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Hydrological model uncertainty due to spatial evapotranspiration estimation methods
- Source :
- Computers & Geosciences. 90:90-101
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index LAI, interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50?03'N, 12?40'E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models. We quantify the uncertainty of hydrological modeling due to spatial ET estimation.We present a series of forest management probabilities from historic forest age maps.The plant physiology-based ET estimation reduced hydrologic uncertainty.Reduced uncertainty suggests the importance of forest growth in water use studies.
- Subjects :
- Hydrology
010504 meteorology & atmospheric sciences
Hydrological modelling
0208 environmental biotechnology
Forest management
02 engineering and technology
Groundwater recharge
Vegetation
Land cover
01 natural sciences
020801 environmental engineering
Evapotranspiration
Streamflow
Environmental science
Computers in Earth Sciences
Interception
0105 earth and related environmental sciences
Information Systems
Subjects
Details
- ISSN :
- 00983004
- Volume :
- 90
- Database :
- OpenAIRE
- Journal :
- Computers & Geosciences
- Accession number :
- edsair.doi...........8d96449ee4997abd4800f60ffb9c8540