مجله آبیاری و زهکشی ایران
سال یازدهم شماره 2 (خرداد و تیر 1396)

Today, widening the gap between supply and demand serious attention to the principles of allocation and management of water supply and water demand is inevitable is necessary.In this regard Vensim model based on the theory of dynamic systems for planning and management of water resources and uses in the catchment of Nishapur in the KhorasanRazavi province were used. Finally policy scenarios are based on the proposed model was implemented. Results analysis of running various scenarios over the next 25 years in Nishabur plain to study the aquifer water level changes due to pressur irrigation systems development was done, so that the development of the first scenario (normal rainfall conditions) showed an increase in annual acreage about 1.38, acreage constant 0.95 and reduce the acreage of about 0.77 m drop in water table of the aquifer will see annual drowdown in aquifer levels over the course of the simulation and reality (about 0.87 m), respectively, an increase of 58 percent, an 8 percent increase and 12% decrease at will. So if fixing reduced acreage of agricultural land and ground water storage can be increased somewhat, and the severe decline in aquifer water level to prevent, however, the use of pressurized irrigation systems coupled with increased acreage loss of aquifer water level will be intensified.

Estimating soil moisture along a vast area is mostly expensive and sometimes undoable. One of the newly available technique is remote sensing, which allows the possible surface soil moisture estimates in a large scale. Therefore, the objective of this research was to investigate the possibility of estimating surface soil moisture using MODIS satellite images in compare to soil moisture measured data. To conduct this research, vegetation and temperature indices from MODIS images were extracted from October 2013 to June 2014 period for Gonbad-e Qavus region, then measurements were calibrated with field measurement data. The results indicated that significant but weak correlations are available between NDVI and NMDI indices with measured surface soil moistures (R= 0.62), while there were highly significant, but negative correlations (p ≤ 0.01; R = -0.89) for LST index and thermal bands of 31 and 32 with surface soil moistures. The TVDI index also had highly significant, but negative correlation (p ≤ 0.01; R = -0.90) with surface soil moisture. There were also highly significant linear and exponential correlations between SWI index and surface soil moisture. In conclusion, the results indicate promising relations for thermal and combined models to estimate surface soil moisture relative to vegetation models.

For evaluating border irrigation, it is needed to use advance data. Due to soil variability, as well as initial and boundary conditions in border irrigation, water advance rate varies considerably indifferent borders. In recent years, Scaling approach has been adopted as a means to reduce measurement data on water and soilissues.The aim of this study is to provide a unique equation, independent of initial and boundary conditions, for evaluation of water advance in border through scaling approach. For this purpose border irrigation was solved under the kinematic wave model and Philips 2-term equation for the infiltration. Physically basedscaling factors were defined, attempted to scale the border irrigation for the advance trajectory. Scaling advance curves followed some certain quations, therefore, power, exponential, and parabolic equations were fitted for water advancing of trajectories. The equations obtained using the scaling and the volume balance equation were evaluated for 25 different borders. Four statistical indicators, i.e. coefficient of determination (R2), distribution around line of perfect aggrement, percentage of model prediction error (Er), and percentage of average relative error (Ea) were used.The results showed that the power model with R2 =0.893, λ=1.003, Er=0.9 and Ea=13.76 performed better than the other two models. In comparison with the volume balance equation, the power equation can be more accurate. Simple form and independent of the soil type equations presented are superior methods over previous researches in this field.

Stepped spillways are used in high dams, diversio dams and in watershed structures. Since gabion structures in many places is a good option, Gabion stepped spillways are being built with a height between 1 to 3 meters and these structures usually can be built with the same form. In this research compare the energy loss in gabion stepped spillways and rigid stepped spillways is done. To reach this goal, models of rigid stepped spillways and gabion stepped spillways was built with the same geometric dimensions and was installed in a laboratory flume with 50cm width and 11m length. Spillways have 1, 2 and 3 steps. Flow with different discharges was flowed in the flume. The results showed that the maximum efficiency of energy losses in the first case (one step) of rigid stepped spillways is 25/8%, the second case (two step) is 56/6% and the third case (three step) is 65/2%. Also the amount of maximum energy losses for the first case (one step) of gabion spillway is 49/9%, the second case (two step) is 71/3% and 73/5% for the third case (three step) respectively. This research showed that stepped gabion structures in the case of 2 and 3 steps have 16/9% and 16/3% (in average) efficiency of energy losses more than rigid structures. Also increasing the flow discharge, reduced the efficiency of energy losses. Further more increase the number of steps increases the energy losses. The effect of the second step in increasing the efficiency of energy losses was more than third step.

Shallow groundwater table changes are important and effective factors in studying and ground water resources management especially in agriculture and drainage issues. Practically, because of lack of the number of observation points, reading and observation, because of time and financial problems, the information availability is limited. Thus, the application of interpolation methods and estimation water level in specific points base to information adjacent points studies have special position in the groundwater resources studies. In this study, deterministic and Geostatistical methods evaluated in order to determine the most appropriate method for Spatial and temporal variability analysis of shallow water table in 1700 hectare areas of agricultural land of Dashte_naz Sari company, in 81 observation well with 500*500 meters regulation grids. The results show that in deterministic methods, Inverse Distance Weighting and radial basis function have more accurate than other methods with a root mean square error of 54 cm to 55.9, and the mean absolute error of 42.1 to 45% and the correlation coefficient of 0.21 and 0.27 for data of 15 March and 21 December. Due to the high spatial variation of water level because of localized drainage problems in this area, deterministic methods and kriging haven’t sufficient precision. For the data of 21 January and 15 April, cokriging method (with the co-variable of water level in the previous period) with 26.7 and 34 cm root mean square and mean absolute error of 17 and 24 percent and correlation coefficient 0.83 and 0.75, have more accuracy. K-Bessel Variogram model also had stronger spatial structure. In the case of high Spatial variability of shallow water table, cokriging geostatistics method with the help of a co-variable will be significant effect on increasing the precision of the spatial distribution of shallow water table and resulting 37% and 50% decrease of root mean square error and 44% and 59% decrease of the average absolute error.

One of the consistency ways to endure precipitation scarcity beside coastal region of country is using unconventional waters such as Sea water. The target of this study is to investigate the feasibility of mixingCaspian Sea water with available common water and different irrigation water levels on yield and oil content of soybean in Golestan province. An experiment in a completely randomized factorial design with 9 treatments and three replications was carried out to investigate the simultaneous effects of salinity of mixing Caspian Sea water with common water and different irrigation water levels on yield and oil content of soybean in research farm of Gorgan University of Agricultural Sciences and Natural Resources. The treatments were including three main treatment irrigation levels of 75 %, 100 % and 125 % of crop water requirement and 3 sub-treatments involved the irrigating with well water with salinity 0.6 dsm-1, 5 dsm-1 (salinity threshold tolerated by soybean) and 8 dsm-1 (Over the salinity threshold) ,With three replication was down in 27 basins with 3 × 3 meters surface. The statistical analysis showed that the effect of Caspian Sea water salinity mixed with well water on the weight of one thousand seeds, plant weight and oil content was significant at the one percent level. Also the effect of irrigation level on weight of one thousand seeds and plant weight was significant on 1 percent but on oil content percent was not significant. Although irrigation water amounts had significant effect on oil content percent at 5 percent probability. For grain yield and biomass, the performance was reduced with increasing salinity levels So that the highest yield was observed in treatment I2S1 (100% of irrigation level and no saline water) and also the lowest yield was observed In treatment I3S3 (125% of irrigation And 8 ds/m of salinity). The highest water efficiency in was observed in control treatment around 29.83 kg/hac.mm and also the lowest efficiency was observed in treatment I3S3 (125% irrigation level with 8 ds/m of salinity) around 6.06 kg/hac.mm.

Vegetation Indices (VI) show different results in green leaf area index (gLAI) estimation. The objective of this study is to estimate the gLAI of winter wheat and barley using spectral vegetation indices and presenting equations that are able to properly estimate gLAI on its entire range without any reduction in VIs’ sensitivity to gLAI. Taking field data into account for developing gLAI estimation equations using different VIs derived from MODIS imagery, accuracy assessment of these functions using statistical indices, sensitivity analysis, and presenting the best-fit function for gLAI estimation are the main steps of this study. gLAI was destructively sampled in the fields of Hezarjolfa agro-industry located in Qazvin irrigation network in 2015.Results showed that gLAI changes from 0.07 to 5.81 for wheat and from 0.01 to 3.76 for barley. VIs used in this study derived from band 1 and 2 of MODIS imagery were Normalized different vegetation index (NDVI), simple ratio (SR), wide dynamic range vegetation index (WDRVI), weighted difference vegetation index (WDVI), and soil adjusted vegetation index (SAVI). The best-fit function was concluded from WDRVI with R2 of 0.78 and RMSE of 0.73. Even though the sensitivity analysis showed that WDRVI can properly estimate gLAI in its entire range, NDVI and SAVI had better results in estimating gLAI

Evapotranspiration is one of the important components for the planning and management of water resources, especially in arid and semi-arid areas. Sorghum (Sorghum bicolor L.) is a plant that is resistance to this condition and it is suitable for forage production. Experiments were carried out in the months of May to October 2015 in accordance with the warm season in the climate of Kerman, to determine the actual evapotranspiration (ETc) and crop coefficients (Kc) of the plant. For measurement of ETc, the prevailing water balance equation and a drainage lysimeter that is located in research farm of Shahid Bahonar University of Kerman were used. Also, the reference evapotranspiration (ETo) was determined from standard FAO-Penman Monteith equation. The results showed that the amount of sorghum Actual evapotranspiration (ETc) from lysimeter was 680.7 mm. Also, plant reference evapotranspiration (ETo) using FAO-Penman-Monteith was 744.3 mm. In this study, crop coefficients in four stages of plant growth (initial, development, middle and end) of sorghum in this climate were determined to be as 0.58, 0.92, 1.12 and 0.98 respectively.

Evaluation of watershed hydrograph is prerequisites for the appropriate design of soil and water resources management programs in the watershed. Therefore, in ungauged watershed, simulation of storm water hydrograph is important for designing flood control measures, determining flood-plain boundaries and watershed management plan. The Clark method is one of the most applicable techniques for simulation direct hydrograph whose efficacy depends upon the accuracy in estimating storage coefficient. However, very limited studies have been conducted to using optimization method for Clark parameter estimation. Therefore, this study is focused on parameter estimation methods of GA and PSO for estimating the k parameter (storage coefficient of Clark model) and compare with graphical method. The Tamar watershed located in Golestan Province with 1515 km2 selected for this purpose. After collected physiographic, rainfall and runoff data for eight storms, the Clark's time-area model was employed for simulation of flow hydrograph and routed to the watershed outlet. The results of study revealed that the Clark’s IUH resulted from PSO optimization method for estimation storage coefficient (K) has better performance with efficiency coefficient of 0.64 than GA and graphical method (efficiency coefficient of 0.60 and 0.52, respectively). The results also, showed that Clark IUH model predicted all hydrograph component with good accuracy.

The sediment rating curve is the most widely used method to estimate river suspended sediment load that shows the relation between conditional mean of suspended sediment load and river discharge using Ordinary Least Square (OLS) regression and is be applied to estimate suspended sediment load as a function of the river discharge. The OLS regression model is sensitive to outliers and when its assumptions including assumptions related to the residuals analysis are not satisfied, is not acceptable. Quantile regression is a statistical method that can be used to overcome these limitations in sediment rating curve analysis. In this study, quantile regression method was used to estimate sediment rating curve using data from Alang-Darreh hydrometry station in Golestan province (recorded period years 1987-2001) and the results were compared with the conventional OLS regression method. The results show that application of OLS regression in sediment rating curve analysis led to bias estimation while quantile regression without OLS regression’s limiting assumptions can be appropriately show the effect of river discharge on different quantiles of suspended sediment load distributions especially in upper and lower tail. In addition, it was found that a the magnitude of impact of river discharge belonging to upper, lower and central quantiles of suspended sediment load respectively and with increase in river discharge, the suspended sediment load show more skewness to the right. Moreover, the quantile regression concept is presented as a very important tool to extract the probability density and cumulative distribution functions of suspended sediment load for specific value of river discharge.

Since the direct surveillance and data collection on the farm costly and not applicable in all farms, therefore the use of mathematical models necessary. The aim of this study was to investigate soil water flow and root water uptake in every furrow irrigation (EFI), Alternate furrow irrigation (AFI) and fixedfurrow irrigation (FFI) and also calibration and verification of HYDRUS-2D model In order to assess its applicability in the above methods. Field data was collected at growing season corn crop in these methods. To better understand the behavior of the model results were evaluated in two scenarios. In the first scenario model using data from EFI and in the second scenario for each irrigation methods independently calibrated (33% data) and validated (67% data). Estimating the parameters was performed based on soil properties from the database Rosetta and it used in HYDRUS-2D inverse solution for optimize. The Results were compared by indices R2, nRMSE, EF and CRM with each other. The measurement results shows that due to the halving of the amount of irrigation water in the AFI root water uptake was not significantly different with EFI, and The maximum uptake was observed at a depth of 30 cm. Range of R2 value was observed from 0.72 to 0.89 and nRMSE between 0.046 and 0.078. According to calculated nRMSE values, performance of the simulation model, was ranked as excellent for simulation. The results showed that the model was calibrated by initial data separately for each irrigation method increases the accuracy of the model.

Crop simulation models are suitable tools for quick- low cost prediction of the effects of structural and managerial changes on agricultural systems. In this research, the capability of CERES- Rice model to predict nitrogen (N) losses was investigated in paddy fields under 3 subsurface drainage systems with 0.9 m drain depth and 30 m drain spacing (D0.9L30), 0.65 m drain depth and 30 m drain spacing (D0.65 30) and 0.65 drain depth and 15 m drain spacing (D0.65L15). During drainage periods of two successive growing seasons of rice (2011- 2012), the losses of N from different drainage systems were measured. The time of phenological changes and rice yield were also determined. The model performance during calibration (2011) and validation 2012) was determined using the model efficiency, index of agreement and normalized root mean square error. The indices were in the acceptable range in both the calibration and validation stages indicating the effectiveness of the model to simulate growth and yield of rice in the studied treatments. During the two growing seasons, the total measured losses of N in the D0.9L30, D0.65L30 and D0.65L15 systems were, respectively, 15.4, 24 and 20.8 kg ha-1 and the corresponding simulated losses were 5.7, 6 and 4.3 kg ha-1, respectively. Measured and simulated N uptakes by rice were in the range of 115.2- 181.4 kg ha-1 and 71.7- 99 kg ha-1, respectively, in the different treatments. Based on the results, accurate prediction of N balance components by CERES- Rice requires basic factors affecting these components in the study condition be considered in the model.

In arid and semi-arid regions due to restriction of access to fresh water resources for agricultural production, the major source of irrigation water is salt water. The goal of this study was to the effect of irrigation by Caspian Sea water on yield and yield components green pepper (Capsicum annum) variety of green Hashemi ingreenhouse conditions. the research was done based in completely randomized design including 3 replications as pot planting in Gorgan University of Agricultural Sciences and Natural Resources during 2015. In this study salinity factors consist of 5 levels (0, 10, 20, 30 and 40 percent of the mixing sea water and tap water). The results showed that effect of irrigation water salinity on shoot fresh and dry weight, number of fruit per plant, yield and fruit fresh weight were highly significant (p>0.01), but steam diameter and Water use effeciency were significant at 5 percent level. the result showed that increasing salinity decreased all characteristic measured, the result showed that increasing 10 percent mixing of sea water tap water has resulted to decreasing of yield 46.9 percent, respectively. The result showed that the use of mixing sea water and tap water, to irrigate green pepper can not be used.

AquaCrop model determines the response of plant to degree of soil fertility stress by a simple and semiquantitative approach. The objective of this study was to evaluate this approach to simulate maize growth parameters under different nitrogen application in semi-arid environment of Iran. The experiment was conducted at the research farm of the College of Aburaihan, during two years (2015 and 2016) and without water stress. Five nitrogen (N) treatments were investigated including no nitrogen (N0), 50(N1), 10 (N2), 150(N3) and 200 kg N. ha-1 (N4) by Randomized Complete Block design with three replications for each year. Calibration was carried out using the data of N0 and N4 for 2015 and validation was performed with data of remaining treatments in 2015 and whole data of 2016. The accuracy of the model in calibration stage was tested using relative root-mean-square error (RRMSE), coefficient of determination (R2) and mean bias error (MBE), which were about 11.8%, 0.995 and 0.51 ton.ha-1 and 11.8%, 0.988, -1.02 ton.ha-1 for estimating biomass development in the N0 and N4 treatments, respectively. The RRMSE, R2 and MBE values for validation treatments were obtained as 19.06 %, 0.920, 0.92 ton.ha-1 for grain yield and 5.32%, 0.975, 0.41 ton.ha-1 for final biomass yield, respectively. The results show that calibrated model estimates soil water content and water productivity in different treatment accurately. Nevertheless, It is demonstrated that AquaCrop was not able to simulate development of biomass and CC precisely during growing season, but it is more accurate in estimating final biomass and grain yield.

One of the influential processes on Total Suspended Solids (TSS) and Turbidity (TUR) removal can behorizontal roughing filter (HRF). Lack of water resources has addressed using of treated wastewater as one of the approaches to solve the problem. Therefore, low cost and natural methods are considered to improve polluted water quality. In this paper, HRF performance was evaluated in pilot scale with four compartments of difference size of sand and also in three filtration rates of 0.5, 1 and 1.5 meter per hour. The performance of constructed HRF was monitored throughout the pilot operation period under the effect of effluent from a wastewater treatment plant which contains TSS and TUR exceeding the Iranian Environment Protection Organization limits(even for agricultural use which its permissive standard is more than the allowable one for discharging surface water). Comparing the three filtration rates indicated that maximum efficiency, which is equal to 72 percent, has occurred in 0.5 meter per hour. Analyzing of samples in the rate of 0.5 meter per hour showed that as filter operation time (T) increases, at first, TSS and TUR removal rise to 72 and 54 percent until the third month of T and then falls to 39 and 33.5 percent to the end of T, respectively. It was demonstrated that the four compartments HRF, in comparison with three compartments in previous studies improve system efficiency. Moreover, according to Iranian Environment Protection Organization standards, outlet TSS from the HRF with four compartments (40 mg/L) was within the allowable limits to discharge surface water and suitable for use in agriculture and irrigation.

Infiltration is a major soil hydraulic property that has effective role on water and soil resources researches. Field methods of infiltration measuring are time consuming and costly. Therefore an indirect estimation method such as transfer functions is concerned. In this study were derived pedotransfer functions of infiltration of surface irrigation in both GMDH neural network and regression methods by the chemical and physical properties of soil and water. Due to this purpose, 17 soil samples were gathered from Foumanat plain of Guilan province. Physical and chemical properties of soil including soil texture, soil size distribution, particle density, bulk density, soil water retention curve, electrical conductivity, sodium absorption ratio, organic matter content and pH were measured and infiltration experiment were conducted in physical model to evaluate the effects of three treatments of water height on soil surface including 3, 5 and 7 cm and three treatments of sodium adsorption ratio including 1.7, 2.5 and 9. The results showed that GMDH neural network method estimate infiltration more accurate (R2 =0.82) than regression method (R2 =0.75). Regression equations showed that hydraulic parameters of irrigation water including water standing on soil surface and contact surface of water with soil had more effect on infiltration than chemical properties of water and soil. In GMDH method, SAR of water resource, sand percentage and soil moisture in 100 cm matric potential were recognized more effective parameter on infiltration estimation.