the study of it is of great importance. Several effective factors on this non-linear phenomenon have caused the discharge to be assumed as being accidental. According to the basics the chaos theory, the seemingly random and chaotic systems have regular patterns that are predictable. In this research, by using methods of phase space mapping, correlation dimension, largest Liapunov exponent and Fourier spectrum power, a period covering 43 years of Zayandehrud River discharge (1971-2013) was evaluated and analyzed based on the chaos theory. According to the results, the non-integer value of the correlation dimension for Eskandari and Ghale Shahrokh stations (3.34 and 3.6) showed that there was a chaotic behavior in the upstream of Zayandehrud-Dam Reservoir. On the other hand, in the Tanzimi-Dam station, the correlation dimension curve was ascending with respect to the embedding dimension, showing that the studied time-series in the downstream of Zayandehrud-Dam Reservoir was random. The slope of the Lyapunov exponent curve for Eskandari, Ghale Shahrokh and Tanzimi-Dam stations was 0.0104, 0.017 and 0.0192, respectively, and the prediction horizon in the chaotic stations was 96 and 59 days. The non-periodical feature of time series was studied by using the Fourier spectrum power. The wide bandwidth, besides other indices, showed that river discharge in the upstream stations of Zayandehrud Reservoir was chaotic.
