Catchment Management Research Articles

CLAMity: Mixtures of agricultural pesticides as multiple stressors in a bivalve species

Pesticides play a vital role in ensuring global food security amid a growing global population; however, their movement away from application sites can pose significant risks to the health of non-target species. Pollution of freshwater is a key contributor to the high extinction rates of freshwater species, which often face exposure to a complex “cocktail” of pollutants simultaneously. A better understanding of pesticide interactions will enable more targeted policies and land management practices to mitigate environmental damage while ensuring food security. In this study, Corbicula fluminea (Asian clam) were exposed to binary pesticide mixtures commonly found in two rivers in the South of England. The exposures involved individual pesticides and mixtures at a concentration of 0.1μg/L per pesticide. Selected molecular markers were targeted and proved to be impacted by the timing and the pesticide mixture; an Integrated Biomarker Response (V2) value was also calculated. Our results show that both seasonality and the chemicals characteristics of the pesticides may significantly modulate their toxicity, both individually and in a mixture. When put into the context of catchment management this data combined with pesticide monitoring could improve estimating ecological risk. To the authors’ knowledge, this is the first study to assess the molecular responses of these mixtures in bivalve molluscs using the IBRv2 value following exposure to combined pesticides.

Impact of Forest Dieback on Hydrology and Nitrogen Export Using a New Dynamic Water Quality Model

AbstractForest status is crucial for catchment hydrology and water quality but is increasingly disturbed by human activities and climatic factors. Therefore, it is urgently necessary to develop water quality models that can adapt to these changes. This study used a new dynamic Hydrological Predictions for the Environment (HYPE) model to assess the effect of rapid and continuous forest changes on catchment hydrology and nitrogen export. The modified HYPE model was implemented for the 25 years period in the Große Ohe catchment in Germany, which has experienced severe forest dieback and recovery. Due to the stochastic nature of infestation events, data covering the entire process of forest change are rare. The modified HYPE model performed well at different scales for discharge and dissolved inorganic nitrogen (DIN) export. It was able to (a) capture the timing of peak flows and the seasonal DIN concentration dynamics and (b) reflect the initial increase and subsequent decrease trend in discharge and DIN export in accordance with forest dieback and regeneration. The increase in nitrogen export after forest dieback primarily resulted from reduced forest uptake and increased soil nitrogen availability from tree residues. The difference in runoff and nitrogen export increment with or without regeneration highlights the importance of forest regeneration in restoring catchment hydrology and water quality. Additionally, a decrease in DIN export after residue removal implies the impact of sound post‐disturbance management strategies. The dynamic modeling under changing catchment forests can enhance the analysis of catchment water quality and effectively support forest management.

Assessment of catchment water resources allocation under climate change in Luwombwa sub-catchment, Zambia

The uncertainty in climate change and high water demand pose pressure on the natural water resources supply. Not only does this require better understanding but also a call for immediate interventions, mitigation and adaptive measures. This study evaluates catchment water resources in the Luwombwa sub-catchment in Zambia through statistical analysis in the downscaling of past, present and future climatic variables from the CMIP6 climatic model. These variables are then integrated into WEAP - a semi-distributed hydrological and water evaluation model - to perform water demand and allocation scenario modelling. Mult-site calibration and validation were conducted on five selected micro-catchments within Luwombwa sub-catchment. The model performance was assessed usng the R2, NSE and PBIAS as the objective functions. Satisfactory values of 92 % for R2, 82 % for NSE and 6.9 % for PBIAS were achieved. This allowed for scenario modelling on water demand and allocation among competing users. Three future scenarios (2022–2050) were developed from the historical to baseline (1988–2022) and included state of water resources availability under climate change, expansion of irrigation area and impact of dam construction in the sub-catchment. The study reveals a decrease of 20 % in sub-catchment's water availability resulting from 9.3 % (equivalent to 4oC) rise in maximum temperature and 4.5 % reduction in rainfall within the entire sub-catchment. This is especially under the persistence of SSP370 climate variability scenario projections downscaled from four GCM models by the year 2050. The study further revealed that the change point for anticipated future climate extremes is likely to occur between 2027 and 2030. The results are indicative of downward trends in streamflow under climate change and socioeconomic development leading to increase in water value and water scarcity. The insights from the study are critical to inform formulation of effective catchment water resources management strategies such as the development of management plans and adapation measures in the face of climate change and the needs for different stakeholders involvement.

Runoff Dynamics and Soil Erosion Assessment using a SWAT Model at Upper Cauvery River Basin

The increasing availability of geospatial datasets on watershed characteristics and hydro-meteorological variables emphasises the importance of integrated hydrological models for effective catchment management. Climatic and physiographic determinants such as topography, land use, soil properties, and anthropogenic interventions substantially influence a catchment's hydrological equilibrium. The SWAT model was used to elucidate rainfall-runoff dynamics in the Upper Cauvery River Basin, Karnataka, India (36,682 km²), applying the SCS Curve Number (CN) method for runoff estimation. Runoff was estimated for 2012–2021 using rainfall data from the Indian Meteorological Department (IMD), soil data from the FAO, and land use/land cover and slope datasets.Soil erosion, exacerbated by intensified agricultural practices, was evaluated using the Revised Universal Soil Loss Equation (RUSLE) model integrated with Geographic Information Systems (GIS). The SWAT model results showed that runoff accounted for 15-20% of the total precipitation, with an annual soil loss of 2027.95 tons. The predominance of agricultural land use, covering 66.29% of the basin, significantly contributed to high runoff, whereas the forested areas (26.48%) demonstrated a low runoff potential. About 38% of the basin exhibited a very low soil loss risk, while 11% was classified as high risk and 9% as very high risk. The SWAT model is recognized for its robustness, and this research aims to leverage its capabilities to validate its effectiveness in estimating runoff and erosion, providing crucial insights for advancing sustainable catchment resource management.

Optimization of Neighborhood Public Space Design Based on Physical Environment Simulation and Crowd Simulation—A Case Study of Xiaomi’s Changping Campus

Digital technology has brought drastic changes to the design methods, values, and design tools of neighbourhood public spaces, thereby changing the behavioural patterns of people in neighbourhood public spaces. Therefore, people’s requirements for urban public space have changed and are characterised by high efficiency, high precision, humanization, and high aesthetics. Scholars at home and abroad have conducted many studies and practises on the application of digital technology to neighbourhood design, but there is a lack of systematic research practises on the use and analysis of multi-faceted data. This paper selects the Xiaomi Beijing Changping II design project, simulates and deduces the physical environment of its location, simulates the results of the natural environment by using the data of sunshine, wind, and water catchment in the physical environment, and then simulates the crowd’s action paths by combining kinetic algorithms and ant algorithms to optimise the design methods, processes, and results of the neighbourhood public space on the basis of this research. The research team designed five groups of programmes for the project based on different design methods and processes, and conducted a comparative study of the five groups of programmes through the hierarchical analysis method in conjunction with the fuzzy comprehensive evaluation method, as well as discussing them in conjunction with the actual bidding results of the project and the scoring conclusions of the industry experts. The results of the study show that the design scheme for neighbourhood public space based on physical environment simulation and crowd simulation is better able to take advantage of the analytical and predictive advantages of the technology and unite with the designer’s aesthetic interests, balancing the data objectivity and aesthetic subjectivity in the design process. The method is more likely to achieve a design solution that combines systematicity, foresight, rationality, and aesthetics, and provides an empirical case for the application of data simulation in public space, aiming to improve the rationality of public space design and solve the data-objective problems faced by the design of public space at this stage.

Comparative effect of traditional and collaborative watershed management approaches on flood components

AbstractIdentifying the critical areas of flood generation and determining the optimal measures for flood control and management (FCM) is one of the most important basics of watershed management. Therefore, the current study was carried out to prioritize sub‐watersheds (SWs) based on flood generation using physical (Ph‐MA), technical (Te‐MA), comanagerial (Com‐MA), and conjunct management approaches (Con‐MA), as well as determining the quantitative effects of the proposed FCM measures in the Cheshmeh‐Kileh Watershed, Iran. To prioritize SWs based on flood generation, geo‐environmental criteria were used in Ph‐MA, HEC‐HMS software was used in Te‐MA, and semi‐structured interviews with local stakeholders were used in Com‐MA. Finally, using the Condorcet algorithm based on game theory, SWs were prioritized in each approach. In the semi‐structured interviews, stakeholders were asked to provide suggested measures for FCM. Finally, the effect of each measure on the flood components was quantified. Based on the results, the measure of 10% improvement of forest cover in the entire watershed from the category of Con‐MA was selected as the optimal measure. In the return periods of 2, 5, 10, 20, 50, and 100 years, the effectiveness of this measure was 80.08%, 70.09%, 58.10%, 55.67%, 50.58%, and 43.62%, respectively. The influence of Con‐MA based on non‐structural and structural measures on reducing the components of peak flow and flood volume was more than other approaches. In general, it can be concluded that non‐structural measures have more effect than structural measures in FCM in the study watershed. The methods and approaches used in this study can be directly used by local executive managers, decision‐makers, and policymakers of watershed management and flood management activities.

Mining and urbanization affect river chemical water quality and macroinvertebrate communities in the upper Selenga River basin, Mongolia (revised version)

Mongolia is a country with a quickly growing economy mainly based on the mining of gold, copper, coal, and other minerals. Mining, urbanization, and agriculture impact the water quality in the upper Selenga River basin in northern Mongolia, which is the center of the Mongolian economy. Previous measurements of pollution loads were alarming, but restricted to chemical measurements. Here, for the first time, we combine freshwater biomonitoring and laboratory water quality data across a broad gradient of water quality and land use intensity. We track the effects of different types of pollution on aquatic invertebrates and test their use as bioindicators. We collected water samples, environmental parameters, and macroinvertebrates at 36 sampling sites at the rivers of Tuul, Kharaa, and Orkhon and their tributaries Sugnugur, Boroo, Sharyn Gol, Gatsuurt, and Yeröö. PCA of catchment water quality distinguished three groups of pollutants prevalent at the sites, (1) nutrients, (2) salt ions (Cl−, Na+, Mg2+, So42−, Ca2+) and mining by-products (B, Sr, U, Mo), and (3) (heavy) metals, which often exceeded regulatory standards. We recorded a total of 59 macroinvertebrate taxa belonging to 31 families in seven insect orders plus Amphipoda and Gastropoda. Species diversity declined with higher impact. Five environmental factors structured macroinvertebrate community composition in RDA: elevation of sample location, site total nitrogen, dissolved oxygen, electrical conductivity, and water chemistry. We conclude that macroinvertebrate communities are an appropriate and inexpensive tool for monitoring water quality in Mongolia and suggest government action to establish a long-term monitoring program.

Estimating sediment delivery ratio using the RUSLE-IC-SDR approach at a complex landscape: A case study at the Lower Snowy River area, Australia

Understanding the dynamics of sediment transport and deposition in natural landscapes is critical to developing cost-effective mitigation measures to control soil erosion and protect ecosystems. However, none of a single existing model can quantify sediment delivery ratio (SDR) and the impact factors such as vegetation and geomorphology, especially in a complex landscape. In this case study, we applied an integrated approach including the revised universal soil loss equation (RUSLE) and the index of connectivity (IC) to assess hillslope erosion and SDR, namely RUSLE-IC-SDR, across a complex landscape in the Lower Snowy River area, Australia. The RUSLE factors were derived from a high-resolution (2 m) digital elevation model (DEM), digital soil maps, high-resolution rainfall data and remotely sensed fractional vegetation cover. A seven-class landform classification was delineated from the high-resolution DEM using a fuzzy logic landform model (FLAG). We further examined the impacts of rainfall, vegetation cover and geomorphology on sediment dynamics and distribution across the study area. Field and laboratory data from 10 plot sites across the study area were collected and used for model validation. This case study showed that the RUSLE-IC-SDR approach can assess the overall sediment budget and the impacts of rainfall, vegetation cover and geomorphology across a complex landscape. Findings from this study can identify and track the areas likely to generate high sediment yield for developing ecological restoration, feral animal management and other catchment management measures.

Bridging the knowledge-action gap: A framework for co-producing actionable knowledge

Rapidly increasing knowledge on environmental problems and their potential solutions is underused by policy and practice. This mismatch constitutes a knowledge-action gap. To bridge the gap, the concept of actionable knowledge has been proposed, which is often understood as outputs, data, policy briefs, or other types of products. We instead propose to understand actionable knowledge as a process that has (1) cumulative and stepwise, (2) iterative and cyclical, and (3) coevolutionary characteristics. These characteristics are often considered in isolation or even to be in contradiction with each other. We integrate these three characteristics in an analysis of transdisciplinary project developing a catchment-scale land use roadmap and catchment coordination in the Kiiminkijoki river catchment, northern Finland. Our analysis is based on four general phases in a knowledge co-production process (making sense together, knowledge validation, usable outputs, boundary spanning), which are concretized through nine practical steps. We find that collection, analysis, and usage of the knowledge has been even more important for action than the final output (i.e., the roadmap). Furthermore, the process of actionable knowledge does not end with the project but continues with negotiations to establish a catchment coordinator position. Our major finding is that there is no single point in time during a transdisciplinary project to bridge the knowledge–action gap but multiple planned and surprising opportunities emerge during the process. Overall, our approach contributes to advance sustainability transformations in catchment management and governance by understanding how transdisciplinary projects can initiate and are a part of evolving knowledge-action processes.

Exploring spatial and seasonal water quality variations in Kelani River, Sri Lanka: a latent variable approach.

Water quality degradation poses a significant challenge globally, especially in developing nations like Sri Lanka. Extensive monitoring programs designed to address escalating river pollution collect multiple water quality parameters over extended periods and varied locations. However, the sheer volume of data can be overwhelming, making it difficult to process effectively and interpret accurately using conventional methods. In this study, latent variable (LV) and unsupervised machine learning techniques were used to investigate spatial and seasonal variations of surface water quality for 17 parameters across 17 locations along the Kelani River, Sri Lanka, using monthly water quality parameters from 2016 to 2020. Pearson's correlation matrix identified 10 parameters significantly affecting water quality variations and factor analysis (FA) generated five LVs, accounting for 77% of the total variance in the dataset. The identified LVs showed multiple methods of river pollution.Hierarchical clustering analysis and self-organizing mapping methods clustered stations in a closely analogous manner. Stations near industrial zones and the river mouth showed higher water quality variance, often exceeding national guidelines. Correlation testing revealed strong relationships between water quality and catchment hydrometeorological variations during monsoonal seasons. Spatial analyses showed increased LV variance in the Lower Kelani River Basin, indicating higher pollutant levels in different seasons. Industrial effluents (LV-2 and LV-4) and domestic and municipal sewage (LV-3 and LV-5) exhibit greater seasonal fluctuations. The results showed that the proposed LV approach has the potential to assist authorities in addressing water pollution amidst the complexity of multiple water quality parameters.

Integrated Morphometric and Hypsometric Analysis of Niragantipalli Micro Watershed Using Remote Sensing and Geographical Information System Techniques

Employing Remote sensing (RS) and geographic information system (GIS) for the morphometric parameters analysis are discovered to be tremendous usefulness in the prioritization of watersheds for soil, water conservation and natural resource management at micro watershed level. The analysis of morphometric parameters plays a crucial role for understanding and managing watersheds. In current study an, attempt was to determine the morphological parameters of Niragantipalli micro-watershed in Chikkaballapura District of Karnataka, India. For detail study, Google earth pro, GPS visualizer conversion toll and Arc GIS were used for preparation of DEM and delineation of the watershed boundary. GIS was used for evaluation of basic, linear, areal and relief aspects of morphometric parameters. The Niragantipalli micro-watershed occupies an area of 632 ha with third order stream (truck order) and dendritic drainage pattern. The mean bifurcation ratio of the micro-watershed is 2.5 it suggests that the drainage system formed on homogeneous rock when the influences of geologic structures on the network of streams were negligible and generate sharp peak flow. With a drainage density of 1.31 km/km2, the drainage network is extremely coarse. The watershed is elongated, as shown by the form factor of 0.27 and elongation ratio of 0.58. The results from the morphometric analysis of the watershed are very beneficial for developing and designing conservation structures of soil and watershed management measures. The hypsometric curves’ structure as well as estimated hypsometric integral results reflects the Niragantipalli Micro Watershed erosional stages. As a result, the study concludes that morphometric and hypsometric analysis findings may be useful to stakeholders participating in catchment development and management projects.

SPLIT DUCT AC LEAKAGE MONITORING SYSTEM VIA GOOGLE SHEETS

General Background: Split duct air conditioners are prone to leaks, often resulting from corrosion in water catchment systems, which can lead to significant operational hazards such as electrical fires. Specific Background: Given the prevalence of these issues, there is an urgent need for effective monitoring solutions to maintain optimal air conditioner performance and prevent leaks. Knowledge Gap: Current monitoring systems lack integration with real-time data reporting mechanisms that can alert users promptly to potential issues. Aims: This research aims to develop a monitoring device utilizing NodeMCU ESP8266, water level sensors, and Google Sheets to enable real-time monitoring and management of water levels in split duct air conditioners. Results: The device successfully operates by turning on the fan when water levels are below 2 cm and activating the pump when levels exceed this threshold. The data is continuously sent to Google Sheets, allowing for easy monitoring and management. Novelty: This study presents a novel approach to air conditioner leak monitoring by integrating IoT technology, offering an efficient and user-friendly solution for residents. Implications: The developed monitoring tool significantly enhances the ability to detect and manage potential leaks in real time, thereby improving safety and operational efficiency. Future research should focus on enhancing sensor accuracy through specialized equipment and exploring alternative IoT platforms for improved data visualization, thereby providing users with an even more effective monitoring experience.

Aerial imagery for geological hazard management in Alpine catchments

Aerial imagery for geological hazard management in Alpine catchments

Climate change impacts on the hydrological behaviour of watershed in northeastern Tunisia (Oued El Abid watershed)

Climate change significantly impacts watershed hydrology, altering water supplies, natural disasters, and eco-hydrologic processes. These effects vary geographically, with some regions facing severe droughts while others experience increased precipitation and flooding. Climate change influences atmospheric evaporation demand, precipitation patterns, vegetation composition, streamflow characteristics, and groundwater dynamics. The temperature increases and rainfall changes in some watersheds can lead to increased potential evapotranspiration and decreased streamflow and soil water. Flood frequency analyses indicate an overall increasing trend in the latter half of the 21st century. The Oued El Abid catchment area, as like all catchments in northern Tunisia, is likely to be subject to major climatic and hydrological variations as a result of climate change. Advanced hydrological modelling using the HBV-Light model was set up to simulate current conditions and future scenarios based on Afric-Cordex climate models. The model demonstrates robust performance, achieving Nash-Sutcliffe Efficiency (NSE) values of 0.71 in calibration (1972-1992), and 0.66 in validation from 1993-2001. This climate change has a direct effect on the hydrological projections, which reveal significant changes, with annual flow reductions ranging from 35% to 43%, with more severe impacts under the RCP8.5 scenario for 2069-2099. Spring and summer seasons are particularly vulnerable, showing flow decreases of up to 68% and over 40%, respectively, extreme monthly variability is projected, reaching 88% reduction in July under RCP8.5. This research provides important results for water resource managers, highlighting the necessity of long-term planning and sustainable water management practices in the face of climate change.

Sedimentation Analysis Study in Lake Tondano Due to the Development of the Surrounding Area

Background Population growth has increased the need for food, putting great pressure on the environment. This has triggered economic development and land use alternation, which have a major impact on the hydrological cycle. Natural and human factors have impacted the water catchment area of uncontrolled land cover changes in Lake Tondano, which is shallow from a depth of 36 meters to 14 meters due to soil erosion. Objective This research emphasizes the assessment of the lake, considering the efforts of conservation and analyzing its influence on the erosion rate and shallowing of the lake. The impact of land use dynamics on sedimentation is essential in providing alternative efforts for land conservation and, subsequently, optimum utilization. Methods The analyzing process requires rainfall data and land use maps, including soil type maps and land slope data, while the process itself is assisted by spreadsheets and GIS. In addition, the Universal Soil Loss Equation (USLE) and Sediment Delivery Ratio (SDR) model deliver the expected result of the total sediment production entering the lake. Results The calculated total value of actual sediment production governs the thickness of sediment deposition at the bottom of the lake. Conclusion The research concludes that the thickness of sediment deposition at lake bottom can be resolved by the total value of actual sediment production, whereas the value is analyzed from the USLE and SDR models previously correlated to bathymetry measurement.

Could California's groundwater resource management lessons be beneficial to England?

In California, Groundwater Sustainability Agencies (GSAs) are basin/catchment-specific water organizations mandated by the Sustainable Groundwater Management Act of 2014 to manage groundwater sustainably by 2040/2042. A GSA can charge replenishment fees for pumped groundwater and these fees can be used to: (a) monitor basin hydrologic conditions; (b) improve the water budget accuracy; (c) increase water availability through management actions and projects; (d) mitigate undesirable results; and/or (e) pay for activities including issuing allocations and limiting production to allocations. In England, housing is frequently proposed in river basin catchments that face water resource challenges. High profile examples are the Arun Valley and Cambridge. The current National Planning Policy Framework manages water resource planning strategically through water company Water Resource Management Plans or Environment Agency River Basin Management Plans. These processes can be slow to respond to development requirements. England might look to California's practices that require water users and developers to pay for ‘water credits’ or fees. This could involve a ‘Watermaster’ charged with local or catchment scale resource management and project implementation. This Watermaster could engage all stakeholders including the local water company, farmers, the Environment Agency and the local authority, none of whom is well positioned to act in isolation.

Assessing sediment dynamics and retention services in the vulnerable mountain ecosystem of the Indian Himalayas.

Sediment loss and export pose significant global environmental issues, profoundly affecting water quality, soil fertility, and ecosystem stability, particularly in vulnerable mountain ecosystems like the Indian Himalayas. The present study used remote sensing data and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) sediment delivery ratio (SDR) model to analyze spatial-temporal variations in soil loss (SL), sediment export (SE), and sediment retention (SR) capabilities in the South Shimla watershed, Himachal Pradesh, India, from 1993 to 2023. The findings showed significant changes in land use and land cover (LULC): evergreen forest and scrub land decreased sharply by 11.53% and 36.43%, respectively, while agricultural areas and built-up areas increased notably by 71.16% and 215.76%, respectively. Despite a decline of 19.18% in SL and 24.43% in SE, sediment loss and export varied across the study area, highlighting the heterogeneous nature of sediment dynamics. The overall retention capacity increased by 2.59%, with scrub forests playing a critical role in SR, while built-up areas showed the lowest retention. Northern and central sub-watersheds (SWs) experienced a significant decrease in retention capacity (from - 1.92 to - 11.6%), whereas those in the southern and eastern regions saw an increase in SR (from 3.69 to 28.24%). These results underscore the complex interactions between LULC changes, sediment dynamics, and retention services, highlighting the importance of preserving natural ecosystems and informing policy for landscape-based conservation and development planning in the vulnerable Himalayan region.

Understanding the drivers of the catchment hydrological cycle of the Jonkershoek Valley catchment, South Africa

Understanding trends in hydro-climate variables and the impacts of land use on the streamflow is crucial for the development of appropriate catchment water management strategies. Jonkershoek (146 km2) is an important headwater catchment in the Table Mountain Group (TMG) geological region, contributing flow to the Cape Winelands District Municipality in the Western Cape. This study analyses hydro-climate variables at annual, monthly, and seasonal scales using an integrated approach composed of statistical homogeneity testing for abrupt changes, Mann-Kendall tests for trend analysis, and the Indicators of Hydrological Alteration (IHA) tool for streamflow alterations. Analyses were conducted for three headwater sub-catchments within the Jonkershoek value, each with different land use history.Homogeneity test of rainfall and streamflow data spanning from 1946 to 2019 identified gradual downwards change points for annual rainfall and streamflow across the sub-catchments. Moreover, the change points for streamflow were inconsistent with those of rainfall. The identified change points in streamflow were consistent with the timing of afforestation activities in Tierkloof, whereas in Bosboukloof and Langrivier they could be attributed to earlier climatic variability. Furthermore, Mann-Kendall test detected significant (p < 0.05) decreasing trends for both annual and seasonal rainfall which coincided with most of the streamflow trends. Trends were strongest for the winter season suggesting a possible shift in climate patterns which influence winter rainfall. Winter streamflows declined by 15.5%–39.5%. Analysis of hydrological flow indices indicated significant decrease in 1-,7- and 30-day annual maximum extremes during afforestation which were attributed to high evapotranspiration rates of pines. The opposite was observed during clearfelling period in Bosboukloof. The median monthly flow also showed a decrease for winter months. This shows that climate variability and land-use change by afforestation have major impacts on streamflow. The findings of this study are important to inform policymakers on the impacts of climate change and land use, allowing pro-active mitigation and adaptation.

Profiling efforts to establish voluntary stewardship in a river catchment

River water quality in Ireland is in decline. The Maigue River in County Limerick exemplifies this decline with degrading chemical and ecological water quality. The most significant pressures are agriculture, and to a lesser extent, hydromorphology, urban and domestic wastewater systems. Because human activity is a main source of pressure on riverine systems and natural habitats, part of the solution rests in increasing local community interest, involvement, and cooperation in water and catchment management initiatives. This study profiles efforts made to foster engagement with residents of the Maigue River catchment. A devastating pollution event precipitated the formation of a community water group that provided initiatives to increase public involvement in events and projects focusing on river water quality and biodiversity. Most of the initiatives would not have been possible without the individual attributes of local participants, an organisational structure (Maigue Rivers Trust), and champion (Project Officer), and supporting funds, training, and resources. These bottom-up efforts demonstrate that voluntary engagement supported by core funding helped further the public participation aims of conservation legislation (Water Framework Directive and River Basin Management Plans) and expanded catchment stewardship. However, future sustainability, with meaningful improvements in water quality, requires time, a functioning structure, and adequate resources, as part of a coherent integrated catchment management approach, if trusting relationships with local communities are to be developed and maintained.

Drought reduces nitrogen supply and N2O emission in coastal bays

Severe droughts are increasingly prevalent under global climate change, disrupting watershed hydrology and coastal nitrogen cycling. However, the specific effects of drought on nitrogen transport from land to sea and subsequent nitrogen dynamics remain inadequately understood. In this study, we evaluated the consequences of the 2020–2022 drought on nitrogen supply and N2O emissions in Xiamen Bay, Southeast China. The results showed that drought significantly reduced annual NH4N, NO2N, and NO3N concentrations in Xiamen Bay by 49.4 %, 32.1 %, and 40.3 %, respectively, compared with the pre-drought year of 2019. The decline in NH4N concentration was mainly attributed to reduced surface runoff across all seasons. NO3N and NO2N concentrations declined only during spring and summer, primarily due to increased potential evapotranspiration (PET) hindering nitrogen supply via groundwater and concurrently enhancing land denitrification. Annual N2O emission from Xiamen Bay decreased by 40.0∼72.7 % during the drought, highly correlated with the decline in the concentrations of NO3N, DIN, and DTN (p < 0.001). Comparative analysis revealed that NO3N concentration exhibited consistent negative linear regressions with PET and declined as evaporative demand drought conditions worsened across Xiamen Bay, Sansha Bay, and Chesapeake Bay throughout 2010–2022. NH4N concentration showed a positive regression with river discharge in Xiamen Bay, but negative regressions in the other two bays. Our results indicates that drought reduces N2O emission primarily driven by nitrate substrate reduction in the bay. This study provides new insights for predicting coastal nitrogen dynamics and greenhouse gas emissions under global environmental change.