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    Mapping surface temperature in a hyper-saline lake and investigating the effect of temperature distribution on the lake evaporation

    , Article Remote Sensing of Environment ; Volume 136 , 2013 , Pages 374-385 ; 00344257 (ISSN) Sima, S ; Ahmadalipour, A ; Tajrishy, M ; Sharif University of Technology
    2013
    Abstract
    Remote sensing is an effective tool for capturing spatial and temporal variations of water surface temperature (WST) in large lakes. The WST of Urmia Lake in northwestern Iran was examined from 2007 to 2010, using MODIS land surface temperature (LST) products. Spatial and temporal (diurnal, monthly, seasonal and inter-annual) variations of Urmia Lake WST were also investigated. Results indicate that the MODIS-derived WSTs are in a good agreement with the in situ data (R2=0.92 and bias=-0.27). Spatial analysis of WST revealed that there are three thermal zones along the lake: the shallow region in barriers of the causeway, islands and the shoreline; the south part; and the deep north parts.... 

    Assessment of 2DH and pseudo-3D modelling platforms in a large saline aquatic system: Lake Urmia, Iran

    , Article Hydrological Processes ; Vol. 28, Issue. 18 , 2014 , pp. 49534970 ; ISSN: 10991085 Zeinoddini, M ; Tofighi, M. A ; Bakhtiari, A ; Sharif University of Technology
    Abstract
    The main objective of this paper is to provide comparative quantitative examinations on the capabilities of two-dimensional horizontal and pseudo-three-dimensional (3D) modelling approaches for simulating spatial and temporal variability of the flow and salinity in Lake Urmia, Iran. The water quality in the lake has been an environmentally important subject partly because this shallow hypersaline aquatic ecosystem is considered to be one of the largest natural habitats of a unique multicellular organism, Artemia urmiana. This brine shrimp is the major food source for many of the protected and rare shorebirds that visit the lake. A.urmiana can grow and survive in certain ranges of salinity,... 

    Revisiting bathymetry dynamics in Lake Urmia using extensive field data and high-resolution satellite imagery

    , Article Journal of Hydrology ; Volume 603 , 2021 ; 00221694 (ISSN) Danesh Yazdi, M ; Bayati, M ; Tajrishy, M ; Chehrenegar, B ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    Bathymetric mapping for an accurate estimation of stored water volume in drying lakes is a key information for an effective monitoring of their recession or restoration status. Extraction of bathymetry in shallow saline lakes using remote sensing techniques has always been challenging due to the complex influences imposed by the physical properties of substrate and the spatial variability of salinity. In this study, we developed a machine learning-based model to quantify the implicit, non-linear relationship between water depth and surface reflectance by leveraging extensive in-situ data and high-resolution satellite imagery. We trained and tested the learning model in the hyper-saline Lake... 

    Increasing risk of meteorological drought in the Lake Urmia basin under climate change: Introducing the precipitation–temperature deciles index

    , Article Journal of Hydrology ; Volume 592 , 2021 ; 00221694 (ISSN) Abbasian, M. S ; Najafi, M. R ; Abrishamchi, A ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    Meteorological droughts due to the concurrent occurrence of low-precipitation and high-temperature events can lead to severe negative impacts on agriculture, economy, ecosystem, and society. This study proposes a novel framework to characterize such drought conditions based on the joint variability of precipitation–temperature, particularly under climate change. Generalized hierarchical linear model is used to downscale precipitation and temperature at multiple stations from the outputs of nine General Circulation Models (GCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5. A bivariate drought index called Precipitation–Temperature Deciles Index (PTDI) is developed using... 

    Increasing risk of meteorological drought in the Lake Urmia basin under climate change: Introducing the precipitation–temperature deciles index

    , Article Journal of Hydrology ; Volume 592 , 2021 ; 00221694 (ISSN) Abbasian, M. S ; Najafi, M. R ; Abrishamchi, A ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    Meteorological droughts due to the concurrent occurrence of low-precipitation and high-temperature events can lead to severe negative impacts on agriculture, economy, ecosystem, and society. This study proposes a novel framework to characterize such drought conditions based on the joint variability of precipitation–temperature, particularly under climate change. Generalized hierarchical linear model is used to downscale precipitation and temperature at multiple stations from the outputs of nine General Circulation Models (GCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5. A bivariate drought index called Precipitation–Temperature Deciles Index (PTDI) is developed using... 

    Using satellite data to extract volume-area-elevation relationships for Urmia Lake, Iran

    , Article Journal of Great Lakes Research ; Volume 39, Issue 1 , March , 2013 , Pages 90-99 ; 03801330 (ISSN) Sima, S ; Tajrishy, M ; Sharif University of Technology
    2013
    Abstract
    Urmia Lake in the northwest of Iran is the second largest hyper-saline lake worldwide. During the past two decades, a significant water level decline has occurred in the lake. The existing estimations for the lake water balance are widely variable because the lake bathymetry is unknown. The main focus of this study is to extract the volume-area-elevation (V-A-L) characteristics of Urmia Lake utilizing remote sensing data and analytical models. V-A-L equations of the lake were determined using radar altimetry data and their concurrent satellite-derived surface data. Next, two approximate models, a power model (PM) and a truncated pyramid model (TPM), were parameterized for Urmia Lake and...