Characteristics of Waters during Transitional Season, Senimba Waters
DOI:
https://doi.org/10.48048/tis.2022.4495Keywords:
Senimba bay, Oceanography, ECMWF, ADCP, Least-squareAbstract
Characteristics of Waters During Transitional Season, Senimba Bay, Batam Indonesia. Senimba Bay is a water area in Batam City. It is necessary to develop the waters of Senimba Bay due to its location around the bay, which is still not arranged. Development such as changes in sea transportation lines and structuring the bay area requires Hidro-oceanography data, such as current data, waves, tides, and bathymetry. The research discusses the Gulf of Senimba waters' characteristics in the transition season, namely in April-May. The primary data taken is current data, bathymetry, waves, tides, and secondary data is wind data from ECMWF. Retrieval of current and wave data using ADCP (Acoustic Doppler Current Profiler) with several layers of depth. The method used for tides is Least-Square. Flow in the transition season in the Gulf of Senimba waters has a southwest direction during the high tide and northeast when low tides with mixed tides are double inclines, and the direction of the wind blows dominant towards the northeast. These waters have a minimum depth of –12.60 m Mean Sea Level (MSL) and maximum value –0.03 m MSL with current modeling. It produces no significant changes and only occurs in the direction of current in specific locations because location bathymetry factors influence it.
HIGHLIGHTS
- Construction and shipping lanes are in dire need of hydro-oceanographic data processing, especially in industrial areas
- The characteristics of the waters are very important to be seen every season of the year, this greatly determines the patterns and characteristics of waters
- The waters of Senimba Bay, Batam are more dominant in producing sea surface currents caused by winds that point to the northeast
- The depth of the sea is very important to get in doing hydro-oceanographic data modeling, this really determines the level of accuracy of the resulting model data
GRAPHICAL ABSTRACT
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