Nasrin Fathollahzadeh Attar

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• Ph.D.
• PostDoc Position at The University of Texas at Arlington

Water quality is an essential component in managing surface and groundwater resources and for various uses; it is considered a necessary principle in planning. This study aims to map the groundwater quality of the Qazvin Plain aquifer in Iran for agricultural use based on the Wilcox classification method. For this purpose, the parameters of electri...

Accurate estimation of evapotranspiration (ET) is crucial for efficient water resource management, particularly in the face of climate change and increasing water scarcity. This study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers, selected according to PRISMA guidelines, to evaluate the performa...

Accurate prediction of daily river flow (Qt) is a challenging task in hydrological modeling, particularly vital for flood mitigation and water resource management. This study introduces an advanced M5 Prime (M5P) predictive model designed to estimate Qt and one- and two-day-ahead river flow forecasts (i.e. Qt+1 and Qt+2). The performance of ensembl...

Temperature variations play an important role in driving future extreme precipitation and its potential impact. In order to adapt to the ongoing climate-change it is therefore essential to adjust the design precipitation amounts used in engineering and risk management. Sub-hourly extremes are particularly concerning, because they have significant i...

The amount of rainfall in different regions is influenced by various factors, including time, place, climate, and geography. In the Lake Urmia basin, Mediterranean air masses significantly impact precipitation. This study aimed to model precipitation in the Lake Urmia basin using monthly rainfall data from 16 meteorological stations and five machin...

In the context of global climate change, windstorms pose significant environmental, ecological, and socioeconomic challenges. Mountainous and forested regions of Europe, including the Veneto region in northern Italy, have been devastated by unprecedented events such as the storms in July 2023 and Vaia in October 2018, raising the question whether s...

Streamflow prediction is one of the critical components of hydrological interactions and a vital step for integrated water resources management for different water-related sectors. Accurate streamflow prediction can provide significant information about flood mitigation, irrigation operation, and land use planning. The study aims to improve data qu...

Rivers receive a large amount of pollution due to the wide concentration of human activities. This study investigated the effects of climate change on the Dez river water quality and the application of an improvement scenario to improve the Dez river's water quality. The QUAL2kw model was used to simulate water quality parameters. Comparison of err...

Nowadays, dealing with data in all sciences is very critical. Data science and data engineering are exciting disciplines to turn data into bright understanding. Finding statistical characteristics and communicating data by some techniques such as visualization. R is a rapidly growing, statistical, open-source software with many libraries and packag...

Changes in land use due to urbanization, industrialization, and agriculture will adversely affect water quality at all scales. This study examined the possible effects of future land use on the water quality of the Dez River located in Iran. The QUAL2Kw dynamic model was used to simulate the water quality of the Dez River. Data and information avai...

During snowmelt in mountainous areas, runoff can play an important role in providing water to the region. This study examined the effect of climate change on runoff in Ajichai, Iran, since it affects air warming and faster melting of snow and ice. Using the sixth report provided by IPCC, the future temperature and precipitation in the years 2015–21...

As recently shown by the storm Vaia that hit Northeastern Italy in the fall of 2018, extreme wind represents a critical weather-related hazard in this region. Over the course of this century, changes in the frequency of extreme windstorms are expected. Obtaining an accurate understanding of wind speed distribution in present and future conditions i...

This article explores the forecasting capabilities of three classic linear and nonlinear autoregressive modeling techniques and proposes a new ensemble evolutionary time series approach to model and forecast daily dynamics in stream dissolved organic carbon (DOC). The model used data from the Oulankajoki River basin, a boreal catchment in Northern...

Accurate prediction of reference evapotranspiration (ET0) is very valuable since it directly affects the amount of agricultural water needed, the allocation of water consumption and the management of irrigation systems. This research consists of two parts; in the first part, ET0 was predicted by two machine learning models (artificial neural networ...

An alternative energy source such as solar is one of the most important renewable resources. A reliable solar radiation prediction is essential for various applications in agriculture, industry, transport, and the environment because they reduce greenhouse gases and are environmentally friendly. Solar radiation data series have embedded fluctuation...

The behavior of hydrological processes is periodic and stochastic due to the influence of climatic factors. Therefore, it is crucial to develop the models based on their periodicity and stochas-tic nature for prediction. Furthermore, forecasting the streamflow, as one of the main components of the hydrological cycle, is a primary subject. In this s...

Snow cover area on a river basin, affects so many meteorologic and environmental parameters. By growing remote sensing technology, nowadays snow cover area could be measured on a regular basis for scientific purposes. In this study, the monthly average of snow cover area of the Baranduz river basin from West Azerbaijan in Iran had been used for mod...

A gradient boosting regression tree (GBT) approach is introduced for one- and three-month ahead standardized precipitation-evapotranspiration index (SPEI) classification for Antalya and Ankara in Turkey. First, the numerical target series of SPEI-6 was converted into the categorical vectors of extreme wet, wet, near normal, dry, and extremely dry l...

Implementing a reliable computational model for predicting the reference evapotranspiration (ET 0 ) process is essential for several agricultural and hydrological applications, especially for the rural water resource systems, water use allocations, utilization and demand assessments, and the management of irrigation systems. In this research, two a...

Accurate streamflow prediction is essential in reservoir management, flood control, and operation of irrigation networks. In this study, the deterministic and stochastic components of modeling are considered simultaneously. Two nonlinear time series models are developed based on autoregressive conditional heteroscedasticity and self-exciting thresh...

Water quality has a crucial impact on human health; therefore, water quality index modeling is one of the challenging issues in the water sector. The accurate prediction of water quality index is an essential requisite for water quality management, human health, public consumption, and domestic uses. A comprehensive review as an initial attempt is...

this is my doctorate thesis proposal. i am trying to analyze the trend of the snow cover area in Baranduz river basin. also model the snow cover area by artificial intelligence models.

Hydrological modeling is one of the important subjects in managing water resources and the processes of predicting stochastic behavior. Developing Data-Driven Models (DDMs) to apply to hydrological modeling is a very complex issue because of the stochastic nature of the observed data, like seasonality, periodicities, anomalies, and lack of data. As...

https://figshare.com/articles/neural-network-add-in-1-5-4-setup_exe/7460756 And a good news that the new version of this add-in is coming in winter.

Owing to the importance of dew point temperature (Tdew) as a determining factor in hydrological parameters, especially water vapor and evaporation, we aim for the estimation of Tdew by three different computational models including gene expression programming (GEP), multivariate adaptive regression splines (MARS), and support vector machine (SVM) m...