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Reservoir sediment characterisation by diffuse reflectance spectroscopy in a semiarid region to support sediment reuse for soil fertilization

  • Purpose: Soil erosion by water yields sediment to surface reservoirs, reducing their storage capacities, changing their geometry, and degrading water quality. Sediment reuse, i.e., fertilization of agricultural soils with the nutrient-enriched sediment from reservoirs, has been proposed as a recovery strategy. However, the sediment needs to meet certain criteria. In this study, we characterize sediments from the densely dammed semiarid Northeast Brazil by VNIR-SWIR spectroscopy and assess the effect of spectral resolution and spatial scale on the accuracy of N, P, K, C, electrical conductivity, and clay prediction models. Methods Sediment was collected in 10 empty reservoirs, and physical and chemical laboratory analyses as well as spectral measurements were performed. The spectra, initially measured at 1 nm spectral resolution, were resampled to 5 and 10 nm, and samples were analysed for both high and low spectral resolution at three spatial scales, namely (1) reservoir, (2) catchment, and (3) regional scale.Purpose: Soil erosion by water yields sediment to surface reservoirs, reducing their storage capacities, changing their geometry, and degrading water quality. Sediment reuse, i.e., fertilization of agricultural soils with the nutrient-enriched sediment from reservoirs, has been proposed as a recovery strategy. However, the sediment needs to meet certain criteria. In this study, we characterize sediments from the densely dammed semiarid Northeast Brazil by VNIR-SWIR spectroscopy and assess the effect of spectral resolution and spatial scale on the accuracy of N, P, K, C, electrical conductivity, and clay prediction models. Methods Sediment was collected in 10 empty reservoirs, and physical and chemical laboratory analyses as well as spectral measurements were performed. The spectra, initially measured at 1 nm spectral resolution, were resampled to 5 and 10 nm, and samples were analysed for both high and low spectral resolution at three spatial scales, namely (1) reservoir, (2) catchment, and (3) regional scale. Results Partial least square regressions performed from good to very good in the prediction of clay and electrical conductivity from reservoir (<40 km(2)) to regional (82,500 km(2)) scales. Models for C and N performed satisfactorily at the reservoir scale, but degraded to unsatisfactory at the other scales. Models for P and K were more unstable and performed from unsatisfactorily to satisfactorily at all scales. Coarsening spectral resolution by up to 10 nm only slightly degrades the models' performance, indicating the potential of characterizing sediment from spectral data captured at lower resolutions, such as by hyperspectral satellite sensors. Conclusion: By reducing the costly and time-consuming laboratory analyses, the method helps to promote the sediment reuse as a practice of soil and water conservation.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Thayslan Carvalho, Arlena BrosinskyORCiDGND, Saskia FoersterORCiD, Adunias Teixeira, Pedro Henrique Augusto MedeirosORCiD
DOI:https://doi.org/10.1007/s11368-022-03281-1
ISSN:1439-0108
ISSN:1614-7480
Titel des übergeordneten Werks (Englisch):Journal of soils and sediments : protection, risk assessment and remediation
Verlag:Springer
Verlagsort:Heidelberg
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:03.08.2022
Erscheinungsjahr:2022
Datum der Freischaltung:13.05.2024
Freies Schlagwort / Tag:Brazil; Sediment characterization; Sediment reuse; Semiarid; Spectroscopy; Surface; reservoirs
Band:22
Seitenanzahl:21
Erste Seite:2557
Letzte Seite:2577
Fördernde Institution:Brazilian Coordination for the Improvement of Higher Education Personnel; (CAPES) [88881.371462/2019-01]; Brazilian National Council for; Scientific and Technological Development (CNPq); Project DEAL
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer Review:Referiert
Publikationsweg:Open Access / Hybrid Open-Access
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
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