Forecasting the impact of temporal land use change on steep terrain watersheds in Costa Rica
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| Autor: | |
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| Formato: | artículo original |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2013 |
| Descripción: | The land use/land cover change simultaneous model based on the Markov Chain Analysis, Cellular Automata (CA_MARKOV) and Multi-Criteria-Evaluation (MCE), was used to predict the impact of the land use temporal change to 2025 over the Toyogres and Zopilote rivers watersheds in Costa Rica. The hydrologic model SWMM was previously calibrated and validated using various real rainfall storms in order to serve a hydrological analysis platform. The historical records for both models were based on aerial photography form the 1997 TERRA mission and multi-spectral images taken by the WorldView-2 satellite in 2011. Based on the model’s predictions/projections for 2025, an increase of around 15% over the peak flow for the Toyogres River and 26% for the Zopilote River would be the consequence of a high intensity rainfall storm (maximum precipitated volume of 53.56 mm and maximum intensity of 120 mm/hr/5min). This is particularly relevant for the Zopilote catchment due to its limited hydraulic capacity. This is a direct consequence of an increase in the impervious area, related to the SWMM‘s percentage-imperviousarea (pimp), which is a key parameter in the rainfallrunoff generation processes. The land uses that experimented major changes were HDRES, MDRES, LDRES and CROPS. Regardless of its final objective, further investigation is needed in order to calibrate and validate the outcomes projected by this kind of models. |
| País: | RepositorioTEC |
| Institución: | Instituto Tecnológico de Costa Rica |
| Repositorio: | RepositorioTEC |
| Lenguaje: | Español |
| OAI Identifier: | oai:repositoriotec.tec.ac.cr:2238/7960 |
| Acceso en línea: | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/1514 https://hdl.handle.net/2238/7960 |
| Access Level: | acceso abierto |
| Palabra clave: | Hydrology; IDRISI; Markov; modeling; SWMM Hidrología; IDRISI; Markov; modelación; SWMM |