Topographic filtering simulation model for sediment source apportionment

Cho, Se Jong; Wilcock, Peter Richard; Hobbs, Benjamin F.

doi:10.1016/j.geomorph.2018.02.014

Cited by 7 publications

(13 citation statements)

References 41 publications

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“…In the Le Sueur, for instance, we were able to combine the earlier work on sediment sources with intensive biogeochemical data collection to look at the role of sediment on phosphorus sources and transformations (Baker, ). We also focused our most intense modeling efforts in the Le Sueur (Cho et al, , ; Czuba et al, , ). Lastly, partnering with the IML‐CZO increases both the ability to compare results from the MRB with other intensively managed agricultural watersheds and the potential to link discoveries in critical zone research from the IML‐CZO field sites with the most intensive monitoring (Upper Sangamon River in Illinois and Clear Creek in Iowa) back to the MRB.…”

Section: Discussion: Opportunities Enabled By Observatory‐scale Effortsmentioning

confidence: 99%

“…MOSM simulates water and sediment routing across the watershed and incorporates different styles of management options that either reduce erosion of field and near‐channel sediment sources or reduce sediment delivery to streams. It utilizes the innovative Topofilter model (Cho et al, ) to simulate spatially variable sediment delivery ratios for field and stream components, and the detailed sediment budget described in section to provide near‐channel sediment inputs. MOSM was later coupled with an additional component that tracked development of waterfowl habitat allowing one to compare cost‐benefit tradeoffs for competing objectives (i.e., sediment reduction vs. waterfowl habitat).…”

Section: Reduced Complexity Modelingmentioning

confidence: 99%

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The Power of Environmental Observatories for Advancing Multidisciplinary Research, Outreach, and Decision Support: The Case of the Minnesota River Basin

Gran

Dolph

Baker

et al. 2019

Water Resources Research

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Observatory‐scale data collection efforts allow unprecedented opportunities for integrative, multidisciplinary investigations in large, complex watersheds, which can affect management decisions and policy. Through the National Science Foundation‐funded REACH (REsilience under Accelerated CHange) project, in collaboration with the Intensively Managed Landscapes‐Critical Zone Observatory, we have collected a series of multidisciplinary data sets throughout the Minnesota River Basin in south‐central Minnesota, USA, a 43,400‐km2 tributary to the Upper Mississippi River. Postglacial incision within the Minnesota River valley created an erosional landscape highly responsive to hydrologic change, allowing for transdisciplinary research into the complex cascade of environmental changes that occur due to hydrology and land use alterations from intensive agricultural management and climate change. Data sets collected include water chemistry and biogeochemical data, geochemical fingerprinting of major sediment sources, high‐resolution monitoring of river bluff erosion, and repeat channel cross‐sectional and bathymetry data following major floods. The data collection efforts led to development of a series of integrative reduced complexity models that provide deeper insight into how water, sediment, and nutrients route and transform through a large channel network and respond to change. These models represent the culmination of efforts to integrate interdisciplinary data sets and science to gain new insights into watershed‐scale processes in order to advance management and decision making. The purpose of this paper is to present a synthesis of the data sets and models, disseminate them to the community for further research, and identify mechanisms used to expand the temporal and spatial extent of short‐term observatory‐scale data collection efforts.

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Section: Discussion: Opportunities Enabled By Observatory‐scale Effortsmentioning

confidence: 99%

Section: Reduced Complexity Modelingmentioning

confidence: 99%

The Power of Environmental Observatories for Advancing Multidisciplinary Research, Outreach, and Decision Support: The Case of the Minnesota River Basin

Gran

Dolph

Baker

et al. 2019

Water Resources Research

Self Cite

View full text Add to dashboard Cite

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“…Only a fraction of field or bluff sediment delivered to the streams actually makes it all the way to the watershed outlet. To address this sediment delivery problem (De Vente et al, ; Walling, ), we developed an approach that uses high‐resolution topography to link sediment sources to the sediment loads measured at stream gages (Cho et al, ).…”

Section: Context For the Modelmentioning

confidence: 99%

“…MOSM uses the sediment delivery conceptual model to link sediment sources to delivery at the watershed outlet. SDR for each of the 529 SEDSBs is developed from the Topographic Filtering simulation model (Topofilter; Cho et al, ), which links field and near‐channel sediment production rates to annual sediment loading measured at multiple gages throughout the watershed using sediment transfer functions to account for the effects of the watershed topography on sediment delivery and storage.…”

Section: Mosmmentioning

confidence: 99%

“…To do this, we built a modeling framework on a sediment budget in which the magnitude of the total sediment load and of individual sources were well constrained by multiple lines of independent evidence (Belmont et al, ; Gran et al, ). We use a novel topographic filtering model to link distributed sediment sources to the measured annual sediment load at the watershed outlet via spatially distributed values of sediment delivery ratio (SDR; Cho et al, ). The modeling framework incorporates conservation actions through their effect on either sediment production or sediment delivery.…”

Section: Introductionmentioning

confidence: 99%

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Simulation Model for Collaborative Decision Making on Sediment Source Reduction in an Intensively Managed Watershed

Cho

Wilcock

Belmont

et al. 2019

Water Resources Research

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We developed a watershed sediment source and delivery model for use in evaluating conservation trade-offs in southern Minnesota, where sediment loading has been identified as a priority and there is substantial public investment in cleaner water. The model was developed in a stakeholder process and links user-specified management options to reductions in sediment loading at the outlet of a 2,880-km 2 intensively farmed watershed. The simulation model was formulated to allocate total sediment load among sources, which provides robustness to the model by constraining the relative magnitude of sediment loads and their reduction. A novel topographic filtering approach was used to develop spatially distributed maps of sediment delivery ratio, addressing the problem of storage between source and outlet. The dominant sediment source in the watershed is erosion of steep streamside bluffs in response to increases in river discharge. Rates of bluff erosion as a function of river discharge were determined from sediment loads measured at pairs of gages on individual streams. Using this analysis, upland water storage to reduce peak river flow was included as an option in the model. The model development process was designed to promote transparency and develop stakeholder trust through multiple meetings in which an underlying sediment budget was developed and refined. The model runs rapidly, providing real-time response to user choice and supporting Monte Carlo simulation of the influence of uncertainty on the calculated sediment load. The stakeholder group used the model to identify a priority strategy for investing public funds to improve water quality.Plain Language Summary Water pollution from excess sediment poses serious threats to the livelihood of aquatic ecosystem as well as recreation. We present a watershed model, developed through a collaboration with local stakeholders, that evaluates different conservation scenarios to reduce sediment source and delivery. The model is used to bring consensus among stakeholders in identifying a priority strategy for investing public funds to improve water quality.

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A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments

et al. 2021

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The impact of climate change on future soil loss is commonly assessed with soil erosion models, which are suggested to be an important source of uncertainty. Here, we present a novel soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments. The model ensemble consists of five continuous process‐based soil erosion models that run at a daily time step (i.e., DHSVM, HSPF, INCA, MMF, SHETRAN). The models were implemented in the SPHY hydrological model and simulate detachment by raindrop impact, detachment by runoff, and immediate deposition. The soil erosion model ensemble was applied in a semiarid catchment in the southeast of Spain. We applied three future climate scenarios based on global mean temperature rise (+1.5, +2 and +3°C). Data from two contrasting regional climate models were used to assess how an increase and a decrease in projected extreme precipitation affect model uncertainty. Soil loss is projected to increase (up to 95%) and decrease (up to −30%) under climate change, mostly reflecting the change in extreme precipitation. Model uncertainty is found to increase with increasing slope, extreme precipitation and runoff, which reveals some inherent differences in model assumptions among the five models. Moreover, the model uncertainty increases in all climate change scenarios, independent of the projected change in annual precipitation and extreme precipitation. This stresses the importance to consider model uncertainty through model ensembles of climate, hydrology, and soil erosion in climate‐change impact assessments.

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Topographic filtering simulation model for sediment source apportionment

Cited by 7 publications

References 41 publications

The Power of Environmental Observatories for Advancing Multidisciplinary Research, Outreach, and Decision Support: The Case of the Minnesota River Basin

The Power of Environmental Observatories for Advancing Multidisciplinary Research, Outreach, and Decision Support: The Case of the Minnesota River Basin

Simulation Model for Collaborative Decision Making on Sediment Source Reduction in an Intensively Managed Watershed

A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments

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