Height Above the Nearest Drainage to Predict Flooding Areas in São Luiz do Paraitinga, São Paulo
Abstract Natural events associated to environmental disasters has increased with climate changes. Understanding the watershed behavior allows the managers to execute an efficient land use planning. By using as a study area the municipality of São Luiz do Paraitinga, the study’s goal was apply the Height Above the Nearest Drainage Model, which allows categorizing areas based on simulations of water level variations, to evaluate flooding risks at the municipality. The data were processed using ArcGIS Desktop v. 10.3, System for Automated Geoscientific Analysis and TerraHidro. The flood susceptibility map was generated with spatial resolution of 30 m. It was simulated water level variations of 7, 9, 12 and 15 meters and, according to the model, areas with high or very high flood susceptibility cover approximately 13% of the study area (81 km2). In general, the methods used afforded coherent results given the resolution of source data and available information.
| Main Authors: | , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro
2021
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| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872021000200307 |
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| Summary: | Abstract Natural events associated to environmental disasters has increased with climate changes. Understanding the watershed behavior allows the managers to execute an efficient land use planning. By using as a study area the municipality of São Luiz do Paraitinga, the study’s goal was apply the Height Above the Nearest Drainage Model, which allows categorizing areas based on simulations of water level variations, to evaluate flooding risks at the municipality. The data were processed using ArcGIS Desktop v. 10.3, System for Automated Geoscientific Analysis and TerraHidro. The flood susceptibility map was generated with spatial resolution of 30 m. It was simulated water level variations of 7, 9, 12 and 15 meters and, according to the model, areas with high or very high flood susceptibility cover approximately 13% of the study area (81 km2). In general, the methods used afforded coherent results given the resolution of source data and available information. |
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