Integrated modeling of land use and climate change in watersheds: assessment of impacts on ecosystem services and water quality

• Grant number: 24/18380-9
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: May 01, 2025
• End date: July 31, 2027
• Field of knowledge: Agronomical Sciences - Agricultural Engineering - Soil and Water Engineering
• Principal Investigator: Glauco de Souza Rolim
• Grantee: Polyana Pereira
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil

Abstract

The Watersheds of the Piracicaba, Capivari, and Jundiaí Rivers (PCJ), covering a total area of 15,377 km², are located in one of the most densely populated and industrialized regions of Brazil. These watersheds face significant challenges due to urban expansion and the intensification of agricultural and industrial activities. Additionally, climate change further increases the pressure on water quality, highlighting the urgency of effective water management. This study proposes the innovative development of an integrated model to predict the future water quality in the PCJ watersheds, based on the integration of multiple data sources and modeling approaches. Geographic data will be utilized, including digital elevation models, soil information, conservation units, proximity to watercourses and urban centers, as well as land use and cover patterns, environmental data, climate change scenarios, and socioeconomic contexts (such as municipal Gross Domestic Product by sector, agricultural production, and licensed activities), along with chemical parameters of water quality. Simulations of land use and cover for the years 2033, 2043, and 2053 will be carried out using the PLUS model, grounded in socioeconomic scenarios. Climate projections from the Shared Socioeconomic Pathways (SSP), derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6), will be associated with these simulations, forming a dataset that unifies socioeconomic, climatic, and land use aspects. This dataset will be applied to LSTM and Random Forest algorithms to model the water quality parameters, which will be used in the calculation of the following Water Quality Indices (WQIs): NSF Water Quality Index (WQINSF), Raw Water Quality Index for Public Supply (RWQIP), Water Quality Index for Aquatic Life Protection (WQA), and the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI). The spatio-temporal variability of ecosystem services related to water will be assessed using the InVEST platform, providing a comprehensive view of environmental impacts and ecological functions in the region. The results of this study will enable the identification of critical areas, anticipation of potential impacts, and the proposal of mitigation and adaptation measures. Thus, the developed model will serve as a valuable tool to support the formulation of public policies and conservation strategies, ensuring the sustainability of water resources in the PCJ watersheds in the face of increasing anthropogenic pressures and climate change.