Gypsum saturation degrees and precipitation potentials from Dead Sea - seawater mixtures

2009 ◽  
Vol 6 (5) ◽  
pp. 416 ◽  
Author(s):  
Itay J. Reznik ◽  
Jiwchar Ganor ◽  
Assaf Gal ◽  
Ittai Gavrieli
Keyword(s):  
Surface Water ◽  
Water Level ◽  
Water Column ◽  
Sea Water ◽  
Theoretical Calculations ◽  
Dead Sea ◽  
Gypsum Precipitation ◽  
The Dead ◽  
Rate Of Decline ◽  
The 1960S

Environmental context. Since the 1960s the Dead Sea water level has dropped by nearly 30 m and over the last decade the rate of decline accelerated to over 1 m per year. Conveying seawater to the Dead Sea to stabilise or even raise its water level is currently being considered but may result in ‘whitening’ of the surface water through the formation of minute gypsum crystals that will remain suspended in the water column for a prolonged period of time. This paper is a first step in attaining the relevant physical and chemical parameters required to assess the potential for such whitening of the Dead Sea. Abstract. Introduction of seawater to the Dead Sea (DS) to stabilise its level raises paramount environmental questions. A major concern is that massive nucleation and growth of minute gypsum crystals will occur as a result of mixing between the SO42–-rich Red Sea (RS) water and Ca2+-rich DS brine. If the gypsum will not settle quickly to the bottom it may influence the general appearance of the DS by ‘whitening’ the surface water. Experimental observations and theoretical calculations of degrees of saturation with respect to gypsum (DSG) and gypsum precipitation potentials (PPT) were found to agree well, over the large range but overall high ionic strength of DS–RS mixtures. The dependency of both DSG and PPT on temperature was examined as well. Based on our thermodynamic insights, slow discharge of seawater to the DS will result in a relatively saline upper water column which will lead to enhanced gypsum precipitation.

Dead Sea Water Levels Analysis Using Artificial Neural Networks and Firefly Algorithm

2022 ◽  
pp. 1118-1129
Author(s):  
Nawaf N. Hamadneh
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Water Level ◽  
Firefly Algorithm ◽  
Sea Water ◽  
Dead Sea ◽  
Water Levels ◽  
Artificial Neural ◽  
The Dead ◽  
Predicted Values

In this study, the performance of adaptive multilayer perceptron neural network (MLPNN) for predicting the Dead Sea water level is discussed. Firefly Algorithm (FFA), as an optimization algorithm is used for training the neural networks. To propose the MLPNN-FFA model, Dead Sea water levels over the period 1810–2005 are applied to train MLPNN. Statistical tests evaluate the accuracy of the hybrid MLPNN-FFA model. The predicted values of the proposed model were compared with the results obtained by another method. The results reveal that the artificial neural network (ANN) models exhibit high accuracy and reliability for the prediction of the Dead Sea water levels. The results also reveal that the Dead Sea water level would be around -450 until 2050.

scholarly journals Vulnerability of tourism development to salt karst hazards along the Jordanian Dead Sea shore

2018 ◽  
Author(s):  
Najib Abou Karaki ◽  
Simone Fiaschi ◽  
Killian Paenen ◽  
Mohammad Al-Awabdeh ◽  
Damien Closson
Keyword(s):  
Sea Water ◽  
Warning System ◽  
Dead Sea ◽  
Northern Coast ◽  
Karst System ◽  
Base Level ◽  
Geological Discontinuities ◽  
The Dead ◽  
Remote Sensing Techniques ◽  
The 1960S

Abstract. The Dead Sea shore is a unique young and dynamic evaporite karst system. It started developing in the 1960s, when the main water resources that used to feed the terminal lake were diverted towards deserts, cities and industries. The Dead Sea water level started to lower at an accelerating pace, exceeding 1 meter per year during the last decade, causing a hydrostatic disequilibrium between the underground fresh waters and the base level. This battery-like system provides the energy needed for the development of underground cavities, hectometre-size landslides, and vertical erosion of channels during flash-floods. The geological discontinuities are the weakest points where the system can re-balance and where most of the energy is dissipated through erosional processes. Groundwater is moving rapidly along these discontinuities to reach the dropping base level. The salt that soars the sediments matrix is dissolved along the paths favouring the development of enlarged conduits, cavities, and the proliferation of ground collapses (sinkholes). Despite these unfavourable environmental conditions, large touristic projects have flourished along the northern coast of the Jordanian Dead Sea. In this work, thanks to the application of remote sensing techniques combined with repeated field observations, we show that a 10 kilometres-long strip of land along the Dead Sea shore that encompass several touristic infrastructures is exposed to subsidence, sinkholes and landslides. Furthermore, we point out the importance of setting up an early warning system to warn the authorities prior to the triggering of hazardous events, limiting or preventing possible disastrous consequences related to hydrogeological hazards.

Dead Sea Water Levels Analysis Using Artificial Neural Networks and Firefly Algorithm

2020 ◽  
Vol 11 (3) ◽  
pp. 19-29
Author(s):  
Nawaf N. Hamadneh
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Water Level ◽  
Firefly Algorithm ◽  
Sea Water ◽  
Statistical Tests ◽  
Dead Sea ◽  
Water Levels ◽  
Artificial Neural ◽  
The Dead

In this study, the performance of adaptive multilayer perceptron neural network (MLPNN) for predicting the Dead Sea water level is discussed. Firefly Algorithm (FFA), as an optimization algorithm is used for training the neural networks. To propose the MLPNN-FFA model, Dead Sea water levels over the period 1810–2005 are applied to train MLPNN. Statistical tests evaluate the accuracy of the hybrid MLPNN-FFA model. The predicted values of the proposed model were compared with the results obtained by another method. The results reveal that the artificial neural network (ANN) models exhibit high accuracy and reliability for the prediction of the Dead Sea water levels. The results also reveal that the Dead Sea water level would be around -450 until 2050.

An assessment of the Dead Sea level change using remotely sensed data

2021 ◽  
Author(s):  
Musab Mbideen ◽  
Balázs Székely
Keyword(s):  
Remote Sensing ◽  
Water Level ◽  
Surface Area ◽  
Dead Sea ◽  
Spectral Radiance ◽  
Water Volume ◽  
Surface Model ◽  
Atmospheric Effects ◽  
Level 1 ◽  
The Dead

<p>Remote Sensing (RS) and Geographic Information System (GIS) instruments have spread rapidly in recent years to manage natural resources and monitor environmental changes. Remote sensing has a vast range of applications; one of them is lakes monitoring. The Dead Sea (DS) is subjected to very strong evaporation processes, leading to a remarkable shrinkage of its water level. The DS is being dried out due to a negative balance in its hydrological cycle during the last five decades. This research aims to study the spatial changes in the DS throughout the previous 48 years. Change detection technique has been performed to detect this change over the research period (1972-2020). 73 Landsat imageries have been used from four digital sensors; Landsat 1-5 MSS C1 Level-1, Landsat 4-5 TM C1 Level-1, Land sat 7 ETM+ C1  Level-1, and Landsat 8 OLI-TIRS C1 Level. After following certain selection criteria , the number of studied images decreased. Furthermore, the Digital Surface Model of the Space Shuttle Radar Topography Mission and a bathymetric map of the Dead Sea were used. The collected satellite imageries were pre-processed and normalized using ENVI 5.3 software by converting the Digital Number (DN) to spectral radiance, the spectral radiance was converted to apparent reflectance, atmospheric effects were removed, and finally, the black gaps were removed. It was important to distinguish between the DS lake and the surrounding area in order to have accurate results, this was done by performing classification techniques. The digital terrain model of the DS was used in ArcGIS (3D) to reconstruct the elevation of the shore lines. This model generated equations to detect the water level, surface area, and water volume of the DS. The results were compared to the bathymetric data as well. The research shows that the DS water level declined 65 m (1.35 m/a) in the studied period. The surface area and the water volume declined by 363.56 km<sup>2 </sup>(7.57 km<sup>2</sup>/a) and 53.56 km<sup>3</sup> (1.11 km<sup>3</sup>/a), respectively. The research also concluded that due to the bathymetry of the DS, the direction of this shrinkage is from the south to the north. We hypothesize that anthropogenic effects have contributed in the shrinkage of the DS more than the climate. The use of the DS water by both Israel and Jordan for industrial purposes is the main factor impacting the DS, another factor is the diversion of the Jordan and Yarmouk rivers. Our results also allow to give a prediction for the near future of the DS: the water level is expected to reach –445 m in 2050, while the surface area and the water volume is expected to be 455 km<sup>2</sup> and 142 km<sup>3</sup>, respectively. </p>

The Dead Sea: Deepening of the Mixolimnion Signifies the Overture to Overturn of the Water Column

Science ◽  
1979 ◽  
Vol 206 (4414) ◽  
pp. 55-57 ◽  
Author(s):  
I. STEINHORN ◽  
G. ASSAF ◽  
J. R. GAT ◽  
A. NISHRY ◽  
A. NISSENBAUM ◽  
...  
Keyword(s):  
Water Column ◽  
Dead Sea ◽  
The Dead

scholarly journals Dead Sea evaporation by eddy covariance measurements vs. aerodynamic, energy budget, Priestley–Taylor, and Penman estimates

2018 ◽  
Vol 22 (2) ◽  
pp. 1135-1155 ◽  
Author(s):  
Jutta Metzger ◽  
Manuela Nied ◽  
Ulrich Corsmeier ◽  
Jörg Kleffmann ◽  
Christoph Kottmeier
Keyword(s):  
Energy Budget ◽  
Water Budget ◽  
Heat Storage ◽  
Sea Water ◽  
Correlation Coefficients ◽  
Dead Sea ◽  
Eddy Covariance Measurements ◽  
Lake Evaporation ◽  
The Dead ◽  
Storage Term

Abstract. The Dead Sea is a terminal lake, located in an arid environment. Evaporation is the key component of the Dead Sea water budget and accounts for the main loss of water. So far, lake evaporation has been determined by indirect methods only and not measured directly. Consequently, the governing factors of evaporation are unknown. For the first time, long-term eddy covariance measurements were performed at the western Dead Sea shore for a period of 1 year by implementing a new concept for onshore lake evaporation measurements. To account for lake evaporation during offshore wind conditions, a robust and reliable multiple regression model was developed using the identified governing factors wind velocity and water vapour pressure deficit. An overall regression coefficient of 0.8 is achieved. The measurements show that the diurnal evaporation cycle is governed by three local wind systems: a lake breeze during daytime, strong downslope winds in the evening, and strong northerly along-valley flows during the night. After sunset, the strong winds cause half-hourly evaporation rates which are up to 100 % higher than during daytime. The median daily evaporation is 4.3 mm d−1 in July and 1.1 mm d−1 in December. The annual evaporation of the water surface at the measurement location was 994±88 mm a−1 from March 2014 until March 2015. Furthermore, the performance of indirect evaporation approaches was tested and compared to the measurements. The aerodynamic approach is applicable for sub-daily and multi-day calculations and attains correlation coefficients between 0.85 and 0.99. For the application of the Bowen ratio energy budget method and the Priestley–Taylor method, measurements of the heat storage term are inevitable on timescales up to 1 month. Otherwise strong seasonal biases occur. The Penman equation was adapted to calculate realistic evaporation, by using an empirically gained linear function for the heat storage term, achieving correlation coefficients between 0.92 and 0.97. In summary, this study introduces a new approach to measure lake evaporation with a station located at the shoreline, which is also transferable to other lakes. It provides the first directly measured Dead Sea evaporation rates as well as applicable methods for evaporation calculation. The first one enables us to further close the Dead Sea water budget, and the latter one enables us to facilitate water management in the region.

Long-term prediction of the water level and salinity in the Dead Sea

2002 ◽  
Vol 16 (14) ◽  
pp. 2819-2831 ◽  
Author(s):  
B. N. Asmar ◽  
Peter Ergenzinger
Keyword(s):  
Water Level ◽  
Dead Sea ◽  
Term Prediction ◽  
The Dead ◽  
Long Term Prediction

scholarly journals Dead Sea evaporation by eddy covariance measurements versus aerodynamic, energy budget, Priestley–Taylor, and Penman estimates

2017 ◽  
Author(s):  
Jutta Metzger ◽  
Manuela Nied ◽  
Ulrich Corsmeier ◽  
Jörg Kleffmann ◽  
Christoph Kottmeier
Keyword(s):  
Linear Function ◽  
Heat Storage ◽  
Sea Water ◽  
Correlation Coefficients ◽  
Vapour Pressure Deficit ◽  
Dead Sea ◽  
Eddy Covariance Measurements ◽  
The Dead ◽  
Daily Evaporation ◽  
Storage Term

Abstract. The Dead Sea water budget is no longer in equilibrium. The lake level decline exceeds 1 m a−1 and causes severe environmental problems, such as a shifting of the fresh/saline groundwater interface and climatic changes. As the Dead Sea is a terminal lake, located in an arid environment, evaporation is the key component of the Dead Sea water budget and accounts for the main loss of water. However, the actual amount of evaporation as well as the governing factors are unknown. Therefore, for the first time, long-term eddy covariance measurements were performed for a period of one year, starting in March 2014. The total annual amount measured at this location was 994 ± 81 mm a−1. The median daily evaporation rate reaches 4.3 mm d−1 in July and only 1.1 mm d−1 in December. The wind velocity and vapour pressure deficit were identified as the main governing factors of evaporation throughout the year. Consequently, the local wind systems define the diurnal evaporation cycle. In the evening, strong downslope winds govern the wind field and cause evaporation amounts which are up to 100 % higher than during daytime, and also during the night evaporation rates are accelerated compared to daytime evaporation, due to strong northerly along-valley flows. Furthermore, a robust and reliable regression model is presented to calculate sub-daily and multiday evaporation values with a linear function of wind velocity and vapour pressure deficit. An overall correlation coefficient of 0.8 is achieved and the cross validation results in a prediction error of 4.8 %. Finally, indirect evaporation approaches were tested for their applicability for the Dead Sea and compared to the measurements. The aerodynamic approach is applicable for sub-daily and multi-day calculations and attains correlation coefficients between 0.85 and 0.99. For the application of the Bowen-Ratio-Energy-Balance (BREB) method and the Priestley–Taylor method, measurements of the heat storage term are inevitable to calculate evaporation on time scales up to one month. Without the heat storage term, the equations yield strong seasonal biases and over- or underestimate daily evaporation rates by up 100 %. The usage of an empirically gained linear function or a hysteresis model depending on the net radiation to estimate the heat storage term was not accurate enough to provide reliable evaporation amounts. The Penman equation was adapted to calculate realistic evaporation amounts, by using an empirically gained linear function for the heat storage term. The correlation coefficients are above 0.9, the daily mean difference is only 0.5 mm d−1 and the estimated annual amount is within the range of the measurement uncertainties. In summary, this study provides the first directly measured amounts of Dead Sea evaporation and applicable methods to calculate evaporation.

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