Publications

This study investigated the impact of hydrometeorological data and forecast information availability on improving hydropower production and storage management in reservoir systems, and the associated costs of data production. The methodological approach integrated stochastic optimization and rolling horizon optimization with forecasts to address both short- and long-term operating targets when determining daily reservoir release decisions over the planning horizon. Three hydrometeorological data scenarios were organized to assess the quantitative benefits and to trace the costs, thereby establishing benefit–cost relationships. The large-scale hydropower system in the Paraná River Basin, Brazil, was used as case study. The results show that improved hydrometeorological data and information allows for better water storage management across time, which increases energy production and value. Up to a 15% increase in hydropower production over a 5-year simulation period was obtained, and the incremental benefits for the modeled system were 2 orders of magnitude greater than the cost of producing the hydrometeorological information. Specifically, every USD 1 invested in incremental hydrometeorological information generated a return of USD 775 when subseasonal forecasts replaced stochastic ensembles for reservoir storage management. However, further improvement in the forecast system would be limited to an additional 2.3% maximum gains in energy, indicating decreasing incremental benefits. Finally, the methods and results are helpful to justify resource commitment necessary to data gathering and forecast systems that will allow reservoir and power operations to be continuously improved and adapted in the future.

We present an overview of the unprecedent hydrological event that occurred in Rio Grande do Sul state in late April and early May 2024, causing floods and landslides in a scale that was not seen before in Brazil. The rainfall that caused the disaster is incomparable to any recent event in Brazil at large spatial and temporal scale. The intense and long-lasting precipitation led to record floods from small rivers with drainage areas below 1000 km2 to the Patos Lagoon, which drains more than 180,000 km2. The rainfall also led to landslides that rank first in Brazil in terms of spatial scale and number of occurrences. Mountain rivers experienced flash floods with extreme water levels, while in the lowlands the large rivers and the Patos Lagoon experienced long duration flooding, with stage remaining high for about 30 days. The flood event is probably ranked first in terms of displaced people and damage to property and infrastructure in Brazil. Almost 200 fatalities occurred due to the disaster and protection structure failures. The April-May hydrological event show a glimpse of what can be expected along the coming decades due to climate change in a region that covers South Brazil, and parts of the neighboring countries.

Urban stormwater management funding is a significant challenge, requiring resources for infrastructure operation, maintenance, rehabilitation and expansion, while still addressing fairness and affordability to users. This paper provides a single approach combining hydrologic, finance and planning elements to support the stormwater fee design fully integrated to the finance strategy to implement stormwater and flood protection actions. The approach combines a novel, spatially-based Hydrological Externality Index (HEI), calibrated through expert opinion or hydrological models, with the design of a composite fee system based on the Polluter-Pays Principle that addresses equity and different lot categories. The revenues provided by the stormwater fee are simulated against the Equivalent Uniform Annual Costs of multiple portfolios of stormwater investment demands, allowing identification of different long-term financially sustainable stormwater planning strategies. The spatial heterogeneity in hydrological processes revealed in the HEI map identifies high-impact areas to guide sustainable urban planning and opportunities to lower drainage fees to some users. The composite fee system showed skewed fee distribution with higher charges for large industrial lots and lower fees for low-income neighborhoods, promoting affordability. The analysis allowed the Urban Stormwater and Flood Protection plan temporal framework to be organized for long-term finance sustainability, prioritizing actions of operation and maintenance and scheduling expansion projects for latter in the planning horizon. While even the lower fees could resolve the operation costs associated with sewers and polders, higher fees would still be necessary to fully cover maintenance costs and some of the expansion costs. The positive cash flow towards the end of the planning horizon indicates potential for leveraging future revenues.

This study presents a new method to incorporate the No Net Loss (NNL) principle within corporate Environmental, Social, and Governance (ESG) frameworks. This principle aims to ensure that biodiversity losses from human activities are fully offset. In this context, we tackle two main challenges: managing epistemic uncertainties in environmental modeling and accurately assessing compensatory areas needed to replace lost habitats. Focusing on Brazil’s diverse biomes, which are undergoing rapid changes, we highlight the role of expert opinion surveys in addressing the uncertainties of the InVEST Habitat Quality, a model that simulates changes in landscape integrity under different land use scenarios. Our analysis across three of Brazil’s regions – Caatinga Semi-arid, Cerrado Savanna, and Atlantic Forest – leverages open-source data to reveal substantial habitat losses due to activities like wind farm development, mining, and intensive agriculture, leading to a widespread decline in habitat quality. We introduce the Equivalent Biodiversity Area (EBA) metric to support NNL and Net Gain of Biodiversity efforts, measured in hectares. Findings show a reduction in EBA across all studied areas, highlighting the need for effective compensation strategies. Such strategies should merge Legal Reserves and ecological restoration into ESG policies, encourage landholder collaboration, and align with larger environmental efforts, such as watershed revitalization and Biodiversity Credits markets.

This paper proposes a dual-feedback process that links watershed plan actions with raw water charges. A dedicated decision support model is created to implement this process and allow long-term financial sustainability analysis. The model offers real-time analysis of various watershed actions using customizable prioritization criteria integrated with different water pricing configurations, including user-polluter pays and beneficiary-pays principles, as well as other funding sources. Application to the Piracicaba–Capiravi– Jundiaí Basins in Brazil shows how important water management and water quality improving actions can be funded through water charges and how finance gaps can be resolved through a shared Vision Modelling approach.

Hydrological models are useful to support ecosystem services restoration. However, when planning the expansion of Nature-based Solutions and Payments for Ecosystem Services, there are requirements including the principle of additionality, representation of multiple runoff mechanisms and calculation of farm-scale spatial outputs and epistemic uncertainty. While addressing these aspects is important to make future planning more effective (investment costs and water benefits) it is also challenging. This paper integrates, in a single modeling framework, the main requirements highlighted. This allows an improved selection of top priority areas with farm-scale spatial resolution and a deeper understanding of how epistemic modeling uncertainty affects the results, which is relevant to evaluate the risks of overestimating ecosystem services benefits. The modeling approach is demonstrated in a case study watershed in the Atlantic Forest biome (Brazil). The PLANS model is introduced, which uses the design of TOPMODEL to simulate both simulates both saturation-excess and infiltration-excess runoff at the farm-scale resolution. Also, it uses a novel saturation index based in a composition of Height Above the Nearest Drainage and Topographical Wetness Index terrain descriptors. We applied the Generalized Likelihood Uncertainty Estimation method, aided by an evolutionary algorithm, to estimate output epistemic uncertainty. Results show that uncertainty substantially affects priority definition (97% ranking change), and that simulated topographic effects can overcome local effects of land cover and soil type. With better data, uncertainty evaluation indicates that the restoration program in the study case could have the cost of its allocation policy reduced by up to 27%, showing that it can be made more cost-effective with the methods proposed.

In this paper we justify and exemplify four principles that we believe are fundamental to guide the use of hydrological models in the mapping of priority areas in watershed revitalization programs. These principles are: (1) the additionality of ecosystem services; (2) the influence of topography; (3) the spatial scale at the rural lot level, and; (4) the epistemic uncertainty of modeling. With the application of the PLANS model in the Arroio Castelhano (RS) basin, we explored the concept of hydrological anomaly, the importance of the variable contribution area, the relevance of differentiating rural lots and that hydrological models are not “crystal balls”, presenting uncertainty bands in time and space. Uncertainty information, however, can be very useful for defining a priority index for rural lots.

How and when to upscale and finance nature-based solutions in watersheds in order to improve downstream urban water security is a global concern. In this paper we address such challenge by providing a novel method for planning the expansion of a chosen set of nature-based solutions that couples optimization of sequential decision-making, hydrology modelling and hydroeconomics in a single modeling framework. The benefits were considered the avoided costs of water scarcity and water treatment perceived downstream. The optimal expansion schedule of decisions was then defined under the objective function of minimizing total cost. We demonstrated the framework by applying it to a set of benchmark alternative scenarios for the Sinos River watershed (Brazil). We found that the optimal schedule of nature-based solutions expansion is sensitive to the initial land use and future drivers. Treatment cost reduction was the greatest feature in some scenarios, confirming it as a strategy for addressing water quality issues of degraded watersheds. But the accounting of water scarcity cost introduced a tradeoff: expansion of nature-based solutions in well-preserved watersheds may not worth the investment. Future research may improve current limitations in scope and models without structural changes in the framework. Practical implications of this work arise from the funding of watershed payments for environmental services projects by institutions and governments, which demand evidence-based policies to support investment of public resources.

Technological hazard assessments are extremely rare in Brazil, despite their importance for planning. Aquatic systems are of particular concern, since they are the endpoint of every process occurring in the watershed, including technological disasters. Thus, our goal is to map the technological hazard vulnerability in lagoon systems though a geographic information systems (GIS) model. The technological hazard vulnerability model consists of the spatial overlapping of technological pressure and fragility, having environmental systems as spatial units. The methodology was applied to the lagoon systems of the Rio Grande do Sul State, Southern Brazil, as a case study. The very high vulnerability of the Northern Guaíba Lake is due to the high concentration of technological infrastructures combined with high fragilities of wetland systems. In the Patos Lagoon Estuary, highly vulnerable systems consist mostly in shallow waters. The Mirim Lagoon was less vulnerable compared to other systems, due to a much smaller occurrence of elements of technological pressure. The proposed methodology allowed for the identification of environmental systems particularly vulnerable to technological hazards, where management efforts must be more intense. The results were used for the Ecological-Economic Zoning of the Rio Grande do Sul, as well as to revise the water quality framework of the Patos Lagoon estuary, currently underway.