Сравнение методов

	HEC-RAS	Индекс нормализованного различия (NDVI)	Модель SWAT
Область	Геофизика	Геофизика	Геофизика
Семейство	Process / pipeline	Process / pipeline	Process / pipeline
Год появления	1995	1973	1998
Автор метода	US Army Corps of Engineers Hydrologic Engineering Center	Rouse, Haas, Schell, and Deering	Jeff Arnold and others at USDA-ARS
Тип	1D/2D river hydraulics and flood inundation modeling	Spectral index for vegetation assessment	Process-based watershed and water quality simulation
Основополагающий источник	Brunner, G. W. (2010). HEC-RAS river analysis system hydraulic reference manual. US Army Corps of Engineers Hydrologic Engineering Center.	Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1973). Monitoring vegetation systems in the Great Plains with ERTS. Third Earth Resources Technology Satellite Symposium Proceedings, 1, 309-317.	Arnold, J. G., Srinivasan, R., Muttiah, R. S., & Williams, J. R. (1998). Large area hydrologic modeling and assessment part I: Model development. Journal of the American Water Resources Association, 34(1), 73-89.
Другие названия	HEC-RAS	NDVI	SWAT
Связанные	3	3	3
Сводка	HEC-RAS (Hydrologic Engineering Center River Analysis System) is a hydraulic modeling software developed by the US Army Corps of Engineers that computes water surface elevation and velocity in open channels and floodplains, and depicts inundation extent and depth. Since its introduction in 1995, HEC-RAS has become the de facto standard for floodplain delineation, dam break analysis, and flood risk assessment for regulatory and engineering purposes.	The Normalized Difference Vegetation Index (NDVI) is a spectral index computed from satellite or aerial multispectral imagery that quantifies vegetation greenness and vigor. Introduced by Rouse and colleagues in 1973 using Landsat data, NDVI has become the most widely used remote sensing metric for vegetation monitoring, drought assessment, crop productivity forecasting, and land cover change detection.	The Soil and Water Assessment Tool (SWAT) is a process-based watershed model that simulates the hydrological cycle, sediment transport, nutrient cycling, pesticide fate, and land management impacts across a watershed or large basin. Developed by Jeff Arnold and colleagues at USDA-ARS in 1998, SWAT has become a standard tool for evaluating non-point source pollution, assessing climate change impacts on water resources, and designing best management practices.