Vegetation change in response to grazing and water level decline in the Enot Zukim Nature Reserve (En Fescha), Israel

Water level fluctuations resulting from natural and anthropogenic factors have been projected to affect the functions and structures of wetland vegetation communities. Therefore, it is important to assess the impact of the hydrological gradient on wetland vegetation. This paper presents a case study on the Honghe National Nature Reserve (HNNR) in the Sanjiang Plain, located in Northeast China. In this study, 210 plots from 18 sampling line transects were sampled in 2011, 2012, and 2014 along the hydrological gradient. Using a Gaussian logistic regression model, we determined a relationship between three wetland plant species and a hydrologic indicator—a combination of the water level and soil moisture—and then applied that relationship to simulate the distribution of plants across a larger landscape by the geographic information system (GIS). The results show that the optimum ecological amplitude of Calamagrostis angustifolia to the hydrological gradient based on the probability of occurrence model was [0.09, 0.41], that of Carex lasiocarpa was [0.35, 0.57], and that of Carex pseudocuraica was [0.49, 0.77]. The optimum of Calamagrostis angustifolia was 0.25, Carex lasiocarpa was 0.46, and Carex pseudocuraica was 0.63. Spatial distribution probability maps were generated, as were maps detailing the distribution of the most suitable habitats for wetland vegetation species. Finally, the model simulation results were verified, showing that this approach can be employed to provide an accurate simulation of the spatial distribution pattern of wetland vegetation communities. Importantly, this study suggests that it may be possible to predict the spatial distribution of different species from the hydrological gradient.

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Climate change or irrigated agriculture – what drives the water level decline of Lake Urmia

Scientific Reports ◽

10.1038/s41598-019-57150-y ◽

2020 ◽

Vol 10 (1) ◽

Cited By ~ 10

Author(s):

Stephan Schulz ◽

Sahand Darehshouri ◽

Elmira Hassanzadeh ◽

Massoud Tajrishy ◽

Christoph Schüth

Keyword(s):

Climate Change ◽

Water Level ◽

Irrigated Agriculture ◽

Lake Urmia ◽

Water Level Decline

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Model Test Study on Embankment Instability Induced by Rapid Drawdown of Water Level at Yellow River Downstream

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.160-162.750 ◽

2010 ◽

Vol 160-162 ◽

pp. 750-755

Author(s):

Yu Kun Zhao ◽

Ji Hong Yang ◽

Qing An Li

Keyword(s):

Water Level ◽

Model Test ◽

Yellow River ◽

Digital Camera ◽

Hydrodynamic Pressure ◽

Test Methods ◽

Test Study ◽

Short Period ◽

Water Lever ◽

Water Level Decline

Rapid drawdown of water level is one of the most important factors that influencing the embankment stability. Based on the principle of geomechanical model test and hydroaulic model test methods, the model test was performed to study Yellow River downstream embankment instability induced by rapid drawdown of water level. The slope models with geometric scale of 1:25, 1:45, 1:62.5 were constructed in the transparent plexiglass model box with 1.6m long, 0.8m wide and 0.6m high. Changes on the slope were recorded during water level decline at different velocity by digital camera and slope tracer etc. The model test results showed that during the rapid drawdown process, there was only small cracks and not slippage in advance; when the water level dropped to a certain height, the sliding distance increased suddenly, which showed that the rate of water level decline was behind the river water, and the slope weight and downslope hydrodynamic pressure by the saturation line in slope body were higher than water lever exceeds the sliding force in a very short period of time, which caused landslide; after the sliding body appearing, slide was continuous and not mutation.

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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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