Mapping water ecosystem services: Evaluating InVEST model predictions in data scarce regions

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 an...

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Published in:Environmental modelling & software : with environment data news Vol. 138; p. 104982
Main Authors: Benra, F., De Frutos, A., Gaglio, M., Álvarez-Garretón, C., Felipe-Lucia, M., Bonn, A.
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 01.04.2021
Elsevier Science Ltd
Subjects:
Blue ecosystem services
Catchments
Chile
computer software
Data scarce regions
Decision making
Ecosystem management
Ecosystem service model
Ecosystem services
ecosystems
Land use
land use change
Performance evaluation
Predictions
rain
Rainfall
snow
South America
Stream discharge
Stream flow
Sustainability management
Temporal variations
Water management
Water monitoring
Water regulation
Water supply
Water yield
Chile
South America
Data scarce regions
Ecosystem service model
Water regulation
Water supply
Blue ecosystem services
ISSN:1364-8152, 1873-6726
Online Access:Get full text
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Summary: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. [Display omitted] •InVEST Seasonal Water Yield Model (SWYM) is used to model monthly and annual water flows.•We compare SWYM estimations to observed streamflow data in 224 basins.•Annual estimations are more precise than monthly ones.•SWYM performs better in rainier regions and in drier years.•SWYM does not perform well in snow-dominated and arid regions.
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ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2021.104982