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Interception measurements and assessment of Gash model performance for a tropical semi-arid region
(2009)
Semi-arid environments usually face water scarcity and conflicts for its use; therefore a complete understanding of the water balance in these regions is desired. To evaluate interception, measurements of precipitation, throughfall and stemflow were carried out in a Brazilian tropical semi-arid experimental watershed with well preserved Caatinga vegetation. Data analysis indicates that interception losses correspond to 13% of total rainfall, representing an important process in the watershed's water balance, where runoff is only 6% of total precipitation. Gash interception model was applied in the region with good results for long term simulation. Nevertheless, the model produced significant but not systematic errors on a daily basis. This was attributed to its incapability of representing the temporal variation of precipitation during the event, which is a major factor affecting interception. Rainfall intensity was shown to be a good parameter to determine an applicability threshold for Gash model in the study area.
The hydrological cycle is a dynamic system by its nature, but sometimes accelerated through anthropogenic activity. A "hydrological change" (i.e. a water cycle that is significantly changing over a longer period of time) can be very different in character, depending on the specific natural conditions and the underlying spatial and temporal scales. Such changes may affect the availability and quality of water as essential pre-requisites for human development and ecosystem stability. Hydrological extremes, such as floods and droughts, may also be affected, what is also vitally important, because of their profound economic and societal impacts. Anthropogenically induced hydrological change can be attributed to three main external causes: first, the Earth's climate is changing significantly and thus directly affecting the terrestrial hydro-systems via the exchange of energy and heat. The second major issue is the land cover and its management that has been modified fundamentally by conversion of land for agriculture, forestry, and other purposes such as industrialisation and urbanisation. Finally, water resources are being used more than ever for human development, especially for agriculture, industrial activities, and navigation. If the regional terrestrial hydrological cycle is changing and counter-measures are desirable, it is from a scientific perspective mandatory to understand the extent and nature of such changes, and, especially, to identify their possible anthropogenic origin. There are, however, fundamental gaps in our knowledge, in particular about the role of feedbacks between individual processes and compartments of the hydrological cycle or the relevance of the interactions with other sub-systems of our planet, such as the atmosphere or the vegetation. This paper mentions several examples of hydrological change and discusses their identification, interaction processes, and feedback mechanisms, along with modelling issues. The possibilities and limitations of modelling are demonstrated by means of two studies: one from the river-lake system on the Middle-Havel River and one from the catchment of the Wahnbach Reservoir. The applied model systems comprise a series of consecutively coupled individual models (so-called one-way-coupling). Model systems that are able reflect feedback effects (two-way- coupling) are still in the development stage. It became clear that the applied model systems were able to reproduce the observed dynamics of the hydrological cycle and of selected matter fluxes. However, one has to be aware that the simulated time periods and scenarios represent rather moderately transient conditions, what is the justification why the one-way-coupling seems to be applicable. Furthermore, it was shown that the modelling uncertainty is considerably large. Nevertheless, this uncertainty can be distinguished from effects of changed internal systems dynamics or from changed boundary conditions, what is a basis for the usability of such model systems for prognostic purposes.
This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9- year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles. in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in multi-model ensembles. The reasons behind these observations may relate to the effects of the weighting schemes, non- stationarity of the climate series and possible cross-correlations between models.
This paper introduces the project on 'Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM)' that aims at investigating the envelope of predictions on changes in hydrological fluxes due to land use change. As part of a series of four papers, this paper outlines the motivation and setup of LUCHEM, and presents a model intercomparison for the present-day simulation results. Such an intercomparison provides a valuable basis to investigate the effects of different model structures on model predictions and paves the ground for the analysis of the performance of multi-model ensembles and the reliability of the scenario predictions in companion papers. in this study, we applied a set of 10 lumped, semi-lumped and fully distributed hydrological models that have been previously used in land use change studies to the low mountainous Dill catchment. Germany. Substantial differences in model performance were observed with Nash-Sutcliffe efficiencies ranging from 0.53 to 0.92. Differences in model performance were attributed to (1) model input data, (2) model calibration and (3) the physical basis of the models. The models were applied with two sets of input data: an original and a homogenized data set. This homogenization of precipitation, temperature and leaf area index was performed to reduce the variation between the models. Homogenization improved the comparability of model simulations and resulted in a reduced average bias, although some variation in model data input remained. The effect of the physical differences between models on the long-term water balance was mainly attributed to differences in how models represent evapotranspiration. Semi-lumped and lumped conceptual models slightly outperformed the fully distributed and physically based models. This was attributed to the automatic model calibration typically used for this type of models. Overall, however, we conclude that there was no superior model if several measures of model performance are considered and that all models are suitable to participate in further multi-model ensemble set-ups and land use change scenario investigations.
The Southern Pre-Pyrenees experienced a substantial land-use change over the second half of the 20th century owing to the reduction of agricultural activities towards the formation of a more natural forest landscape. The land-use change over the last 50 years with subsequent effects on water and sediment export was modelled with the process-based, spatially semi-distributed WASA-SED model for the meso-scale Canalda catchment in Catalonia, Spain. It was forwarded that the model yielded plausible results for runoff and sediment yield dynamics without the need of calibration, although the model failed to reproduce the shape of the hydrograph and the total discharge of several individual rainstorm events, hence the simulation capabilities are not yet considered sufficient for decision-making purposes for land management. As there are only a very limited amount of measured data available on sediment budgets with altered land-use and climate change settings, the WASA-SED model was used to obtain qualitative estimates on the effects of past and future change scenarios to derive a baseline for hypothesis building and future discussion on the evolution of sediment budgets in such a dryland setting. Simulating the effects of the past land-use change, the model scenarios resulted in a decrease of up to 75% of the annual sediment yield. whereas modelled runoff remained almost constant over the last 50 years. The relative importance of environmental change was evaluated by comparing the impact on sediment export of land-use change, that are driven by socio-economic factors, with climate change projections for changes in the rainfall regime. The modelling results suggest that a 20% decrease in annual rainfall results in a decrease in runoff and sediment yield, thus an ecosystem stabilisation in regard to sediment export which can only be achieved by a substantial land-use change equivalent to a complete afforestation. At the same time, a 20% increase in rainfall causes a large export of water and sediment resources out of the catchment, equivalent to an intensive agricultural use of 100% of the catchment area. For wet years, the effects of agricultural intensification are more pronounced, so that in this case the intensive land-use change has a significantly larger impact on sediment generation than climate change. The WASA-SED model proved capable in quantifying the impacts of actual and potential environmental change, but the reliability of the simulation results is still circumscribed by considerable parameterisation and model uncertainties.