Paulo Rógenes Monteiro Pontes

MGB-IPH model for hydrological and hydraulic simulation of large floodplain river systems coupled with open source GIS

Abstract Large-scale hydrological models are useful tools for water resources studies, however, river network flow routing is generally represented using simplified methods, which may lead to simulation errors in flat regions. We present recent improvements to the large-scale hydrological model MGB-IPH to improve its capability of simulating large river basins with extensive floodplains. We also describe the coupling of MGB-IPH to an open source GIS and a large set of developed pre-processing tools with a user-friendly interface for remote sensing data preparation and output visualization. The new features implemented are demonstrated applying the model to the whole Araguaia river basin (380,000 km2). Results are compared to the previous MGB-IPH routing method, observed flow and water level data and remote sensing imagery, showing improvement in the representation of floodplain inundation dynamics. The test case also shows that the proposed model software framework amplifies possibilities of large-scale simulation of ungauged basins.

On river‐floodplain interaction and hydrograph skewness

Understanding hydrological processes occurring within a basin by looking at its outlet hydrograph can improve and foster comprehension of ungauged regions. In this context, we present an extensive examination of the roles that floodplains play on driving hydrograph shapes. Observations of many river hydrographs with large floodplain influence are carried out and indicate that a negative skewness of the hydrographs is present among many of them. Through a series of numerical experiments and analytical reasoning, we show how the relationship between flood wave celerity and discharge in such systems is responsible for determining the hydrograph shapes. The more water inundates the floodplains upstream of the observed point, the more negatively skewed is the observed hydrograph. A case study is performed in the Amazon River Basin, where major rivers with large floodplain attenuation (e.g., Purus, Madeira, and Jurua) are identified with higher negative skewness in the respective hydrographs. Finally, different wetland types could be distinguished by using this feature, e.g., wetlands maintained by endogenous processes, from wetlands governed by overbank flow (along river floodplains). A metric of hydrograph skewness was developed to quantify this effect, based on the time derivative of discharge. Together with the skewness concept, it may be used in other studies concerning the relevance of floodplain attenuation in large, ungauged rivers, where remote sensing data (e.g., satellite altimetry) can be very useful.

Sobre o Uso da Persistência de Previsões Determinísticas de Vazão para a Tomada de Decisão

Medium-range streamflow forecasts, which are generated using rainfall-runoff models forced by numerical precipitation predictions, are very useful for the anticipation of hydrological events. Traditionally these predictions are deterministic, but in the last decade the movement for generating ensemble streamflow forecasts has been gaining strength. In the middle ground between these two techniques (deterministic and ensembles) the use of persistence information from deterministic streamflow forecasts for decision making, using it as an uncertainty measurement, appears to be an interesting strategy. This research investigates precisely these possible benefits of using forecasts based on persistence as uncertainty information measurement. Results suggest that the use of forecasts based on persistence have advantages over single deterministic forecasts on the higher lead times.