مجله تحقیقات منابع آب ایران
سال سوم شماره 3 (پیاپی 9، زمستان 1386)

Iran is a drought region which is located in middle meridian of earth. Especially in mountains, precipitations fall as snowfall and provide water supply for warm season. Therefore, it is so important for hydrologists and water resource engineers to determinate boundary of snow cover to be able to estimate water supply. In this study, snow cover area in Central Alborz mountains were detected using NOAA-AVHRR and TERRA-MODIS data using threshold determination in near infrared band. Discrimination between snow and clouds is one of the important problems in snow mapping using satellite data. Clouds are very diverse and have high reflection in visible and NIR band but snow shows low reflectance in this band. In MODIS snow mapping algorithm, first using NDSI, snow pack detected but for discrimination between snow and other wet lands we utilized threshold in 1, 2, 4 and 6 bands. In NOAA-AVHRR algorithm were also used threshold forAlbedo of band 1 and 3 and brightness temperature 3 and 4. Snow areas in AVHRR is 5303 square kilometers in March 27th 2004 and full snow, fractal snow and clouds areas in MODIS data were 994, 2570 and 2505 square kilometers in March 25th 2003, respectively. Finally, using interrelation between hydro-climatology parameters 2.9°C were calculated as minimum temperature of snowfall and height of corresponding 0° C were calculated for snow permanence height in Central Alborz.

Potential evapotranspiration (ET0) rates are needed for irrigation scheduling. ET0 rates are commonly from weather parameters. The Penman-Monteith, is now accepted for computation of ET0. It requires several input parameters, some of which have no actual measurements but are estimated from measured weather parameters. In this study, the suitability of fuzzy regression was examined for estimating daily potential evapotranspiration with grass reference crop and compared with Artificial Neural Networks (ANN) and Penman-Monteith methods.The daily climatic data of the Ekbatan station in Hamadan, including maximum and minimum temperature, maximum and minimum relative humidity, wind speed and sunny hours are introduced as input data and ET0 as output data. ET0 values estimated from the fuzzy regression method were compared with direct ET0 measurements from lysimeters, and with ET0 estimations obtained using the Penman-Manteith equation and the ANN method. The estimated ET0 values from a fuzzy regression model using five input parameters, including maximum and minimum temperature, mean relative humidity, wind speed and sunny hours were obtained with RMSE=0.69mm/day, R2 =0.88. The estimated ET0 values from a artificial neural networks model using the same input parameters were obtained with RMSE=0.74mm/day, R2 =0.84. The estimated ET0 values from Penman-Monteith model were obtained with RMSE=1.21mm/day, R2 =0.84. Thus, in this study the fuzzy regression is the best method.

This paper studies available methods for isochrone delineation in converging flow and compare those with kinematic wave approach. This paper also tries to introduce a method based on wave motion theory instead of empirical methods. Authors in their pervious research on parallel flow showed that many of the available methods give travel time with supposition of proportionality of time to equilibrium with an exponent of distance of points to outlet. Investigation on a large range of exponents shown that using the exponent derived from Kinematic wave theory, is the best one and gives the closest answer to analytical solution for rising limb of hydrograph. The obtained results for converging flow approve the results achieved in parallel flow analysis. The equations governing on Converging flow is so complicated that there are only a few solutions for rising limb of hydrograph. The time– Area method is one of the most suitable and the simplest techniques of watershed routing, and can be potentially used as a distributed model. Linking this model with GIS software is easily performed. Results of the present research, by omitting the limitation of empirical delineation of isochrones, make Time Area method capable of solving overland flow on watersheds of any type, easily and perfectly.

Sustainable development and optimized exploitation of the groundwater resources depend on accurate estimation of aquifer hydraulic parameters. Different methods exist for estimation of hydraulic parameters of aquifers. One of the classic methods for estimating these parameters is analyzing the pumping test data by graphical methods. Nowadays, probabilistic optimization methods, i.e. simulated annealing and genetic algorithm (GA), based on evolution rules, are took into attentions due to their high abilities. In this article, the efficiency of the GA is assessed inestimating confined aquifer parameters. For this purpose, hydraulic parameters of four confined aquifers are calculated by using GA and they are compared with results of graphical methods. The results indicate that intelligent GA technique is efficient, reliable and powerful method for estimation of confined aquifers hydraulic parameters.

Study of extreme precipitations and related extreme events is of great importance in policy making and planning in variety of sectors including agriculture, water management, urbanization and building, and road and transportation. Hence, much attention has been paid to different methods of analysis of extreme precipitations during recent years. To study extreme precipitations over Iran, we used extreme precipitation indices like Maximum 1-day precipitation (Rx1day), Maximum consecutive 5-day precipitation (Rx5day), Simple precipitation intensity index (SDII), Number of days with precipitation equal to or greater than 10, 20, and 25 mm (R10mm, R20mm, and R25mm), Maximum number of consecutive dry and wet days (CDD and CWD), Total precipitation when daily amounts are greater than 95th and 99th percentile of wet days(R95 p and R99 p), and Total precipitation in wet days (PRCPTOT). Our used data were limited to daily precipitation data from only 27 of Iranian synoptic stations that have reliable data and covering standard normal period 1961-1990. We found all three behaviors of stationarity, positive and negative trends over the country. As trends for majority of the indices were positive in regions like Hormozgan, Esfahan, and Tehran, but on the contrary, they were negative for majority of the indices in regions like Azerbaijan and Fars. Former results correspond well with findings of Intergovernmental Panel on Climate Change (IPCC) that expects higher number of occurrences of extreme precipitation events beyond of tropical region. Positive trends for 10 indices in Babolsar and negative trends for 10 indices in Bushehr and Tabriz (7 out of 10 are significant at 0.05 level) indicate complex behaviors of extreme precipitation over the country Occurrence of very abnormal values like total precipitation of 1 mm in Bandar abbas in 1962 have significantly affected slopes of trends in most of the extreme precipitation indices.

This paper introduces the 1D hydrodynamic and water quality, FASTER model. this model was first developed by kashefipour in Environmental Research Centre in Cardiff University, UK. FASTER is able to determine water elevation and discharge using numerical solution of the Saint Venant Unsteady and non uniform equations. The implicit Crank-Nikolson central scheme with staggered method was applied for the hydrodynamic module of the model. The influence line technique was used in the numerical solution and as a result the solution remains implicit for all reaches and junctions. The water quality module of the model is able to simulate eleven different water quality parameters including coliforms, BOD, DO, and etc. In this paper the FASTER model is introduced and its abilities is shown using two examples in hydrodynamic simulations and one standard example in water quality simulation.

Spatial distribution of snow depth is affected by topographic parameters. To estimate the snow depth, parameters like elevation, slope and aspect were evaluated in relation to snow depth. To this, 258 points located inside the area under study (Samsami Basin) of 5.2 Km2 with a range of elevation from 2287 to 2933m were selected and the depth of snow packs were measured for them late February 2006. For the evaluation of the effect of these parameters on snow depth, correlation analysis method was used. The result of analyzing the correlation of snow depth with elevation was positive and significant at 5% level for up to 2780m. However, for elevation more than 2780m, this relation was inverse with no significance at 5% level. The correlation of snow depth with the degree of slope which ranged between 3.8 to 14.85 did not show a meaningful relation at 5% level, but showed an inverse relation. For the degree of slope more than 14.85, the correlation relation was positive, but with no significance at 5% level. Finally, the relation of snow depth with the aspect from 0 to 166 degrees (Azimuth), showed a good and significant correlation at 5% level. However, significant correlation was not obtained for the aspect ranging between 172 to 204 and 206 to 359 degrees at 5% level.

Suspended load in water are a problem dam reservoir management. Accordingly a pre-construction study on suspended load is needed for dams and other hydraulic structures. There are several methods all of which need the results from the field sampling from the river under study or the conjunctive rivers. Because of limited data, interpolation and/or extrapolation will normally be necessary. In this research, regarding the absence of gauges on Seydon River, data from other stations in the basin were used. The result was used on the area-ratio basis. This study was done using single line Sediment Duration Curve (SDC), double line and seasonal SDC, and, FAO methods. The result are then compared to the PESIAC method resulted in the selection of the best method for study area.