Dataset Information

A macromodel dns/swat dataset for the sediment yield analysis in the raba river basin (Carpathian mts.).

ABSTRACT: A database has been created as a result of the Raba River basin (Carpathian Mts., Poland) mapping/projection in the Macromodel DNS/SWAT. The sediment yield simulations (SYLD) in each of the 36 designated sub-basins have been performed, taking also into account seasonal variability. The model subsequently has been used as a reference/baseline for subsequent variant scenarios, simulating forecasted changes in the environment. The generated data ultimately allowed for creation of the current dataset. The impact of 20 variant scenarios, simulating forecasted climate and land use changes, on the sediment yield values was analyzed. The applied scenarios took into account various possibilities, from hypothetical ones, where only one parameter has been changed, to combined ones, which included simultaneous change of selected parameters. Short-term (2021-2050) and long-term (2071-2100) time horizons have also been included in this analysis. Sediment yield values and their variability, depending on the season, can be successfully used as reference values for the other mountain and sub-mountainous catchments, both in the Carpathian Mts., and throughout central Europe. Due to the permanent lack of monitoring data on the sediment yields, not only in Poland, the presented database is a valuable source of information. Moreover, spatial and temporal predictions of sediment yield changes are necessary to decide on actions which should be taken to reduce impact of climate changes at the basin scale. This data can be also used as a basis for further research related to the transport of pollutants adsorbed on sediment particles.

SUBMITTER: Orlinska-Wozniak P

PROVIDER: S-EPMC7721601 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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A macromodel dns/swat dataset for the sediment yield analysis in the raba river basin (Carpathian mts.).

Orlińska-Woźniak Paulina P Szalińska Ewa E Wilk Paweł P

Data in brief 20201123

A database has been created as a result of the Raba River basin (Carpathian Mts., Poland) mapping/projection in the Macromodel DNS/SWAT. The sediment yield simulations (SYLD) in each of the 36 designated sub-basins have been performed, taking also into account seasonal variability. The model subsequently has been used as a reference/baseline for subsequent variant scenarios, simulating forecasted changes in the environment. The generated data ultimately allowed for creation of the current datase ...[more]

PMID: 33313364

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Project description:Increasing complexity in human-environment interactions at multiple watershed scales presents major challenges to sediment source apportionment data acquisition and analysis. Herein, we present a step-change in the application of Bayesian mixing models: Deconvolutional-MixSIAR (D-MIXSIAR) to underpin sustainable management of soil and sediment. This new mixing model approach allows users to directly account for the 'structural hierarchy' of a river basin in terms of sub-watershed distribution. It works by deconvoluting apportionment data derived for multiple nodes along the stream-river network where sources are stratified by sub-watershed. Source and mixture samples were collected from two watersheds that represented (i) a longitudinal mixed agricultural watershed in the south west of England which had a distinct upper and lower zone related to topography and (ii) a distributed mixed agricultural and forested watershed in the mid-hills of Nepal with two distinct sub-watersheds. In the former, geochemical fingerprints were based upon weathering profiles and anthropogenic soil amendments. In the latter compound-specific stable isotope markers based on soil vegetation cover were applied. Mixing model posterior distributions of proportional sediment source contributions differed when sources were pooled across the watersheds (pooled-MixSIAR) compared to those where source terms were stratified by sub-watershed and the outputs deconvoluted (D-MixSIAR). In the first example, the stratified source data and the deconvolutional approach provided greater distinction between pasture and cultivated topsoil source signatures resulting in a different posterior distribution to non-deconvolutional model (conventional approaches over-estimated the contribution of cultivated land to downstream sediment by 2 to 5 times). In the second example, the deconvolutional model elucidated a large input of sediment delivered from a small tributary resulting in differences in the reported contribution of a discrete mixed forest source. Overall D-MixSIAR model posterior distributions had lower (by ca 25-50%) uncertainty and quicker model run times. In both cases, the structured, deconvoluted output cohered more closely with field observations and local knowledge underpinning the need for closer attention to hierarchy in source and mixture terms in river basin source apportionment. Soil erosion and siltation challenge the energy-food-water-environment nexus. This new tool for source apportionment offers wider application across complex environmental systems affected by natural and human-induced change and the lessons learned are relevant to source apportionment applications in other disciplines.

Dataset Information

A macromodel dns/swat dataset for the sediment yield analysis in the raba river basin (Carpathian mts.).

Publications

A macromodel dns/swat dataset for the sediment yield analysis in the raba river basin (Carpathian mts.).

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