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Rivers are important water resources for human life, but sometimes cause irreparable damages. The flood plains are fertile terrains which are endangered by flood. Flood hazard mapping is one of the basic methods in flood fighting. In order to decline flood damages, the simulation of the hydraulic behavior of the rivers during flood occurrence is very important. In this study, areas that are flooded were zoned along Siahrood and Goharrood rivers (Rasht City, northern Iran). The rivers bed and banks terrains of Goharrood and Siahrood were simulated using HEC-GeoRAS extension and digital map (scale: 1000). Pick discharges with different return periods were estimated using stochastic analysis. HEC-RAS software and geographical information system were applied for simulating the hydraulic behavior of the rivers and providing flood zoning map. The GIS was an efficient tool for data-processing and mapping stages. Finally, the flood zones associated with 2, 10, 25, 50, 100 and 200 years return periods were mapped and necessary analysis were conducted during the present research. The results showed that some parts of Rasht City (river bank terrains) are endangered flood hazard.

Artificial neural networks (ANNs) have become one of the most promising tools for rainfall simulation since a few years ago. However, most of the researchers have focused on rainfall intensity records as well as on watersheds, which generally are utilized as input records of other hydro-meteorological variables. The present study was conducted in Kechik station, Golestan Province (northern Iran). The normal multi-layer perceptron form of ANN (MLP–ANN) was selected as the baseline ANN model. The efficiency of GDX, CG and L–M training algorithms were compared to improve computed performances. The inputs of ANN included temperature, evaporation, air pressure, humidity and wind velocity in a 10 minute increment The results revealed that the L–M algorithm was more efficient than the CG and GDX algorithm, so it was used for training six ANN models for rainfall intensity forecasting. The results showed that all of the parameters were proper inputs for simulating rainfall, but temperature, evaporation and moisture were the most important factors in rainfall occurrence.

Urbanization is a pervasive global trend. The development of residential areas and road network in Hajighoshan watershed (northern Iran) has been observed in the recent several decades. The objective of this study is the quantitative investigation of the effects of impervious surfaces development and urban development on runoff generation and flood hazard. The study of urban area development was carried out using aerial photos, topographic maps and satellite images. Also a rainfall-runoff model was presented using GIS (HEC-GeoHMS extension) and HEC-HMS model. Then, the model was optimized with initial loss and SCS-Lag parameters. The optimized model was evaluated using the other 4 events of flood .In the next stage, the development of impervious surfaces was included in the validated hydrologic model and their effects on intensifying runoff generation and flood hazard was investigated quantitatively during the recent forty years. The results showed that the runoff generation potential has increased in Hajighoshan watershed because of urban development during forty years ago.

Springs are the important water resources, which thier study is necessary in terms of their management and exploitation. In northern Iran, the karst springs locate in the central Alborz highlands and alluvial springs on the Caspian southern coasts.The Karst and alluvial springs discharge is variable because of different conditions in terms of aquifer, topography and precipitation .This study has been done to simulate the karst and alluvial springs discharge and to compare their hydrologic conditions. So, 80 karst springs and 82 alluvial springs were investigated in central Alborz and on the Caspian southern coasts. Two models were presented to simulate the karst and alluvial springs discharge using Multivariate Regression analysis (SPSS software).Then, their efficiency was considered. Finally, the models and the results of regression analyses were compared. The results showed that the most important factors of the karst springs discharge are aquifer formation (its porosity) and site elevation, but about the alluvial springs, the hydraulic conductivity of aquifer formation and aquifer depth are the most important factors.

The process of water quality testing is money/time-consuming, quite important and difficult stage for routine measurements. Therefore, use of models has become commonplace in simulating water quality. In this study, the coactive neuro-fuzzy inference system (CANFIS) was used to simulate groundwater quality. Further, geographic information system (GIS) was used as the pre-processor and post-processor tool to demonstrate spatial variation of groundwater quality. All important factors were quantified and groundwater quality index (GWQI) was developed. The proposed model was trained and validated by taking a case study of Mazandaran Plain located in northern part of Iran. The factors affecting groundwater quality were the input variables for the simulation, whereas GWQI index was the output. The developed model was validated to simulate groundwater quality. Network validation was performed via comparison between the estimated and actual GWQI values. In GIS, the study area was separated to raster format in the pixel dimensions of 1 km and also by incorporation of input data layers of the Fuzzy Network-CANFIS model; the geo-referenced layers of the effective factors in groundwater quality were earned. Therefore, numeric values of each pixel with geographical coordinates were entered to the Fuzzy Network-CANFIS model and thus simulation of groundwater quality was accessed in the study area. Finally, the simulated GWQI indices using the Fuzzy Network-CANFIS model were entered into GIS, and hence groundwater quality map (raster layer) based on the results of the network simulation was earned. The study's results confirm the high efficiency of incorporation of neuro-fuzzy techniques and GIS. It is also worth noting that the general quality of the groundwater in the most studied plain is fairly low. [ABSTRACT FROM AUTHOR]

A new analytical methodology for computing synthetic seismograms in 3-D anelastic media is applied to the modelling of the local records of the 2003 Bam Mw 6.6 earthquake, Southeastern Iran. The method is based on the combination of the modal summation technique with the asymptotic ray theory. The 3-D models are determined by a set of vertically heterogeneous sections (1-D structures) that are juxtaposed on a regular grid. The distribution of these sections in the grid is done in such a way to satisfy the condition of applicability of the WKBJ approximation, that is, the lateral variation of all the elastic parameters has to be small with respect to the prevailing wavelength. The procedure, described very briefly, has been applied for the area of the destructive 2003 December 26 Bam earthquake Mw 6.6, with a maximum cut-off frequency of 6 Hz. Synthetic seismograms show fine agreement with recorded signals when comparing shapes, amplitudes and spectra and evidence the relevance of 3-D effects. [ABSTRACT FROM PUBLISHER]