Simulating the hydrological response of a small tropical forest watershed (Mata Atlantica, Brazil) by the AnnAGNPS model.
Sci Total Environ
; 636: 737-750, 2018 Sep 15.
Article
en En
| MEDLINE
| ID: mdl-29727841
Given the intrinsic hydrological cycle made of large input of water vapour and intense precipitation producing large volumes of water and sediment, modelling runoff and water losses in humid tropical watersheds is important for forest and water resources management. For instance, reliable simulations of the water cycle in such environments are a prerequisite for predictions of water quality, soil erosion and the climate change effects on water resources. The distributed parameter, physically based, continuous simulation, daily time step AnnAGNPS model, was implemented in almost completely forested (98% of its area, 0.56â¯km2) Cunha watershed (Brazil) to assess its capability to simulate hydrological processes under tropical conditions. The simulated surface runoff was compared to 4-year observations with statistical indices on several time scales. The model, running with default CN of forest, showed poor predictions of runoff. After increasing CN from 63 to 72 by calibration, the runoff prediction capability of AnnAGNPS was satisfactory on annual, seasonal and monthly scales, while daily runoff predictions were less accurate. Modelling water losses at event scale showed that the effect of forest vegetation on water retention during a single precipitation was more limited than for longer periods (months, seasons and years), since evapo-transpiration and interception account for small shares (>20%) of total precipitation. This study demonstrated that the AnnAGNPS model has reliable runoff prediction capacity in tropical forest watersheds at the annual and seasonal scales (Eâ¯>â¯0.73), whereas daily runoff simulations are less accurate (Eâ¯=â¯0.44). The use of this model may prove an important tool for water resource and territory management in tropical rainforests.
Texto completo:
1
Banco de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
País/Región como asunto:
America do sul
/
Brasil
Idioma:
En
Revista:
Sci Total Environ
Año:
2018
Tipo del documento:
Article