Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Qualifizierungsarbeiten |
| URL | http://elib.uni-stuttgart.de/opus/volltexte/2003/1437/ |
| Titel (primär) | Hydrological consequences of land use / Land cover and climatic changes in mesoscale catchments |
| Autor | Samaniego, L.
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| Quelle | Mitteilungen / Institut für Wasser- und Umweltsystemmodellierung |
| Erscheinungsjahr | 2003 |
| Department | CHS |
| Heft | 118 |
| Seite bis | 179 |
| Sprache | englisch |
| Keywords | Land use/cover; Monte-Carlo-Simulation; Non-parametric-tests; Robust-estimators; Runoff-modelling; Landnutzung; Statistik; Abfluss; Hydrologie |
| Abstract | Many hydrologic studies reported in the literature indicate that observed changes of various characteristics of the water cycle largely depend on the geographic location and the scale at which such a study is carried out. In general, the water cycle of a given basin may be modified due to climatic and/or land use/cover changes. Identifying, however, the causes of the observed variability at the mesoscale is a challenging task because of the lack of data describing the spatial distribution of relevant explanatory variables and the unknown spatial heterogeneity of parameter values. This study proposes a general method that attempts to split the observed variability of a given characteristic of a basin's runoff along the time axis into two independent components, one that is only explained by climatic fluctuations, and a second one that is exclusively explained by land cover changes. The proposed algorithm works as follows. Given a set of explanatory variables, it initially calibrates and assesses the goodness of the fit of as many non-linear models as feasible combinations of these variables exist, then, it estimates the robustness of every model using a cross-validation technique, and finally, it assesses the statistical significance of each explanatory variable employing a permutation test. The optimisation of the parameters of each model is carried out by a generalized reduced gradient algorithm. Finally, the algorithm selects the most robust model as that which best accomplishes simultaneously the following criteria: 1) it should have the least number of variables but explain as much as possible the variance of the sample; 2) it should be robust to outliers (i.e. the minimum cross-validation statistic); and 3) all its variables should be significant at 5% level. Lastly, those hydrological models calibrated for a given set of runoff characteristics were linked with a stochastic land use/cover change model in order to simulate the effects of the hydrological consequences of land use/cover and climatic changes in a mesoscale catchment. The magnitude of these effects was assessed in a probabilistic way by a sequential Monte-Carlo simulation provided four different scenarios which take into account likely developments of macro-climatic and socio-economic conditions relevant for a given study area. The proposed methodology was developed and tested in the upper catchment of the Neckar River covering an area of about 4000 km2; however, its application in other catchments is possible. |
| dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=5174 |
| Samaniego, L. (2003): Hydrological consequences of land use / Land cover and climatic changes in mesoscale catchments Dissertation, Universität Stuttgart Mitteilungen / Institut für Wasser- und Umweltsystemmodellierung Universität Stuttgart, Stuttgart, 179 pp. |
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