Dissecting the effect of rainfall variability on the statistical structure of peak flows
This study examines the role of rainfall variability on the spatial scaling structure of peak flows using the Whitewater River basin in Kansas as an illustration. Specifically, we investigate the effect of rainfall on the scatter, the scale break and the power law (peak flows vs. upstream areas) reg...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Language: | English |
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2012
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| Online Access: | https://hdl.handle.net/10356/95606 http://hdl.handle.net/10220/8336 |
| _version_ | 1811690307348070400 |
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| author | Mandapaka, Pradeep V. Krajewski, Witold F. Gupta, Vijay K. Mantilla, Ricardo. |
| author_facet | Mandapaka, Pradeep V. Krajewski, Witold F. Gupta, Vijay K. Mantilla, Ricardo. |
| author_sort | Mandapaka, Pradeep V. |
| collection | NTU |
| description | This study examines the role of rainfall variability on the spatial scaling structure of peak flows using the Whitewater River basin in Kansas as an illustration. Specifically, we investigate the effect of rainfall on the scatter, the scale break and the power law (peak flows vs. upstream areas) regression exponent. We illustrate why considering individual hydrographs at the outlet of a basin can lead to misleading
interpretations of the effects of rainfall variability. We begin with the simple scenario of a basin receiving spatially uniform rainfall of varying intensities and durations and subsequently investigate the role of storm advection velocity, storm variability characterized by variance, spatial correlation and intermittency. Finally, we use a realistic space–time rainfall field obtained from a popular rainfall model that combines the aforementioned features. For each of these scenarios, we employ a recent formulation of flow velocity for a network of channels, assume idealized conditions of runoff generation and flow dynamics and calculate peak flow scaling exponents, which are then compared to the scaling exponent of the width function maxima. Our results show that the peak flow scaling exponent is always larger than the width function scaling exponent. The simulation scenarios are used to identify the smaller scale basins, whose response is dominated by the rainfall variability and the larger scale basins, which are driven
by rainfall volume, river network aggregation and flow dynamics. The rainfall variability has a greater impact on peak flows at smaller scales. The effect of rainfall variability is reduced for larger scale basins as the river network aggregates and smoothes out the storm variability. The results obtained from simple scenarios are used to make rigorous interpretations of the peak flow scaling structure that is obtained from rainfall generated with the space–time rainfall model and realistic rainfall fields derived from NEXRAD radar data. |
| first_indexed | 2024-10-01T06:01:55Z |
| format | Journal Article |
| id | ntu-10356/95606 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:01:55Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | ntu-10356/956062020-09-26T21:32:18Z Dissecting the effect of rainfall variability on the statistical structure of peak flows Mandapaka, Pradeep V. Krajewski, Witold F. Gupta, Vijay K. Mantilla, Ricardo. DRNTU::Engineering::Civil engineering::Water resources This study examines the role of rainfall variability on the spatial scaling structure of peak flows using the Whitewater River basin in Kansas as an illustration. Specifically, we investigate the effect of rainfall on the scatter, the scale break and the power law (peak flows vs. upstream areas) regression exponent. We illustrate why considering individual hydrographs at the outlet of a basin can lead to misleading interpretations of the effects of rainfall variability. We begin with the simple scenario of a basin receiving spatially uniform rainfall of varying intensities and durations and subsequently investigate the role of storm advection velocity, storm variability characterized by variance, spatial correlation and intermittency. Finally, we use a realistic space–time rainfall field obtained from a popular rainfall model that combines the aforementioned features. For each of these scenarios, we employ a recent formulation of flow velocity for a network of channels, assume idealized conditions of runoff generation and flow dynamics and calculate peak flow scaling exponents, which are then compared to the scaling exponent of the width function maxima. Our results show that the peak flow scaling exponent is always larger than the width function scaling exponent. The simulation scenarios are used to identify the smaller scale basins, whose response is dominated by the rainfall variability and the larger scale basins, which are driven by rainfall volume, river network aggregation and flow dynamics. The rainfall variability has a greater impact on peak flows at smaller scales. The effect of rainfall variability is reduced for larger scale basins as the river network aggregates and smoothes out the storm variability. The results obtained from simple scenarios are used to make rigorous interpretations of the peak flow scaling structure that is obtained from rainfall generated with the space–time rainfall model and realistic rainfall fields derived from NEXRAD radar data. Accepted version 2012-07-23T04:03:34Z 2019-12-06T19:18:11Z 2012-07-23T04:03:34Z 2019-12-06T19:18:11Z 2009 2009 Journal Article Mandapaka, P. V., Krajewski, W. F., Mantilla, R., & Gupta, V. K. (2009). Dissecting the Effect of Rainfall Variability on the Statistical Structure of Peak Flows. Advances in Water Resources, 32(10), 1508–1525. https://hdl.handle.net/10356/95606 http://hdl.handle.net/10220/8336 10.1016/j.advwatres.2009.07.005 en Advances in water resources © 2009 Elsevier. This is the author created version of a work that has been peer reviewed and accepted for publication by Advances in Water Resources, Elsevier. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: DOI[http://dx.doi.org/10.1016/j.advwatres.2009.07.005]. application/pdf |
| spellingShingle | DRNTU::Engineering::Civil engineering::Water resources Mandapaka, Pradeep V. Krajewski, Witold F. Gupta, Vijay K. Mantilla, Ricardo. Dissecting the effect of rainfall variability on the statistical structure of peak flows |
| title | Dissecting the effect of rainfall variability on the statistical structure of peak flows |
| title_full | Dissecting the effect of rainfall variability on the statistical structure of peak flows |
| title_fullStr | Dissecting the effect of rainfall variability on the statistical structure of peak flows |
| title_full_unstemmed | Dissecting the effect of rainfall variability on the statistical structure of peak flows |
| title_short | Dissecting the effect of rainfall variability on the statistical structure of peak flows |
| title_sort | dissecting the effect of rainfall variability on the statistical structure of peak flows |
| topic | DRNTU::Engineering::Civil engineering::Water resources |
| url | https://hdl.handle.net/10356/95606 http://hdl.handle.net/10220/8336 |
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