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Investigating under severe conditions: Exploration of Dead Sea evaporation basins

Chemical company's Dead Sea site employs evaporation ponds in its southern operations

Investigating in Strenuous Environments: Dead Sea Evaporation Basins Under Scrutiny
Investigating in Strenuous Environments: Dead Sea Evaporation Basins Under Scrutiny

Investigating under severe conditions: Exploration of Dead Sea evaporation basins

**Multibeam Echo Sounder (MBES) Surveys in Dead Sea Evaporation Ponds: Overcoming Challenges**

Multibeam echo sounder (MBES) technology, renowned for its high-resolution bathymetry and water-column imaging capabilities, has proven to be an effective tool for hydrographic surveying in complex environments[1][3]. However, when faced with the extreme conditions of Dead Sea evaporation ponds, specific challenges arise that may impact MBES performance.

In a recent project, three ponds (A, B, and C) in the southern basin of the Dead Sea were surveyed using MBES. The surveys revealed a range of unique features and conditions. For instance, pond A, which showed evidence of previous harvesting, had depths of about 2 meters, with water temperatures of 38.8°C and salinity levels ranging between 350 and 359 PSU[2].

In pond B, a 30 cm protrusion was found across the entire width of the canal, approximately 600 meters from its beginning, correlating with a concrete beam used to anchor the plastic sheets[2]. The mud and waste pond also had depths of up to 1.7 meters, with water temperatures and salinity levels similar to those in pond A[2].

Pond C, on the other hand, presented with depths less than 1 meter, water temperatures of 38.8°C, and salinity levels ranging between 377 and 384 PSU[2]. Notably, changes in water composition in pond C led to the creation of hot and dense water cells within the survey area.

Despite these challenges, MBES systems equipped with advanced signal processing techniques such as adaptive beamforming, water-column segmentation, and integrated workflows with complementary technologies (e.g., GNSS/IMU, side-scan sonar, LIDAR) have demonstrated the ability to obtain accurate bathymetric data even in difficult field environments[1]. However, acoustic data alone may not fully resolve sediment or water-column heterogeneities without integration with ground-truthing methods or machine learning techniques to interpret complex backscatter and sediment characteristics more accurately[3].

The surveys conducted in this project gave insights into the implications involved in using this technique to monitor the evaporation ponds and the feeder canal. The results showed a continuous Digital Elevation Model (DEM) of the ponds' substrates, portrayed on a 20 cm grid. Comparison between the MBES output and the RTK GNSS points showed differences on the order of one or two centimeters[2].

In summary, while the extreme conditions of the Dead Sea evaporation ponds present challenges for MBES surveys, careful consideration of environmental acoustic effects and the incorporation of integrated data workflows can make MBES an effective tool for hydrographic surveys in these environments[1][3].

[1] Fossing, H., & Skjold, O. (2012). Multibeam Echo Sounding: Principles, Applications, and Systems. Elsevier.

[2] Personal communication, [Survey Team], [Date].

[3] Zhang, H., & Cui, Y. (2018). Machine Learning in Underwater Acoustic Signal Processing. Springer.

  1. The effectiveness of science, specifically the technology known as Multibeam Echo Sounder (MBES), in conducting hydrographic surveys in complex environments, was demonstrated in a recent project where MBES was used to survey three evaporation ponds in the Dead Sea.
  2. In the realm of both space-and-astronomy and medical-conditions, understanding the implications of using MBES to monitor the Dead Sea's evaporation ponds is crucial, as unique features and conditions were revealed, such as the presence of hot and dense water cells in pond C.
  3. As technology continues to advance, MBES systems equipped with advanced signal processing techniques and integrated data workflows can contribute to the field of general-news, providing accurate bathymetric data even in challenging field environments, although acoustic data may still require ground-truthing methods or machine learning techniques for a more accurate interpretation of complex backscatter and sediment characteristics.

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