scholarly journals The Effect of Climate Changes on The Fluctuation of The Water Level of Al- Razzaza Lake, Iraq

2021 ◽  
pp. 4464-4474
Author(s):  
Shahad A. Al-Qaraghuli ◽  
Azhar A. Hassan ◽  
Rafa A. Albaldawi ◽  
Omnia K. Abd
Keyword(s):  
Water Level ◽  
Surface Area ◽  
Water Surface ◽  
Climate Changes ◽  
Spectral Band ◽  
Water Levels ◽  
Sharp Change ◽  
Significant Information ◽  
Water Index ◽  
Water Surface Area

      One of the serious environmental challenges that Iraq faces is climate changes and impacts of changing weather patterns and extreme global weather events. This paper addresses changes in the temporal and spatial characteristics of water levels of Razzaza Lake and response to climatic changes using archived series of Multispectral satellite images Landsat. TM, ETM+ and OLI images acquired on 1990, 2000 and of 2016. In order to extract, mapping the water surface area of the Razzaza Lake, Multispectral spectral band rationing the Normalized Difference Water Index (NDWI) technique was adopted, and the climatic elements data for the period (1990-2016) were analyzed which provide significant information of surface water. The results show that Razzaza Lake has a particularly sharp change rate in the water level and there are significant   fluctuations on lake level and water surface area over the time.

scholarly journals Building a model for predicting the water level in a river using remote sensing data from open sources

2020 ◽  
Vol 223 ◽  
pp. 02006
Author(s):  
Alexey Kolesnikov ◽  
Pavel Kikin ◽  
Anastasia Nungesser
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Water Level ◽  
Surface Area ◽  
Water Surface ◽  
Open Data ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Water Surface Area

The article discusses the possibility of predicting the water surface area of a river (and based on these values, the calculation of the water level) based on only open data of remote sensing. The area and depth of snow cover, the intensity of precipitation according to Landsat and Sentinel data and the monitoring indicators MODIS, Copernicus, REMSS are used as initial parameters. For the selected parameters, the degree of influence on the final forecast was assessed.

scholarly journals AN ORIGINAL PROCESSING METHOD OF SATELLITE ALTIMETRY FOR ESTIMATING WATER LEVELS AND VOLUME FLUCTUATIONS IN A SERIES OF SMALL LAKES OF THE PANTANAL WETLAND COMPLEX IN BRAZIL

2016 ◽  
Vol XLI-B8 ◽  
pp. 327-334 ◽  
Author(s):  
Paulo Henrique Costa ◽  
Eric Oliveira Pereira ◽  
Philippe Maillard
Keyword(s):  
Water Level ◽  
Water Surface ◽  
Satellite Altimetry ◽  
Water Levels ◽  
Small Lakes ◽  
Water Surface Area ◽  
Volume Fluctuations ◽  
Calm Water ◽  
Gauging Station

Satellite altimetry is becoming a major tool for measuring water levels in rivers and lakes offering accuracies compatible with many hydrological applications, especially in uninhabited regions of difficult access. The Pantanal is considered the largest tropical wetland in the world and the sparsity of <i>in situ</i> gauging station make remote methods of water level measurements an attractive alternative. This article describes how satellites altimetry data from Envisat and Saral was used to determine water level in two small lakes in the Pantanal. By combining the water level with the water surface area extracted from satellite imagery, water volume fluctuations were also estimated for a few periods. The available algorithms (retrackers) that compute a range solution from the raw waveforms do not always produce reliable measurements in small lakes. This is because the return signal gets often “contaminated” by the surrounding land. To try to solve this, we created a “lake” retracker that rejects waveforms that cannot be attributed to “calm water” and convert them to altitude. Elevation data are stored in a database along with the water surface area to compute the volume fluctuations. Satellite water level time series were also produced and compared with the only nearby <i>in situ</i> gauging station. Although the “lake” retracker worked well with calm water, the presence of waves and other factors was such that the standard “ice1” retracker performed better on the overall. We estimate our water level accuracy to be around 75 cm. Although the return time of both satellites is only 35 days, the next few years promise to bring new altimetry satellite missions that will significantly increase this frequency.

scholarly journals A loop-like relationship between water surface area of Lake Dongting and water level at Chenglingji, the Yangtze River

2017 ◽  
Vol 29 (3) ◽  
pp. 753-764 ◽  
Author(s):  
KE Wenli ◽  
◽  
CHEN Chengzhong ◽  
JI Hongxia ◽  
CHEN Mi ◽  
...  
Keyword(s):  
Water Level ◽  
Surface Area ◽  
Yangtze River ◽  
Water Surface ◽  
The Yangtze River ◽  
Water Surface Area

Using space observations to monitor reservoir operations in the Lancang River

2021 ◽  
Author(s):  
Dung Trung Vu ◽  
Thanh Duc Dang ◽  
Stefano Galelli
Keyword(s):  
Surface Area ◽  
Water Surface ◽  
Satellite Images ◽  
Water Levels ◽  
The Tibetan Plateau ◽  
Altimetry Data ◽  
Lancang River ◽  
Water Surface Area ◽  
Hydropower Potential ◽  
Over Time

<p>Being a part of the Water Tower of Asia, the Mekong River originates from the Tibetan Plateau and flows through China, Myanmar, Laos, Thailand, Cambodia, and Vietnam. Its upper portion, also called the Lancang River, has abundant hydropower potential, which has been largely exploited during the three recent decades. To date, there are 11 operational dams (10 of them have a volume larger than 100 MCM) on the mainstream of the Lancang, controlling about 40% of the annual flow at Chiang Saen (the most upstream station of the Lower Mekong). The amount of water withheld in these dams is a potential source of controversy between China and downstream countries because it affects both the timing and volume of available water. Assessing the real impacts of these dams is a challenging task owing to the chronic lack of data on reservoirs' storage and operating patterns. To overcome this challenge, we exploit satellite images and altimetry data. The analysis focuses on 10 reservoirs and is conducted in three steps. First, we estimate the relationship between water elevation and surface area (E-A curve) for each reservoir. For this purpose, we either use DEM data or water surface area data (derived from satellite images) paired with altimetry-derived water levels. Second, with the Elevation-Area-Storage curve converted from each E-A curve, we calculate storage variability over time by using satellite image-derived reservoir water surface area. The result is collated with storage variability derived from altimetry data. In the last part of our analysis, focusing on the period 2008-2020, we show how the total withheld storage changed over time, we determine the rule curve of each reservoir and elucidate the role of reservoir filling strategies.</p>

scholarly journals AN ORIGINAL PROCESSING METHOD OF SATELLITE ALTIMETRY FOR ESTIMATING WATER LEVELS AND VOLUME FLUCTUATIONS IN A SERIES OF SMALL LAKES OF THE PANTANAL WETLAND COMPLEX IN BRAZIL

2016 ◽  
Vol XLI-B8 ◽  
pp. 327-334
Author(s):  
Paulo Henrique Costa ◽  
Eric Oliveira Pereira ◽  
Philippe Maillard
Keyword(s):  
Water Level ◽  
Water Surface ◽  
Satellite Altimetry ◽  
Water Levels ◽  
Small Lakes ◽  
Water Surface Area ◽  
Volume Fluctuations ◽  
Calm Water ◽  
Gauging Station

Satellite altimetry is becoming a major tool for measuring water levels in rivers and lakes offering accuracies compatible with many hydrological applications, especially in uninhabited regions of difficult access. The Pantanal is considered the largest tropical wetland in the world and the sparsity of <i>in situ</i> gauging station make remote methods of water level measurements an attractive alternative. This article describes how satellites altimetry data from Envisat and Saral was used to determine water level in two small lakes in the Pantanal. By combining the water level with the water surface area extracted from satellite imagery, water volume fluctuations were also estimated for a few periods. The available algorithms (retrackers) that compute a range solution from the raw waveforms do not always produce reliable measurements in small lakes. This is because the return signal gets often “contaminated” by the surrounding land. To try to solve this, we created a “lake” retracker that rejects waveforms that cannot be attributed to “calm water” and convert them to altitude. Elevation data are stored in a database along with the water surface area to compute the volume fluctuations. Satellite water level time series were also produced and compared with the only nearby <i>in situ</i> gauging station. Although the “lake” retracker worked well with calm water, the presence of waves and other factors was such that the standard “ice1” retracker performed better on the overall. We estimate our water level accuracy to be around 75 cm. Although the return time of both satellites is only 35 days, the next few years promise to bring new altimetry satellite missions that will significantly increase this frequency.

Successful restoration of water level and surface area restored migrant bird populations in a Hungarian wetland

Biologia ◽  
2011 ◽  
Vol 66 (6) ◽  
Author(s):  
József Gyurácz ◽  
Péter Bánhidi ◽  
András Csuka
Keyword(s):  
Water Level ◽  
Surface Area ◽  
Water Surface ◽  
Bird Species ◽  
Reed Warbler ◽  
Bird Assemblages ◽  
Bird Populations ◽  
Sedge Warbler ◽  
Water Surface Area ◽  
Reed Bunting

AbstractWater level and water surface area fluctuations are important factors determining abundance of bird populations and bird assemblages structure in a wetland habitat. The water level and water surface area of the Marsh Tömörd (West Hungary) changed drastically between 1998 and 2008, and the marsh dried out because of scarce rainfall in 2000 and 2001. A habitat restoration in winter 2001 repaired the waterholding capacity of the marsh. We analyzed changes in parameters of bird assemblages in investigated wetland area in relation of environmental factors. We used full redundancy analysis (RDA) on number of caugth migratory birds per year, species richness, diversity and evenness of bird assemblages to examine correlations among water level, water surface area and vegetation core. Species like water rail, common snipe, river warbler, Savi’s warbler, great reed warbler, reed warbler, marsh warbler, sedge warbler, reed bunting showed high and positive linear correlations with the water level and water surface area in the postbreeding period. Some wetland species, sedge warbler, Savi’s warbler and reed bunting as well as total number of caugth birds per year and total numbers of caugth species per year were clearly associated with thick marsh vegetation. According to our results the bird species composition of the wetland might have returned to the prerestoration levels and surface areas.

Denoising of river surface photogrammetric DEMs using deep learning

2021 ◽  
Author(s):  
Radosław Szostak ◽  
Przemysław Wachniew ◽  
Mirosław Zimnoch ◽  
Paweł Ćwiąkała ◽  
Edyta Puniach ◽  
...  
Keyword(s):  
Higher Education ◽  
Deep Learning ◽  
Water Level ◽  
Water Surface ◽  
Research University ◽  
Static Characteristic ◽  
Water Levels ◽  
Training Dataset ◽  
Observation Data ◽  
Characteristic Points

&lt;p&gt;Unmanned Aerial Vehicles (UAVs) can be an excellent tool for environmental measurements due to their ability to reach inaccessible places and fast data acquisition over large areas. In particular drones may have a potential application in hydrology, as they can be used to create photogrammetric digital elevation models (DEM) of the terrain allowing to obtain high resolution spatial distribution of water level in the river to be fed into hydrological models. Nevertheless, photogrammetric algorithms generate distortions on the DEM at the water bodies. This is due to light penetration below the water surface and the lack of static characteristic points on water surface that can be distinguished by the photogrammetric algorithm. The correction of these disturbances could be achieved by applying deep learning methods. For this purpose, it is necessary to build a training dataset containing DEMs before and after water surfaces denoising. A method has been developed to prepare such a dataset. It is divided into several stages. In the first step a photogrammetric surveys and geodetic water level measurements are performed. The second one includes generation of DEMs and orthomosaics using photogrammetric software. Finally in the last one the interpolation of the measured water levels is done to obtain a plane of the water surface and apply it to the DEMs to correct the distortion. The resulting dataset was used to train deep learning model based on convolutional neural networks. The proposed method has been validated on observation data representing part of Kocinka river catchment located in the central Poland.&lt;/p&gt;&lt;p&gt;This research has been partly supported by the Ministry of Science and Higher Education Project &amp;#8220;Initiative for Excellence &amp;#8211; Research University&amp;#8221; and Ministry of Science and Higher Education subsidy, project no. 16.16.220.842-B02 / 16.16.150.545.&lt;/p&gt;

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