Sharif Digital Repository

The objective of this research is to enhance the accuracy of temperature and pressure variables derived from global meteorological models such as ERA5 using machine learning and deep learning (ML-DL) techniques. Since variables like temperature and pressure are critical metrics for various processes and decision-making in fields such as agriculture and limnology, and they serve as input variables in most hydrological, hydrodynamic, and meteorological models, accessing high-precision time series with appropriate temporal resolution is of great importance. Currently, global meteorological models like ERA5 provide relatively long time series of these variables on a grid with spatial resolutions... 

The present study aims to evaluate the flood risk of Poldokhtar city probabilistically using Monte Carlo Simulations (MCS). Two-dimensional (2D) models, which are highly accurate, have been used widely for flood modeling. However, they are not suitable for applications such as MCSs that need to be repeated many times or real-time flood forecasting applications, which require that flood inundation maps quickly be produced. In the current study, we developed a data-driven surrogate model based on the Least Squares Support Vector Machine (LS-SVM), a supervised machine learning method, to predict flood depth in order to simulate similar results to 2D hydraulic modeling. HEC-RAS was used for 2D... 

The purpose of this study is to investigate the resilience of the urban water supply network against earthquakes, A hydraulic analysis of the water supply network was implemented in Rtx software to study the effective parameters in the resilience of the network. Rtx software is a tool for assessing the reliability and resilience of communities and infrastructure to natural hazards by taking into account related uncertainties. The water supply network, like other networks, is affected by earthquakes. The seismic damage varies depending on the vulnerability of the network, the intensity of the earthquake, the focal depth, and the distance from the epicenter. Thus, it reduces the ability of the... 

Vertical turbulent mixing in lakes plays a critical role in the distribution and transfer of nutrients, oxygen, and heat, significantly impacting lake productivity and the growth of algae and aquatic plants. During summer, the persistent and intense solar radiation creates a thermal stratification in lakes, which inhibits deep vertical mixing. In stratified lakes and oceans, small-scale mixing processes are key drivers of vertical fluxes that transport particles and substances, including nutrients, pollutants, and microorganisms. Despite the significant influence of small-scale turbulent mixing, numerical models of stratified lakes often neglect these effects due to the challenges associated... 

The purpose of this research is to investigate the capability of process-oriented modeling and deep learning for monitoring and forecasting the water quality of stratified lakes and to provide a unified framework integrating these two models to improve the monitoring and prediction of water quality. In this thesis, the process-oriented General Ocean Turbulence Model (GOTM) has been developed to simulate the hydrodynamic and thermodynamic processes of Gull Lake from 2008 to 2017. Subsequently, the MLP deep learning model has been employed to study the lake's key water quality indicators during this period. Meteorological data serves as input for the GOTM. Calibration and validation of the... 

Due to anthropogenic activities and climate change, Lake Urmia, one of the largest hypersaline lakes, is exposed to desiccating. The increase in salinity in this lake up to more than 400 p.s.u has endangered the ecology of this lake. In this study, a three-dimensional, unstructured grid and finite volume model FVCOM has been developed to investigate Lake Urmia's hydrodynamics, salinity, and water temperature over the year 2016. Some of the model inputs were lake bathymetry, meteorological data (including air temperature and pressure, wind speed and direction, short-wave and longwave radiation), precipitation, evaporation, river flux, salinity, and temperature. The model was calibrated... 

Wetlands are valuable ecosystems that have a wide variety of functions to protect biodiversity, natural, economic and social values. Hydrological changes and nutrient enrichment, resulting from population growth, economic development and climate change are threatening the wetlands. Recently, assessing spatial and temporal variations of water quality has become an important aspect of the physical and chemical characterization of aquatic environments. Anzali wetland is one of the international wetlands in Iran, located in the southern part of the Caspian Sea in Gilan province. This wetland has been exposed to many pollution sources including agricultural, industrial, and municipal wastewater... 

Water resources globally are facing significant stress due to overexploitation. In recent decades, the balance between the available water resources and the amount of water consumption in the catchment area of Lake Urmia due to human factors and natural phenomena like climate change has been severely disrupted. In the last 20 years, the cumulative impact of these factors has led to a dramatic reduction in Lake Urmia’s water level by over 8 meters, with a concomitant rise in water salinity. To address the hydrodynamic challenges of Lake Urmia, it is crucial to understand the upstream watersheds. Thirteen perennial rivers, primarily the Zarinehroud and Simineroud, fulfill the water rights... 

Considering the significant impact of salinity and temperature on the life of aquatic ecosystems, the growth of plants and animals, and the health of people; it is necessary to predict the spatiotemporal distribution of these qualitative characteristics in aquatic environments by using precise algorithms through hydrodynamic models. This research presents an improved algorithm for calculating qualitative characteristics of aquatic environments, such as salinity, during the wet/drying processes. The developed algorithm in this study has been incorporated into FVCOM which is a three-dimensional hydrodynamic model. The current algorithm governing the FVCOM model is not capable of accurately... 

The relative lack of research concerning the potential impacts of climate change on different sectors in developing countries, especially the Middle Eastern countries, as the essential prerequisite of climate policy actions has made these countries the frontline against climate impacts. To fill this gap, in the first phase, we first analyzed spatial distributions and trends in thirty-seven hydro-climatic mean and extreme indices across Iran based on the state-of-the-art reanalysis datasets (ERA5-Land and AgERA5) at the county level from 1986 to 2015 using several nonparametric approaches such as multiple modified Mann-Kendall statistical tests and Sen’s Slope estimator. Their interannual... 

The problem of PM pollutants has become one of the main environmental concerns of Tehran city due to the growth of city population and industrialization. As a consequence of this problem there is an increasing trend in the number of unhealthy days in Tehran in terms of air quality in recent years. Solving this problem needs strict regulations to limit the amount of pollutants released from vehicles, industries and power plants. To help this cause, this study investigates the effect of emissions and climate change under RCP scenarios on future PM2.5 concentration in Tehran by using WRF-SMOKE-CMAQ modeling system. The result of simulation of climate conditions under RCP8.5 scenario in 2050... 

In recent years, global salt lakes have faced severe environmental challenges. Lake Urmia, the world’s second-largest hyper saline lake, is located in the northwest of Iran, has experienced a significant shrinkage in last years. Lake Urmia is a terminal lake where water enters through precipitation and rivers inflow and loses through evaporation. Analysis of long-term trends (1990-2018) using the Mann-Kendall test indicates no significant trend in precipitation, an increasing trend in evaporation, and a decreasing trend in river discharge. However, precipitation during 1990-1999 (beginning of accelerated lake drying) showed a decreasing trend. An investigation of the correlation between... 

The motion of a surface wave in a two-layer fluid can lead to generation of sub-harmonic interfacial waves through a nonlinear resonant interaction mechanism. The interfacial waves grow exponentially in time until they reach a maximum amplitude and then oscillate down to a final amplitude, referred to as ultimate amplitude, in long term. This may lead to considerable mixing of the layers in miscible fluid and increase the thickness of the diffuse layer. Experiments show that the diffuse layer causes frequency shift and decreases the ultimate amplitude. In this study, long time behavior of interfacial waves in a two layer immiscible fluid was investigated. A two-layer immiscible system... 

This research develops a probabilistic framework for evaluating community resilience subject to earthquake events by modeling the water distribution system and its prevailing inter- and intra-dependencies with other infrastructure systems of the community. This framework is entitled “Rtx,” which is under continuous development at the Center for Infrastructure Sustainability and Resilience Research (INSURER) at Sharif University of Technology, Tehran, Iran. It quantifies the community resilience by integrating hazard models, risk models, and recovery models within an agent-based simulation. Comprehensive modeling of the water distribution system requires a library of probabilistic models,... 

The aim of this research is to use data assimilation in hydrodynamic modeling of Lake Urmia, which is known as one of the world's hypersaline lakes. In other words, it is the first time that the development of a numerical model for Lake Urmia has been accompanied by data assimilation. In recent years, Lake Urmia has experienced unfavorable climatic conditions, resulting in a decline of over 8 meters in its water level over the past 20 years. Hydrodynamic analysis of the lake can play a crucial role in major management decisions for restoration of the lake ecosystem. In this project, the three-dimensional FVCOM model was used to perform numerical modeling, and efforts were made to improve... 

Nowadays, because of the importance of saving energy resources and also environmental issues, utilization of catalysts are increased in industry and products. In the last decades, a lot of efforts have been devoted to develop novel methods for heterogenizing of the homogeneous catalyst in order to combine the advantages of the both the homogeneous and the heterogeneous catalysts. Among the different solid supports, graphene with high surface area and distinctive mechanical and electronical properties have been introduces as an emerging support for heterogenizing of the homogeneous catalysts. On the other hand, the use of ionic liquid has been developed due to a broad range of polarity, low... 

Bread, as an essential item in Iranian food menu, is a very sensitive food item in our country. However, the bread types currently produced in the country have a low quality and consequently a high level of losses. The proposed solution for this problem is to change the pattern of bread production from the traditional method to the industrial method. In this research, after designing a feasibility structure, we evaluate the project of building an industrial bread production factory from two technical and financial points of view and estimate total investiment costs and production costs. Then we estimate the sale income and evaluate indexes like net present value, internal rate of return,...