Introduction: In drainage and irrigation network capacity design and determination, reference evapotranspiration (ETo) plays significant role. Methods applied for estimated reference evapotranspiration classified in two direct and computational methods. Amongst computational methods it might point to Penman- Monteith method. This method requires radiation, temperature, humidity and wind speed data with high reliability rate in vast ranges of climates and areas represent precise outcome from reference plant Evapotranspiration. …

Understanding of the hydrodynamic performance of an Autonomous Underwater Vehicle (AUV) is essential to investigate of its capability to perform a mission. Dynamic simulation of the equations of motion and analyzing the vehicle maneuverability is a useful tool for performing these evaluations. To achieve this aim the sensitivity of maneuvering of an underwater vehicle to changes of hydrodynamic coefficients can be investigated. In the current study the sensitivity of maneuverability of an AUV to changes of added mass coefficients is considered. In the first step the hydrodynamic coefficients of the AUV are calculated using analytical-semi empirical method. Next the six degree freedom of dynamic equation for this vehicle is solved and the behavior of turning maneuverer is simulated. In the following by changing the different added mass coefficients the behavior change of the underwater vehicle is evaluated. The results shows that the steady turning radius of the maneuver is insensitive to added mass elements, where the advance length which is the character of the transient phase has the most sensitivity to added mass elements. While tactical diameter which is the combination of steady and transient phases has average sensitivity to added mass parameters.

Flood forecasting in a sound way leading to correct results has been a challenge for all researchers and engineers for many decades, which is the basic reason for developing many different types of mathematical rainfall runoff models. Correct estimation of infiltration during a storm is essential to a justified and rational modeling of runoff at watershed scale. There are many experimental or mathematical models for simulating infiltration and deriving net rainfall with pros and cons. In the present research, instead of evaluating infiltration simulation methods solely, four more widely used methods; namely, ɸ index, Horton, Green-Ampt and SCS methods were selected to find out their effects on the performance of a kinematic wave based geomorphological model called KW-GIUH. Furthermore, a sensitivity analysis with respect to different infiltration methods and different overland and channel roughness coefficient were performed. Horton and ɸ method led to a better performance of the model in terms of observed and simulated hydrographs in the study watershed. In this regard, Nash-Sutcliffe efficiency indices for Horton and ɸ index methods were obtained as 94. 9 and 90. 3, respectively, while it was 77. 7 for Green– Ampt and 76. 3 for SCS infiltration method. According to results of sensitivity analysis, KW-GIUH performance has the most and least sensitivity when using Green– Ampt and ɸ index as the infiltration method, respectively. Although studying in a steep watershed with an overland slope of about 17% and a small area of about 38 km2, changing the overland roughness coefficient has more effect on the model performance comparing with the change of channel roughness coefficient. Simulated flood peaks changed about 64 % due to changing the overland roughness coefficient while this value amounted to 25% for channel one. Shortly, it is concluded that KW-GIUH is highly sensitive to infiltration simulation method and overland roughness coefficient.

Infiltration is a complex process that changed by initial moisture and water head on the soil surface. The main objective of this study was to estimate the coefficients of infiltration equations, Kostiakov-Lewis, Philip and Horton, and evaluate the sensitivity of these equations and their coefficients under various initial conditions (initial moisture soil) and boundary (water head on soil surface). Therefore, one-and two-dimensional infiltration for basin (or border) irrigation were simulated by changing the initial soil moisture and water head on soil surface from irrigation to other irrigation using the solution of the Richards’ equation (HYDRUS model). To determine the coefficients of infiltration equations, outputs of the HYDRUS model (cumulative infiltration over time) were fitted using the Excel Solver. Comparison of infiltration sensitivity equations and their coefficients in one-and two-dimensional infiltration showed infiltration equations and their sensitivity coefficients were similar function but quantitatively in most cases sensitive two-dimensional equations and their coefficients were greater than one dimension. In both dimensions the soil adsorption coefficient Philip equation as the sensitive coefficient and Horton equation as the sensitive equation under various initial moisture soil and water head on soil surface were identified.

The aerodynamic coefficients of any flying object can be estimated with high accuracy, by aero-ballistic tests, monitored in aerodynamic laboratories. For test-running management, it is necessary to determine the number and type of estimated variables and the station placement of each test. For this purpose, the sensitivity of variables under measurement, in relation to the associated aerodynamic coefficients must be calculated and surveyed. As the trajectory path is a nonlinear equation with six degrees of freedom, in this article we estimate the aerodynamic coefficients and sensitivity of each output to the changes of aerodynamic coefficients using the least square method and fisher data matrix. In other word, if the test data such as the speed and pitch angle are to be measured in an aero-ballistic test, the results of this research can specify their accuracy and sensitivity to each aerodynamic coefficient and the relevant coefficient errors.

Different strategies are existed for adjusting with water shortage, of which the strategy of suitable policies adoption by determining optimum production function can be mentioned. Water shortage and quality degradation of soil and water resources is one of main factors of production reduction. Therefore, this study was carried out for determination of tomato sensitivity coefficients and its water-salinity-yield optimum function in Karaj. The experiment was performed as a complete randomized design with three replicates including two factors; Salinity and irrigation water.Salinity and irrigation water factors consisted of four levels (S1=0.7, S2=4, S3=8 and S4=12 dS/m) and three levels (W1=100, W2=75 and W3=50 percent of water requirement), respectively. The Soil texture was sandy loam. Yield data were fitted on different forms production functions (simple linear, logarithmic linear, Quadratic and Transcendental) and the optimum one was determined after sensitivity analysis. Then, the values of water use efficiency and plant sensitivity coefficients were determined. Results of sensitivity analysis showed that the quadratic production function is optimal production and it can be recommended. Investigation of the maximum values of error (ME) showed that the logarithmic linear and simple linear functions have had the highest error. In the irrigation treatments, W1S1 (control) and W2S1 (75% of water requirement) with 7.57 and 7.5 Kg /m3 respectively had the highest water use efficiency.However, water use efficiency decreases if the drought and salinity increases. The average value of Ky, in the condition of combined salinity and drought stress was 1.696. Moreover, Plant sensitivity values (Ks) decreases if salinity and drought increases and the lowest value of Ks were belong to W3S4 (0.57). The iso-yield curve showed that by increasing of irrigation amounts, water with higher salinity can be applied without yield change.

The sediment load estimation is essential for watershed management and soil conservation strategies. The sediment rating curve is the most common approach for estimating the sediment load when the observed sediment records are not available. With regard to the measurement errors and the limitation of available data, the sediment rating curve has a degree of uncertainty which should be accounted for. Thus, in this work, a stochastic Monte-Carlo simulation approach was employed to measure the degree of uncertainty and to analyze the sensitivity of sediment rating equation to changing the coefficients "a" and "b" at the Zoshk hydrometric station. Results of the Monte-Carlo simulation using 5000 samplings showed that in the hydrologic regimes of normal high flow, normal low flow and normal, the contribution of the coefficient "a" to variance is significantly higher than the contribution of the coefficient "b" to sediment load variance. However, this condition is conversely for the hydrologic regime of maximum flow. The sensitivity analysis confirmed a higher sensitivity of the sediment rating equation to the coefficient "a" than that to the coefficient "b" in the hydrologic regimes of normal high flow, normal low flow and normal. However, in maximum flow, the sediment rating equation showed a higher non-linear and more regulated sensitivity to the changes of the coefficient "b" than "a". In all flow regimes, the coefficient "a" has a wider 95% uncertainty band, in comparison with that for the coefficient "b", which establishes a higher level of uncertainty. The sediment rating equation showed a high degree of uncertainty in the hydrologic regime of minimum flow (lower than 0. 3 m3. s-1). In this condition, all observed sediment records place outside the 95% and 97. 5% of the uncertainty band. However, in medium and high flows, most of the observed sediment records are bracketed by the uncertainty band of 95% and 97. 5%.

Facilities built in areas affected by earthquake activity, such as tunnels, which have always been an integral part of human life, must withstand both dynamic and static loading. It has led to the need for practical studies on the effects of earthquakes on underground structures and the factors affecting their destruction. For this purpose, in this research, at first different patterns of tunnel’s excavation were investigated and by using Plaxis 2D software and based on Tabas earthquake in Iran, sensitivity analysis on geotechnical parameters of the soil surrounding tunnel such as cohesion, friction angle, unit weight and modulus of elasticity was carried out, and the parameters whose changes have the greatest and least effects on the bending moment changes on the tunnel lining are introduced. The results show that tunnel excavation patterns significantly affect the bending moment, axial forces, displacements, and surface settlement of the tunnel. Often, by dividing tunnel excavation area to small parts, the values of bending moment, axial forces, displacements, and surface settlement of the tunnel decreases in static analysis. Also, outputs of sensitivity analysis on geotechnical parameters of the soil surrounding tunnel showed that modulus of elasticity of the soil surrounding tunnel has the most effect and cohesion changes have the least effect on bending moment induced on tunnel lining..

Nowadays, environmental pollutions especially water pollution is increasingly developing. One of the problems of entering the pollutants to rivers is reduction in the concentration of river dissolved oxygen. In order to manage the water resources, amount of dissolved oxygen should be predicted. This study presents a novel equation for simulating the concentration of river dissolved oxygen by adding the oxygen production and consumption in the river factors to equation for transmission-diffusion of minerals in the soil. The resultant equation was separated in finite differential method and by using implicit pattern. Calculations were done by encodings in MATLAB software. In order to calibrate and confirm the dissolved oxygen model, data derived from Zayanderood River around Zob-Ahan factory of Isfahan and Mobarakeh Steel Complex was used. By using some data, coefficients of model were determined. Analyzing the sensitivity of model coefficients showed that aeration constant (Kr) had the most effect on predicting the model. Since depends on hydraulic parameters of river, sensitivity of depth and pace of river was studied and finally depth of river was introduced as the most sensitive variable.