Journal of Watershed Ecology Open Access

Why Watershed Ecology?

Integrating Copernicus Earth Observation and Artificial Intelligence for Habitat Suitability Modeling of Pinctada radiata in Semi-Enclosed Coastal Watersheds of Central Greece

Semi-enclosed coastal systems are highly dynamic environments where benthic organisms are exposed to strong hydrographic gradients and increasing anthropogenic pressures. This study assessed the habitat suitability of the pearl oyster Pinctada radiata in two contrasting Mediterranean gulfs of Central Greece, the Maliakos and the South Evoikos, by integrating Copernicus Earth Observation (EO) products with an Artificial Intelligence (AI) modeling framework. Environmental variables, including sea surface temperature, salinity, chlorophyll-a concentration, current velocity, and dissolved oxygen, were derived from satellite and marine datasets and used to train a multi-algorithm ensemble combining Maximum Entropy (MaxEnt), Extreme Gradient Boosting (XGBoost), and a Convolutional Neural Network (CNN). The ensemble model showed strong predictive skill (AUC = 0.94; TSS = 0.80) and identified temperature, dissolved oxygen, and substrate type as the main drivers of habitat suitability. Spatial projections indicated that roughly two-thirds of the study area currently supports favorable conditions for P. radiata, particularly in shallow, low-energy, mesotrophic zones. Under a simulated +2 °C warming scenario, highly suitable habitats declined by about 20%, highlighting the species’ sensitivity to future thermal stress and subsequent oxygen depletion, demonstrating the value of EO-driven AI approaches for anticipating ecological change in vulnerable coastal systems.

BMAA-Producing Cyanobacteria and Fish Contamination in Italy: An Emerging One Health Concern

β-N-methylamino-L-alanine (BMAA), a non-proteinogenic amino acid produced by various cyanobacteria, has emerged as a significant concern in the context of the One Health framework due to its neurotoxic effects and potential ecological and public health implications. Cyanobacteria, found ubiquitously in freshwater, marine, and terrestrial environments, can contaminate water sources and food chains with different toxins, including BMAA, which can produce a sinergic action with other environmental neurotoxic contaminants (such as Methylmercury) and other cyanotoxins, such as Microcystins. Human exposure occurs primarily through the consumption of contaminated drinking water and aquatic food products. BMAA accumulation in neural tissues has been linked to the degeneration of motor neurons and the formation of neurofibrillary tangles, mimicking pathological features observed in amyotrophic lateral sclerosis (ALS) and Alzheimer’s disease. This exposure is associated with a spectrum of symptoms, collectively termed ALS/parkinsonism dementia complex (ALS/PDC), characterized by progressive muscular paralysis, rigidity, cognitive decline, and ultimately, fatal outcomes. The increasing prevalence of cyanobacteria blooms, driven by climate change and anthropogenic factors, underscores the urgent need for comprehensive research into BMAA toxicity, environmental monitoring, and mitigation strategies. This work shows BMAA contamination data of fish fauna living in several Italian lakes affected by recurrent cyanobacterial blooms, quantified by Elisa Assay. It also explores the emerging issue of BMAA contamination from a One Health perspective, highlighting its multifaceted impact on ecosystems, animal health, and human well-being.

Comparing Drone and Satellite DEMs for Hydrodynamic Flood Modeling in a Rural Brazilian Catchment

The rural region of the municipality of Bananal (SP, Brazil) experiences recurrent flooding events associated with rising water levels in tributaries of the Bananal River, especially during periods of intense rainfall. This study aimed to compare the performance of different Digital Elevation Models (DEMs), one derived from NASA orbital data and another generated from drone-based aerophotogrammetric surveys, in identifying and mapping flood-prone areas. The objective was to assess whether drone field campaigns are essential for this type of analysis or whether orbital DEMs are sufficient for the hydrodynamic characterization of the area. Hydrodynamic models were developed using the software QGIS, HidroFlu—for watershed parametrization and inflow estimation, and MODCEL—for hydrodynamic simulation, with spatial resolutions of 10 m, 30 m, and 50 m, in order to analyze the impact of topographic detail on simulation results. Two approaches were tested for defining boundary conditions: one based on precipitation data with a 25-year return period, and another based on the Bananal River discharge estimated from the watershed. The results indicated that the model based on the drone-derived DEM, with 10 m resolution and boundary conditions defined by river discharge, showed the best performance in representing floodable areas. However, the findings also highlight that high-resolution DEMs entail higher operational costs, due to the need for field activities and greater computational capacity to run the simulations.

A Reproducible R–Fortran Toolkit for Groundwater Flow and Contaminant Transport Modeling in Watershed Applications

Uncertainty and calibration are major challenges in hydrologic and hydraulic analysis, especially in watershed applications involving groundwater flow and contaminant transport. This study presents an integrated modeling framework for comprehensive simulation of groundwater flow and contaminant transport, with automated calibration and sensitivity analysis capabilities. The framework extends traditional Fortran-based modeling by incorporating the statistical, numerical, and visualization strengths of the R environment. In the proposed approach, the Fortran code is executed within R, while the Fortran program employs a finite-volume time-splitting method to discretize the governing equations of groundwater flow and contaminant transport. Integration with R statistical packages improves model calibration, sensitivity evaluation, and visualization of groundwater contamination results. To illustrate the applicability of the framework, two test cases of groundwater flow and contaminant transport through porous media were conducted. Results demonstrate the accuracy, efficiency, and enhanced visualization capabilities of the integrated system. Ultimately, the framework is intended to support three-dimensional analysis of pollution plume evolution in heterogeneous media and to investigate interactions among multiple contaminant sources in watershed systems.

Holdiversity (和多样性): An Integrative Concept Toward Sustainability

Facing the multiple challenges brought about by global change and social development, this paper proposes the conceptual framework of “Holdiversity (和多样性)”, which defines human diversity, biological diversity, and environmental diversity as an interdependent, co-evolving, coupled system. This approach aims to systematically comprehend the synergistic mechanisms between humans and nature, facilitating the construction of trade-off strategies for sustainable development. Furthermore, this paper proposes that the watershed can serve as a fundamental operational unit for Holdiversity research. Its distinct natural boundaries and hierarchical structure enable it to effectively carry the spatial superposition and feedback coupling of multiple diversities. This concept aims to provide an integrated framework for interdisciplinary research and to offer a novel perspective on implementing the United Nations Sustainable Development Goals (SDGs).

Driftless Area Streams in Karstic Agricultural Watersheds: Best Management Practices, Biotic Integrity, and Environmental Stressors

To protect streams in agricultural watersheds, best management practices (BMPs) are implemented to reduce or prevent contaminated runoff from reaching surface waters. Over the course of three growing seasons (2000–2002), this study assessed physical, chemical, and biological indicators of water quality at 13 total stream sites in two agricultural watersheds (Garvin Brook, Whitewater River) in southeastern Minnesota USA, where BMPs have been used for over 50 years prior to the study period. Some sites in both watersheds exhibited impaired water quality due to high turbidities, high levels of total suspended solids (TSS) and fecal coliform bacteria, and low fish and benthic macroinvertebrate biotic integrities. Non-metric multi-dimensional scaling of water quality indicators and principal components analysis of fish and invertebrate communities highlighted varying degrees of differences between watersheds. On average, Garvin watershed sites exhibited better water quality during 2000–2002 than sites in the Whitewater watershed, likely because more headwater reaches were surveyed in Garvin Brook. A fish community index biotic integrity (IBI) was significantly negatively correlated with turbidities, TSS, and fecal coliform bacteria levels, but the benthic macroinvertebrate community IBI was not correlated to any water quality indicator or to the fish IBI. More recent studies in these watersheds and current impaired waters listings continue to indicate significant and ongoing water quality issues, so continued water quality monitoring is needed in these two watersheds to highlight and prioritize problematic subwatersheds for future conservation efforts to reduce or prevent agriculture-related runoff from reaching the stream networks.

Impacts of Climate Variability and Change on Hydrological Dynamics in the Koliba-Corubal Basin (Guinea and Guinea-Bissau): Modelling Historical and Future Flows by GR4J under CMIP6 Climate Scenarios

The Koliba-Corubal basin, located between Guinea and Guinea-Bissau, is a key area for water resource management, but it is vulnerable to the effects of climate change. This article aims to analyze historical and future hydrological trends in this basin using the GR4J hydrological model in order to assess the impact of climate change on water availability. The study is based on past climate data (1981–1993) and future projections from CMIP6 climate models, applied to three climate change scenarios: SSP 126, SSP 370, and SSP 585. The results show a significant decrease in river flows in the basin, with reductions of up to 65.6% by the end of the century, especially under the SSP 370 and SSP 585 scenarios. Dry periods are especially affected, with a marked decline in monthly flows, seriously impacting water resource management for agriculture and drinking water supply. Using Mann-Kendall and Pettitt statistical tests, the study also identifies potential breaks in the time series of flows. The results of this analysis highlight the urgency of adopting climate change adaptation strategies and the need for sustainable water resource management in the Koliba-Corubal basin to meet the challenges posed by these changes.

Unsustainable River Management Will Prevent the Achievement of the SDGs

River ecosystems sustain socio-economic development via the provision of essential ecosystem services, which are of direct relevance to achieving the Sustainable Development Goals (SDGs). A paradigm shift in river management over the last 30 years, away from engineered channels that predominantly increase drainage efficiency, towards more restorative and holistic approaches that integrate hydrological, geomorphological, and ecological systems, makes this an ideal time to reflect on both the successes and future trajectories in river ecosystem management. Therefore, we synthesize published research on river ecosystems within the SDG framework using a suite of knowledge visualization tools. Co-occurrence analysis reveals that research in river ecosystem science can be broadly split into three themes: water quality, water flow, and aquatic organisms, and that most published work spans more than one of these themes. Co-word network evolution reveals a significant increase over the past decade in research on climate change, emerging pollutants, and the dynamics of riparian communities. Regions with different levels of socio-economic development exhibit markedly different research priorities. Correlation analysis between article keywords and the SDGs reveals synergies and trade-offs between river ecosystems and the achievement of 130 of the targets. Under the SDGs framework, these findings highlight frontier research priorities and provide a knowledge base to support the sustainable management of river ecosystems in the face of future challenges.

Influence of Nutrient Enrichment and Temperature on Aquatic Invertebrate Communities in a Tropical Riverine System in Kenya

One of the major concerns in freshwater ecosystems is nutrient enrichment from human sources, which causes significant effects on aquatic biodiversity and ecological functioning. This study, therefore, investigated the order and family levels of Odonata, Diptera, and Coleoptera responses to nutrient enrichment along River Kiminini, Trans-Nzoia County, Kenya. Field sampling was conducted from July to September 2023. Duplicate water samples were taken from ten sampling stations labelled (S1–S10), twice a month for three months. The concentrations of nitrate–nitrogen and phosphate–phosphorus were measured calorimetrically using standard procedures; the Ascorbic Acid method for phosphates–phosphorus and the Brucine method for nitrates–nitrogen. A spectrophotometer was used to measure absorbance. A standard kick net was used at each station to collect the macroinvertebrates (Odonata, Diptera, and Coleoptera). Using an updated taxonomic key, the macroinvertebrate samples were sorted and identified to their family level under a dissecting microscope, and abundance counts were made. Direct field observations were used to record human activity at each station. The R programming language was used to conduct all statistical analyses. The water quality status for each station was determined using the Nutrient Pollution Index, which was calculated based on ecologically relevant nutrient thresholds. The Nutrients Pollution Index scores ranged from 9.66 (S5) to 17.2 (S3). All the stations were greater than 6, indicating very high pollution levels and a significant risk of eutrophication. At the family level, Dytiscidae, Coenagrionidae, and Lestidae were abundant in less polluted stations and fewer in highly polluted stations. For instance, Coenagrionidae had the highest numbers in station S1 (32) and declined drastically in the highly polluted station S9 (3). The same trend was observed for Lestidae, with the highest numbers in stations S1 and S2 (21) and declining in station S9 (1). Dytiscidae also had higher numbers in the relatively less polluted station S7 (10) and lowest in the highly polluted station S3 (1). On the other hand, Chironomidae was observed to be tolerant to organic pollution. Chironomidae had their highest numbers in station S9 (30) and declined in moderately cleaner stations S5, S6, and S8, which had a similar record of 6 organisms. According to the findings, it is necessary to enhance biomonitoring and guide riverine management plans under nutrient stress and increasing water temperatures by incorporating functional and taxonomic diversity into water quality assessments.

Why Watershed Ecology?

Driftless Area Streams in Karstic Agricultural Watersheds: Best Management Practices, Biotic Integrity, and Environmental Stressors

To protect streams in agricultural watersheds, best management practices (BMPs) are implemented to reduce or prevent contaminated runoff from reaching surface waters. Over the course of three growing seasons (2000–2002), this study assessed physical, chemical, and biological indicators of water quality at 13 total stream sites in two agricultural watersheds (Garvin Brook, Whitewater River) in southeastern Minnesota USA, where BMPs have been used for over 50 years prior to the study period. Some sites in both watersheds exhibited impaired water quality due to high turbidities, high levels of total suspended solids (TSS) and fecal coliform bacteria, and low fish and benthic macroinvertebrate biotic integrities. Non-metric multi-dimensional scaling of water quality indicators and principal components analysis of fish and invertebrate communities highlighted varying degrees of differences between watersheds. On average, Garvin watershed sites exhibited better water quality during 2000–2002 than sites in the Whitewater watershed, likely because more headwater reaches were surveyed in Garvin Brook. A fish community index biotic integrity (IBI) was significantly negatively correlated with turbidities, TSS, and fecal coliform bacteria levels, but the benthic macroinvertebrate community IBI was not correlated to any water quality indicator or to the fish IBI. More recent studies in these watersheds and current impaired waters listings continue to indicate significant and ongoing water quality issues, so continued water quality monitoring is needed in these two watersheds to highlight and prioritize problematic subwatersheds for future conservation efforts to reduce or prevent agriculture-related runoff from reaching the stream networks.utf-8

Holdiversity (和多样性): An Integrative Concept Toward Sustainability

Facing the multiple challenges brought about by global change and social development, this paper proposes the conceptual framework of “Holdiversity (和多样性)”, which defines human diversity, biological diversity, and environmental diversity as an interdependent, co-evolving, coupled system. This approach aims to systematically comprehend the synergistic mechanisms between humans and nature, facilitating the construction of trade-off strategies for sustainable development. Furthermore, this paper proposes that the watershed can serve as a fundamental operational unit for Holdiversity research. Its distinct natural boundaries and hierarchical structure enable it to effectively carry the spatial superposition and feedback coupling of multiple diversities. This concept aims to provide an integrated framework for interdisciplinary research and to offer a novel perspective on implementing the United Nations Sustainable Development Goals (SDGs).utf-8

Unsustainable River Management Will Prevent the Achievement of the SDGs

River ecosystems sustain socio-economic development via the provision of essential ecosystem services, which are of direct relevance to achieving the Sustainable Development Goals (SDGs). A paradigm shift in river management over the last 30 years, away from engineered channels that predominantly increase drainage efficiency, towards more restorative and holistic approaches that integrate hydrological, geomorphological, and ecological systems, makes this an ideal time to reflect on both the successes and future trajectories in river ecosystem management. Therefore, we synthesize published research on river ecosystems within the SDG framework using a suite of knowledge visualization tools. Co-occurrence analysis reveals that research in river ecosystem science can be broadly split into three themes: water quality, water flow, and aquatic organisms, and that most published work spans more than one of these themes. Co-word network evolution reveals a significant increase over the past decade in research on climate change, emerging pollutants, and the dynamics of riparian communities. Regions with different levels of socio-economic development exhibit markedly different research priorities. Correlation analysis between article keywords and the SDGs reveals synergies and trade-offs between river ecosystems and the achievement of 130 of the targets. Under the SDGs framework, these findings highlight frontier research priorities and provide a knowledge base to support the sustainable management of river ecosystems in the face of future challenges.utf-8

Impacts of Climate Variability and Change on Hydrological Dynamics in the Koliba-Corubal Basin (Guinea and Guinea-Bissau): Modelling Historical and Future Flows by GR4J under CMIP6 Climate Scenarios

The Koliba-Corubal basin, located between Guinea and Guinea-Bissau, is a key area for water resource management, but it is vulnerable to the effects of climate change. This article aims to analyze historical and future hydrological trends in this basin using the GR4J hydrological model in order to assess the impact of climate change on water availability. The study is based on past climate data (1981–1993) and future projections from CMIP6 climate models, applied to three climate change scenarios: SSP 126, SSP 370, and SSP 585. The results show a significant decrease in river flows in the basin, with reductions of up to 65.6% by the end of the century, especially under the SSP 370 and SSP 585 scenarios. Dry periods are especially affected, with a marked decline in monthly flows, seriously impacting water resource management for agriculture and drinking water supply. Using Mann-Kendall and Pettitt statistical tests, the study also identifies potential breaks in the time series of flows. The results of this analysis highlight the urgency of adopting climate change adaptation strategies and the need for sustainable water resource management in the Koliba-Corubal basin to meet the challenges posed by these changes.utf-8

Influence of Nutrient Enrichment and Temperature on Aquatic Invertebrate Communities in a Tropical Riverine System in Kenya

One of the major concerns in freshwater ecosystems is nutrient enrichment from human sources, which causes significant effects on aquatic biodiversity and ecological functioning. This study, therefore, investigated the order and family levels of Odonata, Diptera, and Coleoptera responses to nutrient enrichment along River Kiminini, Trans-Nzoia County, Kenya. Field sampling was conducted from July to September 2023. Duplicate water samples were taken from ten sampling stations labelled (S1–S10), twice a month for three months. The concentrations of nitrate–nitrogen and phosphate–phosphorus were measured calorimetrically using standard procedures; the Ascorbic Acid method for phosphates–phosphorus and the Brucine method for nitrates–nitrogen. A spectrophotometer was used to measure absorbance. A standard kick net was used at each station to collect the macroinvertebrates (Odonata, Diptera, and Coleoptera). Using an updated taxonomic key, the macroinvertebrate samples were sorted and identified to their family level under a dissecting microscope, and abundance counts were made. Direct field observations were used to record human activity at each station. The R programming language was used to conduct all statistical analyses. The water quality status for each station was determined using the Nutrient Pollution Index, which was calculated based on ecologically relevant nutrient thresholds. The Nutrients Pollution Index scores ranged from 9.66 (S5) to 17.2 (S3). All the stations were greater than 6, indicating very high pollution levels and a significant risk of eutrophication. At the family level, Dytiscidae, Coenagrionidae, and Lestidae were abundant in less polluted stations and fewer in highly polluted stations. For instance, Coenagrionidae had the highest numbers in station S1 (32) and declined drastically in the highly polluted station S9 (3). The same trend was observed for Lestidae, with the highest numbers in stations S1 and S2 (21) and declining in station S9 (1). Dytiscidae also had higher numbers in the relatively less polluted station S7 (10) and lowest in the highly polluted station S3 (1). On the other hand, Chironomidae was observed to be tolerant to organic pollution. Chironomidae had their highest numbers in station S9 (30) and declined in moderately cleaner stations S5, S6, and S8, which had a similar record of 6 organisms. According to the findings, it is necessary to enhance biomonitoring and guide riverine management plans under nutrient stress and increasing water temperatures by incorporating functional and taxonomic diversity into water quality assessments.utf-8

BMAA-Producing Cyanobacteria and Fish Contamination in Italy: An Emerging One Health Concern

β-N-methylamino-L-alanine (BMAA), a non-proteinogenic amino acid produced by various cyanobacteria, has emerged as a significant concern in the context of the One Health framework due to its neurotoxic effects and potential ecological and public health implications. Cyanobacteria, found ubiquitously in freshwater, marine, and terrestrial environments, can contaminate water sources and food chains with different toxins, including BMAA, which can produce a sinergic action with other environmental neurotoxic contaminants (such as Methylmercury) and other cyanotoxins, such as Microcystins. Human exposure occurs primarily through the consumption of contaminated drinking water and aquatic food products. BMAA accumulation in neural tissues has been linked to the degeneration of motor neurons and the formation of neurofibrillary tangles, mimicking pathological features observed in amyotrophic lateral sclerosis (ALS) and Alzheimer’s disease. This exposure is associated with a spectrum of symptoms, collectively termed ALS/parkinsonism dementia complex (ALS/PDC), characterized by progressive muscular paralysis, rigidity, cognitive decline, and ultimately, fatal outcomes. The increasing prevalence of cyanobacteria blooms, driven by climate change and anthropogenic factors, underscores the urgent need for comprehensive research into BMAA toxicity, environmental monitoring, and mitigation strategies. This work shows BMAA contamination data of fish fauna living in several Italian lakes affected by recurrent cyanobacterial blooms, quantified by Elisa Assay. It also explores the emerging issue of BMAA contamination from a One Health perspective, highlighting its multifaceted impact on ecosystems, animal health, and human well-being.utf-8

Integrating Copernicus Earth Observation and Artificial Intelligence for Habitat Suitability Modeling of Pinctada radiata in Semi-Enclosed Coastal Watersheds of Central Greece

Semi-enclosed coastal systems are highly dynamic environments where benthic organisms are exposed to strong hydrographic gradients and increasing anthropogenic pressures. This study assessed the habitat suitability of the pearl oyster Pinctada radiata in two contrasting Mediterranean gulfs of Central Greece, the Maliakos and the South Evoikos, by integrating Copernicus Earth Observation (EO) products with an Artificial Intelligence (AI) modeling framework. Environmental variables, including sea surface temperature, salinity, chlorophyll-a concentration, current velocity, and dissolved oxygen, were derived from satellite and marine datasets and used to train a multi-algorithm ensemble combining Maximum Entropy (MaxEnt), Extreme Gradient Boosting (XGBoost), and a Convolutional Neural Network (CNN). The ensemble model showed strong predictive skill (AUC = 0.94; TSS = 0.80) and identified temperature, dissolved oxygen, and substrate type as the main drivers of habitat suitability. Spatial projections indicated that roughly two-thirds of the study area currently supports favorable conditions for P. radiata, particularly in shallow, low-energy, mesotrophic zones. Under a simulated +2 °C warming scenario, highly suitable habitats declined by about 20%, highlighting the species’ sensitivity to future thermal stress and subsequent oxygen depletion, demonstrating the value of EO-driven AI approaches for anticipating ecological change in vulnerable coastal systems.utf-8

Comparing Drone and Satellite DEMs for Hydrodynamic Flood Modeling in a Rural Brazilian Catchment

The rural region of the municipality of Bananal (SP, Brazil) experiences recurrent flooding events associated with rising water levels in tributaries of the Bananal River, especially during periods of intense rainfall. This study aimed to compare the performance of different Digital Elevation Models (DEMs), one derived from NASA orbital data and another generated from drone-based aerophotogrammetric surveys, in identifying and mapping flood-prone areas. The objective was to assess whether drone field campaigns are essential for this type of analysis or whether orbital DEMs are sufficient for the hydrodynamic characterization of the area. Hydrodynamic models were developed using the software QGIS, HidroFlu—for watershed parametrization and inflow estimation, and MODCEL—for hydrodynamic simulation, with spatial resolutions of 10 m, 30 m, and 50 m, in order to analyze the impact of topographic detail on simulation results. Two approaches were tested for defining boundary conditions: one based on precipitation data with a 25-year return period, and another based on the Bananal River discharge estimated from the watershed. The results indicated that the model based on the drone-derived DEM, with 10 m resolution and boundary conditions defined by river discharge, showed the best performance in representing floodable areas. However, the findings also highlight that high-resolution DEMs entail higher operational costs, due to the need for field activities and greater computational capacity to run the simulations.utf-8

A Reproducible R–Fortran Toolkit for Groundwater Flow and Contaminant Transport Modeling in Watershed Applications

Uncertainty and calibration are major challenges in hydrologic and hydraulic analysis, especially in watershed applications involving groundwater flow and contaminant transport. This study presents an integrated modeling framework for comprehensive simulation of groundwater flow and contaminant transport, with automated calibration and sensitivity analysis capabilities. The framework extends traditional Fortran-based modeling by incorporating the statistical, numerical, and visualization strengths of the R environment. In the proposed approach, the Fortran code is executed within R, while the Fortran program employs a finite-volume time-splitting method to discretize the governing equations of groundwater flow and contaminant transport. Integration with R statistical packages improves model calibration, sensitivity evaluation, and visualization of groundwater contamination results. To illustrate the applicability of the framework, two test cases of groundwater flow and contaminant transport through porous media were conducted. Results demonstrate the accuracy, efficiency, and enhanced visualization capabilities of the integrated system. Ultimately, the framework is intended to support three-dimensional analysis of pollution plume evolution in heterogeneous media and to investigate interactions among multiple contaminant sources in watershed systems.utf-8