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Resumen:
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Soil erosion by water can cause agricultural soil losses, desertification, water pollution, reservoir
sedimentation, local excess of erosion (such as bridge scour) or deposition, etc. For this reason, the
assessment ...[+]
Soil erosion by water can cause agricultural soil losses, desertification, water pollution, reservoir
sedimentation, local excess of erosion (such as bridge scour) or deposition, etc. For this reason, the
assessment of soil erosion and sediment transport is a key component of integrated catchment
management. One of the most useful and up-to-date tools available to catchment managers for soil
erosion and sediment transport assessment is distributed modelling. During the last few decades, many
sedimentological distributed models were developed and applied for a wide range of climates and
basins. Their main advantage is that they allow spatial interpolation or extrapolation of their results.
Nevertheless, their use is still limited by some constraints. One of the most relevant limitations to the
use of such models is the lack of recorded sediment transport data to be used for model calibration and
validation. It is widely recognised that both sediment discharge series and soil erosion measurements
are only available in a few and small- to medium-size experimental catchments. The aim of this
dissertation is to investigate the possibility of using reservoir sedimentation data as a source of proxy
information for sedimentological model calibration and validation. In order to carry out this task, a
distributed sedimentological model called TETIS was tested in set of catchments with different sediment
data availability. First of all, the TETIS model, developed over the last years by the research group of
hydrological and environmental modelling of the Technical University of Valencia, is described,
especially focusing on the new features developed within this dissertation (sedimentological sub-model
automatic calibration algorithm, small pond sediment retention module, etc.). Then, the model is
applied to three catchments with different sediment data availability. The first case-study is the
Goodwin Creek catchment (Mississippi, US), an experimental catchment with high sediment transport
data availability. The model performance is evaluated, and some considerations are made on the
estimation of the sediment volume deposited into the drainage network at the beginning of a rainstorm.
The second case-study is the Rambla del Poyo catchment (Valencia, Spain), a medium size semi-arid
catchment draining to a coastal lagoon with severe sedimentation problems. The TETIS sedimentological
sub-model is calibrated and validated using check-dam sedimentation volumes as an estimator of the
total sediment transport. A detailed description of the alluvial stratigraphy infilling a check dam that
drains a 12.9 km2
sub-catchment was used as indirect information of sediment yield data. A further
application was also developed in this catchment in order to investigate the possibility of calibrating and
validating both the hydrological and the sediment sub-models by using reservoir sedimentation volumes
and employing neither water nor sediment discharge direct records. The third case-study is the Ésera
River catchment (Huesca, Spain), a 1,500 km2 Pyrenean catchment drained by a large reservoir. The
depositional history of the reservoir was reconstructed and used for sediment sub-model
implementation. The model results were compared with gauged suspended sediment data in order to
verify model robustness. The results of this dissertation indicate that TETIS model is a robust tool which
provides a reliable reconstruction of the catchment sediment cycle. Its implementation is subject to data
availability, both for parameter estimation and for model calibration and validation. Nevertheless, this
dissertation proved that sediment records can be replaced by reservoir sedimentation volumes with
satisfactory results, taking into account reservoir trap efficiency and sediment dry bulk density. Two
modelling approaches were proposed for sediment model implementation, depending on the data
availability. These methodologies proved to be consistent and provided a correct estimation of the
sediment transport. Nevertheless, further research is needed to address model limitations and to
reduce model results uncertainty
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