Integrating coarse-scale uncertain soil moisture data into a fine-scale hydrological modelling scenario
In a hydrological modelling scenario, often the modeller is confronted with external data, such as remotely-sensed soil moisture observations, that become available to update the model output. However, the scale triplet (spacing, extent and support) of these data is often inconsistent with that of t...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2011-10-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | http://www.hydrol-earth-syst-sci.net/15/3101/2011/hess-15-3101-2011.pdf |
| _version_ | 1818236153609846784 |
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| author | H. Vernieuwe B. De Baets J. Minet V. R. N. Pauwels S. Lambot M. Vanclooster N. E. C. Verhoest |
| author_facet | H. Vernieuwe B. De Baets J. Minet V. R. N. Pauwels S. Lambot M. Vanclooster N. E. C. Verhoest |
| author_sort | H. Vernieuwe |
| collection | DOAJ |
| description | In a hydrological modelling scenario, often the modeller is confronted with external data, such as remotely-sensed soil moisture observations, that become available to update the model output. However, the scale triplet (spacing, extent and support) of these data is often inconsistent with that of the model. Furthermore, the external data can be cursed with epistemic uncertainty. Hence, a method is needed that not only integrates the external data into the model, but that also takes into account the difference in scale and the uncertainty of the observations. In this paper, a synthetic hydrological modelling scenario is set up in which a high-resolution distributed hydrological model is run over an agricultural field. At regular time steps, coarse-scale field-averaged soil moisture data, described by means of possibility distributions (epistemic uncertainty), are retrieved by synthetic aperture radar and assimilated into the model. A method is presented that allows to integrate the coarse-scale possibility distribution of soil moisture content data with the fine-scale model-based soil moisture data. The method is subdivided in two steps. The first step, the disaggregation step, employs a scaling relationship between field-averaged soil moisture content data and its corresponding standard deviation. In the second step, the soil moisture content values are updated using two alternative methods. |
| first_indexed | 2024-12-12T12:05:20Z |
| format | Article |
| id | doaj.art-cc221f6b2222456f8afc18e51cb00b82 |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-12-12T12:05:20Z |
| publishDate | 2011-10-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-cc221f6b2222456f8afc18e51cb00b822022-12-22T00:25:00ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382011-10-0115103101311410.5194/hess-15-3101-2011Integrating coarse-scale uncertain soil moisture data into a fine-scale hydrological modelling scenarioH. VernieuweB. De BaetsJ. MinetV. R. N. PauwelsS. LambotM. VancloosterN. E. C. VerhoestIn a hydrological modelling scenario, often the modeller is confronted with external data, such as remotely-sensed soil moisture observations, that become available to update the model output. However, the scale triplet (spacing, extent and support) of these data is often inconsistent with that of the model. Furthermore, the external data can be cursed with epistemic uncertainty. Hence, a method is needed that not only integrates the external data into the model, but that also takes into account the difference in scale and the uncertainty of the observations. In this paper, a synthetic hydrological modelling scenario is set up in which a high-resolution distributed hydrological model is run over an agricultural field. At regular time steps, coarse-scale field-averaged soil moisture data, described by means of possibility distributions (epistemic uncertainty), are retrieved by synthetic aperture radar and assimilated into the model. A method is presented that allows to integrate the coarse-scale possibility distribution of soil moisture content data with the fine-scale model-based soil moisture data. The method is subdivided in two steps. The first step, the disaggregation step, employs a scaling relationship between field-averaged soil moisture content data and its corresponding standard deviation. In the second step, the soil moisture content values are updated using two alternative methods.http://www.hydrol-earth-syst-sci.net/15/3101/2011/hess-15-3101-2011.pdf |
| spellingShingle | H. Vernieuwe B. De Baets J. Minet V. R. N. Pauwels S. Lambot M. Vanclooster N. E. C. Verhoest Integrating coarse-scale uncertain soil moisture data into a fine-scale hydrological modelling scenario Hydrology and Earth System Sciences |
| title | Integrating coarse-scale uncertain soil moisture data into a fine-scale hydrological modelling scenario |
| title_full | Integrating coarse-scale uncertain soil moisture data into a fine-scale hydrological modelling scenario |
| title_fullStr | Integrating coarse-scale uncertain soil moisture data into a fine-scale hydrological modelling scenario |
| title_full_unstemmed | Integrating coarse-scale uncertain soil moisture data into a fine-scale hydrological modelling scenario |
| title_short | Integrating coarse-scale uncertain soil moisture data into a fine-scale hydrological modelling scenario |
| title_sort | integrating coarse scale uncertain soil moisture data into a fine scale hydrological modelling scenario |
| url | http://www.hydrol-earth-syst-sci.net/15/3101/2011/hess-15-3101-2011.pdf |
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