 |
| Titel |
Incorporating landscape classifications in hydrological conceptual models A case study for a central European meso-scale catchment |
| VerfasserIn |
S. Gharari, M. Hrachowitz, F. Fenicia, H. H. G. Savenije |
| Konferenz |
EGU General Assembly 2012
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250060354
|
|
|
|
|
|
| Zusammenfassung |
| Landscape classification into meaningful hydrological units has important implications for
hydrological modeling. Conceptual hydrological models, such as HBV- type models, are
most commonly designed to represent catchments in a lumped or semi-distributed way at
best, i.e. treating them as single entities or sometimes accounting for topographical and land
cover variability by introducing some level of stratification. These oversimplifications can
frequently lead to substantial misrepresentations of flow generating processes in the
catchments in question, as feedback processes between topography, land cover and
hydrology in different landscape units can arguably lead to distinct hydrological
patterns.
By making use of readily available topographical information, hydrological units can be
identified based on the concept of “Height above Nearest Drainage” (HAND; Rennó et al.,
2008; Nobre et al., 2011). These hydrological units are characterized by different
distinct hydrological behavior and can thus be assigned different model structures
(Savenije, 2010). In this study we classified the Wark Catchment in Grand Duchy of
Luxembourg which exhibits three distinct landscape units: plateau, wetland and
hillslope using a 5Ã5 m2 DEM. A revised and extended version of HAND gave
preliminary estimates of uncertainty in the landscape unit identification as they were
implemented in a stochastic framework. As the transition thresholds between the landscape
units are a priori unknown, they were calibrated against landscape units observed
in the field using a single probability based objective function. As a result, each
grid cell of the DEM was characterized by a certain probability of being a certain
landscape unit, producing maps of dominant landscape and therefore hydrological
units.
The maps of the landscape classification using HAND and slope in a probabilistic framework
were then used to determine the proportions of the three individual hydrological response
units in the catchment. The classified landscapes were used to assign different model
structures to the individual hydrological response units. As an example deep percolation was
defined as dominant process for plateaus, rapid subsurface flow as dominant process
for hillslopes and saturation overland flow as dominant process for wetlands. The
modeled runoffs from each hydrological unit were combined in a parallel set-up to
proportionally contribute to the total catchment runoff. The hydrological units are, in
addition, linked by a common groundwater reservoir. The parallel hydrological units,
although increasing the number of parameters, have the benefit of comparative
calibration. As an example, one may consider the lag time of wetland to be shorter
than the lag time of water traveling to the outlet from a plateau. Moreover, due
to the dominance of forest on hillslopes in this catchment, hillslope interception
should be higher than interception on plateaus which are mainly used for agriculture
in the Wark catchment. Furthermore fluxes and processes can be compared. For
example, actual evaporation from wetland can potentially be higher than other entities
within a catchment as wetland is water logged and evaporation thus less supply
limited than on plateaus. To include all the comparisons and criteria in calibration,
an evolutionary algorithm was used. The algorithm was adapted and applied in a
way that in subsequent steps more and more comparative criteria are forced to be
satisfied. At the end of the calibration it is expected that all the criteria should be
satisfied.
Including landscape classification into hydrological models seems to be a powerful tool
which not only allows to consider and to make use of crucial feedback processes controlling
the evolution of the hydrological system together with the eco-system but may also lead to
more detailed information on how a catchment may work than a simple lumped
model. |
|
|
|
|
|
|