Comparative study using spectroscopic and mineralogical fingerprinting for suspended sediment source apportionment in a river–reservoir system

IF 2.8 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL
Arnab Das, Renji Remesan, Somsubhra Chakraborty, Adrian L. Collins, Ashok Kumar Gupta
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Abstract

The need to control soil erosion has received increasing attention, but quantitative data on the sources of suspended sediment in many river–reservoir systems is still lacking. The goal of this research was to compare the application of spectroscopic [mid-infrared (MIR)] and mineralogical [X-ray diffraction (XRD)] fingerprints for assessing relative sediment source contributions from different land use groups (agricultural lands, forests and human settlements) in the Konar–Damodar river–reservoir system in India. Source apportionment was estimated using partial least square (PLS) regression for spectroscopic tracers (MIR) and the Bayesian MixSIAR model for mineralogical tracers. Both methods identified differences between the pre- and post-monsoon sediment contributions of forests (overall contribution bounds of ~35–43%). During monsoon seasons, both fingerprinting methods indicated agricultural land use as the primary source of suspended sediment. Although there were some temporal variations in the predicted contributions of the land use sources, the MIR-PLS and mineralogical–MixSIAR methods produced comparable ranges. The respective variations in contributions, using MIR-PLS and mineralogical–MixSIAR, were ~31 to 66% compared with ~36 to 61% for agricultural lands, ~21 to 43% compared with ~15 to 39% for forests and ~16 to 37% compared with ~19 to 32% for human settlements.

Abstract Image

利用光谱学和矿物学指纹分析法对河流-水库系统中的悬浮泥沙来源进行比较研究
控制水土流失的必要性已受到越来越多的关注,但在许多河流水库系统中,仍然缺乏有关悬浮泥沙来源的定量数据。本研究旨在比较光谱[中红外(MIR)]和矿物学[X 射线衍射(XRD)]指纹的应用,以评估印度科纳尔-达莫达河流-水库系统中不同土地利用群体(农田、森林和人类居住区)的相对沉积物来源。对光谱示踪剂(MIR)采用偏最小二乘法(PLS)回归,对矿物学示踪剂采用贝叶斯混合示踪剂模型(MixSIAR)估算来源分配。这两种方法都确定了季风前和季风后森林沉积物贡献率之间的差异(总体贡献率范围约为 35-43%)。在季风季节,两种指纹识别方法都表明农业用地是悬浮沉积物的主要来源。虽然土地利用源的预测贡献率在时间上存在一些差异,但 MIR-PLS 和矿物学-MixSIAR 方法得出的贡献率范围相当。使用 MIR-PLS 和矿物学-MixSIAR,农业用地的贡献率分别为 ~31% 至 66%,而矿物学-MixSIAR 为 ~36% 至 61%;森林的贡献率为 ~21% 至 43%,而矿物学-MixSIAR 为 ~15% 至 39%;人类住区的贡献率为 ~16% 至 37%,而矿物学-MixSIAR 为 ~19% 至 32%。
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来源期刊
Earth Surface Processes and Landforms
Earth Surface Processes and Landforms 地学-地球科学综合
CiteScore
6.40
自引率
12.10%
发文量
215
审稿时长
4 months
期刊介绍: Earth Surface Processes and Landforms is an interdisciplinary international journal concerned with: the interactions between surface processes and landforms and landscapes; that lead to physical, chemical and biological changes; and which in turn create; current landscapes and the geological record of past landscapes. Its focus is core to both physical geographical and geological communities, and also the wider geosciences
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