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Sediment clues in flood mitigation: the key to determining the origin, transport, and degree of heavy metal contamination
Hydrology Research ( IF 2.6 ) Pub Date : 2021-02-01 , DOI: 10.2166/nh.2020.119
K. V. Annammala 1, 2 , N. A. Mohamad 2 , D. Sugumaran 2 , L. S. Masilamani 2 , Y. Q. Liang 2 , M. H. Jamal 3 , Z. Yusop 1, 2 , A. R. M. Yusoff 4 , A. Nainar 5
Affiliation  

This study seeks to identify sediment sources, quantify erosion rates, and assess water quality status via sediment fingerprinting, the Modified Laser Erosion Bridge (MLEB) method, and various pollution indices (PIs), respectively, in the humid tropics (Malaysia). Geochemical elements were used as tracers in sediment fingerprinting. Erosion rates were measured at 3,241 points that encompass high conservation value forests (HCVFs); logged forests (LFs); mature oil palm (MOP); and mature rubber (MR) plantations. Annual erosion rates were 63.26–84.44, 42.38, 43.76–84.40, and 5.92–59.32 t ha−1 yr−1 in the HCVF, LF, MOP, and MR, respectively. Via sediment fingerprinting, logging and agricultural plantations were identified as the major contributors of the sediment. PIs also indicated the highest level of pollution in those catchments. This study highlighted three main messages: (i) the feasibility and applicability of the multiproxy sediment fingerprinting approach in identifying disaster-prone areas; (ii) the MLEB as a reliable and accurate method for monitoring erosion rates within forested and cultivated landscapes; and (iii) the adaptation of PIs in providing information regarding the status of river water quality without additional laboratory analyses. The combination of these approaches aids in identifying high-risk and disaster-prone areas for the prioritisation of preventive measures in the tropics.



中文翻译:

缓解洪水的泥沙线索:确定重金属污染的来源,运输和程度的关键

这项研究旨在通过湿地热带地区(马来西亚)分别通过沉积物指纹识别,改进的激光侵蚀桥(MLEB)方法和各种污染指数(PIs)来识别沉积物来源,量化侵蚀率并评估水质状况。地球化学元素被用作沉积物指纹图中的示踪剂。对侵蚀率的测量值为3,241个点,其中包括高保护价值森林(HCVF);伐木森林(LFs); 成熟油棕(MOP);和成熟的橡胶(MR)种植园。年侵蚀率分别为63.26-84.44、42.38、43.76-84.40和5.92-59.32 t ha - 1-1分别在HCVF,LF,MOP和MR中显示。通过泥沙指纹识别,伐木和农业人工林被确定为泥沙的主要贡献者。绩效指标还表明这些流域的污染程度最高。这项研究突出了三个主要信息:(i)多代理沉积物指纹识别方法在识别易受灾地区的可行性和适用性;(ii)MLEB是监测森林和耕地景观内侵蚀率的可靠而准确的方法;(iii)在不进行额外实验室分析的情况下,对PI进行调整以提供有关河流水质状况的信息。这些方法的结合有助于确定高风险和易发生灾害的地区,以便优先考虑热带地区的预防措施。

更新日期:2021-02-15
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