The effect of spatial variability on output from the water erosion prediction project soil erosion computer model.

Persistent Link:
http://hdl.handle.net/10150/191165
Title:
The effect of spatial variability on output from the water erosion prediction project soil erosion computer model.
Author:
Parker, Ronald Dean,1948-
Issue Date:
1991
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Spatial variability is all that stands between hydrology and science, forcing us to deal in probabilities and averages. Because of scale, we can not consider forces on individual soil particles, water molecules and solute ions when addressing human size problems. We must therefore look at aggregate properties and mean values for parameters and inputs in computer modeling of hydrologic phenomena. This research explores the impact of spatially variable inputs on the Water Erosion Prediction Project soil erosion computer program. Distributions of input variables are generated and assigned randomly to a grid of homogeneous rangeland hillslope elements. Values for runoff volume and sediment loss from each flow path are recorded and averaged to provide a distribution of outputs in the form of a sensitivity analysis. Variabilities of slope, slope length, soil textures, soil characteristics, terrain, convex and concave slopes, soil saturation, rainfall amount and vegetation were examined. Results show that use of mean inputs values in the WEPP representative hillslope model yields very similar outputs to the spatially variable research model using a distribution of inputs in all simulations in the case of totally random bare rangeland soils. When a decreasing trend in soil clay content is introduced in the variable model, the hillslope model using average values as inputs no longer provides a good estimate of the sediment loss. When random vegetation is generated and added to the simulation, runoff volume continues to be similar between the two models, but the sediment loss is much higher in the spatially variable model. In addition, the results of the standard hillslope model are much less responsive to changes in slope than those of the spatially variable model. It is concluded that spatial variability of soils must be considered when there is a linear change in input values with slope position. Likewise spatial variability of vegetation needs to be addressed in order to accurately estimate erosion on the rangeland watersheds considered in this dissertation. It is also found that this type of simulation provides a model for sensitivity analysis of a complex computer programs. Physically related inputs can be generated in such a way as to preserve the desired interrationships and distributions of inputs can be directly compared to generated distributions of outputs.
Type:
Dissertation-Reproduction (electronic); text
Keywords:
Hydrology.; Watershed management.; Soil erosion.; Clay soils.
Degree Name:
Ph. D.
Degree Level:
doctoral
Degree Program:
Renewable Natural Resources; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Lane, Leonard J.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleThe effect of spatial variability on output from the water erosion prediction project soil erosion computer model.en_US
dc.creatorParker, Ronald Dean,1948-en_US
dc.contributor.authorParker, Ronald Dean,1948-en_US
dc.date.issued1991en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractSpatial variability is all that stands between hydrology and science, forcing us to deal in probabilities and averages. Because of scale, we can not consider forces on individual soil particles, water molecules and solute ions when addressing human size problems. We must therefore look at aggregate properties and mean values for parameters and inputs in computer modeling of hydrologic phenomena. This research explores the impact of spatially variable inputs on the Water Erosion Prediction Project soil erosion computer program. Distributions of input variables are generated and assigned randomly to a grid of homogeneous rangeland hillslope elements. Values for runoff volume and sediment loss from each flow path are recorded and averaged to provide a distribution of outputs in the form of a sensitivity analysis. Variabilities of slope, slope length, soil textures, soil characteristics, terrain, convex and concave slopes, soil saturation, rainfall amount and vegetation were examined. Results show that use of mean inputs values in the WEPP representative hillslope model yields very similar outputs to the spatially variable research model using a distribution of inputs in all simulations in the case of totally random bare rangeland soils. When a decreasing trend in soil clay content is introduced in the variable model, the hillslope model using average values as inputs no longer provides a good estimate of the sediment loss. When random vegetation is generated and added to the simulation, runoff volume continues to be similar between the two models, but the sediment loss is much higher in the spatially variable model. In addition, the results of the standard hillslope model are much less responsive to changes in slope than those of the spatially variable model. It is concluded that spatial variability of soils must be considered when there is a linear change in input values with slope position. Likewise spatial variability of vegetation needs to be addressed in order to accurately estimate erosion on the rangeland watersheds considered in this dissertation. It is also found that this type of simulation provides a model for sensitivity analysis of a complex computer programs. Physically related inputs can be generated in such a way as to preserve the desired interrationships and distributions of inputs can be directly compared to generated distributions of outputs.en_US
dc.description.notehydrology collectionen_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.typetexten_US
dc.subjectHydrology.en_US
dc.subjectWatershed management.en_US
dc.subjectSoil erosion.en_US
dc.subjectClay soils.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineRenewable Natural Resourcesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairLane, Leonard J.en_US
dc.contributor.committeememberFogel, Martin M.en_US
dc.contributor.committeememberHawkins, Richard H.en_US
dc.contributor.committeememberPost, Donald F.en_US
dc.contributor.committeememberHuete, Alfredo R.en_US
dc.identifier.oclc213416592en_US
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