Enhancing Environmental Management through GLDAS Data and Trend Analysis Techniques

Código

I-EBHE0065

Autores

Welber Ferreira Alves, Juliana Oliveira Bartolomeu, Jéssica Soares da Rocha

Tema

WG 1.09: Effective Aquifer Governance for Agriculture

Resumo

The application of satellite imagery in environmental management has emerged as a critical tool in addressing contemporary ecological challenges. The integration of satellite-based data, particularly from the Global Land Data Assimilation System (GLDAS), has significantly enhanced our ability to monitor, model, and manage environmental systems. GLDAS products, which provide high-resolution, near-real-time terrestrial data, offer invaluable insights into land surface conditions, hydrological cycles, and climate dynamics. One of the key applications of GLDAS products in environmental management is the assessment and management of water resources. Accurate information on soil moisture, groundwater storage, and surface runoff is crucial for water resource planning, especially in regions prone to droughts or floods. GLDAS data facilitate the monitoring of these variables, enabling the identification of trends and anomalies that may signal impending water shortages or surpluses. Trend analysis techniques, such as the Mann-Kendall test, play a significant function in interpreting GLDAS data. The Mann-Kendall test is a non-parametric method used to identify trends in time series data, making it particularly suitable for environmental data, which often exhibit non-linear and non-normal distributions. Hence, the combination of GLDAS products and trend analysis enhances the ability to forecast future environmental conditions and develop proactive management plans. This paper explores the pivotal role of GLDAS in environmental management, emphasizing its utility in assessing water resources. The main objective is to apply the Mann-Kendall test to GLDAS data related to the soil profile and groundwater to investigate trends in recharge water rates over the last two decades (2003-2023) in the Federal District, Brazil?s capital. By applying the Mann-Kendall test to GLDAS products, researchers can detect significant trends in environmental variables, such as increasing soil moisture deficits or declining groundwater levels, which can compromise water management, especially in regions where agriculture is dependent on it. Autocorrelation was also verified through the series, and based on that, either the original Mann-Kendall test or a modified Mann-Kendall test was chosen. The analysis of GLDAS data revealed important trends in soil moisture and groundwater levels over the past two decades, highlighting the utility of satellite-based observations in environmental management. The presence of autocorrelation within the data series necessitated the use of a modified Mann-Kendall test, ensuring the robustness and reliability of the trend analysis. The results indicated a consistent decreasing trend in both soil moisture and groundwater levels, albeit with varying slopes, underscoring the urgency of implementing sustainable water management practices in agriculture. These findings emphasize the importance of integrating high-resolution satellite data and advanced trend analysis techniques in environmental monitoring. As ecological challenges continue to intensify, the ability to accurately detect and interpret trends becomes increasingly vital for the development of effective and adaptive environmental management strategies. The comprehensive insights provided by GLDAS products, coupled with sophisticated analytical methods, offer a powerful framework for understanding and mitigating the impacts of environmental change, thereby supporting resilience and sustainability in resource management.