Regionalizing nonparametric models of precipitation amounts on different temporal scales
Parametric distribution functions are commonly used to model precipitation amounts corresponding to different durations. The precipitation amounts themselves are crucial for stochastic rainfall generators and weather generators. Nonparametric kernel density estimates (KDEs) offer a more flexible way...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2017-05-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | http://www.hydrol-earth-syst-sci.net/21/2463/2017/hess-21-2463-2017.pdf |
| _version_ | 1811265338542653440 |
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| author | T. Mosthaf A. Bárdossy |
| author_facet | T. Mosthaf A. Bárdossy |
| author_sort | T. Mosthaf |
| collection | DOAJ |
| description | Parametric distribution functions are commonly used to model precipitation
amounts corresponding to different durations. The precipitation amounts
themselves are crucial for stochastic rainfall generators and weather
generators. Nonparametric kernel density estimates (KDEs) offer a more
flexible way to model precipitation amounts. As already stated in their name,
these models do not exhibit parameters that can be easily regionalized to run
rainfall generators at ungauged locations as well as at gauged locations. To
overcome this deficiency, we present a new interpolation scheme for
nonparametric models and evaluate it for different temporal resolutions
ranging from hourly to monthly. During the evaluation, the nonparametric
methods are compared to commonly used parametric models like the
two-parameter gamma and the mixed-exponential distribution. As water volume
is considered to be an essential parameter for applications like flood
modeling, a Lorenz-curve-based criterion is also introduced. To add value to
the estimation of data at sub-daily resolutions, we incorporated the
plentiful daily measurements in the interpolation scheme, and this idea was
evaluated. The study region is the federal state of Baden-Württemberg in
the southwest of Germany with more than 500 rain gauges. The validation
results show that the newly proposed nonparametric interpolation scheme
provides reasonable results and that the incorporation of daily values in the
regionalization of sub-daily models is very beneficial. |
| first_indexed | 2024-04-12T20:21:51Z |
| format | Article |
| id | doaj.art-bb5e443579a946a199ef8c1d3a3512d5 |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-04-12T20:21:51Z |
| publishDate | 2017-05-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-bb5e443579a946a199ef8c1d3a3512d52022-12-22T03:17:59ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382017-05-012152463248110.5194/hess-21-2463-2017Regionalizing nonparametric models of precipitation amounts on different temporal scalesT. Mosthaf0A. Bárdossy1Institute for Modeling Hydraulic and Environmental Systems, Universität Stuttgart, Stuttgart, GermanyInstitute for Modeling Hydraulic and Environmental Systems, Universität Stuttgart, Stuttgart, GermanyParametric distribution functions are commonly used to model precipitation amounts corresponding to different durations. The precipitation amounts themselves are crucial for stochastic rainfall generators and weather generators. Nonparametric kernel density estimates (KDEs) offer a more flexible way to model precipitation amounts. As already stated in their name, these models do not exhibit parameters that can be easily regionalized to run rainfall generators at ungauged locations as well as at gauged locations. To overcome this deficiency, we present a new interpolation scheme for nonparametric models and evaluate it for different temporal resolutions ranging from hourly to monthly. During the evaluation, the nonparametric methods are compared to commonly used parametric models like the two-parameter gamma and the mixed-exponential distribution. As water volume is considered to be an essential parameter for applications like flood modeling, a Lorenz-curve-based criterion is also introduced. To add value to the estimation of data at sub-daily resolutions, we incorporated the plentiful daily measurements in the interpolation scheme, and this idea was evaluated. The study region is the federal state of Baden-Württemberg in the southwest of Germany with more than 500 rain gauges. The validation results show that the newly proposed nonparametric interpolation scheme provides reasonable results and that the incorporation of daily values in the regionalization of sub-daily models is very beneficial.http://www.hydrol-earth-syst-sci.net/21/2463/2017/hess-21-2463-2017.pdf |
| spellingShingle | T. Mosthaf A. Bárdossy Regionalizing nonparametric models of precipitation amounts on different temporal scales Hydrology and Earth System Sciences |
| title | Regionalizing nonparametric models of precipitation amounts on different temporal scales |
| title_full | Regionalizing nonparametric models of precipitation amounts on different temporal scales |
| title_fullStr | Regionalizing nonparametric models of precipitation amounts on different temporal scales |
| title_full_unstemmed | Regionalizing nonparametric models of precipitation amounts on different temporal scales |
| title_short | Regionalizing nonparametric models of precipitation amounts on different temporal scales |
| title_sort | regionalizing nonparametric models of precipitation amounts on different temporal scales |
| url | http://www.hydrol-earth-syst-sci.net/21/2463/2017/hess-21-2463-2017.pdf |
| work_keys_str_mv | AT tmosthaf regionalizingnonparametricmodelsofprecipitationamountsondifferenttemporalscales AT abardossy regionalizingnonparametricmodelsofprecipitationamountsondifferenttemporalscales |