Journal of Water and Soil
Year:2010 | Volume:24 | Issue:4|Papers Count:22

The unit hydrograph is one of the most important and usual methods to estimate flood discharge from observed data. Development of unit hydrographs using precipitation and runoff analysis is impossible in watersheds with lack of basic data. Therefore, empirical methods or models based on watershed characteristics can be used to estimate hydrographs. The proper application of instantaneous unit hydrograph theory is very efficient for watershed with lack of rainfall data unless the necessary parameters are determined with high accuracy. In this research, the effects of changes in travel time between isochrones in determining time-area curves and leading to Clark instantaneous unit hydrographs were evaluated with the help of geographical information system for forest Kasilian watershed. The comparison of estimated and observed hydrographs by using qualitative and quantitative criteria for travel times between 0.25 to 3h showed that the 3h-travel time of isochrones has had the highest accuracy in determination of time- area curve in estimation of flood resulting from Clark instantaneous unit hydrograph. The results emphasized on the necessity of proper selcetion and calibration of time intervals in unit hydrograph development.

Long term trend analysis of meteorological variables has a great importance in climate change detection studies. The purpose of this study was to assess changes in relative humidity and dew point temperature over the period 1973-2003. Monthly data of relative humidity and dew point temperature of 22 synoptic stations of Iran were obtained from Iran Meteorological Organization (IRIMO). These stations represent different climates of the country based on De Martonne climatic classification. All seasonal and annual series have been checked for normality with the Kolmogorov-Smirnov test. Time trends of both variables were analyzed using parametric and non-parametric techniques (Least square linear regression, Mann-Kendall and rho-Spearman correlation coefficient). Based on the results of Mann-Kendall test, the most significant increasing trend of both variables exists in summer season and the least trend of relative humidity was observed in winter season. The most and least increasing trend of dew point temperature was observed in spring and autumn respectively. Using rhospearman correlation coefficient, the most significant decreasing trend of relative humidity was observed in annual and spring time series. Parametric test of regression analysis revealed no specific trend in dew point series, but all seasonal series of relative humidity showed trend. In general, the decreasing trend of series was more that increasing trend. The results indicated that no specific climatic pattern of trends can be suggested.

Parent material is considered as the most important soil forming factor in arid and semiarid regions. This study was carried out to determine the effect of different parent materials composition on physico-chemical and mineralogical properties of soils and also soil classification in the north of Chaharmahal-Va-Bakhtiari province.Seven different kinds of parent materials including granite, basalt, limestone, shale, mica-schist, gneiss and amphibolite were chosen and three different locations were selected for excavation and description of soil profiles. Then, soil samples were taken and soil physico-chemical and mineralogical properties were determined for representative profiles of each site and their related parent rocks. Results showed that physico-chemical properties, clay mineralogy and soil classification have been considerably affected by parent materials. Most of the soils in the region had only A and BC horizons and classified as Entisols but the soils derived from shale and gneiss rocks are classified as Inceptisols because of the existence of the diagnostic B horizon. Soil taxonomy from subgroup or family level clearly shows the difference among the soils studied which indicates the importance of soil classification at the lower levels for management purposes. Clay mineralogy showed that chlorite, kaolinite and Mica (except surface horizon of the soil developed over basalt rock and rock sample of shale) were present in all the soils studied and seem to be inherited only from parent materials. Smectite has pedogenic origin in the basaltic and the granitic soils. These clay minerals show lithologic origin in the soils derived from limestone whereas both lithologic and pedogenic origins seem for the soil derived from gneiss rock. Vermiculite seems to be lithologic in the soil developed over amphibolite and pedogenic in the soil derived from shale and mica-schist rocks.

Construction of buildings and different structures leads to soil consolidation and as a result to soil settlement. Soil settlement is a function of variety of factors such as pressure deformation, depletion of pore water and etc. One way for estimating the soil settlement is to use the compression index which can be determined through consolidation test. Determination of this index in laboratory is time consuming. Therefore, in recent decades the researches have tried to relate this coefficient to some soil parameters, such as plastic limit, liquid limit, void ratio, specific gravity and so on, which can be easily measured in laboratory. There are therefore many empirical equations in the literature in this regard. In this paper the correlation of fine soil properties and compression index has been investigated using artificial neural network (ANN). A comparison was also carried out between the measured compression index in laboratory with the corresponding values obtained from the empirical equations and ANN model. The results showed that the Rendon-Herrero relationship calculates this index much better than the other considered empirical equations with the highest correlation coefficient and minimum error.It was found that the ANN model performed better than the Rendon-Herrero formula with higher accuracy in estimating the compression index. It was also found that the calibration of the coefficients in Rendon-Herrero formula from the existing data does not significantly improve the accuracy of this equation.

Some of common hydraulic methods for designing pressurized irrigation systems are: (i) unit head loss method, (ii) (maximum allowable) velocity method, and (iii) percent head loss method. In this research, a twostage economic optimization algorithm was introduced to design pressurized irrigation systems and was developed in LINGO programming environment. Results obtained by this model were compared with the ones from the foregoing hydraulic methods for a hypothetical sprinkle irrigation system comprised of 3 manifolds to assess the performance of the new algorithm. The results showed that this optimization algorithm resulted in 3% lower costs for a small irrigation system and favorable distribution uniformity. Also it was concluded that system design according to unit head loss method with maximum 0.01 m.m-1 head loss resulted in the highest distribution uniformity in comparison to the other methods and the optimization algorithm, unit head loss method with maximum 0.02 m.m-1 head loss and maximum allowable velocity method followed it. The standard deviation of the sprinklers outflow values as compared to the namely outflow value were estimated 0.1, 0.03, 0.05 and 0.12 lit.s-1 for the optimization method, unit head loss method with maximum 0.01 m.m-1 head loss, unit head loss method with maximum 0.02 m.m-1 head loss, maximum allowable velocity method, respectively.

Evapotranspiration is one of the basic components of the hydrological cycle and is essential for estimating irrigation water requirement. In recent years, the use of intelligent systems for estimation of hydrological related parameters has increased dramatically. The objective of this study was to evaluate the possibility of estimating daily reference evapotranspiration by using artificial intelligence systems, and to compare these systems together. The potential of using the adaptive neuro-fuzzy inference system (ANFIS) and the artificial neural network (ANN) techniques was investigated for estimating daily reference evapotranspiration (ETo). Various daily climatic data including daylight hours, air temperature, relative humidity, and wind speed from three synoptic weather stations (Esfahan, Kerman and, Yazd) located in the extreme arid climatic regions of Iran were used as inputs to the ANFIS and ANN techniques to estimate ETo as calculated by the FAO56 Penman-Monteith (F-P-M) equation. A comparison was made between the estimates provided by the ANN and ANFIS and those of the following empirical models: The Makkink, Priestley-Taylor, Hargreaves-Samani, FAO Blaney-Criddle, and Ritchie. Root mean squared errors, mean bias errors, and determination coefficient statistical indices were used for the evaluation of the performance of the models. Results revealed that the ANN and ANFIS techniques could be employed successfully for modeling daily ETo process. The ANFIS85 model with three input parameters including solar radiation, maximum air temperature, and wind speed estimated ETo with a higher degree of a accuracy than empirical models. The FAO Blaney-Criddle model was found to perform better than other empirical models included in this study.

Infiltration is the most important and difficult property in evaluation of surface irrigation systems. The importance of knowing infiltration equation for interpretation of surface irrigation hydraulic and difficulties of accurate estimation of infiltration parameters led to consuming time and cost in designing irrigation systems. In fact, the objective of this study was to present a new developed method for estimating Philip infiltration equation parameters by using two points of advance phase and compare this method with Elliott and Walker two-point method, Benami and Ofen advance method, Shepard et al. and Valiantzas et al. one-point methods. For this purpose, seven data sets measured in the field under different conditions e.g. length, slope and discharge flow were used. By using Hydrodynamic model (SIRMOD software) and estimated infiltration equation parameters by different 5 methods above, advance and recession phases were simulated in order to investigate the accuracy of estimated infiltration equation parameters. The results showed that developed method in this study had the lowest error (4.8%) for border irrigation and Shepard et al. (13.9%) and developed (14.2%) methods had the lowest error for furrow irrigation in estimating total infiltrated volume. Benami and Ofen (19.5%), and developed (6.6%) methods had the lowest standard error in prediction of advance phase for furrow and border irrigations, respectively. Whereas in prediction of recession phase, Shepard et al. and developed methods had the best accuracy for furrow and border irrigations, respectively.

Emitter is the key component in drip irrigation system. It is necessary to have a comprehensive understanding of the flow mechanisms within drip irrigation emitters to design emitters that have a high performance. The use of computational fluid dynamics (CFD) to research the flow characteristics is appropriate because the labyrinth flow path is narrow and its boundary is complex. In this study, the flow in labyrinth channels was simulated by using the method of computational fluid dynamics (CFD) to calculate the distributions of pressure and velocity of the flow, and to calculate the relationship between pressure and rate of discharge for three sample of one type emitter. The emitters were destroyed and sizes of those channels were calculated by photography with Scanning Electronic Microscope (SEM). To calculate the relationship between pressure and rate of discharge as well as simulation of flow in emitters' channels, laminar flow model and turbulence model were applied. Verification of the results obtained from the CFD simulation was conducted in laboratory, according to the ISO9261 standard.The results of simulation for the labyrinth channel well matched the measured data in laboratory Computational fluid dynamics provides a promising tool to help in the design of labyrinth channels used in drip emitters.

For watershed management and water resources planning need to know hydrological relationships among the time series of monthly runoff depth especially at small watersheds. To investigate the ability of selected mathematical model for simulation of monthly runoff depth, 7 catchments were selected in and around of Zanjan province. Areas of all selected catchments are less than 170km2 and acceptable hydrometric data time series long equal 6 to 27 years. At every selected catchments depth of precipitation, runoff and potential evapotranspiration by method of Blaney-Criddle estimated for months of every water year. Sometimes because of shifting partial of winter snow melt runoff to spring season, the monthly hydrometer data was divided to total and sectional data series so that proportion of runoff depth to precipitation depth was less than one certainly. After calibrated the coefficients of mathematical model named (GR2M) by application of all or partial of data series based on maximizing Nash-Sutcliffe coefficient as model performance criterion. Result is that by application of only the partial of data series, Nash-Sutcliffe coefficient is increased 10%. So from viewpoint of geological formations and rock units the sub watersheds divided into two clusters with difference measure of 0.14 about the quantity of outside basin calibration coefficient. Precise of calibrated model of (GR2M) for small and similar climatology condition based on height from sea level and geology conditions evaluated average to good.

In this research, the dynamics of local scour processes is studied in the context of the erosion that takes place downstream from a submerged sluice gate. The most important factors, which affect the local scour processes downstream of the sluice gate are identified and grouped by dimensional analysis to obtain the dimensionless parameters. Experiments were carried out in a horizontal rectangular flume of 9 m long, 0.5 m wide and 0.6 m height. Two gradations of uniform non-cohesive bed material were used for various tailwater depths and flow rate conditions. A total of 22 tests were carried out, each for a period of 12 h. An equilibrium scour condition was not attained over this time period for any of the tests, although a similarity in the bed profiles is observed in the region close to the rigid apron. Based on the experimental data, new dimensionless equations and graphs are presented to determine the shape and dimensions of characteristic lengths of scour hole such as maximum depth of hole and its position, brink scour depth, maximum extension of whole, dune height and its distance from the end of apron. Also, the results are compared with previous researches.

Soil erosion is a hazard associated with agriculture in tropical and semi-arid areas and is important for its long-term effect on soil productivity and sustainable agriculture. Erosion also leads to environmental damage through sedimentation, pollution and increased flooding. This research has been performed in order to assessment and determination of soil resistance or weakness against erosion and also determination of effective factors in this process. Measurements have been accomplished in experimental plots outfitted with runoff and sedimentation reservoirs that located in semi-arid rangeland fields at northeastern Khorasan Razavi province. In this study, many of physical and chemical soil properties, vegetative cover density percentage and slope of the field was measured and finally the relationship between these factors and the amount of eroded soil due to 43 events of erosive rainfall was studied by statistical softwares. The linear multiple regression indicated that three factors of vegetative cover density percentage, percentage of coarse gravel (13-75 mm) in surface layer of soil and slope percentage of the field are the most important factors affecting on soil erosion, respectively. Therefore, management of vegetative cover and slope of the studied rangeland fields are the first steps to reduce the potential of soil erosion.

Protection of soil organic carbon (SOC), as most important soil quality indicator, is the main factor in sustainable agriculture and soil ecosystem conservation. SOC distribution is mainly affected by soil management status. This research was conducted to investigate the effects of physical and management variables on SOC variations and to quantify the relative importance of these variables on SOC distribution in a rainfed watershed by use of canonical discriminate analysis (CDA) and stepwise discriminate analysis techniques. SOC quantities in soil sampling points were classified in four quality categories as: poor, low, medium and high. Then the effects of 30 physical and management variables on prediction of SOC classes were evaluated. Results indicated that among predicting models with physical exploratory variables, model with soil characteristics as independent variables including TNV, SP, gravel, clay and sand was able to reasonably predict optimum SOC class. But all models with management exploratory variable were able to predict optimum SOC class by use of first linear combination of canonical functions at a<0.0001. Model M5 showed highest canonical correlation with the first linear combination. All the variable combinations in significant models were able to predict poor and low SOC classes, precisely. Only M5 model had highest ability to distinguish high class of SOC. Among management variables, tillage system scenario and its components had highest impacts on SOC variability in this rainfed watershed. Stepwise discriminate analysis was able to distinguish the effects of winter fallow system on SOC status improvement.

Trend analysis conducted on streamflow of the Northwest of Iran rivers in three times span namely month, season and annual after removing the effect of all significant serial correlation. Data used were the information of sixteen hydrometric stations selected from 1353 to 1383. Sen’s estimator was used to estimate trend line slope. Three significance levels, 1%, 5% and 10% were used to test trends. Results showed that in annual time scale streamflow of all rivers located in the northwest of Iran had negative trends. The lowest slope of trend line for annual time scale belonged to the Vanyar station, which is equal to -4.49 m3/s/yr. In seasonal time scale, significant negative trends observed for all stations, in which the strongest belonged to spring. In monthly time scale, the numbers of months with negative trends were great than that of the positive trends and about half of the stations had negative trends in the second six months of the year. In general, trends of streamflow of most of stations were statistically negative at 10% level in the three past decades.

Infiltration is very important in management of surface irrigation. Mathematical models that have been developed for infiltration are generally functioning of infiltration opportunity Time. In this study prediction of average depth of infiltration evaluated is using ANN, ANFIS and MLRM methods using initial soil moisture content and furrows inflow rate. Field studies were conducted in five different cities during 1998-2007, under various soil textures. To develop coefficients of Kostiakoff Luis infiltration volumetric water balance method was used. Results showed that regression models were more accurate in heavier soils. Neural Network models were suitable for medium textured soils. These models tend to overestimate infiltration in heavy soils and under estimate in Lighter soils. However ANFIS method was capable of estimating infiltration in any situation with high accuracy.

In this study, corn-field furrow irrigation was conducted to investigate the effect of fertigation on distribution uniformity and nitrate losses through surface runoff. Twelve experiments were carried out during two years (2008 and 2009) in free drainage furrows having 165 m length and 0.006 m/m slope in Karaj.Required fertilizer was applied based on soil analysis in four stages during the growing period: before planting, in seven- leaf stage, shooting stage and earring stage. The outflow from the experimental furrows was measured by WSC flumes. Nitrate concentration of water samples taken during the experiments was analyzed by spectra photometer. Collected data during the first year were used to specify the best time of fertilizer injection in order to achieve the lowest fertilizer losses. The results revealed that the best time of injection was 20 minutes in the end of irrigation. This time was used to apply the fertilizer in second year. Runoff- losses of nitrate in the first year ranged between 5.7 to 42 percent whereas in second year using optimized time (20 min) nitrate losses through runoff was 1.4 to 12.3 percent. Also, the results of the fertigation model showed that the model estimated water and fertilizer losses reasonably well. The correlation coefficient between measured and predicted data by the model was 0.85 and 0.8 for water and fertilizer losses, respectively during two years of experiment.

Soil water movement with root water uptake is a key process transport of water and chemicals in the soilplant system. In this study, two-dimensional root water uptake model was developed, which can be incorporated into numerical flow models. Root water uptake model includes root density distribution function, potential transpiration and soil water stress-modified factor. Root water uptake parameters were optimized, minimizing the residuals between simulated and measured water content data. Tube-time domain reflectometry (TDR) was used to measure soil volumetric water content around a surface-irrigated apple tree at 12 locations. The measured data are compared against the outputs from the numerical simulation of the soil water dynamics that uses Richards’ equation. It shows that 30% of water was drawn from the radial distance of 30-60 cm and average water uptake from the soil layer of 20-40 cm accounts for 60% of the total water uptake. Simulated and measured water contents were in excellent agreement (R2=0.97). Potentially the numerical model is a useful tool to various problems related to flow transport with plant water uptake in variably saturated soils.

Field capacity and permanent wilting point are the most important potential points in modeling and management of agiculutral products water requirement. Direct methods of identifying water content are time consuming and expensive. So use of pedotransfer functions for converting easily measurable characterictics to hydraulic charachteristics is a suitable solution to solve this problem. In this research efficency of NeuroMultistep outflow and K nearest neighborhood Models in deriving PTFs for identifying water content in FC and PWP for 122 soil samples of north and north east of Iran was investigated. In addition effect of different input parameters and data for deriving in both methods was specified. Results showed that in general KNN method (RMSE=0.027) had better results than NNs models (RMSE=0.037). Also we can say that sensitivity of NNs to quality and kind of deriving data is very high and heterogeneous data can decrease the efficiency of these models and increase the RMSE around 100%. Also the results showed that considering one or more hydraulic parameters as an input can improve the modeling results.

The climate change has direct impacts on hydrological process such as evaporation by water surface, transpiration of plant, charge of groundwater, run off and snow melt. In this paper, probable impacts of climate change on evapotranspiration were studied. For this reason, impacts of climate change on temperature (mean, maximum and minimum) and precipitation under A2 scenario and three periods (2010-2039, 2040-2069 and 2070-2099) and by using statistical downscaling of HadCM3 output in kashaf rood basin were investigated. In future stage with estimated parameters, evapotranspiration of plants at cropping pattern include wheat, sugar beet, tomato, apple and corn by Hargrives-Samani equation was calculated and for various periods were comparison. The results indicated that temperature (mean, maximum and minimum) have increased rather than 1961-1990 in all periods. Predicted mean annual precipitation has not significant different but the pattern of precipitation will change in various seasons. Thus, amount of precipitation will decrease for summer and winter months and will increase for spring and autumn months. Calculated evapotranspiration for all months and all periods will increase by rising temperature. Amount of increasing at evapotranspiration will larger for warmer months of year by more increasing in temperature. The results indicated that with rising in temperature by 1,2 and 4 centigrade, water requirement of cropping pattern in this plain will increasing by 6,10 and 16% respectively.

The solar radiation received by earth surface is one of the most applicable parameter that is usable in projects and hydrology, agriculture, Meteorology and climatological modeling. Since very expensive instrument for measuring the radiation, had been suggested many different experimental equations by researchers to estimate this parameter in different climate. In this research, seven models of estimate of short wave solar radiation including 1- the model of Angstrom–Prescott suggested by FAO, 2- the calibrated model of Angstrom–Prescott by Khalili & Rezaei Sadr, 3- the calibrated model of Angstrom–Prescott by Khalili & Rezaei Sadr by using Absorption spectrum of water vapor, 4- calibrated model of Angstrom–Prescott by Alizadeh & Khalili, 5- Linear Regression Model of Alizadeh & Khalili, 6- Sabbagh model and 7- Glover & McCuloch model, were investigated to recommend the suitable model for this area. Results of comparing calculated amounts of these models whit amounts of measured by piranometr shows that by using coefficient of determination, the models of 1, 2 and 4 (equal 0.8505, 0.8507 and 0.8507 respectively) have higher correlation with actual amounts. But because of a little different of R2 between these models and less amounts of RMSE, MBE and t indexes (equal 2.68, 0.16 and 0.59 respectively) in model 1, can recommend this model as the suitable model of estimate of solar radiation in this climate.