On the performance of conceptual and physically based modelling approach to simulate a headwater catchment in Brazil. (March 2022)
- Record Type:
- Journal Article
- Title:
- On the performance of conceptual and physically based modelling approach to simulate a headwater catchment in Brazil. (March 2022)
- Main Title:
- On the performance of conceptual and physically based modelling approach to simulate a headwater catchment in Brazil
- Authors:
- Melo, Pâmela A.
Alvarenga, Lívia A.
Tomasella, Javier
Santos, Ana Carolina N.
Mello, Carlos R.
Colombo, Alberto - Abstract:
- Abstract: Conceptual large-scale distributed hydrological models (e.g. MHD-INPE) were developed to not only be used with limited available data but also to match the scale of atmospheric models. However, it is unknown if it can be representative for small watersheds in rural mountainous regions, which are crucial not only for agriculture, but also for water supply for several uses. Therefore, the objective of this study is to assess MHD-INPE performance in a headwater catchment with complex terrain alongside to a distributed physically based model (DHSVM). The Lavrinha Watershed (LW) has a drainage area of 6.7 km 2, being 63% of the catchment occupied by native vegetation (Atlantic Rainforest), while the remaining area is mainly occupied by pasture for livestock farming. MHD-INPE and DHSVM were applied using a soil moisture zone map derived from the height above the nearest drainage (HAND) algorithm. The runoff simulated by the MHD-INPE better fits the observed data, with a validation Nash-Sutcliffe efficiency (NSE) of 0.70 for the daily scale, compared to a 0.55 in DHSVM. In the evapotranspiration simulation, both models showed similar trends, being 49% of the precipitation in the MHD-INPE and 46% in the DHSVM, while the observed value was 49%. For the baseflow, the MHD-INPE fitted better to the observed streamflow, whereas the DHSVM underestimated it during the dry season. Thus MHD-INPE was able to accurately simulate the streamflow in a mountainous headwater catchment inAbstract: Conceptual large-scale distributed hydrological models (e.g. MHD-INPE) were developed to not only be used with limited available data but also to match the scale of atmospheric models. However, it is unknown if it can be representative for small watersheds in rural mountainous regions, which are crucial not only for agriculture, but also for water supply for several uses. Therefore, the objective of this study is to assess MHD-INPE performance in a headwater catchment with complex terrain alongside to a distributed physically based model (DHSVM). The Lavrinha Watershed (LW) has a drainage area of 6.7 km 2, being 63% of the catchment occupied by native vegetation (Atlantic Rainforest), while the remaining area is mainly occupied by pasture for livestock farming. MHD-INPE and DHSVM were applied using a soil moisture zone map derived from the height above the nearest drainage (HAND) algorithm. The runoff simulated by the MHD-INPE better fits the observed data, with a validation Nash-Sutcliffe efficiency (NSE) of 0.70 for the daily scale, compared to a 0.55 in DHSVM. In the evapotranspiration simulation, both models showed similar trends, being 49% of the precipitation in the MHD-INPE and 46% in the DHSVM, while the observed value was 49%. For the baseflow, the MHD-INPE fitted better to the observed streamflow, whereas the DHSVM underestimated it during the dry season. Thus MHD-INPE was able to accurately simulate the streamflow in a mountainous headwater catchment in southeast Brazil, despite its large spatial scale. Highlights: Poorly monitored headwater catchments in Brazil are fundamental for several uses. Studies on multiple uses of broader scale requires the use of large-scale modelling. Performance of large-scale hydrologic models is unknown in headwater watersheds. Large-scale and physically based models were applied in a headwater watershed. Grid-cell large-scale model can produce reliable estimations on headwater watershed. … (more)
- Is Part Of:
- Journal of South American earth sciences. Volume 114(2022)
- Journal:
- Journal of South American earth sciences
- Issue:
- Volume 114(2022)
- Issue Display:
- Volume 114, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 114
- Issue:
- 2022
- Issue Sort Value:
- 2022-0114-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-03
- Subjects:
- Lumped model -- Hydrology -- Streamflow simulation -- Evapotranspiration
Geology -- Latin America -- Periodicals
Earth sciences -- Latin America -- Periodicals
Geology -- Antarctica -- Periodicals
Earth sciences -- Antarctica -- Periodicals
Geology -- Caribbean Area -- Periodicals
Earth sciences -- Caribbean Area -- Periodicals
Géologie -- Amérique latine -- Périodiques
Sciences de la terre -- Amérique latine -- Périodiques
Géologie -- Antarctique -- Périodiques
Sciences de la terre -- Antarctique -- Périodiques
Géologie -- Caraïbes (Région) -- Périodiques
Sciences de la terre -- Caraïbes (Région) -- Périodiques
Earth sciences
Geology
Antarctica
Caribbean Area
Latin America
Periodicals
550.5 - Journal URLs:
- http://www.sciencedirect.com/science/journal/08959811 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jsames.2021.103683 ↗
- Languages:
- English
- ISSNs:
- 0895-9811
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5066.002400
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20800.xml