Vegetation patterns of a rapidly drying up salt lake                     ecosystem: Lake Urmia, NW Iran

Lake Urmia (LU) is considered as the largest salt water lake in Iran and has severe restrictions on water resources and becoming a salt lake increasingly. The LU drought will Couse ecological, health, social and economic problems. Land-use change and the increasing of salt areas evaluated in this work using satellite imagery. We evaluated the present situation and changes of the lake area in the past and further changes until 2025. The results indicated that from 1987 to 2000, the process of change has slowed down and less than 2% of the lake’s water area was reduced, and from 2000 to 2010, these shrinking processes were faster and more than 28% of the lake water area disappeared. The intensity of the shrinking from 2010 to 2014 is very severe. Using the Land Transformation Model, the continuation of the changes was modeled until 2025. The results of the modeling indicate the conversion of the water lake to salt lake in this period, and in the north part, the shallow waters occupy 0.7% of the total lake area. The result shows that climate change was not the significant factors for drying up of the lake but human factors such as building dams to store water for irrigation, increasing groundwater use by established deeper wells for agricultural irrigation were the important factors for drying. With changing of management of the waters leading to the lake and the transfer of new water resources to the lake between 2014 and 2016, the area of the lake increased to a double. It was evident that by proper planning and managing of water resources, the lake’s restoration can be achieved.

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The Great Salt Lake Ecosystem (Utah, USA): long term data and a structural equation approach

Ecosphere ◽

10.1890/es10-00091.1 ◽

2011 ◽

Vol 2 (3) ◽

pp. art33 ◽

Cited By ~ 57

Author(s):

Gary E. Belovsky ◽

Doyle Stephens ◽

Clay Perschon ◽

Paul Birdsey ◽

Don Paul ◽

...

Keyword(s):

Structural Equation ◽

Salt Lake ◽

Great Salt Lake ◽

Lake Ecosystem ◽

Equation Approach ◽

Term Data

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Investigation of correlation of the variations in land subsidence (detected by continuous GPS measurements) and methodological data in the surrounding areas of Lake Urmia

Nonlinear Processes in Geophysics ◽

10.5194/npg-19-675-2012 ◽

2012 ◽

Vol 19 (6) ◽

pp. 675-683 ◽

Cited By ~ 5

Author(s):

K. Moghtased-Azar ◽

A. Mirzaei ◽

H. R. Nankali ◽

F. Tavakoli

Keyword(s):

Time Series ◽

Land Subsidence ◽

Salt Lake ◽

Linear Trend ◽

Groundwater Resources ◽

Time Interval ◽

Gps Measurements ◽

Lake Urmia ◽

North West ◽

Continuous Gps

Abstract. Lake Urmia, a salt lake in the north-west of Iran, plays a valuable role in the environment, wildlife and economy of Iran and the region, but now faces great challenges for survival. The Lake is in immediate and great danger and is rapidly going to become barren desert. As a result, the increasing demands upon groundwater resources due to expanding metropolitan and agricultural areas are a serious challenge in the surrounding regions of Lake Urmia. The continuous GPS measurements around the lake illustrate significant subsidence rate between 2005 and 2009. The objective of this study was to detect and specify the non-linear correlation of land subsidence and temperature activities in the region from 2005 to 2009. For this purpose, the cross wavelet transform (XWT) was carried out between the two types of time series, namely vertical components of GPS measurements and daily temperature time series. The significant common patterns are illustrated in the high period bands from 180–218 days band (~6–7 months) from September 2007 to February 2009. Consequently, the satellite altimetry data confirmed that the maximum rate of linear trend of water variation in the lake from 2005 to 2009, is associated with time interval from September 2007 to February 2009. This event was detected by XWT as a critical interval to be holding the strong correlation between the land subsidence phenomena and surface temperature. Eventually the analysis can be used for modeling and prediction purposes and probably stave off the damage from subsidence phenomena.

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Palaeoecological significance of the spores of the liverwort Riella (Riellaceae) in a late Pleistocene long pollen record from the hypersaline Lake Urmia, NW Iran

Review of Palaeobotany and Palynology ◽

10.1016/j.revpalbo.2008.04.004 ◽

2008 ◽

Vol 152 (1-2) ◽

pp. 66-73 ◽

Cited By ~ 26

Author(s):

Morteza Djamali ◽

Harald Kürschner ◽

Hossein Akhani ◽

Jacques-Louis de Beaulieu ◽

Abdolhossein Amini ◽

...

Keyword(s):

Late Pleistocene ◽

Hypersaline Lake ◽

Pollen Record ◽

Lake Urmia ◽

Nw Iran

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Estimation of shallow groundwater evaporation from dried-up areas of Lake Urmia, Iran

10.5194/egusphere-egu2020-21046 ◽

2020 ◽

Author(s):

Sahand Darehshouri ◽

Nils Michelsen ◽

Christoph Schüth ◽

Stephan Schulz

Keyword(s):

Water Level ◽

Salt Lake ◽

Shallow Groundwater ◽

Irrigated Agriculture ◽

Lake Area ◽

Lake Urmia ◽

Night Time ◽

Undisturbed Soil ◽

Custom Made ◽

Water Level Decline

Lake Urmia, located in the northwest of Iran, had an initial volume of about 19 km3 and a surface area of 5,700 km2 (Alipour, 2006). Once one of the largest hypersaline lakes in the world, this UNESCO Biosphere Reserve site currently shows a remarkable water level decline. About 70% of the lake area (Tourian et al., 2015) and more than 90% of its volume were lost between 2000 and 2014 (Schulz et al., 2020). The lack of a precise water balance of the Lake Urmia catchment is one of the challenges authorities are facing in their efforts to restore the lake to its ecological level. Here, key issues are that lake evaporation rates are mostly assumed and that evaporation of shallow groundwater from dried-up areas (up to 3,000 km2) is often ignored. The objective of this study is to obtain evaporation rate estimates for the dried-up parts of the Urmia lake bed. To this end, we set up a laboratory experiment with undisturbed soil columns collected from dried-up areas of the lake. With the help of a custom-made low-cost environmental chamber, the columns were subject to day- and night-time weather conditions typical for the area. Performed measurements comprise water level logging and monitoring of mass losses from the columns due to evaporation. First experimental results will be presented.&#160;References Alipour, S., 2006. Hydrogeochemistry of seasonal variation of Urmia Salt Lake, Iran. Saline Systems 2, 9. doi:10.1186/1746-1448-2-9Schulz, S., Darehshouri, S., Hassanzadeh, E., Tajrishy, M., Sch&#252;th, C., 2020. Climate change or irrigated agriculture &#8211; what drives the water level decline of Lake Urmia. Sci. Rep. 1&#8211;10. doi:10.1038/s41598-019-57150-yTourian, M.J., Elmi, O., Chen, Q., Devaraju, B., Roohi, S., Sneeuw, N., 2015. A spaceborne multisensor approach to monitor the desiccation of Lake Urmia in Iran. Remote Sens. Environ. 156, 349&#8211;360. doi:10.1016/j.rse.2014.10.006&#160;

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A late Pleistocene long pollen record from Lake Urmia, Nw Iran

Quaternary Research ◽

10.1016/j.yqres.2008.03.004 ◽

2008 ◽

Vol 69 (03) ◽

pp. 413-420 ◽

Cited By ~ 135

Author(s):

Morteza Djamali ◽

Jacques-Louis de Beaulieu ◽

Madjid Shah-hosseini ◽

Valérie Andrieu-Ponel ◽

Philippe Ponel ◽

...

Keyword(s):

Late Glacial ◽

Interglacial Period ◽

Pollen Record ◽

Glacial Period ◽

Last Interglacial ◽

Lake Urmia ◽

Nw Iran ◽

Shrub Steppe ◽

Isotope Record ◽

Palynological Study

A palynological study based on two 100-m long cores from Lake Urmia in northwestern Iran provides a vegetation record spanning 200 ka, the longest pollen record for the continental interior of the Near East. During both penultimate and last glaciations, a steppe ofArtemisiaand Poaceae dominated the upland vegetation with a high proportion of Chenopodiaceae in both upland and lowland saline ecosystems. WhileJuniperusand deciduousQuercustrees were extremely rare and restricted to some refugia,Hippophaë rhamnoidesconstituted an important phanerophyte, particularly during the late last glacial period. A pronounced expansion inEphedrashrub-steppe occurred at the end of the penultimate late-glacial period but was followed by extreme aridity that favoured anArtemisiasteppe. Very high lake levels, registered by both pollen and sedimentary markers, occurred during the middle of the last glaciation and late part of the penultimate glaciation. The late-glacial to early Holocene transition is represented by a succession ofHippophaë, Ephedra, Betula, Pistaciaand finallyJuniperusandQuercus. The last interglacial period (Eemian), slightly warmer and moister than the Holocene, was followed by two interstadial phases similar in pattern to those recorded in the marine isotope record and southern European pollen sequences.

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The Effects of Artemia Cyst Harvesting on the Salt Lake Ecosystem

Journal of Siberian Federal University Biology ◽

10.17516/1997-1389-0333 ◽

2020 ◽

pp. 348-357

Author(s):

Liudmila I. Litvinenko ◽

Aleksander I. Litvinenko ◽

Elena G. Boyko ◽

Kirill V. Kutsanov ◽

Marina A. Korentovich

Keyword(s):

Salt Lake ◽

Lake Ecosystem ◽

Hypersaline Lake ◽

Daily Production ◽

Artemia Cyst ◽

Main Components ◽

Artemia Cysts ◽

Artemia Population ◽

B Coefficients

In Russia, the main stocks of Artemia cysts and cyst harvesting activities are concentrated in Western Siberia. About 1,100 tons of cysts are harvested annually, including 180 tons in the Kurgan Region and 140 tons from Medvezhye Lake (about 2 % of their world harvest). The purpose of this study was to determine the degree of influence of Artemia cyst harvesting on the ecosystem of a salt lake in a case study of Medvezhye Lake. The main trophic components of the ecosystem – phytoplankton, zooplankton, and zoobenthos – were analyzed. The salinity of the brine of Medvezhye Lake varied between 110 and 320 g/dm3 in different years. Phytoplankton in the lake function throughout the year. They are characterized by small cell sizes, low biomass (0.76±0.24 mg/L) and daily production (1.03±0.18 mgO2/L or 0.3±0.05 gC/m2), and high levels of A/B and P/B coefficients. Zooplankton and zoobenthos are represented mainly by Artemia. The biomass of Artemia shrimp reached 21.9±3.2 mg/L (219 kg/ha) on average during 1995-2018. During this period, the stock of cysts formed annually in the lake was 114.5±14.3 kg/ha; the harvest was 23.7±3.0 kg/ha (21 % of the stock). The main components of the ecosystem – phytoplankton – Artemia shrimp – Artemia cysts – were produced annually in the following proportions: 8390:2678:115 kg/ha·year (75:24:1 %). The removal of 23.7 kg/ha of the cysts (0.22 % of the production of all components) from the lake is negligible compared to the other components of the ecosystem. The residual density of cysts after harvesting, which is necessary for the reproduction of the Artemia population for the next season during the 1st generation, is 10 kg/ha. Averaged data indicate that the amount of Artemia cysts left in the ecosystem of Medvezhye Lake after cyst harvesting is 91 kg/ha, i.e. 9 times greater than the minimum required density. The results reported in the present study indicate that the current level of cyst harvesting cannot have any significant impact on the ecosystem of the hypersaline lake

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Application of Artificial Intelligence in Agrometeorology

10.21203/rs.3.rs-565358/v1 ◽

2021 ◽

Author(s):

Homayoun Faghih ◽

Javad Behmanesh ◽

Hossein Rezaie ◽

Keivan Khalili

Keyword(s):

Precision Agriculture ◽

Gene Expression Programming ◽

Wheat Yield ◽

Growth Period ◽

Percentage Error ◽

Lake Urmia ◽

Climate Effect ◽

Drying Up ◽

Rainfed Wheat ◽

First Time

Abstract Replacing irrigated with rainfed crops and sustainable production of major rainfed plants (such as wheat) can be an efficient strategy to restore water resources that are drying up. Identifying plant response to climate is essential to advancing this strategy and planning for precision agriculture. Wheat is the main plant of Saqez in the Lake Urmia basin of Iran, whose yield is associated with severe fluctuations. This study was conducted to investigate the climate effect on wheat yield fluctuation. For this purpose, the method of growing degree days (GDDs) and the Zadoks scale were used to divide the wheat growth period into seven stages. Forty-seven climatic variables of the first six stages were used to do factor analysis and to develop the model for forecasting pre-harvest yield. Gene expression programming (GEP), artificial neural networks (ANNs), and multivariate linear regression (MLR) methods were applied to develop the model. The results showed that 90.7% of the total variance of 47 variables can be explained by 10 factors. Eighty-two percent of yield variations were modeled by these 10 factors (r = 0.91). The mean absolute percentage error (MAPE) for the models developed by the GEP and ANN methods was 26%, and its amount for the MLR model was 35%. In this study, for the first time, the GEP method was used to model rainfed wheat yield. Comparison with MLR and ANN methods shows that GEP is suitable for modeling in this field.

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