Fingerprinting the spatial sources of fine-grained sediment deposited in the bed of the Mehran River, southern Iran

Assessment of soil erosion in the Upper Citarum watershed for sustainability of the Saguling reservoir: unmixing model approach

The Citarum watershed and the Saguling reservoir are vital natural resources in Indonesia, affecting the livelihood of West Java and the DKI Jakarta population. This study aimed to assess the soil erosion in the Upper Citarum watershed and identify its source. The study used the fallout radionuclide technique, geochemical tracers, and an unmixing model to measure soil erosion and the contribution of suspended sediment sources due to erosion. Soil bulk transects and surface soil were sampled using a coring tool on the Ciwidey and Cisangkuy sub-watersheds. Riverbank and suspended sediment samples were collected from tributaries and rivers. With 137Cs, 40% of the samples had values below the minimum detectable activity, and vice versa for 210Pbex, all samples are detectable. For mitigation, bare land needs to be recovered due to its erosion (25.6 t ha-1 year-1) exceeding the tolerance erosion value (17 t ha-1 year-1). Statistically, Mg and Na were the most appropriate composite tracers for suspended sediment contribution. The unmixing model predicted the sediment contributors from bare land (58%), the riverbank (32.7%), and plantation land (9.3%). Proper land conservation could reduce sediment supply by almost 14.7% and extend the reservoir's life. This is the first study to report the feasibility of the unmixing model in Indonesia.

The spatio-temporal dynamics of suspended sediment sources based on a novel indexing approach combining Bayesian geochemical fingerprinting with physically-based modelling

Applications of sediment source fingerprinting continue to increase globally as the need for information to support improved management of the sediment problem persists. In our novel research, a Bayesian fingerprinting approach using MixSIAR was used with geochemical signatures, both without and with informative priors based on particle size and slope. The source estimates were compared with a newly proposed Source Sensitivity Index (SSI) and outputs from the INVEST-SDR model. MixSIAR results with informative priors indicated that agricultural and barren lands are the principal sediment sources (contributing ∼5-85% and ∼5-80% respectively during two sampling periods i.e. 2018-2019 and 2021-2022) with forests being less important. The SSI spatial maps (using % clay and slope as informative priors) showed >78% agreement with the spatial map derived using the INVEST-SDR model in terms of sub-catchment prioritization for spatial sediment source contributions. This study demonstrates the benefits of combining geochemical sediment source fingerprinting with SSI indices in larger catchments where the spatial prioritization of soil and water conservation is both challenging but warranted.