Streamflow Forecasts in Poorly Documented Basins from Meteorological Fields
Abstract
This paper describes research undertaken in support of a project that seeks to enable the interpretation of predicted meteorological fields in terms of the streamflow in poorly documented catchments. The focus in this presentation is on addressing the issues involved in parameterizing and calibrating the hydrological model to do this in basins where available local data is limited. Hydrological modeling depends on the information available for basin characterization and model validation and calibration and most publicly available models require information not readily available in many regions of the world. Therefore, alternative approaches to the characterization of a basin are required so that stakeholders can benefit from climate forecasts via model estimates of streamflow. An alternative methodology for the parameterization of a basin using globally and publicly available data is proposed for the Modular Modeling System Precipitation Runoff Modeling System (MMS-PRMS). The methodology is based on deriving topography, soil and vegetation parameters from remote sensing and processed digital maps. In this study this model was forced with daily rainfall observations from a local rain gauge network between 1948 and 1978 and the resulting streamflow predictions evaluated and the model calibrated against long records of daily observations. The short-term predictive capabilities of the calibrated model are then tested using daily rainfall forecasts derived from the North American Regional Reanalysis (NARR) from 1979 to 1990. The methodology is tested in the basin of the "Rio Grijalva", which is located in southern Mexico. Use of the model in this basin benefits from the alternative characterization methods described because the local information available for this basin is not sufficient to parameterize physically-based hydrological models. Additionally, the events responsible for the rainfall variability during the wet-season in this basin include diverse weather phenomena, including tropical cyclones, ITCZ movement, and Easterly Waves, large-scale characteristics of which are expected to be captured by the NARR (which has a 32km grid size) and the sparse rain gauge network. The study provides insight into the feasibility of using alternative parameterization approaches for daily streamflow modeling.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2006
- Bibcode:
- 2006AGUFM.H53C0643U
- Keywords:
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- 1805 Computational hydrology;
- 1816 Estimation and forecasting;
- 1840 Hydrometeorology;
- 1847 Modeling;
- 1860 Streamflow