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ARS Home » Plains Area » El Reno, Oklahoma » Grazinglands Research Laboratory » Agroclimate and Natural Resources Research » Research » Publications at this Location » Publication #363269

Research Project: Uncertainty of Future Water Availability Due to Climate Change and Impacts on the Long Term Sustainability and Resilience of Agricultural Lands in the Southern Great Plains

Location: Agroclimate and Natural Resources Research

Title: Using multiple composite fingerprints to quantify source contributions and uncertainties in an arid region

Author
item NIU, BAICHENG - Chinese Academy Of Sciences
item Zhang, Xunchang
item QU, JIANJUN - Chinese Academy Of Sciences
item LIU, BENLI - Chinese Academy Of Sciences
item Homan, Joel
item TAN, LIHAI - Chinese Academy Of Sciences
item AN, ZHISHAN - Chinese Academy Of Sciences

Submitted to: Journal of Soils and Sediments
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/15/2019
Publication Date: 8/16/2019
Citation: Niu, B., Zhang, X.J., Qu, J., Liu, B., Homan, J.W., Tan, L., An, Z. 2019. Using multiple composite fingerprints to quantify source contributions and uncertainties in an arid region. Journal of Soils and Sediments. 20:1097–1111. https://doi.org/10.1007/s11368-019-02424-1.
DOI: https://doi.org/10.1007/s11368-019-02424-1

Interpretive Summary: Soil erosion causes an environmental issue for farmlands with reduced nutrient-rich topsoil. Erosional conservation methods at a watershed scale require spatially distributed sediment source information. This study quantified sediment sources in the arid Danghe Reservoir watershed of northwestern China and quantified uncertainty (variance) of the estimated sediment contributions. Surface soil and sediment samples were collected, and a linear mixing model along with a multiple composite fingerprinting method was used to estimate proportions of three potential sediment sources (two alluvial fans and the high mountains.) The results showed that the method could obtain accurate estimates of the contributions with a total mean absolute relative error of 3.5%. The major contributions were consistently coming from the high mountains for all six particle groups. The overall estimated mean proportions were 48.96%, 26.48%, and 24.56% from the high mountains, south alluvial fan, and north alluvial fan, respectively. Most uncertainty or variance came from the sediment mixtures, rather than from each source, indicating that more sediment samples than source surface samples should be taken to improve the accuracy of the proportional contributions for all methods using sediment source fingerprinting technique. This finding would be useful to soil conservationists for making better conservation plans based on more accurate estimation of sediment source contributions.

Technical Abstract: Erosion causes soil or layers of soil to be redistributed and/or removed, potentially resulting in an environmental issue for farmlands with reduced nutrient-rich topsoil. Erosional conservation methods at a watershed scale require spatially distributed sediment sources information. Accordingly, this study investigated a multiple composite particle size tracking method, sediment source fingerprinting, to determine originating sources of downstream sedimentary deposits, and quantify uncertainty of the estimated contributions. The study area was the Danghe Reservoir watershed in northwest China. Data was collected from the north and south alluvial fans as well as the high mountains in the watershed. In total, 66 samples were collected from the north alluvial fan, the south alluvial fan, and the high mountains and all samples were divided into six particle size groups. Based on geochemical properties of distributed sediment samples and a linear mixing model, a multiple composite fingerprinting method with multiple particle size tracking was used to estimate proportions of three potential source contributions for a downstream sediment mixture. The uncertainty of principal sediment source contributions was quantified using the Gaussian first order approximation. The results showed that the investigated method could obtain accurate estimates of the contributions with a total mean absolute relative error of 3.47% and with a relatively narrow 95% confidence interval. The major soil erosion contributions consistently came from the high mountains for all six particle groups. The overall estimated mean proportions were 48.96%, 26.48%, and 24.56% from the high mountains, south alluvial fan, and north alluvial fan, respectively. Furthermore, the Gaussian first order approximation revealed that more than 60% of the total uncertainty contribution was a byproduct of the downstream sediment mixture, while each individual sediment source produced less than 15% of the absolute uncertainty. Acquiring watershed scale sediment source information is challenging and the investigated multiple source fingerprinting method proved accurate. A majority of the contribution uncertainties were associated with the downstream sediment mixture, which is a byproduct of the sediment sink inheriting the spatial and temporal variations of all contributing sources. Consequently, a larger sample size is needed for sediment mixtures, compared to each sediment source, in order to increase the accuracy of the source proportion estimation.