A composite approach towards understanding the mechanisms and driving variables of river mouth variability: A case study of the Da Dien River mouth

ABSTRACT

This research aims to present a composite approach to characterizing the intra-annual and interannual variability in inlet throat width and understanding its mechanism (how, when, and why it varies). The techniques used include remote sensing imagery analysis, spectral and cross-spectral analyses, correlation analyses, and random forest variable importance. The Da Dien River mouth (DDRM), which is located in southern Central Vietnam and experiences a strong annual signal of climate regimes, was selected as a case study to demonstrate the applicability of the approach. The results show that the narrowing/widening of the DDRM throat width is highly dynamic and variable under the significant dominant influence of wave height, tide and river flow, which seasonally and interannually vary according to the monsoon regime, El Niño/Southern Oscillation and sunspot number variations (better correlation with ENSO events). The overall throat width decreases during El Niño/the positive QBO phase and increases during La Niña periods/the negative QBO phase. The difference in river flow magnitudes is the main cause for the constriction/expansion of the DDRM throat width. The successful application of the study approach to the DDRM case study demonstrates its usefulness and ability to be applied to other case studies in tropical monsoon regions.

KEYWORDS:

• Coastal inlet
• monsoon
• intra- and interannual variability
• uneven data
• composite approach
• Da Dien River mouth

Acknowledgments

Nhu Y Nguyen was funded by Vingroup JSC and supported by the Postdoctoral Scholarship Programme of Vingroup Innovation Foundation (VINIF), Vingroup Big Data Institute (VinBigdata), code VINIF.2021.STS.28.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Postdoctoral Scholarship Programme of Vingroup Innovation Foundation (VINIF), Vingroup Big Data Institute (VinBigdata) [VINIF.2021.STS.28].