scholarly journals Changing Causes of Drought in the Urmia Lake Basin—Increasing Influence of Evaporation and Disappearing Snow Cover

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3273
Author(s):  
Maral Habibi ◽  
Iman Babaeian ◽  
Wolfgang Schöner
Keyword(s):  
Water Level ◽  
Reanalysis Data ◽  
Urmia Lake ◽  
Drought Indices ◽  
Lake Basin ◽  
Water Balance Components ◽  
Lake Water Level ◽  
Study Results ◽  
Key Factor ◽  
Urmia Lake Basin

The water level of the Urmia Lake Basin (ULB), located in the northwest of Iran, started to decline dramatically about two decades ago. As a result, the area has become the focus of increasing scientific research. In order to improve understanding of the connections between declining lake level and changing local drought conditions, three common drought indices are employed to analyze the period 1981–2018: The Standard Precipitation Index (SPI), the Standard Precipitation-Evaporation Index (SPEI), and the Standardized Snow Melt and Rain Index (SMRI). Although rainfall is a significant indicator of water availability, temperature is also a key factor since it determines rates of evapotranspiration and snowmelt. These different processes are captured by the three drought indices mentioned above to describe drought in the catchment. Therefore, the main objective of this paper is to provide a comparative analysis of drought over the ULB by incorporating different drought indices. Since there is not enough long-term observational data of sufficiently high density for the ULB region, ECMWF Reanalysis data version 5(ERA5) has been used to estimate SPI, SPEI, and SMRI drought indicators. These are shown to work well, with AUC-ROC > 0.9, in capturing different classes of basin drought characteristics. The results show a downward trend for SPEI and SMRI (but not for SPI), suggesting that both evaporation and lack of snowmelt exacerbate droughts. Owing to the increasing temperatures in the basin and the decrease in snowfall, drought events have become particularly pronounced in the SPEI and SMRI time series since 2010. No significant SMRI drought was detected prior to 1995, thus indicating that sufficient snowfall was available at the beginning of the study period. The study results also reveal that the decrease in lake water level from 2010 to 2018 was not only caused by changes in the water balance components, but also by unsustainable water management.

Water level instability analysis of Urmia Lake Basin in the northwest of Iran

2020 ◽  
Vol 13 (4) ◽  
Author(s):  
Fatemeh Bashirian ◽  
Dariush Rahimi ◽  
Saeed Movahedi ◽  
Reza Zakerinejad
Keyword(s):  
Water Level ◽  
Urmia Lake ◽  
Lake Basin ◽  
Instability Analysis ◽  
Northwest Of Iran ◽  
Urmia Lake Basin

scholarly journals INVESTIGATING AND MODELLING EFFECTS OF CLIMATICALLY AND HYDROLOGICALLY INDICATORS ON THE URMIA LAKE COASTLINE CHANGES USING TIME SERIES ANALYSIS

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 5-9
Author(s):  
M. Ahmadijamal ◽  
M. Hasanlou
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Water Level ◽  
Polynomial Regression ◽  
Urmia Lake ◽  
Lake Basin ◽  
Fourth Degree ◽  
Periodic Behavior ◽  
Lake Water Level ◽  
Series Analysis

Study of hydrological parameters of lakes and examine the variation of water level to operate management on water resources are important. The purpose of this study is to investigate and model the Urmia Lake water level changes due to changes in climatically and hydrological indicators that affects in the process of level variation and area of this lake. For this purpose, Landsat satellite images, hydrological data, the daily precipitation, the daily surface evaporation and the daily discharge in total of the lake basin during the period of 2010-2016 have been used. Based on time-series analysis that is conducted on individual data independently with same procedure, to model variation of Urmia Lake level, we used polynomial regression technique and combined polynomial with periodic behavior. In the first scenario, we fit a multivariate linear polynomial to our datasets and determining RMSE, NRSME and R² value. We found that fourth degree polynomial can better fit to our datasets with lowest RMSE value about 9 cm. In the second scenario, we combine polynomial with periodic behavior for modeling. The second scenario has superiority comparing to the first one, by RMSE value about 3 cm.

scholarly journals Unraveling the Water-Energy-Food-Environment Nexus for Climate Change Adaptation in Iran: Urmia Lake Basin Case-Study

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1282
Author(s):  
Hossein Nasrollahi ◽  
Rasool Shirazizadeh ◽  
Reza Shirmohammadi ◽  
Omid Pourali ◽  
Majid Amidpour
Keyword(s):  
Climate Change ◽  
Sustainable Development ◽  
Water Level ◽  
Holistic Approach ◽  
Urmia Lake ◽  
Lake Basin ◽  
Lake Urmia ◽  
Industrial Sectors ◽  
Ecological Water Level ◽  
Urmia Lake Basin

A holistic approach to the management of water, energy, food, and the environment is required to both meet the socioeconomic demands of the future as well as sustainable development of these limited resources. The Urmia Lake Basin has faced environmental, social, and economic challenges in recent years, and this situation is likely to worsen under the impacts of climate change. For this study, an adaptability analysis of this region is proposed for the 2040 horizon year. Two models, the water evaluation and planning (WEAP (Stockholm Environmental Institute, Stockholm, Sweden)) and the low emissions analysis platform (LEAP (Stockholm Environmental Institute, Boston, MA, USA)), are integrated to simulate changes in water, energy, food, and the environment over these 20 years. Two climate scenarios and nine policy scenarios are combined to assess sustainable development using a multi-criteria decision analysis (MCDA) approach. Results show that, through pursuing challenging goals in agricultural, potable water, energy, and industrial sectors, sustainable development will be achieved. In this scenario, the Lake Urmia water level will reach its ecological water level in 2040. However, social, technical, and political challenges are considered obstacles to implementing the goals of this scenario. In addition, industry growth and industry structure adjustment have the most impact on sustainable development achievement.

Application of Satellite Remote Sensing for Estimation of Dust Emission Probability in the Urmia Lake Basin in Iran

2019 ◽  
Vol 83 (4) ◽  
pp. 993-1002 ◽  
Author(s):  
Mohaddese Effati ◽  
Hossien‐Ali Bahrami ◽  
Mohammad Gohardoust ◽  
Ebrahim Babaeian ◽  
Markus Tuller
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Dust Emission ◽  
Emission Probability ◽  
Urmia Lake ◽  
Lake Basin ◽  
Urmia Lake Basin

Spatial clustering of maximum 24-h rainfall over Urmia Lake Basin by new weighting approaches

2017 ◽  
Vol 38 (5) ◽  
pp. 2298-2313 ◽  
Author(s):  
Zohreh Dehghan ◽  
Seyed Saeid Eslamian ◽  
Reza Modarres
Keyword(s):  
Spatial Clustering ◽  
Urmia Lake ◽  
Lake Basin ◽  
Urmia Lake Basin

scholarly journals Analysis of decadal land cover changes and salinization in Urmia Lake Basin using remote sensing techniques

2017 ◽  
Author(s):  
Yusuf Alizade Govarchin Ghale ◽  
Metin Baykara ◽  
Alper Unal
Keyword(s):  
Remote Sensing ◽  
Soil Salinity ◽  
Spectral Response ◽  
Dust Storms ◽  
Urmia Lake ◽  
Lake Basin ◽  
North West ◽  
Irrigated Lands ◽  
Urmia Lake Basin ◽  
Salty Soil

Abstract. Urmia Lake located in the north-west of Iran, is one of the largest hyper-saline lakes in the world. In recent years, most of the Urmia Lake have been rendered to unusable lands. Drought and rapid increase in agricultural activities are the most important reasons behind the shrinkage of the Lake. This kind of exploitation with the added salinity from irrigation occurring over time has caused increased soil salinity in the basin leading up to desertification. Soil salinity research are crucial to understand underlying causes and consequences of the drying Urmia Lake. In this study, we use remote sensing technology and image processing techniques to detect spatio-temporal variability of salt body, salt affected lands, and development of irrigated lands to estimate the extend of salinization in terms of spectral response of satellite images for the Urmia Lake Basin from 1975 to 2016. The results of this study indicate that salt and salty soil areas has increased dramatically from 1995 to 2014 and more than 5000 km2 of Urmia Lake's water surface area was converted to salt or salty soil bodies during recent years. Salinization and desertification progress are not limited to just dried bottom of the Urmia Lake. Although the area of irrigated lands has increased more than two times during the studied period, soil salinity has increased in regions close to Urmia Lake too. This desertification in the basin have potential to be the source of dust storms, which have adverse effects on people's life and climate as well.

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