Aquatic publication review (28)

Water is one of the most precious resources on Earth, and climate change, pollution and intensive use of natural resources are forcing us to find new solutions to protect it. From innovative purification technologies to satellite tools for monitoring droughts to methods for predicting floods and protecting aquatic ecosystems, science is constantly providing new ideas.

In this review of publications, we discuss research that introduces novel approaches to water conservation. From effective treatment using biocarbon and wood chips, to advanced drought monitoring using satellite technology, to comparing artificial intelligence methods in accurate flood forecasting. We also highlight the ways in which fishing communities are adapting to changing climatic conditions and the difficulties of monitoring food resources in river ecosystems.

1. study combines woodchips and biochar to clean water of pharmaceuticals, nutrients

University of Illinois College of Agricultural, Consumer and Environmental Sciences (2024), Study combines woodchips and biochar to clean water of pharmaceuticals, nutrients. Science Daily.

Faced with the growing problem of water pollution from pharmaceuticals and excess nutrients, scientists have developed an innovative treatment method using a combination of wood chips and biocarbon.

This combination can effectively reduce pollution levels. Due to its porous structure, biocarbon has a large adsorptive surface area, which facilitates the retention of contaminants. Wood chips, on the other hand, are a natural material that supports the purification process by increasing the efficiency of the biocarbon. The results of laboratory and field tests suggest that this method could find wide application in practice, especially in agricultural areas where pharmaceuticals and nutrients are often flushed into ground and surface water.

2. A new Multivariate Drought Severity Index to identify short-term hydrological signals: case study of the Amazon River basin

Lenczuk A., Ndehedehe C., Klos A., Bogusz J. (2024). A new Multivariate Drought Severity Index to identify short-term hydrological signals: case study of the Amazon River basin. Remote Sensing of Environment, 315, 15, 2024, 114464.

The Amazon basin has begun using an innovative Drought Severity Index (MDSI), which uses advanced satellite data and GPS observations to monitor hydrological changes. The index analyzes the vertical displacement of the Earth’s crust with the help of GPS measurements, as well as data from the GRACE mission, which tracks changes in the Earth’s gravitational field, allowing precise assessment of water resource levels. The MDSI shows high consistency with traditional climate indicators such as the Standard Precipitation Index (SPI) and the Drought Index (SPEI), but offers the ability to analyze hydrological dynamics.

The index is based on an advanced mathematical model, the Frank Dome, which combines GPS-DSI and GRACE-DSI data, enabling the identification of hydrological events with higher accuracy than traditional methods. MDSI can extract more drought and flood events, providing a detailed picture of the water situation in the Amazon region. In addition, the new index has proven to be highly consistent with actual river flow data, demonstrating its reliability and accuracy. The use of MDSI gives specialists a more comprehensive tool for analyzing extreme hydrological events, which is crucial for water resources management and decision-making in the face of climate change in the Amazon region.

3. reservoir-based flood forecasting and warning: deep learning versus machine learning

Sooyeon Yi, Jaeeung Yi (2024). Reservoir-based flood forecasting and warning: deep learning versus machine learning. Applied Water Science (2024) 14:237.

Floods are one of the most serious water-related hazards, especially in areas prone to rapid precipitation or snow melt. Traditional forecasting methods, based on hydrological models, are often too imprecise to effectively predict their timing and intensity. Developments in artificial intelligence are opening up new opportunities for flood forecasting, particularly through the use of deep learning and machine learning technologies.

The study, published in Applied Water Science, focuses on improving flood forecasting in urban areas. It was conducted in the Han River Basin in Seoul, South Korea, to compare the effectiveness of several flood forecasting models based on data from different watersheds. The authors tested both non-depth learning (random (RF) and support vector regression (SVR)) and deep learning (LSTM and GRU) models, with the best results using GRU in a scenario involving three reservoirs with long lead times.

The study’s authors concluded that the optimal approach is to use a two-stage forecast model: initial forecasts should be based on data from several reservoirs to ensure a long lead time, while closer to the anticipated flood event, more accurate forecasts can be based on a single reservoir. This approach enables faster issuance of warnings and better preparation for potential evacuation, allowing authorities to respond more effectively and reduce the risk of flooding and damage to urban areas.

4. Not All Those Who Wander Are Lost – Responses of Fishers’ Communities to Shifts in the Distribution and Abundance of Fish

Papaioannou E.A., Selden R.L., Olson J., McCay B.J., Pinsky M.L. and St. Martin K. (2021) Not All Those Who Wander Are Lost – Responses of Fishers’ Communities to Shifts in the Distribution and Abundance of Fish. Front. Mar. Sci. 8:669094.

Climate change is not only affecting terrestrial ecosystems, taking the form of drought or flooding, but also marine environments, where changes in temperature and water levels have a direct impact on the behavior of marine organisms. Fishing communities, which have benefited from the resources of the seas and oceans for generations, are facing challenges related to fish migration, changes in fish abundance and fishing conditions.

A new study shows how fishermen can adjust their fishing practices using spatial mapping of the sea. The technology allows them to track changes in marine ecosystems and select fishing sites to minimize their environmental impact. Spatial mapping takes into account changes in water temperature, resource availability and fish migration, allowing fishing communities to better plan their activities and avoid areas at risk of overfishing. Adapting to changing climate conditions is crucial to the future of fishing and the sustainable use of marine resources.

5. food for fish: Challenges and opportunities for quantifying foodscapes in river networks

Ouellet V., Fullerton A. H., Kaylor M., Naman S., Bellmore R., et al. (2024). Food for fish: Challenges and opportunities for quantifying foodscapes in river networks. WIREs Water. 2024; e1752.

River ecosystems play a key role in maintaining diverse food chains, providing food resources for fish. However, accurately monitoring and quantifying food resources such as plankton, small invertebrates and detritus is challenging, especially in the face of climate change. A study published in WIREs Water provides a detailed analysis of the difficulties encountered and the opportunities for surveying and managing food resources in river networks.

The authors develop the concept of foodscapes, focusing on three key components: food abundance, availability and quality. They attempted to answer three fundamental questions: why it is difficult to estimate food availability, the consequences of uncertainty in these estimates, and what methods exist or are developing to quantify food resources. Their study emphasized the importance of accurate data and a better understanding of the role of food in fish survival, especially in the context of changing water temperatures.

Modern techniques are described, such as environmental DNA (eDNA) analysis, which allows species present in rivers to be identified from water samples. This method offers great potential for monitoring biodiversity and food resources, enabling more precise determination of food availability for fish. In addition, advanced hydrodynamic models make it possible to predict how water flows and changing river morphology affect the distribution of food in different parts of the river network.

The study’s conclusions can contribute to better management of river ecosystems, as well as support efforts to protect biodiversity and sustainability of fish populations in times of climate change and increased environmental stress.