Scholarlink

<p>Detecting past characteristic of hydro-climatic variables can provide a deeper understanding of the effects of climate change on water resources. Among the hydro-meteorological parameters, salinity is one of the most critical factors. This study explored the average monthly salinity trends of the six stations in Ho Chi Minh City for the period from 2007 to 2021, using the Innovative Polygon Trend Analysis (IPTA). IPTA is a simple approach that allows for fine-trend interpretation and avoids the fundamental assumptions in classical methods, such as normality, independence, and pre-whitening. Polygon graphics for monthly salinity data were analyzed using arithmetic mean and standard deviation to assess trend length and slope. The outcomes showed that most of the statistically significant transitions (April–May, November–December) occurred in consecutive months between dry and rainy seasons, with the highest average trend length values of 9.88&#xa0;g/l and 8.31&#xa0;g/l at Ong Thin and Nha Be stations, respectively. Particularly, the maximum length trend in the dry season also highlighted a characteristic of the salinity transition over time. Therefore, the application of IPTA provides insights into many months’ cycles, which are essential for the salinization management of the study area.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Innovative polygon trend analysis for salinity trend detection in Ho Chi Minh City, Vietnam

  • 期刊论文

  • 发表日期：

    2025年1月30日

查看全文
  • Phan Thi Ha,
  • Pham Quoc Khanh,
  • Le Hoang Tu,
  • Nguyen Thi Huyen,
  • Vo Ngoc Quynh Tram,
  • Nguyen Duy Liem,
  • Nguyen Kim Loi

摘要

Detecting past characteristic of hydro-climatic variables can provide a deeper understanding of the effects of climate change on water resources. Among the hydro-meteorological parameters, salinity is one of the most critical factors. This study explored the average monthly salinity trends of the six stations in Ho Chi Minh City for the period from 2007 to 2021, using the Innovative Polygon Trend Analysis (IPTA). IPTA is a simple approach that allows for fine-trend interpretation and avoids the fundamental assumptions in classical methods, such as normality, independence, and pre-whitening. Polygon graphics for monthly salinity data were analyzed using arithmetic mean and standard deviation to assess trend length and slope. The outcomes showed that most of the statistically significant transitions (April–May, November–December) occurred in consecutive months between dry and rainy seasons, with the highest average trend length values of 9.88 g/l and 8.31 g/l at Ong Thin and Nha Be stations, respectively. Particularly, the maximum length trend in the dry season also highlighted a characteristic of the salinity transition over time. Therefore, the application of IPTA provides insights into many months’ cycles, which are essential for the salinization management of the study area.