Journal of Irrigation and Water Engineering
Year:2014 | Volume:4 | Issue:15|Papers Count:10

One of the Catchment Area has it, s own parameters according in infiltration to its continent and soil (soil structure, vegetation complex, pore space). In this research, the shores of eternal rivers of Boshehr studied Mond River- Dashti Township. In this research, with special lattice and digging 60 well, the infiltration of water to soil measured by double ring outdoor test method and by three repetitions to control and determining the equation and computing equations coefficient of infiltration .By computing soft ware's, the rate of infiltration and aggregation infiltration curves depicted and the equations appointed. The computer programs in visual basic language is written in order to determine the equation coefficients that showed the lowest and the minimum standard error (S2) toward the given curves, for 8 models. In this research best coefficient of these models with minimal errors for case studied Catchment Area was chosen. Those programs best coefficients of these experiment-adjusted models with arising errors; by inserting various coefficients models Philip, Kostyakov and SCS, and in regularity are better than Kostyakov-Lowece, Green-Ampt, Overton, Horton and Hall models.

One of methods to reduce water losses in fields is correct programming of irrigation and accurately estimate the crop water requirement form the basis of this programming that is the coefficient of Reference Evapotranspiration. Reference Evapotranspiration is a complex and multivariate phenomenon that depends on climatic factors and most accurate way to estimate it is lysimeter but using Lysimeter requires a lot of time and money, hence the Evapotranspiration estimation is done by meteorological parameters and applying empirical models. These models have the coefficients that each coefficient is representative of regional conditions that equation is calibrated in that area. According to that the evapotranspiration process is complex and nonlinear, therefore using of methods that can this complexity of modeling, it seems necessary. Therefore in this study was used of artificial neural networks for evapotranspiration modeling and in this context of MATLAB software was used. The purpose of this study was to evaluate artificial neural networks and 11 methods known in the estimation of reference crop evapotranspiration for Urmia Kahrizi Research Station. based on daily meteorological data and 4-years data from Lysimeter of the station, Evapotranspiration was calculated to above methods. The results of calculations showed that the Artificial Neural Network has better performance than all the classical methods, it has a RMSE, MAE and R2 respectively is equal to 9.65 (mm/10 day), 7.53 (mm/10 day) and 0.804. Also among the classical method, the Turc with the lowest RMSE, MAE and R2 equal to 11.69 (mm/10 day), 8.99 (mm/10 day) and 0.719 is a priority. Jensen-Haise, Penman-Monteith-Fao 56 and etc methods has been corrected in the next priorities.

Due to the importance of groundwater resources, in order to calculate the average level and estimate the water level in plains, it is necessary to generalize the information collected from point to the plain. Application of geostatistical models has always been associated with error, because the fitness function given in most cases is not include all the experimental. The aim of this study is An investigation on the application of combined geostatistics with optimized Artificial Neural Networks by genetic algorithm in interpolation of groundwater level in Ramhormoz plain. The obtained results from Kriging, Cokriging and IDW methods, are shown cokriging with the Gaussian variogeram in Ramhormoz Plain are the best geostatistical method to estimate the groundwater level and combined with neural networks. results the combination of these two models showed that combined optimized model by genetic algorithm possesses have better evaluation criteria than geostatistical methods to estimate groundwater level and proposed As a reasonable combined model to an estimate of the groundwater level.

This study was conducted to determine the yield response factor potato (ky) to deficit irrigation at different growth stages in a randomized complete block design with five treatment, E0 (Full Irrigation), E1 (85%), E2 (70%), E3 (55%) and E4 (30%) of actual evapotranspiration plant potato in three growth stages T1: seed and vegetative establishment, T2: the full development and T3: get the plant growing season in three years. the sharekord. Evapotranspiration potential of the potato crop was lysimeter drainage water balance method used to estimate the neutron meter. After harvest, yield and yield components were determined and potato yield response coefficient was calculated. The results of data analysis showed that deficit irrigation effects on potato yield is significant at the 5% .Maximum potato yield in full irrigation equal to 43416 kg up to 22150 kg in the lowest 70 percent evapotranspiration treatment- plant evapotranspiration in the third stage of plant growth. evapotranspiration potential of the potato in the region with 944 mm and 542 mm minimum was E4T3 treatment. Coefficient responses yield of potato (Ky) with respect to the treatment of low irrigation for the first stage of growth between 0.65 to 1.18 and the second stage of growth between 0.82 and 1, and in the third stage of growth between 0.7 to 1.17 and the maximum growth season with 1.11 respectively.

Selecting appropriate interpolation method can lead to the production of more accurate maps. The aim of this study was to determine the appropriate method of interpolation and mapping for nitrate and phosphate in the Shahrekord Aquifer from the methods: kriging, co-kriging and inverse distance weighting. For this purpose, the concentrations of nitrate and phosphate were measured in 97 agricultural wells. For both nitrate and phosphate, the ordinary kriging was appropriate and enough. For nitrate, ordinary kriging resulted in R2=0.99, RMSE <1 mg / L and ME <0.1 for nitrate; and R2 close to the unity, RMSE=0.01 and ME close to zero for phosphate. Efficiency of the inverse distance weighting method was weaker than kriging and its efficiency statistic further deteriorated by increasing its exponent from 1 to 5. However, this method is a good alternative for kriging. Co-kriging did not improve the interpolation over kriging and therefore, is not worth the costs and efforts involved. Maps showed that the concentrations of both pollutants increased from the northwestern to the southwestern part of the aquifer. Examination of conformity of observations statistical summary to maps further indicated the applied kriging was appropriate. In general, using ordinary kriging is recommended for mapping of nitrate and phosphate in the Shahrekord Aquifer, due to higher accuracy, less calculation and less required data.

The main problem facing trickle irrigation systems are emitter clogging. Water quality is mainly due to emitters clogging. The purpose of this study was to assess the extent to clogging emitters using water quality in predicting clogging emitters in drip irrigation systems in the country are affected. For this purpose, 10 different parts of the system in terms of different weather conditions were selected. Emitters blocked in each system were collected and the factors that cause clogging in the system have been determined. The results showed that the predicted risk of clogging emitters using common indicators of water quality characteristics based on the realities of what happened in all the systems were combined with high uncertainty. In 60% of cases clogging the emitters to predict potential chemical agents and the other was related to the combined effects of three factors (Physical- Chemical- Biological). But in most cases the actual clogging occurred on emitter's physical factors. The uncertainty of the systems to return them to operation management includes: Lack of proper washing of the central control unit, don't wash pipe network after installation the online emitters, lack of preventive measures include use of chlorination and acid injection into the system if necessary, and most importantly, lack of correct application of fertilizers with irrigation water due to the manner, timing and injection rate of the principles network.

Consideration of water quality and implementation of appropriate actions for preventing of water resources pollution is a very important issue in Iran because of surface water deficit. Sustainable development of agriculture is impossible without considering of surface water quality. Water quality control is a noteworthy issue in irrigation scheduling program of agricultural land. Since surface water quality monitoring and assessment is very expensive and time consuming. Thus, finding a cheap, simple and relatively exact method which can predict the water quality class base on minimum hydro chemical parameters would be very useful. Decision tree as one of the data mining techniques classify data sets based on a tree structure and uses for prediction base on extracting the exiting patterns and roles among data sets. In this study, the decision tree method was used to classify water quality in some hydrometrics stations located at southern side of Sahand Mountain, including Chekan, Girmizigol, Shishovan, Tazekand and Moghanjig. The water quality classes were defined based on if-then rules. The results showed that the decision tree method is able to predict the water quality classes based on small number of hydro chemical parameters with high accuracy.

Evapotranspiration is one of the most important determinants of the hydrological cycle and surface energy balance. In fact Evapotranspiration cause the relationship between such as atmosphere and earth important elements. Most methods that have been presented use point measurements to estimate evapotranspiration. These methods are only suitable for the Local areas due to dynamic and changing nature of regional evapotranspiration are not generalizable to the Basin. Remote sensing has the capability to estimate and to assess the amount of evapotranspiration and its spatial distribution. Surface energy balance algorithm for land (SEBAL) is a new algorithm for estimating evapotranspiration in most parts of the world and other heat fluxes at the surface and have a satisfactory results. In this research evapotranspiration results derived with SEBAL algorithm was compared with FAO evapotranspiration standard method. The results indicate that the algorithm SEBAL determine the actual evapotranspiration in a large area without the need for more meteorological data. The results show that the obtained rate of evapotranspiration in SEBAL algorithm has less than the Penman -Monteith about 1-1.5 mm/d.

The wetted soil volume (WSV) is the most important principle in drip irrigation designing which is applied to determine irrigation intervals of raw crops. Therefore and based on time series techniques ability in modeling and forecasting of hydrological phenomena, a set experiments were conducted at East Azarbaijan Research Center for Agriculture and Natural Resources, Tabriz, Iran with the aim of time series modeling and forecasting of WSV from a point source. The point source discharges were selected as 2, 4 and 8 Lh-1 and WSV were estimated based on vertical and horizontal advance of moisture. Also, wetted soil volumes were estimated for several times. Results showed that WSV had non-stationary behavior during 210 min. Differencing natural logarithm of WSV data were applied to make stationary behavior for WES data. Accordingly, to describe WSV from point sources, ARIMA (1, 1, 0) was recognized as a suitable time series model. Based on achieved model, WSV series were forecasted as 38, 164 and 223×1000 cm3 for the next 90 min (from 210 to 300 min). It is recommended that ARIMA (1, 1, 0) can be applied to model and forecast wetted soil volume in similar soil condition.

In order to the lack of perennial rivers, so maintains of groundwater resources must be used priors programs in the management of Iran water resources. The aim of this paper is study the situation of groundwater resources in Neishaboor plain so that, based on the quantity and quality data in Neishaboor plain approach to exploit potential zoning of groundwater resources plans. Generally, in order to pumping testing results the mean of storage coefficient and the mean of transmission coefficient in studied area are about 1000 m2/d and 0.051. Follow the results for decreasing of groundwater based level is from northeast to south west and from south to central and west. Neishaboor plain aquifer are formed by flows from north, northwest, northeast, east and south are influenced by hydrogeology recharge by Binalood mountains. The maximum and minimum of groundwater base level is 143.9 and 3.96. The east and south of plain have more exploit potential index than to other regions, the central of plain and Neishaboor in order to high quality and low based level, are the low index which the main cause of them is low transmission coefficient (about 200 to 300 m2/d) which resulted the low discharge of well in this regions. The index in central part of the plain is about 0.011 to 0.185 and is located between 0.185-0.261 very low in order to salinity, the main cause of them is high transmission coefficient and declined in Water level in this studied area.