Mapping water ecosystem services: Evaluating InVEST model predictions in data scarce regions
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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in: Environmental Modelling & Software, Jahrgang 138, 104982, 01.04.2021.
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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TY - JOUR
T1 - Mapping water ecosystem services: Evaluating InVEST model predictions in data scarce regions
AU - Benra, Felipe
AU - De Frutos, Angel
AU - Gaglio, M.
AU - Álvarez-Garretón, C.
AU - Felipe-Lucia, María R.
AU - Bonn, Aletta
N1 - Publisher Copyright: © 2021 Elsevier Ltd
PY - 2021/4/1
Y1 - 2021/4/1
N2 - Sustainable management of water ecosystem services requires reliable information to support decision making. We evaluate the performance of the InVEST Seasonal Water Yield Model (SWYM) against water monitoring records in 224 catchments in southern Chile. We run the SWYM in three years (1998, 2007 and 2013) to account for recent land-use change and climatic variations. We computed squared Pearson correlations between SWYM monthly quickflow predictions and streamflow observations and applied a generalized mixed-effects model to evaluate annual estimations. Results show relatively low monthly correlations with marked latitudinal and temporal variations while annual estimates show a good match between observed and modeled values, especially for values under 1000 mm/year. Better predictions were observed in regions with high rainfall and in dry years while poorer predictions were found in snow dominated and drier regions. Our results improve SWYM performance and contribute to water supply and regulation decision-making, particularly in data scarce regions.
AB - Sustainable management of water ecosystem services requires reliable information to support decision making. We evaluate the performance of the InVEST Seasonal Water Yield Model (SWYM) against water monitoring records in 224 catchments in southern Chile. We run the SWYM in three years (1998, 2007 and 2013) to account for recent land-use change and climatic variations. We computed squared Pearson correlations between SWYM monthly quickflow predictions and streamflow observations and applied a generalized mixed-effects model to evaluate annual estimations. Results show relatively low monthly correlations with marked latitudinal and temporal variations while annual estimates show a good match between observed and modeled values, especially for values under 1000 mm/year. Better predictions were observed in regions with high rainfall and in dry years while poorer predictions were found in snow dominated and drier regions. Our results improve SWYM performance and contribute to water supply and regulation decision-making, particularly in data scarce regions.
KW - Ecosystems Research
KW - Ecosystem service model
KW - Water regulation
KW - Water supply
KW - South America
KW - Data scarce regions
KW - Blue ecosystem services
UR - http://www.scopus.com/inward/record.url?scp=85100680839&partnerID=8YFLogxK
U2 - 10.1016/j.envsoft.2021.104982
DO - 10.1016/j.envsoft.2021.104982
M3 - Journal articles
VL - 138
JO - Environmental Modelling & Software
JF - Environmental Modelling & Software
SN - 1364-8152
M1 - 104982
ER -