Resumen
La gran cuenca del Río Grande, ubicada en el noroeste de Jamaica, crítico para el desarrollo, particularmente para vivienda, turismo, agricultura y minería. Es una fuente de sedimentos y nutrientes de recarga para el ambiente costero incluyendo el Parque Marino Bahía Montego. Proponemos un marco integrado de modelado utilizando la herramienta de evaluación de suelo y agua (SWAT) y SIG. Las estadísticas de rendimiento del modelo calculadas para la descarga de alto flujo rindió una eficacia de Nash-Sutcliffe (NSE) de 0.68 y un R2 de 0.70 sugiriendo una buena medición y correlación de descarga simulada (calibrada). Los estados insulares con frecuencia toman decisiones basándose en los impactos de la cuenca. Esto requiere un profundo entendimiento y análisis de factores como los recursos hídricos, uso del suelo/cobertura, sedimentos y nutrientes de recarga entre otros factores a nivel de cuenca. Con financiamiento del Instituto Interamericano para la investigación del Cambio Global (IAI) se examinó la aplicación del modelo de acceso libre en una cuenca jamaiquina. Los resultados de la calibración y validación para caudales fueron similares a los observados en los caudales respectivos, según lo indicado por la eficacia de Nash-Sutcliffe y el coeficiente de determinación. La calibración y validación de los resultados para el caudal son similares a los observados en el caudal. Durante la estación seca el escenario simulado en el uso de suelo urbano predijo un aumento de la escorrentía superficial superior al 150%. Durante la estación lluviosa el aumento de la escorrentía superficial se prevé que alcance desde 98 a 234% lo que representa un riesgo significativo de inundaciones, erosión y otros problemas ambientales. El modelo sugiere que cambios en los usos proyectados de suelo tendrán serios impactos sobre la disponibilidad de agua (caudal), salud de la cuenca, tratamiento de agua potable, inundaciones y ecosistemas costeros sensibles.
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Fig. 1. Performance of Model under Calibration (A) and Validation (B) modes with influence from monthly rainfall data.
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Derechos de autor 2014 Revista de Biología Tropical