Impact Water Quality Research Articles

Optimization of the Interaction Transport System—Transported Medium to Ensure the Required Water Quality

This article addresses a pressing issue concerning the attainment of required drinking water quality in municipal settings. The solution lies in optimizing the interaction among multiple elements involved in this process. The interaction encompasses the transport system with its geometric, physicochemical, and operational characteristics, as well as the transported medium, which is drinking water with its physicochemical, operational, and incrustation characteristics. This article provides an overview of the current state of piped water systems and explores the integration of factors influencing the formation of incrustation to minimize its occurrence. Special attention is given to the meticulous selection of factors that impact water quality, considering their advantages and limitations in the assessment. The optimization process relies on Saaty’s method of comparing individual factors and conducting a thorough multi-criteria analysis. The outcome of the analysis culminated in the development of a three-stage procedure for de-incrustation of pipeline systems. To ensure a comprehensive perspective, it is crucial to approach the entire issue in accordance with ISO 46001-compliant water management systems.

Assessing the climate change adaptability of sustainable land management practices regarding water availability and quality: A case study in the Sorraia catchment, Portugal

In Mediterranean catchments, such as the Sorraia catchment in Portugal, it is expected that climate change will increase drought stress and the deterioration of water quality in reservoirs. Sustainable land management (SLM) practices are seen as an adaption measure for those problems, but the effectiveness on improving climate change impacted water availability and quality on catchment scale is still poorly understood. Therefore, this study aims to evaluate the effectiveness of SLM practices in adapting the impacts of climate change on water availability and quality of the Montargil and Maranhão reservoirs in the Sorraia catchment. A well-calibrated Soil Water Assessment Tool model is used to simulate four scenarios (2041–2071 and 2071–2100; representative climate pathways 4.5 and 8.5), to investigate the effects of climate change on total phosphorus load (TP) in streams, reservoir volume, irrigation use and water exploitation index (WEI). Results showed that WEI will not exceed any water stress level while reservoir water quality will worsen. In particular since the TP load in streams flowing into the reservoirs increases and the volume decreases, it is likely that the existing P limitation for eutrophication will be counteracted. Nevertheless, tested SLM practices were able to decrease the TP load in those streams and increase the reservoir volume under future climates. Overall, this study shows that the SLM practices are effective in adapting to the climate change effects regarding reservoir water quality, without worsening the water availability; thus, it is a promising tool that should be investigated further for application by e.g. local land-users and decision makers.

Nutrient transport in surface runoff and sediment yield on macroplots and zero-order catchments under no-tillage

No-till farming is widely used in grain production in Brazil. However, the lack of runoff control and the low phytomass input are major causes of soil degradation. In addition, surface runoff transports chemical elements, including carbon and nutrients, in dissolved and particulate forms impacting water quality. Given this scenario, this study sought to evaluate the influence of phytomass amount, chiseling, and terracing on nutrient loss (NH4+, NO3− + NO2−, total N, P, K, Ca, Mg, Cu, and Zn) associated with surface runoff, suspended sediments, and to quantify their presence in sediment deposits at the end of the monitoring unit. This study was based on hydrological monitoring in four macroplots and two paired zero-order catchments during rainfall events. The macroplots reproduce use or absence of chiseling with lower or higher phytomass input, and the catchments, presence or absence of terraces. Nutrient concentrations were determined in surface runoff and sediment. In surface runoff, the highest median values of NH4+, NO3− + NO2−, total N, P, K, Ca, Mg, Cu and Zn concentrations in the catchments were 0.9,1.0, 1.5, 0.1, 3.1, 3.9, 1.1, 0.0, and 0.01 mg/L, and in the macroplots 1.0, 1.2, 2.1, 0.2, 3.4, 5.3, 1.7, 0.0, and 0.02 mg/L. In the suspended sediments, the highest median values of P, K, Ca, and Mg concentrations in suspended sediment in the catchments were 0.6, 6.7, 3.4, and 0.8 g kg−1 and in the macroplots 0.6, 6.1, 1.9 and 0.7 g kg−1. Our findings revealed a wide variation in nutrient concentrations in runoff and sediments regardless of the management practices. Nevertheless, the dissolved fraction of surface runoff controls the loss of nutrients during high-magnitude rainfall events. The effects of the increased phytomass and the presence of terraces, affect nutrient losses due to runoff control.

A conceptual model to establish preventive and corrective actions to guarantee water safety following scenarios of tailing dam failure

One of the impacts related to mining dam failures is the change in water quality downstream of the rupture and a knowledge gap is observed in terms of methodologies aimed at the prognosis of impact in water abstractions, a vulnerability that can be identified before a rupture event. Thus, the present work aims to describe a novel methodological proposal, not currently considered by control agencies, of a standard protocol that enables a comprehensive prognosis of the impacts on water quality impact in scenarios of dam failure. Initially, extensive bibliographic research was carried out on the main disruptions events since 1965 intended to better comprehend the impacts on water quality and to identify mitigatory actions proposed by the time. The information provided a framework to propose a conceptual model for the prognosis of water abstractions, with the suggestion of software and studies to comprehend the different scenarios in the event of dam failure. A protocol was prepared to obtain information on potentially affected inhabitants and a multicriteria analysis was developed using the Geographic Information System (GIS) to suggest the employment of preventive and corrective actions. The methodology was demonstrated in the Velhas River basin considering a hypothetical scenario of tailing dam failure. Changes in water quality would be observed in 274 km of its extension, mainly related to alterations in solids, metals, and metalloids’ concentration, in addition to the impact on important water treatment plants. The map algebra and the results suggest the need for structuring actions in cases where the water abstraction is intended for human supply and in populations greater than 100,000 inhabitants. Populations smaller than these, or usages other than human supply, could be supplied by water tank trucks or mixed alternatives. The methodology pointed out the necessity for structuring supply actions with due notice, with the potential to prevent water shortages in scenarios of tailing dam failure and to complement the enterprise resource planning of mining companies.

A Review Paper on the Impact of Municipal Solid Waste Surface Water Quality

A Review Paper on the Impact of Municipal Solid Waste Surface Water Quality

The Race to Reduce Greenhouse Gas Emissions in U.S. Dairy Through Improved Soil Health

AbstractThis is the first article in a new series in Crops & Soils magazine that will look at soil health and greenhouse gas emissions on U.S. dairies associated with crop production. Articles will cover soil health practices, data‐based decision‐making, greenhouse gas measurement in soils, manure application and storage, and informing future carbon markets with science. This article will discuss the Dairy Soil and Water Regeneration project. Using a whole‐systems approach, project researchers are measuring how different management practices—from using cover crops to applying novel fertilizers, including manure‐based products—affect soil health, potentially reduce greenhouse emissions and impact water quality under varying climate and field water management systems. Earn 0.5 CEUs in Sustainability by reading this article and taking the quiz at https://web.sciencesocieties.org/Learning‐Center/Courses.

A biological diatom indices based preliminary assessment of water quality of Thamirabarani river, Southern India

ABSTRACT Diatoms have long been used as bio-indicators for the assessment of surface water quality. This study investigates the biological diatom index (BDI) and water quality index (WQI) for evaluating the water quality impact in the Thamirabarani River, Southern India. Diatom and water samples were taken for the present investigation from ten different locations along the river. The samples were enumerated and the morphometrics valve was documented by light microscopy. In the study area, a total of 70 diatom taxa belonging to 28 genera were recorded. The diatom indices implemented in OMNIDIA software version 6.1 was used to infer the river water quality status. The results showed that based on the BDI and WQI analysis values varied from 6.7 to 17.4 and 48 to 71 were observed. According to the BDI and WQI analysis result during the study period in the river revealed the water quality varied between good (Oligo-mesotrophic) to bad (Eutrophic) ecological conditions. The biological diatom index and water quality index results indicate the respective locations (Site 2, Site 3, Site 7, Site 8, Site 9 and Site 10) represent bad water quality. The result indicated moderate water quality at Sites 4 and Site 6. The diatom indices and water quality index results show the locations Site 1, and Site 5 indicate good water quality. The biological diatom index results from diatom assemblages show more information about the water quality and environmental impact on the river. For the national assessment of water quality better to use diatoms along with physico-chemical parameters variables. Based on the analysis result reveal that the major component of water quality degradation was due to anthropogenic activities, domestic waste and industrial effluents in the study area.

Impact of Parasitic Infection and Water Quality on the Bagrid Fish, Bagrus bajad, Inhabiting Ismailia Canal Waters, Egypt

Impact of Parasitic Infection and Water Quality on the Bagrid Fish, Bagrus bajad, Inhabiting Ismailia Canal Waters, Egypt

Uncovering water quality and evaluating vulnerabilities of small-scale fisheries in Chilika Lagoon, India

Small-scale fisheries (SSFs) play a strong role in sustaining millions of livelihoods, food security, nutrition, and income globally but the fishers engaged in this sector simultaneously experience high levels of vulnerability and processes of marginalisation. Several factors are attributed to the multidimensional vulnerabilities the small-scale fishers experience, spanning both natural (e.g., natural disasters, ecosystem change) and anthropogenic (e.g., policy change, hydrological interventions, aquaculture) pressures. While there is much literature on various natural and human drivers of vulnerability in small-scale fishery communities, an absence of research connecting vulnerability with water quality is evident. Fisher communities often talk about fish in relation to the health of their aquatic habitats wherein water quality is seen as a key parameter. The link between healthy fish and good quality water has significant implications for strong and viable fishing communities. This paper examines these links further by focusing on the nature of vulnerabilities caused by water quality changes in the small-scale fishery system of Chilika Lagoon in India. We undertake detailed analysis of the invasive shrimp aquaculture activities and hydrological interventions for opening of a lagoon inlet with the Bay of Bengal as two dominant drivers adversely impacting water quality and increasing vulnerabilities of the entire small-scale fisheries social-ecological system. Our analysis suggests that there are strong interconnections between changes in water quality and the levels of vulnerabilities in the SSFs of Chilika Lagoon. Pollutants such as pesticides, and organic compounds accumulate in fish tissues and affect their growth, reproduction, and overall health. This led to declines in fish populations, making it more difficult for fishers to make a living. In addition to direct impacts on fish populations, poor water quality also has indirect effects on the social and economic vulnerability of SSFs. For example, contamination of water sources led to the reduced number of fish species reducing the amount of time fishers can spend on fishing activities. This also affected the marketability of fish products, reduced income and increased poverty. To fully understand the interconnections between water quality and vulnerability in SSFs in Chilika Lagoon, it is important to consider both environmental and social factors, as well as the complex feedback loops between these factors. The study helps in bridging a crucial gap in our understanding of the role of water quality in vulnerability analysis within resource dependent communities. We conclude with key insights on possible coping responses and adaptive capacity necessary for the small-scale fisheries communities to transition toward viability.

Isolation and Screening of Aqua-borne fungi from Song River

The Song River in Dehradun, Uttarakhand, India, travels from Dhanaulti to Narendra Nagar and originates as a spring-fed stream on the southern slopes of the Himalayan range's Radi Top of Missouri ridge. Fungi are the principal decomposers and work with bacteria in the environment, thus actively participating in the circulation of environmental nutrient cycles such as nitrogen and phosphorus. The aim of this research is the Isolation and screening of Aqua-borne fungi from different locations of Song River. Twenty water samples were gathered from several locations of song rivers in a 1-liter sterile bottle and used 500 mg, Chloramphenicol to inhibit the growth of bacteria, and 1ml and 0.1 ml water samples were poured into PDA, SDA, Rose Bengal agar Medium and the poured plate incubated 4-10 days for fungi growth. After that, the pure culturing method and microscopic observation with Lacto cotton blue strain were used. We reported some species of fungi Rhodotorula sp. 45%, A. Candidus 70%, Rhizopus sp. 35%, A. Niger 85%, and A. flavus 75%, are found in the Song River sites. One of the most recent discoveries on fungus that demands special attention is the frequency of emerging and opportunistic infections in raw water sources. Because fungus can impact water quality in a number of ways, the microbiota of water should be considered when assessing the microbiological safety and quality of drinking water.

Impacts of a tailings dam failure on water quality in the Doce river: The largest environmental disaster in Brazil

BackgroundOn November 5, 2015, the Fundão Dam, owned by Samarco Mineração SA, experienced a catastrophic failure, releasing approximately 55 to 62 million m3 of mining ore waste into the Doce River. This event had severe consequences as the Doce River serves as a vital source of water and food for numerous communities. ObjectiveEvaluate the spatiotemporal distribution of water parameters before, during, and after the failure of the Samarco tailings dam, with the goal of support the management and restoration of water quality. The study utilizes a long historical series of data from 1997 to 2018. MethodologyIn this study, data from 13,916 measurements of variables including HCO3−, Mg2+, Ca2+, SO42−, pH, EC, and metal(oids) such as Fe, Mn, As, Cu, Ba, Pb, Zn, Cd, Cr, and Ni were compiled. These measurements were collected from 1997 to 2018 to investigate the impact of the dam rupture. ResultsThe dam failure resulted in an increase in high turbidity events and total suspended solids (TSS), leading to a decline in water quality. The Kruskal-Wallis test revealed a homogenization effect along the river watershed caused by the accident, particularly for Pb, Ni, Cd, Cr, and coliforms. Additionally, there was a change in the seasonal distribution of PO43−, NH4+, Na+, SO42−, and Zn. The factor analysis identified four main factors: i) HCO3−, Mg2+, Ca2+, SO42−, pH, and electrical conductivity (37.55%) were indicative of weathering processes from lithotypes; ii) Fe+Mn and the metal(oids) (As, Cu, Ba, Pb, Zn, Cd, Cr, and Ni) (15.89%) were associated with ore waste and regional geology; iii) total coliforms, NO3−, NH4+, and PO43− (9.39%) were linked to anthropogenic influences in the river; and iv) K+, Na+, and Cl− (8.22%) represented the impact of domestic and industrial sewage discharge as well as the marine environment in the lower sector of the Doce River. ConclusionThe dam rupture significantly altered water quality in the Doce River, particularly in relation to metal(oids), three years after the disaster. The presence of ore waste in the bottom sediments creates an environmental liability as it can be remobilized by human activities or extreme weather events, further impacting water quality.

Coupling Machine and Deep Learning with Explainable Artificial Intelligence for Improving Prediction of Groundwater Quality and Decision-Making in Arid Region, Saudi Arabia

Recently, machine learning (ML) and deep learning (DL) models based on artificial intelligence (AI) have emerged as fast and reliable tools for predicting water quality index (WQI) in various regions worldwide. In this study, we propose a novel stacking framework based on DL models for WQI prediction, employing a convolutional neural network (CNN) model. Additionally, we introduce explainable AI (XAI) through XGBoost-based SHAP (SHapley Additive exPlanations) values to gain valuable insights that can enhance decision-making strategies in water management. Our findings demonstrate that the stacking model achieves the highest accuracy in WQI prediction (R2: 0.99, MAPE: 15.99%), outperforming the CNN model (R2: 0.90, MAPE: 58.97%). Although the CNN model shows a relatively high R2 value, other statistical measures indicate that it is actually the worst-performing model among the five tested. This discrepancy may be attributed to the limited training data available for the CNN model. Furthermore, the application of explainable AI (XAI) techniques, specifically XGBoost-based SHAP values, allows us to gain deep insights into the models and extract valuable information for water management purposes. The SHAP values and interaction plot reveal that elevated levels of total dissolved solids (TDS), zinc, and electrical conductivity (EC) are the primary drivers of poor water quality. These parameters exhibit a nonlinear relationship with the water quality index, implying that even minor increases in their concentrations can significantly impact water quality. Overall, this study presents a comprehensive and integrated approach to water management, emphasizing the need for collaborative efforts among all stakeholders to mitigate pollution levels and uphold water quality. By leveraging AI and XAI, our proposed framework not only provides a powerful tool for accurate WQI prediction but also offers deep insights into the models, enabling informed decision-making in water management strategies.

Dynamic analysis of a porous wall fencing offshore fish cage subjected to regular waves

Global aquaculture is in exponential trend to fulfil the demand for seafood due to the rise in world population. Most countries have implemented nearshore farming and reached their limits, which impacts water quality parameters. Offshore farming is the alternative option to counteract this nearshore farming issue and balance the aquaculture demand and supply. The present study construes on the numerical study of the porous wall fencing offshore fish cage subjected to regular waves. The numerical analysis is carried out for four cages by varying porous hole diameters from 0.5 to 0.7 m and without porosity. All the cages are placed at the same water depth of 200 m, interacting with a constant wave height of 6m with wave periods ranging from 6.92 to 19.05 s. Both frequency and time domain analysis are conducted to study the variation of hydrodynamic parameters, namely added mass, wave excitation forces, radiational potential damping, motion responses, and mooring line tension. Among all cage configurations, the cage with 0.5 m diameter porous hole fencing performs better for all wave conditions considered. Also, a scaled model of 1:75 was considered in both experimental and numerical studies for the purpose of validation. It is learnt that experimental parameters such as motion responses and mooring line tension are in good agreement.

The impacts of spatio-temporal variation of natural and agricultural influences on the environmental water quality in a fluvial-lacustrine watershed in China.

Despite the significant impacts of natural factors such as rainfall, topography, soil type, and river network as well as agricultural activities on the environmental water quality, little is known about the influence of their temporal and spatial variations in a fluvial-lacustrine watershed. In this study, a whole process accounting method based the export coefficient model (WP-ECM) was first developed to quantify how natural factors and agricultural activities distribution influenced water quality. A case study was performed in a typical fluvial-lacustrine area - Dongting basin, China. The simulated results indicated that the natural factors can promote and inhibit the migration and transformation of agricultural pollutants generated from the watershed and the spatial distribution of the natural factors displayed high variability. It should be priority to monitor the areas with greater natural impact in the basin. Moreover, the cultivated land area and the number of pig-breeding were positively correlated with the pollutant discharge. From the perspective of the spatial distribution of comprehensive influence, the comprehensive high-impact areas are mainly distributed in the Dongting Lake district in 2005-2010 and in Xiang River watershed in 2010-2020. A key strategy for controlling or reducing the cultivated land area and the intensity of livestock breeding in these high-impacts areas is recommended to reduce the impact of the environmental water quality for the entire basin.

Impact of Water Source and Quality on Survival, Growth and Health of Clarias gariepinus Fingerlings Reared in Indoor Concrete Tanks

This experiment investigated the impact of two water sources and their quality on the survival, growth and health of Clarias gariepinus fingerlings reared in indoor concrete tanks. 400 fingerlings of mean weight 15.33±3.47 g and total length 12.63±1.00 cm (mean±standard deviation) was randomly distributed into four concrete tanks of 12 m3 capacity each. Water quality was analyzed bi-weekly throughout study duration. Growth parameters such as mean weight gain (MWG), specific growth rate (SGR) and feed conversion rate (FCR) were calculated using standard procedures. At study termination, duplicate groups per treatment were assessed for survival rate and a health status check was determined by a hematological evaluation and microscopic examination of parasitic incidence. Results indicated that fish reared in water sourced from bore-hole [BH] performed comparatively significantly better in growth (p < 0.05) than fish in water from earthen pond [EP] as the MWG stood at 294.05±79.17 g for the former against 211.03±54.62 g for the latter with the survival rates for both treatments being in excess of 90%. Additionally, fish reared in EP presented with a higher infestation load of Trichodina spp., although there was no significant difference (U = 7, p > 0.05) between fish reared in EP and BH treatments with regards to their packed cell volume levels and white blood cells. The outcome of this study shed light on the impact a water source can have on the growth and health status of C. gariepinus with a recommendation of microbiological analysis of water supply from open/surface systems before usage for the African catfish aquaculture.

Investigating extreme hydrological risk impact on water quality; evidence from Buffalo catchment headwater, Eastern Cape, South Africa

Evidence from increasing mineralization, micropollutant concentrations, waterborne epidemics, an algal boom, and dissolved organic matter has provided substantial evidence that climate change impacts water quality. While the impact of the extreme hydrological event (EHE) on water quality (WQ) has aroused considerable research interest, research uncertainty has been premised on WQ data scarcity, a short time frame, data non-linearity, data structure, and environmental biases on WQ. This study conceptualized a categorical and periodic correlation using confusion matrices and wavelet coherence for varying standard hydrological drought index (SHDI; 1971–2010) and daily WQ series (1977–2011) of four spatially distinct basins. By condensing the WQ variables using chemometric analyses, confusion matrices were assessed by cascading the SHDI series into 2-, 3-, and 5-phase scenarios. 2-phase revealed an overall accuracy (0.43–0.73), sensitivity analysis (0.52–1.00), and Kappa coefficient (− 0.13 to 0.14), which declines substantially with the phase increase, suggesting the disruptive impact of EHE on WQ. Wavelet coherence depicted the substantial ({R}_{n}^{2}left(u,sright)ge 0.5) mid- and long-term (8–32 days; 6–128 days) co-movement of streamflow over WQ, confirming the varying sensitivity of WQ variables. Land use/land cover mapping and the Gibbs diagram corroborate the eventful WQ evolution by EHE and their spatial variability concerning landscape transformation. Overall, the study deduced that hydrologic extreme triggers substantial WQ disruption with dissimilar WQ sensitivity. Consequently, suitable chemometric indicators of EHE impacts such as WQ index, nitrate-nitrogen, and Larson index at designated landscapes were identified for extreme chemodynamics impact assessment. This study proffers a recommendation for monitoring and managing the impact of climate change, floods, and drought on water quality.

Hydrodynamic modeling of Sharjah lagoons under climate changes, United Arab Emirates (UAE)

The lagoons of Al Khalid, Al Khan and Al Mamzar are among the most important natural assets in the Emirate of Sharjah, as they play an essential role in the coastal socio-economic environment of the area. However, the hydrodynamics of these lagoons in the context of climate change has never been studied. This study presents the results of a hydrodynamic model applied to these lagoons to determine water circulation and flushing time variability, both at present, and in a future with a projected 1m sea level rise (SLR) over the next 100 years. The results show that a 1m SLR would increase the tidal range by 35% and raise the velocity of currents inside the lagoon from an average speed of 0.31 m/s (present) to 0.43 m/s (future), with maximum currents of 1.4 m/s occurring near the tidal inlet during the flood tide and 0.8 m/s during ebb tide. This increase in tidal velocity would also increase the rate of water circulation in the lagoons, significantly reducing the local flushing time. The present conditions revealed that inner areas of the lagoon experience increased local flushing times compared to the outer regions of the lagoon, which may impact water quality status in the inner sectors. Overall, in the model, the local flushing time was reduced from 27 days (present) to 14 days (future), reflecting a 50% reduction. This would suggest that a 1m SLR would result in a more efficient dispersal of materials out of the lagoons.

Examining the Influence of Landscape Patch Shapes on River Water Quality

River water quality can be affected by a range of factors, including both point and non-point sources of pollution. Of these factors, changes in land use and land cover are particularly significant, as they can alter the structure of the landscape and consequently impact water quality in rivers. To investigate the relationship between patch shapes, a measure of landscape structure, and river water quality at the catchment scale, this study utilized spatial data from 39 catchments in the southern basin of the Caspian Sea. This study employed stepwise multivariate regression modeling to explore how changes in landscape structure, which can be measured by landscape metrics including the shape index, the contiguity index, the fractal dimension index, the perimeter–area ratio, and the related circumscribing circle, impact water quality variables. Four regression models—linear, exponential, logarithmic, and power models—were evaluated, and the most appropriate model for each water quality variable was determined using the Akaike information criterion. To validate the models, three groups of accuracy metrics were employed, and Monte Carlo simulation was utilized to analyze the models’ behavior. This study found that landscape structure metrics could explain up to 71% and 82% of the variations in the measures of TDS and Mg, respectively, and the shape index, the contiguity index, and fractal metric were particularly significant in predicting water quality. Moreover, this study verified the accuracy of the models and revealed that changes in landscape structure, such as a decline in patch continuity and an increase in patch complexity, can impact river water quality. The findings of this study suggest optimizing landscape structure metrics in land use planning to reduce river pollution and improve water quality.

Optimization and reflexivity in interdisciplinary agri-environmental scholarship

IntroductionThe Chesapeake Bay and Upper Bann watersheds in the United States and Northern Ireland, respectively, exemplify how agricultural systems contribute to groundwater and surface water pollution, which leads in turn to water quality issues in downstream water bodies. Interdisciplinary research, public outreach, and stakeholder engagement have received increased attention and consideration as pragmatic approaches for addressing these types of complex agri-environmental dilemmas. However, such approaches are far from guaranteed to improve water quality, as political-economic constraints, power asymmetries, cultural differences, divergent incentives, research gaps, and personality differences all complicate the process, and this can ultimately impact water quality efforts.MethodsWe present a holistic approach to addressing these challenges in the Chesapeake Bay and Upper Bann watershed management efforts by integrating the methodological strategies of optimization and reflexivity. Our use of these approaches, widely recognized as respective successful practices in quantitative and qualitative research, is novel in that it focuses directly on the researchers themselves as they discuss, evaluate, and develop potential solutions for complex agri-environmental water quality dilemmas. More specifically, our quantitative optimization is explored via a Functional Land Management (FLM) approach to land and natural resources management, while our qualitative reflexivity is explored through the process of participant observation.ResultsThis paper provides a behind-the-scenes perspective on how interdisciplinary teams can improve their cooperation efficiency when addressing complex agri-environmental issues. In being reflexive, we sought to “optimize” on the methodological, ethical, social, and environmental possibilities of our scholarship. We found that our reflexive work on this project furthered our interest in FLM, a tool that embraced complexity and creativity over rigidity and oversimplification - the very same principles that guided our reflexive work.DiscussionThroughout our collaborative investigation of FLM as a potential solution to soil and water quality issues, we came to appreciate that in order to better understand agri-environmental challenges issues, we also needed to better understand ourselves—our own disciplinary, cultural, and ethical standpoints. Reflexive approaches to research can provide practical guidance in this process by encouraging us to critique and analyze our assumptions, our methodologies, and the socio-historical context of our research.

Hydrochemical Assessment of the Kisköre Reservoir (Lake Tisza) and the Impacts of Water Quality on Tourism Development

Outdoor recreation has grown rapidly in recent years, with an increasing preference for areas in good ecological condition. Since lakes represent some of the most important wetlands, providing a wide variety of ecosystem services, they have become a very popular destination. The present study aimed to assess the water quality of the largest artificial lake in Hungary (Kisköre Reservoir—Lake Tisza), and the role of ecological status in tourism development. Monthly water sampling from the basins of the lake (Tiszavalk, Poroszló, Sarud and Abádszalók basins) took place from April–November 2021 and in 2022. The majority of samples from the river section and from the lake are classified as Ca2+-HCO3− type or mixed Ca2+-Na+-HCO3− type. According to the results, the water quality of each basin is considered excellent or good. Rapid warming of the shallow water of the basins was detected during the summer months, resulting in different hydrochemical characteristics (pH, NH4-N, NO2-N, NO3-N, PO4-P, CODcr BOI5) compared to the river section. Differences in the plant nutrient and oxygen balance component groups have been revealed with hierarchical and two-step cluster analysis as well. The results demonstrated that the hydrochemical properties of the lake’s water are substantially influenced by the filling of the lake in spring from the River Tisza and the significant lowering (1.2 m) of the water level in the autumn each year, allowing the drainage of stagnant water, the removal of accumulated sediments and the oxidation of organic matter. The number of tourists on Lake Tisza has increased rapidly over the last decade, confirming that a wide range of ecosystem services have a significant attractive impact on waterfront activities and ecotourism.