Calibration of Erosion Models

Jetten, Victor; Maneta, Marco P.

doi:10.1002/9781444328455.ch3

Cited by 6 publications

(7 citation statements)

References 79 publications

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“…Moreover, the results were obtained for reference data measured bi‐weekly during relatively long calibration and validation periods. Jetten & Maneta (2011) also note that ‘while calibration fortunately is often done at least in scientific literature, independent validation is far less common’.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, the results were obtained for reference data measured bi-weekly during relatively long calibration and validation periods. Jetten & Maneta (2011) also note that 'while calibration fortunately is often done at least in scientific literature, independent validation is far less common'. Limbrunner (2008), for example, used monthly data on sediment loads for adapting a lumped parameter watershed (2008) Jarritt & Lawrence (2006) calibrated the INCA-SED model for the Enborne and Lambourn catchments and obtained N-S values of 0.32 and 0.36 for SSs, respectively.…”

Section: Discussionmentioning

confidence: 99%

“…It is well known that extreme events are always difficult to model. The GCTE Soil Erosion Network tested the fitness of erosion models to predict the consequences of climate change for erosion using an ensemble modelling approach (Jetten & Maneta, 2011). Their results show that 'many models have problems with prediction of extreme events'.…”

Section: Discussionmentioning

confidence: 99%

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Soil erosion and phosphorus losses under variable land use as simulated by the INCA‐P model

Farkas

Beldring

Bechmann

et al. 2013

Soil Use and Management

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We describe the calibration and application of the Integrated Catchment Phosphorus model (INCA-P) to determine the key factors controlling run-off, sediment and phosphorus (P) losses from a small catchment in southeast Norway. The INCA-P model was parameterized for five land use categories: forest, grassland, urban areas and agricultural areas with and without autumn tillage. Monitoring data from the Norwegian Agricultural Environmental Monitoring Program were used for model calibration at the outlet of the catchment (Skuterud). Available measurements and local expert knowledge were used as reference data on sediment and P loss specific to land uses. We successfully applied the INCA-P model to Nordic conditions: the Nash-Sutcliffe (N-S) statistic, calculated for the calibration period, was 0.82, 0.71 and 0.67 for run-off, sediment and P losses, respectively. For the validation period, the sediment and P losses were slightly overestimated. Scatter plots of observed versus modelled values of run-off, sediment and total P losses indicated that in some cases, the INCA-P model did not adequately represent extreme situations. It is likely that the modelled system behaves in a different way under moderate and large rainfall events, and the model does not represent these. We applied the model to five land use change scenarios to evaluate the possibilities for reducing particle-bound P loads at the catchment outlet. Our results indicate that land use change can lead to more significant reduction in particle and P losses than changes in agricultural practices. The most favourable scenario for freshwater ecosystems would be afforestation: changing half of the agricultural areas to forest would reduce sediment and P losses by 44 and 40%, respectively. Changes in agricultural practice could also improve the situation, especially by reducing areas with autumn tillage to a minimum.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Soil erosion and phosphorus losses under variable land use as simulated by the INCA‐P model

Farkas

Beldring

Bechmann

et al. 2013

Soil Use and Management

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“…It also requires a choice of the model output to be calibrated (e.g., run‐off, phreatic level, sediment concentration, discharge peaks, and sediment flux peaks). Furthermore, multiple different combinations of parameter values might give a good fit (Beven & Binley, ; Jetten & Maneta, ). The decision on parameters to be calibrated depends on information about previous applications (i.e., sensitivity analysis) and/or user experience.…”

Section: Methodsmentioning

confidence: 99%

Assessing the performance of a physically based hydrological model using a proxy‐catchment approach in an agricultural environment

Escobar‐Ruiz

Smith

Blake

et al. 2019

Hydrological Processes

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Physically based models are useful frameworks for testing intervention strategies designed to reduce elevated sediment loads in agricultural catchments. Evaluating the success of these strategies depends on model accuracy, generally established by a calibration and evaluation process. In this contribution, the physically based SHETRAN model was assessed in two similar U.K. agricultural catchments. The model was calibrated on the Blackwater catchment (18 km 2 ) and evaluated in the adjacent Kit Brook catchment (22 km 2 ) using 4 years of 15 min discharge and suspended sediment flux data. Model sensitivity to changes in single and multiple combinations of parameters and sensitivity to changes in digital elevation model resolution were assessed. Model flow performance was reasonably accurate with a Nash-Sutcliffe efficiency coefficient of 0.78 in Blackwater and 0.60 in Kit Brook. In terms of event prediction, the mean of the absolute percentage of difference (μAbs diff ) between measured and simulated flow volume (Qv), peak discharge (Qp), sediment yield (Sy), and peak sediment flux (Sp) showed larger values in Kit Brook (48% [Qv], 66% [Qp], 298% [Sy], and 438% [Sp]) compared with the Blackwater catchment (30% [Qv], 41% [Qp], 106% [Sy], and 86% [Sp]). Results indicate that SHETRAN can produce reasonable flow prediction but performs less well in estimation of sediment flux, despite reasonably similar hydrosedimentary behaviour between catchments. The sensitivity index showed flow volume sensitive to saturated hydraulic conductivity and peak discharge to the Strickler coefficient; sediment yield was sensitive to the overland flow erodibility coefficient and peak sediment flux to raindrop/leaf soil erodibility coefficient. The multiparameter sensitivity analysis showed that different combinations of parameters produced similar model responses. Model sensitivity to grid resolution presented similar flow volumes for different digital elevation model resolutions, whereas event peak and duration (for both flow and sediment flux) were highly sensitive to changes in grid size. K E Y W O R D S catchment modelling, model sensitivity, proxy catchment, sediment yield, SHETRAN

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“…While several well-established soil erosion prediction models are available for watersheds (e.g., Soil and Water Assessment Tool (SWAT; [35]), Water Erosion Prediction Project (WEPP; [36]), GeoWEPP (the Geospatial Interface for the process-based soil erosion prediction model WEPP; [37]), the Agricultural Non-Point Source Model (AGNPS; [38]), Sealing and Transfer by Runoff and Erosion related to Agricultural Management (STREAM; [39]), Erosion-3D [40], Limburg Soil Erosion Model (LISEM; [41]), sediment connectivity is still often not described sufficiently, especially in the underlying hydrological catchment models [42,43]. A number of approaches have been used to model sediment delivery to watercourses (e.g., [44][45][46][47][48][49]; for an overview see [20]). Although much progress has been made over the last two decades, available approaches to model lateral fine sediment connectivity in catchment systems often still do not yield satisfactory results [50,51]; a recent review on indices of sediment connectivity can be found in Heckmann et al [52]).…”

Section: Introductionmentioning

confidence: 99%

Combining Soil Erosion Modeling with Connectivity Analyses to Assess Lateral Fine Sediment Input into Agricultural Streams

Pöppl

Dilly

Haselberger

et al. 2019

Water

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Soil erosion causes severe on- and off-site effects, including loss of organic matter, reductions in soil depth, sedimentation of reservoirs, eutrophication of water bodies, and clogging and smothering of spawning habitats. The involved sediment source-mobilization-delivery process is complex in space and time, depending on a multiplicity of factors that determine lateral sediment connectivity in catchment systems. Shortcomings of soil erosion models and connectivity approaches call for methodical improvement when it comes to assess lateral sediment connectivity in agricultural catchments. This study aims to (i) apply and evaluate different approaches, i.e., Index of Connectivity (IC), the Geospatial Interface for Water Erosion Prediction Project (GeoWEPP) soil erosion model, field mapping and (ii) test a connectivity-adapted version of GeoWEPP (i.e., “GeoWEPP-C”) in the context of detecting hot-spots for soil erosion and lateral fine sediment entry points to the drainage network in a medium-sized (138 km2) agricultural catchment in Austria, further discussing their applicability in sediment management in agricultural catchments. The results revealed that (a) GeoWEPP is able to detect sub-catchments with high amount of soil erosion/sediment yield that represent manageable units in the context of soil erosion research and catchment management; (b) the combination of GeoWEPP modeling and field-based connectivity mapping is suitable for the delineation of lateral (i.e., field to stream) fine sediment connectivity hotspots; (c) the IC is a useful tool for a rapid Geographic Information System (GIS)-based assessment of structural connectivity. However, the IC showed significant limitations for agricultural catchments and functional aspects of connectivity; (d) the process-based GeoWEPP-C model can be seen as a methodical improvement when it comes to the assessment of lateral sediment connectivity in agricultural catchments.

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Calibration of Erosion Models

Cited by 6 publications

References 79 publications

Soil erosion and phosphorus losses under variable land use as simulated by the INCA‐P model

Soil erosion and phosphorus losses under variable land use as simulated by the INCA‐P model

Assessing the performance of a physically based hydrological model using a proxy‐catchment approach in an agricultural environment

Combining Soil Erosion Modeling with Connectivity Analyses to Assess Lateral Fine Sediment Input into Agricultural Streams

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