Abstract's details
Hydrographic Mapping of Chile: SWOT-Based Characterization of National Rivers Through Integrated Hydrological Modeling
Event: 2025 SWOT Science Team Meeting
Session: Hydrology: Global Hydrology Modeling Working Group
Presentation type: Poster
Chile’s river systems are fundamental to national ecological integrity, water security, and socio-economic resilience. However, the country’s hydrological monitoring network remains limited in spatial coverage and temporal resolution due to the sparse distribution of hydrometric stations. This study proposes a transformative approach to Chilean hydrography by leveraging high-resolution satellite observations from the Surface Water and Ocean Topography (SWOT) mission, coupled with state-of-the-art hydrological modeling frameworks.
The research targets a representative array of major river basins, including the Loa, Bío-Bío, Baker, Maipo, Aconcagua, Maule, Cautín, Valdivia, and Imperial Rivers, with a focus on reaches exceeding 100 meters in width, for which SWOT provides optimal observational coverage. The methodology is structured into three principal stages: (1) identification and characterization of stationary hydrological cycles, including water surface elevation (WSE) and inferred discharge patterns, from SWOT observations; (2) integration and calibration of SWOT-derived variables with distributed hydrological models to enhance spatiotemporal continuity; and (3) development of a prototype system for continuous, satellite-based river monitoring at the national scale.
To assess the reliability and added value of satellite-based observations, we perform a comparative analysis between SWOT-derived hydrological metrics and outputs from the ERA5-Land reanalysis. Specifically, we evaluate consistency in seasonal discharge dynamics, runoff timing, and spatial gradients, highlighting both the complementary strengths and limitations of reanalysis-based hydrology in mountainous, data-scarce basins. This cross-validation helps identify biases in land-surface model outputs and informs improved parameterization for large-scale hydrological forecasting.
A key deliverable of the project is the establishment of an open-access hydrological database, encompassing validated time series, statistical summaries, and geospatial visualizations. This resource is designed to support scientific inquiry, water governance, and infrastructure planning.
By addressing critical data gaps in Chile’s freshwater monitoring capabilities, this project provides a foundational framework for long-term riverine observation and risk assessment. Moreover, it enhances national capacity to detect and respond to extreme hydrometeorological events—an increasingly urgent need under evolving climate regimes.
Back to the list of abstractThe research targets a representative array of major river basins, including the Loa, Bío-Bío, Baker, Maipo, Aconcagua, Maule, Cautín, Valdivia, and Imperial Rivers, with a focus on reaches exceeding 100 meters in width, for which SWOT provides optimal observational coverage. The methodology is structured into three principal stages: (1) identification and characterization of stationary hydrological cycles, including water surface elevation (WSE) and inferred discharge patterns, from SWOT observations; (2) integration and calibration of SWOT-derived variables with distributed hydrological models to enhance spatiotemporal continuity; and (3) development of a prototype system for continuous, satellite-based river monitoring at the national scale.
To assess the reliability and added value of satellite-based observations, we perform a comparative analysis between SWOT-derived hydrological metrics and outputs from the ERA5-Land reanalysis. Specifically, we evaluate consistency in seasonal discharge dynamics, runoff timing, and spatial gradients, highlighting both the complementary strengths and limitations of reanalysis-based hydrology in mountainous, data-scarce basins. This cross-validation helps identify biases in land-surface model outputs and informs improved parameterization for large-scale hydrological forecasting.
A key deliverable of the project is the establishment of an open-access hydrological database, encompassing validated time series, statistical summaries, and geospatial visualizations. This resource is designed to support scientific inquiry, water governance, and infrastructure planning.
By addressing critical data gaps in Chile’s freshwater monitoring capabilities, this project provides a foundational framework for long-term riverine observation and risk assessment. Moreover, it enhances national capacity to detect and respond to extreme hydrometeorological events—an increasingly urgent need under evolving climate regimes.