Collaborative Watershed Modeling as Stakeholder Engagement Tool for Science-Based Water Policy Assessment in São Paulo, Brazil
2.1. Study Site
2.2. Collaborative Modeling Process Overview
2.2.1. Stakeholder Engagement
2.2.2. Landscape Management Scenarios
- Minimum Intervention (MI): Although this study is not related in any way to enforcement of the Brazilian Forest Code, the legal definition of Permanent Protected Areas (APP), defining riparian areas and springs buffers for protection, has been used to define this scenario. Restoration of riparian buffer zones in pastures ranges from 5 m for small proprieties to 15 m for larger properties, plus a buffer zone of 500 m around the reservoirs managed by SABESP. The purpose of this scenario is to explore the hydrological benefits of basic legal compliance standards in the CWSS.
- Enhanced Intervention (EI): The enhanced intervention scenario follows the same logic as the minimum intervention scenario but with greater riparian buffer protections, ranging from 30 m to 50 m, plus the 500 m buffer protection around reservoirs.
- Customized RIOS scenario (RIOS): To include a case that prioritizes areas for maximizing infiltration and baseflow given the geophysical characteristics (climate, topography, soil type, and underlying geology), we used the Resource Investment Optimization System (RIOS), designed by The Natural Capital Project, to map and define the extent of this scenario.
2.2.3. Environmental Simulation Models
- Resource Investment Optimization System (RIOS): Developed by the Natural Capital Project (NatCap), RIOS is a spatial modeling tool designed to prioritize areas in watersheds to optimize investments for multiple benefits so as to protect clean water supplies, mitigate flood risks, and contribute toward biodiversity and social goals . RIOS integrates biophysical, social, and economic data to screen the landscape areas, and we used the land-use/land-cover, topography, surficial geology, canopy cover, and climate data to map the locations in the CWSS that would maximize distributed storage of water in the soil columns and vegetations across the watershed (i.e., customized RIOS scenario).
- Fog Interception for the Enhancement of Stream-flow in Tropical Areas (FIESTA): FIESTA is a hydrological model that quantifies hydrological fluxes contributed by fog interception in a watershed and is used to quantify the potential water balance gains for each landscape management scenario . Fog interception is an additional input to water balance when forest captures cloud water that would otherwise pass over the watershed. Additional water from fog capture can play an integral role in biological process as a part of the hydrological cycle in those regions where recurrent dry season creates drought conditions. To estimate this parcel of fog water for each management scenario, FIESTA model was used to map those areas with high potential for fog capture, compute fog capture potential using topographic, land-cover, and climatic data, and allocate the amount for those areas covered in the scenarios.
- Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS): HEC-HMS was originally used by SABESP to simulate event-based (~12–24 h) surface runoff given precipitation, hydrologic network, and reservoir water level data. During the February 2020 workshop with SABESP, we began the process of converting the existing model for long-term continuous hydrologic simulations—a model that simulates both wet and dry weather behaviors—by adapting the Soil Moisture Accounting (SMA) algorithm. We developed four independent models to evaluate individual reservoirs. Subsequently, we identified data need for the long-term hydrologic simulation and worked with SABESP to obtain them. When the long-term hydrologic simulation model setup was completed, we worked with SABESP’s engineering team to calibrate, validate, and evaluate the model framework, input data, and outputs (Figure 6). For further details on model structure and computational algorithm, refer to Acosta et al. .
- Soil and Water Assessment Tool (SWAT): SWAT is a semi-distributed and continuous hydrologic simulation model that includes multiple hydrologic and water chemistry processes . Compared to HEC-HMS, SWAT operates over more detailed and spatially explicit watershed information and hydrologic processes. SWAT uses geospatial attributes, such as soils, land-use/land-cover, topography, and crop management parameters, to predict the response of climatic inputs in the system. We used SWAT to simulate the watershed hydrology and the erosion, transport, and fate of sediment and nutrients. SWAT outputs of water balance simulation are compared to HEC-HMS outputs to assess the general modelling uncertainty and provide additional predictions about water quantity and quality associated with each landscape management scenario. For further details on model structure and computational algorithm, refer to Acosta et al. .
2.2.4. Model Synthesis Evaluation and Intervention Impact Simulation
2.2.5. Economic Evaluation of the Cost of Extreme Drought and Value of Ambient Water Storage
3.1. Biophysical Simulation Summary
3.2. Economic Analysis Summary
4.1. Science–Policy Challenges for Achieving Water Security
4.2. Consideration of Collaborative Modeling for Stakeholder Engagement
Data Availability Statement
Conflicts of Interest
|CWSS||Cantareira Water Supply System|
|IPCC||Intergovernmental Panel on Climate Change|
|GDP||Gross Domestic Product|
|SABESP||São Paulo State Water and Sanitation Company|
|ARSESP||São Paulo State Public Services Regulatory Agency|
|TNC||The Nature Conservancy|
|WRI||World Resources Institute|
|SESYNC||National Socio-Environmental Synthesis Center/University of Maryland|
|PCJ||Piracicaba–Capivarí–Jundiaí Rivers Watershed Committee|
|HEC-HMS||Hydrologic Engineering Center-Hydrologic Modeling System|
|RIOS||Resource Investment Optimization System|
|FIESTA||Fog Interception for the Enhancement of Stream-flow in Tropical Areas|
|SWAT||Soil and Water Assessment Tool|
|SIMA||São Paulo State Secretariat of Infrastructure and Environment|
|PES||Payment for Ecosystem Services|
Appendix A. Historical Land-Use and Land-Cover Change Analysis
Appendix B. Reduced-Complexity Nature and Engineered Infrastructure Simulation Model
Appendix B.1. Model Structure
Appendix B.2. Model Interface: Jaguari Watershed Is Divided into Three Zones
- SB 54 in zone 1
- SB 34 and SB 68 in zone 2, and
- SB 80 and SB 100 in zone 3.
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|Industry Gross Value Added (GVA) loss in municipalities on Cantareira System (USD 1000)|
|Franco da Rocha||4.104||73.653||77.757|
|Water supply and sewage sector Net Value Added (NVA) loss in municipalities served by Cantareira System (USD 1000)|
|Franco da Rocha||1.320||1.121||2.441|
|São Caetano do Sul||2.871||2.579||5.451|
|Avoided costs in the industry with a RIOS scenario (USD 1000)|
|Industry GVA loss in the Cantareira System municipalities (I)||302.691|
|Industry GVA loss in the Cantareira System municipalities under the RIOS scenario (II)||220.266|
|Avoided industry GVA financial losses with the RIOS scenario (III = I–II)||82.425|
|Percentage of avoided industry GVA financial losses (%) (IV = III/I)||27%|
|Avoided costs in the water supply and sanitation services with the RIOS scenario (USD 1000)|
|Loss of water and sanitation services NVA in the municipalities served by the Cantareira System (V)||147.198|
|Loss of water and sanitation services NVA in the municipalities served by the Cantareira System under the RIOS scenario (VI)||105.590|
|Avoided financial loss of water and sanitation services NVA with RIOS (VII = V–VI)||41.608|
|Percentage of avoided financial loss of water and sanitation services NVA with RIOS scenario (%) (VIII = VII/V)||28%|
|Total avoided financial loss (IX = III + VII)||124.032|
|Percentage of total avoided financial loss (%) [X = IX/(I + V)]||28%|
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Cho, S.J.; Klemz, C.; Barreto, S.; Raepple, J.; Bracale, H.; Acosta, E.A.; Rogéliz-Prada, C.A.; Ciasca, B.S. Collaborative Watershed Modeling as Stakeholder Engagement Tool for Science-Based Water Policy Assessment in São Paulo, Brazil. Water 2023, 15, 401. https://doi.org/10.3390/w15030401
Cho SJ, Klemz C, Barreto S, Raepple J, Bracale H, Acosta EA, Rogéliz-Prada CA, Ciasca BS. Collaborative Watershed Modeling as Stakeholder Engagement Tool for Science-Based Water Policy Assessment in São Paulo, Brazil. Water. 2023; 15(3):401. https://doi.org/10.3390/w15030401Chicago/Turabian Style
Cho, Se Jong, Claudio Klemz, Samuel Barreto, Justus Raepple, Henrique Bracale, Eileen Andrea Acosta, Carlos Andres Rogéliz-Prada, and Bruna S. Ciasca. 2023. "Collaborative Watershed Modeling as Stakeholder Engagement Tool for Science-Based Water Policy Assessment in São Paulo, Brazil" Water 15, no. 3: 401. https://doi.org/10.3390/w15030401