Iranian Journal of Irrigation and Drainage
Year:2016 | Volume:10 | Issue:5 |Papers Count:14

Traditional method in flood frequency analysis is parametric approach. This method lacks the ability to describe multimodal and Asymmetric densities. In order to overcome this problem, the nonparametric models can be used. Two methods of nonparametric approach are: fixed and variable kernel density. In fixed kernel density method, the probability density function can be estimated by selecting a kernel function and optimal bandwidth and in variable kernel density method the probability density function can be estimated by selecting a kernel function and bandwidth at each observation point. Cross validation and Rule of thumb are common methods for estimating the optimum bandwidth. In this paper, besides mentioned methods Plug in bandwidth method is used and nonparametric flood frequency analysis is performed using annual maximum flood data of the Dez river. Finally results were compared with parametric method. According to RMSE, it is concluded that plug in bandwidth is the most accurate method for estimating optimum bandwidth. As well as Nonparametric method based on variable kernel density is more accurate than fixed kernel density and both types of these models are more accurate than LP3 distribution.

Reference crop evapotranspiration is one of the important factors of hydrological cycle. This parameter is used to design irrigation systems, hydraulic structures and drainage systems. One of data that required to calculate the amount of reference crop evapotranspiration is solar radiation which in the absence of this data, monthly sunshine duration data will be used. At the most of the weather stations of Iran the data of monthly total sunshine hours is not available at previous years, so the need to rebuild the data is felt. In the present study two kind of artificial neural network model (MLP and RBF) and meteorological data of target station and monthly total sunshine hours of neighbor stations are used to rebuild the missing data. The results showed that using data from meteorological data of target station and neighbor station, the total monthly sunshine reconstructed with high precision. The results of the different scenarios showed that if only the meteorological of target station such as minimum and maximum temperature, average relative humidity, solar radiation, extraterrestrial radiation and straight, dark and cloudy days number is used, with a precision of RMSE=16.79 hour and MAR=6.44% the monthly total sunshine hours is estimated. Also if only the data from nearby stations is used, the estimates would be more conducive to accuracy (RMSE=14.25 hour and MARE=5.71%). The best results were obtained when both weather data set of target station and adjacent stations are used (RMSE=13.78 hour and MARE=4.97%).Comparison of the performance of the ANN-MLP and RBF ANN-MLP showed that the accuracy of MLP neural network is somewhat greater. Finally the time series of monthly total sunshine hours and reference evapotranspiration were renovated.

Accurate estimate of longitudinal dispersion coefficient is important in many hydraulic and environmental problems in rivers such as river engineering, intake designs, modeling flow in estuaries and risk assessments of pollutants into river flows. To accurate investigation of water quality using one dimensional model, the precise estimation of longitudinal dispersion coefficient is required. Direct measurements of longitudinal dispersion coefficients, with the aid of concentration samples taken in upstream and downstream of rivers is rather seldom.Recent research works indicate that, using the data driven method can improve the precise estimation of longitudinal dispersion coefficient in natural rivers. In this research, the usefulness and performance of Group Method of Data Handling (GMDH) approach are examined for predicting longitudinal dispersion coefficient in natural channels. A set of 71 data sets from different river has been gathered so that 51 sets of whole data were used for training and 20remaing sets were used for test data sets. The hydraulic and geometric variables such as mean flow depth (H), width of channel (W), mean flow velocity (U), channel sinuosity (s) and shear velocity (U*) are used as input variables to predict longitudinal dispersion coefficient (Kx). A computer program based on GMDH approach is written in MATLAB software for Kx modeling. Based on the values of various performance indices, R2, RMSE, CC and DR, it is concluded that GMDH model in both training and validation period predicts the longitudinal dispersion coefficient more accurately. Comparison of GMDH model with empirical approach and another data driven method such as ANN, SVM and GA confirm that GMDH shows remarkably good performance in capturing governing pattern in longitudinal dispersion phenomena in natural rivers. Hence GMDH can be used as an efficient computational paradigm in the estimation of longitudinal dispersion coefficient in natural channel.

In recent decades, predicting variations of soil moisture and soil salinity is require for irrigation management in agricultural fields at areas with limited access to water resources. The SALTMED 2013 model is one of the available common models that is including different irrigation systems, different soil types and crop types, and can be used to water, soil, and crop management in field. The physical base of this model is the water and solute transport, evapotranspiration, and water uptake equations. In this paper, the SALTMED 2013 model was used to calibrate and validate of soil moisture and salinity profiles of pistachio tree grown on loam silt soil in a region under desert climate at Southeast Iran, Sirjan. Pistachio trees irrigated by subsurface drip irrigation (SDI) system and saline water with EC=2.5 dS/m. Irrigation frequency was once every 3 days and was done based on the moisture reading using time domain reflectometry (TDR) tube. Soil moisture and salinity variation simulated at distances of 10, 40, 60, and 90 cm from emitter and at depths of 20, 40, 60, 80, and 100 cm from soil surface.The results showed that model accurately simulates soil moisture content near the emitters, but has over-estimate in distances away from the emitter. The results of calibration and validation of the SALTMED model for solute simulate indicated its ability in predicting dynamic distribution of salinity in SDI systems. So, the model can be used as a useful tool in soil- water- plant relations and their management.

In this study, AquaCrop model was used in order to investigate the effect of planting date and supplementary irrigation on the performance of spring lentil in the Qazvin plain. In order to achieve this goal, the model was first calibrated for lentil plant. To determine the optimum planting date, six dates in common period of time of spring lentil planting in the region with interval of 10 days as well as at eight model proposed dates based on precipitation and temperature criteria were selected. The amounts of yield were simulated for each 14 planting dates using calibrated model and four planting dates with the highest yield were determined. Then, for each of these planting dates, the yield values for the two different dates of supplementary irrigation were estimated and compared. Based on the results, the highest yield is related to planting at the period of mid-February to mid-March and the best time for supplementary irrigation is 55 to 65 days after planting at flowering stage. Also, it was concluded that with one stage of supplementary irrigation at the right time, an increase of about 90 percent in lentil crop yield can be achieved compared to rainfed condition with the same planting date.

One of the drought atmospheric phenomena that can in any area done and led to major losses economical, social and environmental. This phenomenon from various sectors of environmental, including the ground water resources during the period of its sovereignty. Effect Drought on groundwater resources far less attention. In this study using the SPI index and the water table level underground standard (SWI data) affected by the drought on underground water resources the Yazd ardakan blue years 82 1381 to 91 1390 for all existing wells and long term statistics for 8 basin has been selected. in the intensity of the spatial. In examining the spatial distribution of drought severity of the decline in the aquifer using map sowftward Gis. The drought in the stations studied were determined by Mann-Kendall. The results showed that in the year 79-1378 and 87-1386 in the water during the worst drought in most of the stations were located. It also examines the impact on the level of ground water hydrological drought of SWI index is used. It also examines the impact on the level of ground water hydrological drought of SWI index is used when the results show the recent drought, caused a drop in water table and groundwater levels are all well studied in Yazd-Ardakan. finally, the correlation coefficient between the depth of the groundwater level and the time scale of annual rainfall, the highest correlation coefficient was found to well Shahneh and Charkhab.

Hydraulic jump is the most important phenomenon in the rapid variable flow is of interest to hydraulic engineers. It has been used for dissipation of kinetic energy downstream of hydraulic structures such as spillways, chutes and gates to protect stilling basin. This study the roughness of the bed and the divergence of basin have studied simultaneously. The experiments have done with the walls diverging angles of 0, 2, 4, 6 and 8 degrees for six different Froude numbers. In total, 190 tests were performed in the range of 5 to 8 Froude numbers. The relative depth reduction of jump in the angles of 0, 2, 4, 6 and 8 degrees have obtained 10, 17.2, 22, 25 and 25.5% respectively. The average reduction of length jump, T, for the angles of 0, 2, 4, 6 and 8 degrees with the rough bed have obtained 45.5, 55, 56.1, 64 and 66.2% respectively. The man reduction of length jump for the cube bars is 60.3%. The loss of energy in the jump EL is equal to the difference between the specific energy before and after the jump, E2 - E1. The relative energy loss, EL/E1, for the angles of 0, 2, 4, 6 and 8 degrees have obtained 58.5, 62.4, 64.1, 65.9 and 67% respectively. In this study, the effect of the square ribs bed on hydraulic jumps was investigated. The divergence of basin without roughness effect also has influenced on reducing the relative length of jump about 37 to 47% and the relative length of jump is proportional to the angle of divergence basin. The results show that both the divergence angle of stilling basin wall and bed roughness of bed have reduced the length and depth of hydraulic jump. This makes it more economical to build a basin and control of jump is better.

Identifying of homogeneous regions from viewpoint of drought occurrence over time, provide understanding the extent of regional droughts in addition to recognition the impact of different effective precipitation systems in different regions. On the basis of this concept, the long term 25 years rainfall data belonging to 120 synoptic meteorological stations which distributed throughout Iran country are used in this study. Standardized precipitation index (SPI) is applied to calculate drought intensity, in 12, 24, 48 time months window and the Kriging method used for drought zoning. Spatial network with 10 kilometers pixel size is considered and interpolated SPIs values is extracted for this network using Arc GIS environment and used to prepare a matrix.The extracted data in matrix form clustered for in different scenarios i.e. annual, biennial and quadrennial, based on K-means method and optimal numbers of clusters calculated considering silhouette plot values. The results show Iran country classified to 12, 9 and clusters considering annual, biennial and quadrennial long term meteorological drought and prolonging drought time window caused reduction in numbers of clusters.Moreover, each of the three Northern provinces that located in southern Caspian Sea rim, classified in separate clusters and southeastern Iran that followed the monsoon precipitation regime, constitute a separate cluster too.

Drought is one of the natural hazards which have serious effects on human life, and environment. This phenomena has a complicated mechanism that its nature had been little-known. Accurate estimation of low flow as an index in water resources management has a great importance. Because of the complicated nature of low flows, a few numbers of studies conducted in this field of study, and the frequency analysis of low flow is of interest to researchers. Therefore, in the present study, the frequency of low flows in the Dez river basin with different durations (7, 10, 15, 30, 60 and 95 days) were done using the distribution functions of the Normal (NOR), Log-Normal (LN), Pearson Type III (P3), Exponential (EXP), Gamma (GAM), Generalized Extreme Value (GEV), Nakagami (NAK), Rayleigh (RAY), Logistic (LOG), Generalized Logistic (GLOG), Generalized Pareto (GPA) and Weibull (WEI). Before fitting the statistical distribution functions on low flow series, the homogeneity and stationarity of low flow series in the Dez river basin were investigated by Augmented Dickey - Fuller (ADF) and modified Mann-Kendall tests, respectively. The results of these tests confirmed the homogeneity and stationarity of used data series. In the next step, above mentioned distribution functions were fitted on low flow series and the goodness of fit were evaluated by normalized root mean square error and Nash- Sutcliffe criteria. The results reveal that the LOG and GEV distribution functions were the best fitness on low flow series in the Dez river basin. The Normal distribution has also good performance in estimating the low flow and because of its easier application can be considered as an alternative for estimating low flow in the Dez river basin by acceptable error.

Climate change is one of humanity's today problems and is considered as a threat to the planet so Identify and predict its elements, is very important for the management of crisis situations. In this study the time variation process of the evapotranspiration parameter for wheat crop, along with the temporal change soft emperature in Isfahan city, was studied. Therefore, data fromsynopticweatherstationsofthe47-year period (1964-2010) were used and with using parametric, Regression Analysis and nonparametric, Mann-Kendall tests, significant for monthly and annual time seriesof95and99percentsignificancelevelswas evaluated. The results showed that the temporal variations of evapotranspiration of wheat have been declining. The most significant monthly evapotranspiration trend was observed in July and August, although there was no significant trend of increasing temperature. Based on the annual time series, evapotranspiration showed a significant downward trend in the level of 99percent, with a slope of about29%, however, the temperature increase was not significant. Comparing the results of both evapotranspiration and temperature changes by both tests indicate that this phenomen on of evaporation paradox existed in Isfahan city.

To determine and locate of the flood-prone areas, effective flood factors in every sub-basin through the flood control studies can play an important and indispensable role in better management of large ecosystems. In this study, the priority of basin flood control operation was done by applying different parameters such as Digital Elevation Method cell size, runoff curve number in three ground moisture, calculation of unit hydrograph with two different method, and presence or absence of depression storage were examined. The result showed that without the presence of depression storage in sub-basins, the effect of Digital Elevation Method cell size and time concentration on potential flooding in the basins, is very negligible in comparison with the runoff curve number parameter but with the increase of depression storage rate; in addition priority is changed and the effect of other parameters on flood basins are increased.

Flood risk analysis studies carry out based on estimation of the probability density function (PDF) of flood peak. Conventional approaches to estimate the probability density function distributions are parametric methods that have constraints such as sensitivity of fitness precision to reduction in sample size. Non-parametric methods to estimate the PDF have fewer restrictions than the parametric distributions. In this study, Exponential, Log-Normal, Gamma and Gumbel as parametric distributions, Ortho-Normal Series method as a non-parametric method, and Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Mean Square Error (MSE) as precision criteria were applied to investigate the precision of mentioned methods and their sensitivity to reduction of annual maximum peak flow series. The precision and change in precision of fitness of parametric and non-parametric distributions to sample size reduction were investigated based on five hydrometry station (with 38 to 48 years recorded datasets) in Golestan province. The results show that the precision of nonparametric ortho-normal series method is considerably higher than parametric distributions. In addition, orthonormal series method is less sensitive to sample size reduction than parametric distribution that makes it as suitable option where the recorded data sets are belonging to relatively short time period.