Modelling the impact of future socio-economic and climate change scenarios on river microbial water quality

Uncertainty assessment for three-dimensional hydrodynamic and fecal coliform modeling in the Danshuei River estuarine system: The influence of first-order parametric decay reaction

Modeling fecal contamination in water bodies is of importance for microbiological risk assessment and management. This study investigated the transport of fecal coliform (e.g., up to 2.1 × 10⁶ CFU/100 ml at the Zhongshan Bridge due to the main point source from the Xinhai Bridge) in the Danshuei River estuarine system, Taiwan with the main focus on assessing model uncertainty due to three relevant parameters for the microbial decay process. First, a 3D hydrodynamic-fecal coliform model (i.e., SCHISM-FC) was developed and rigorously validated against the available data of water level, velocity, salinity, suspended sediment and fecal coliform measured in 2019. Subsequently, the variation ranges of decay reaction parameters were considered from several previous studies and properly determined using the Monte Carlo simulations. Our analysis showed that the constant ratio of solar radiation (α) as well as the settling velocity (v_s) had the normally-distributed variations while the attachment fraction of fecal coliform bacteria (F_p) was best fitted by the Weibull distribution. The modeled fecal coliform concentrations near the upstream (or downstream) stations were less sensitive to those parameter variations (see the smallest width of confidence interval about 1660 CFU/100 ml at the Zhongzheng Bridge station) due to the dominant effects of inflow discharge (or tides). On the other hand, for the middle parts of Danshuei River where complicated hydrodynamic circulation and decay reaction occurred, the variations of parameters led to much larger uncertainty in modeled fecal coliform concentration (see a wider confidence interval about 117,000 CFU/100 ml at the Bailing Bridge station). Overall, more detailed information revealed in this study would be helpful while the environmental authority needs to develop a proper strategy for water quality assessment and management. Owing to the uncertain decay parameters, for instance, the modeled fecal coliform impacts at Bailing Bridge over the study period showed a 25 % difference between the lowest and highest concentrations at several moments. For the detection of pollution occurrence, the highest to lowest probabilities for a required fecal coliform concentration (e.g., 260,000 CFU/100 ml over the environmental regulation) at Bailing Bridge was possibly greater than three.

Climate and landuse change enhance spatio-temporal variability of Dongjiang river flow and ammonia nitrogen

The adverse impacts of climate and landuse change are threatening the availability of water quantity and its quality, yet there are limited understandings in the response of water availability to changing environment at different spatio-temporal scales. Aimed at quantifying the individual and superimposed effects of climate and landuse change on streamflow and ammonia nitrogen (NH₃-N) load in the Dongjiang River Basin (DRB), we dynamically simulated the historical (1981-2010) and future (2030-2070) variation of runoff depth and NH₃-N load coupling multiple regional climate model and landuse data. The increase in runoff depth (avg. +233.9 mm) due to climate change was about 33 times greater than that caused by landuse change (avg. -7.2 mm). Especially in the downstream of DRB (Hong Kong, Shenzhen and Dongguan cities, etc.), the maximum rise of runoff depth under climate change was near twice compared with baseline period, indicating the dominant control of climate change on runoff. Also there existed higher coefficient of variation (C_v) value of runoff in the dry season of downstream DRB, contributing potential great fluctuation in runoff. Besides, the variation of NH₃-N load was jointly influenced by climate and landuse change, revealing an offset or amplification effect. Moreover, the variability of NH₃-N load (C_v value as the metric) increased from 2030, reached a maximum in 2050, following decreased to 2070. The spatial distribution of NH₃-N load, in general, presented a downward trend and concentrated near the water body, while the monthly average NH₃-N load showed distinct peaks in spring and late summer temporally. Overall, the results highlight the significance of investigating the water availability under changing environment and more adaptive strategies should be proposed for better basin water management.

Modeling the fecal contamination (fecal coliform bacteria) in transboundary waters using the scenario matrix approach: a case study of Sutlej River, Pakistan

Surface water quality is among the significant challenges in the Sutlej River basin, passing through Pakistan's most densely populated province. Currently, the overall surface water quality is grossly polluted, mainly due to the direct discharge of wastewater from the urban areas to the Sutlej River directly or through stream networks. Escherichia coli concentrations vary under extreme weather events like floods and droughts and socioeconomic circumstances like urbanization, population growth, and treatment options. This paper assesses the future E. coli load and concentrations using the Soil and Water Assessment Tool (SWAT) along with scenarios based on Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) developed by the Intergovernmental Panel on Climate Change (IPCC). E. coli concentrations according to a more polluted scenario disclose a near and mid future increase by 108% and 173%, and far future increases up to 251% compared to the reference period (baseline) concentrations. The E. coli concentration is reduced by - 54%, - 68%, and - 81% for all the projected time steps compared to the baseline concentrations. While highly improved sewerage and manure management options are adapted, the concentration is further reduced by - 96%, - 101%, and - 105%, respectively, compared to the baseline. Our modeling and scenario matrix study shows that reducing microbiological concentrations in the surface water is possible. Still, it requires rigorous sanitation and treatment options, and socioeconomic variables play an essential role besides climate change to determine the microbiological concentration of water resources and be included in future studies whenever water quality and health risks are considered.

Microbial contamination in surface water and potential health risks for peri-urban farmers of the Bengal delta

Ensuring safe irrigation practices is vital to sustaining food production in water-scarce delta areas. Bangladesh and many other developing countries discharge untreated wastewater into their surrounding surface water bodies, serving as the primary irrigation source. This indirect irrigation of wastewater is believed to pose threats to the farmers, consumers and market vendors and may also affect crop and soil quality. To assess the risk, peri-urban farmers who use surrounding water bodies of Khulna city, Bangladesh, for crop irrigation were selected for the study. The microbial and heavy metal concentrations were measured in water samples collected from various locations over different seasons. For heavy metals As, Co, Ni, Cd, Cr, Cu and Pb, concentrations were below the detection limit, whereas Al, Fe, Mn, Ti and Zn were present but below the FAO recommendation limit for safe irrigation. The mean concentrations of microbial parameters were above the thresholds of WHO guidelines for crop irrigation intended for human consumption. Significant temporal variations in Faecal Coliform, E. coli and Enterococcus concentrations in the water samples were observed. The annual risk of infection for farmers was determined using the screening-level Quantitative Microbial Risk Assessment (QMRA). The results indicated that the annual probability of infection with pathogenic E. coli in different seasons ranges between 5 × 10^-3 to 5 × 10^-2, above the WHO's acceptable threshold for annual risk of infection for safe water reuse in agriculture. During the farmers' survey, around 45% reported health-related issues and more than 26% reported suffering from water-borne diseases after getting in contact with polluted surface water. This illustrates the actuality of the risks in practice. To ensure safe irrigation, the health risks need to be reduced below the acceptable limits. Suggested technical measures include adequate treatment of wastewater before disposal into rivers and access to protective equipment for farmers. This should be complemented by raising awareness through education programs among farmers to reduce accidental ingestion.

Spatial distribution of physicochemical-bacteriological parametric quality and water quality index of Gomti River, India

Surface water bodies are vital source of water for human consumption, domestic needs, agriculture, industrial activities, and also for aquatic life and ecosystems. In this study, a stretch of river Gomti was studied at 5 sites in Lucknow for two consecutive seasons during 2019. The physicochemical-bacteriological parameters of water and sediment samples were analyzed, followed by multivariate statistics. Mean values of pH, turbidity, EC, TS, TDS, TSS, DO, BOD, COD, nitrate, phosphate, sulfate, total alkalinity, total hardness, chloride, and fluoride during the pre-monsoon period were 7.4 ± 0.2, 5.2 ± 3.3 (NTU), 444.4 ± 97.4 (µS/cm), 274.6 ± 61.6, 254.3 ± 50.2, 21.9 ± 11, 5.4 ± 1.6, 10.2 ± 5.9, 31.2 ± 13.3, 1.2 ± 0.5, 1.7 ± 1.1, 25.9 ± 3.7, 204 ± 41.8, 146.2 ± 11.5, 15.5 ± 8.7, and 0.5 ± 0.1 mg/l, respectively. The corresponding values during the post-monsoon season were 7.5 ± 0.2, 5.5 ± 3.2 (NTU), 436 ± 75.1 (µS/cm), 273.7 ± 124.2, 209.7 ± 82.5, 63.9 ± 43.4, 5.6 ± 1.6, 15.8 ± 8.9, 39.2 ± 23.5, 5.4 ± 4.6, 1.4 ± 0.9, 25.5 ± 5, 199.2 ± 36.6, 134 ± 8.6, 20.2 ± 8.9, and 1.7 ± 0.2 mg/l, respectively. Concentration of pollutants significantly increased by 5-15% from sampling station S1 (upstream) to S5 (downstream). Enumerations of fecal coliform and Escherichia coli bacteria were low at S1 but significantly higher at the S5 site. WQI ranged from 88 to 345 during pre-monsoon and 159 to 422 during post-monsoon period, indicating poor water quality which was unsuitable for drinking purposes. Strong positive correlations (≥ 0.9) were observed among pH, chloride, phosphate, sulfate, turbidity, conductivity, TS, TDS, BOD, and COD for water samples during both seasons. The data reveals that pollution load increases gradually from upstream to downstream due to the increasing discharge of raw sewage. Regulatory bodies should formulate strict regulations and ensure their implementation for the protection and management of river water quality.

Resilient planning optimization through spatially explicit, Bi-directional sociohydrological modeling

Stormwater runoff is one critical urban issue that exemplifies the complexity in coupling human and natural systems. Innumerable studies have described and assessed the hydrological responses that result from land-use changes through a 'post land use change' hydrological analysis. Complex systems theory, however, suggests that the urban and ecological systems operate as an intertwined whole. This means that typical one-directional analysis can miss critical components of a bi-directional sociohydrological process. In addition, there is a difference in physical scales between hydrological analysis and policymaking that is often left unresolved. Typical hydrological models are limited to a watershed and are not easily applied to policymaking that is generally demarcated by a political boundary. These types of models also lack the spatial explicitness needed for physical design responses. To address these issues, we develop an integrated, finely scaled, spatially explicit sociohydrological modeling system. The coupled land use/stormwater model projects and assesses bi-directional sociohydrological impacts to changing land uses. We apply and test the system in McHenry County, Illinois, by modeling three scenarios to the year 2045. The results show that residential and commercial developments exhibit different responses to hydrological variables, resulting in varying patterns of land use locational choices. We also find that there is a conflict between developmental preferences that prefer to be located near water (housing) and those that prefer to be located away from runoff-prone water areas (commercial land uses). Our bi-directional modeling system simulates cell-to-cell interactions to produce quantifiable and practically useful outputs. The output for McHenry County, Illinois, includes specific, locational information on how to optimize developmental regulations in response to the contradictory developmental preferences and, more importantly, how to live with runoff in the context of resilience. This research supports the need for cell-based forward-looking modeling to better understand complex urban systems and strategically establish a resilient built environment.

Mapping global inputs and impacts from of human sewage in coastal ecosystems

Coastal marine ecosystems face a host of pressures from both offshore and land-based human activity. Research on terrestrial threats to coastal ecosystems has primarily focused on agricultural runoff, specifically showcasing how fertilizers and livestock waste create coastal eutrophication, harmful algae blooms, or hypoxic or anoxic zones. These impacts not only harm coastal species and ecosystems but also impact human health and economic activities. Few studies have assessed impacts of human wastewater on coastal ecosystems and community health. As such, we lack a comprehensive, fine-resolution, global assessment of human sewage inputs that captures both pathogens and nutrient flows to coastal waters and the potential impacts on coastal ecosystems. To address this gap, we use a new high-resolution geospatial model to measure and map nitrogen (N) and pathogen-fecal indicator organisms (FIO)-inputs from human sewage for ~135,000 watersheds globally. Because solutions depend on the source, we separate nitrogen and pathogen inputs from sewer, septic, and direct inputs. Our model indicates that wastewater adds 6.2Tg nitrogen into coastal waters, which is approximately 40% of total nitrogen from agriculture. Of total wastewater N, 63% (3.9Tg N) comes from sewered systems, 5% (0.3Tg N) from septic, and 32% (2.0Tg N) from direct input. We find that just 25 watersheds contribute nearly half of all wastewater N, but wastewater impacts most coastlines globally, with sewered, septic, and untreated wastewater inputs varying greatly across watersheds and by country. Importantly, model results find that 58% of coral and 88% of seagrass beds are exposed to wastewater N input. Across watersheds, N and FIO inputs are generally correlated. However, our model identifies important fine-grained spatial heterogeneity that highlight potential tradeoffs and synergies essential for management actions. Reducing impacts of nitrogen and pathogens on coastal ecosystems requires a greater focus on where wastewater inputs vary across the planet. Researchers and practitioners can also overlay these global, high resolution, wastewater input maps with maps describing the distribution of habitats and species, including humans, to determine the where the impacts of wastewater pressures are highest. This will help prioritize conservation efforts.Without such information, coastal ecosystems and the human communities that depend on them will remain imperiled.

Modelling the interplay of future changes and wastewater management measures on the microbiological river water quality considering safe drinking water production

Rivers are important for drinking water supply worldwide. However, they are often impacted by pathogen discharges via wastewater treatment plants (WWTP) and combined sewer overflows (CSO). To date, accurate predictions of the effects of future changes and pollution control measures on the microbiological water quality of rivers considering safe drinking water production are hindered due to the uncertainty of the pathogen source and transport variables. The aim of this study was to test an integrative approach for an improved understanding of these effects, i.e. climate change and population growth as well as enhanced treatment at WWTPs and/or prevention of CSOs. We applied a significantly extended version of QMRAcatch (v1.0 Python), a probabilistic-deterministic model that combines fate and transport modelling with quantitative microbial infection risk assessment. The impact of climatic changes until the period 2035-2049 was investigated by a conceptual semi-distributed hydrological model, based on regional climate model outputs. QMRAcatch was calibrated and validated using site- and source-specific data (human-associated genetic microbial source tracking marker and enterovirus). The study showed that the degree to which future changes affect drinking water safety strongly depends on the type and magnitude of faecal pollution sources and are thus highly site- and scenario-specific. For example, if the load of pathogens from WWTPs is reduced through enhanced treatment, climate-change driven increases in CSOs had a considerable impact. Preventing CSOs and installing enhanced treatment at the WWTPs together had the most significant positive effect. The simultaneous consideration of source apportionment and concentrations of reference pathogens, focusing on human-specific viruses (enterovirus, norovirus) and cross-comparison with bacterial and protozoan pathogens (Campylobacter, Cryptosporidium), was found crucial to quantify these effects. While demonstrated here for a large, wastewater-impacted river, the approach is applicable at other catchments and pollution sources. It allows assessing future changes and selecting suitable pollution control measures for long-term water safety planning.

Water quality prospective in Twenty First Century: Status of water quality in major river basins, contemporary strategies and impediments: A review

Water quality improvement is one of the top priorities in the global agenda endorsed by United Nation. In this review manuscript, a holistic view of water quality degradation such as concerned pollutants, source of pollution, and its consequences in major river basins around the globe (at least 1 from each continent and a total of 16 basins) is presented. Additionally, nine contemporary techniques such as field scale evaluation, watershed scale evaluation, strategies to identify critical source areas, optimization strategies for placement of best management practices (BMPs), social component in watershed modeling, machine learning algorithms to address water quality problems in complex natural systems concomitant with spatial heterogeneity, establishing a total maximum daily loads (TMDLs), remote sensing in monitoring water quality, and developing water quality index are discussed. Next, the existing barriers to improve water quality are classified into primary and secondary impediments. A detail discussion of three primary impediments (climate change, urbanization and industrial activities, and agriculture) and ten secondary impediments (availability of water quality data, complexity of system, lack of skilled person, environmental legislation, fragmented mandate, limitation in resources, environmental awareness, resistance to change, alteration of nutrient ratio by river damming, and emerging pollutants) are illustrated. Finally, considering all the existing knowledge gaps pertaining to contemporary strategies, a future direction of water quality research is outlined to significantly improve the water quality around the globe.

Potential Impacts of Climate and Land Use Change on the Water Quality of Ganga River around the Industrialized Kanpur Region

The heavily industrialised Kanpur region is the most polluted stretch of the Ganga river because of excessive pollutant discharge from the industries. Agricultural runoff along with climate change further adds to the pollution risk in this industrialised stretch of Ganga. In this paper, we analyse the potential impacts of climate change and land use change on the water quality in this stretch under hypothetical scenarios using the water quality model, QUAL2K. Water quality indicators of Dissolved Oxygen (DO), Biochemical Oxygen Demand, ammonia, nitrate, total nitrogen, organic-, inorganic- and total phosphorous and faecal coliform are assessed for eight climate change and six land use land cover scenarios. Eutrophic conditions are observed in this stretch of the river for all scenarios, implying severe impacts on aquatic life. DO is identified as the most sensitive indicator to the climate change scenarios considered, while nutrients and faecal coliform are more sensitive to the land use scenarios. Increase in agricultural land area leads to larger nutrient concentration while increase in built-up area causes an increase in faecal coliform concentration. Results from this hypothetical study could provide valuable guidance for improving the water quality of the Ganges in future climate change and land use change scenarios.

Quantifying public health risks from exposure to waterborne pathogens during river bathing as a basis for reduction of disease burden

A Quantitative Microbial Risk Assessment (QMRA) technique was applied to assess the public health risk from exposure to infectious microorganisms at bathing areas of three rivers in Bangladesh. The QMRA assessed the probability of illness due to the accidental ingestion of river water impacted by untreated sewage. The simplified QMRA was based on average concentrations of four reference pathogens Escherichia coli (E. coli) O157:H7, Cryptosporidium spp, norovirus and rotavirus relative to indicator bacterium E. coli. Public health risk was estimated as the probability of infection and illness from a single exposure of bathers. The risks of illness were ranged from 7 to 10% for E. coli O157:H7, 13 to 19% for Cryptosporidium, 7 to 10% for norovirus and 12 to 17% for rotavirus. The overall risk of illness at the rivers was slightly higher in children (9-19%) compared to adults (7-16%). The risks of illness in individuals exposed to the river bathing were unacceptably high, exceeding the USEPA acceptable risk of 3-6 illnesses per hundred bathing events. This study gives a basis for reducing the burden of disease in the population by applying appropriate risk management. Findings and methods of this study will be helpful for other countries with similar socio-economic and geographic settings.

Climate Change Policy Implications of Sustainable Development Pathways in Korea at Sub-National Scale

Climate action is goal 13 of UN’s 17 Sustainable Development Goals (SDG). Future impacts of climate change depend on climatic changes, the level of climate change policy, both mitigation and adaptation, and socio-economic status and development pathways. To investigate the climate change policy impact of socio-economic development pathways, we develop three pathways. Climate change affects socio-economic development in many ways. We interpret global storylines into South Korean contexts: Shared Socio-economic Pathway 1 (SSP1), SSP2, and SSP3 for population, economy, and land use. SSP elements and proxies were identified and elaborated through stakeholder participatory workshops, demand survey on potential users, past trends, and recent national projections of major proxies. Twenty-nine proxies were quantified using sector-specific models and downscaled where possible. Socio-economic and climate scenarios matrixes enable one to quantify the contribution of climate, population, economic development, and land-use change in future climate change impacts. Economic damage between climate scenarios is different in SSPs, and it highlights that SSPs are one of the key components for future climate change impacts. Achieving SDGs generates additional incentives for local and national governments as it can reduce mitigation and adaptation policy burden.

Impacts of a changing earth on microbial dynamics and human health risks in the continuum between beach water and sand

Although infectious disease risk from recreational exposure to waterborne pathogens has been an active area of research for decades, beach sand is a relatively unexplored habitat for the persistence of pathogens and fecal indicator bacteria (FIB). Beach sand, biofilms, and water all present unique advantages and challenges to pathogen introduction, growth, and persistence. These dynamics are further complicated by continuous exchange between sand and water habitats. Models of FIB and pathogen fate and transport at beaches can help predict the risk of infectious disease from beach use, but knowledge gaps with respect to decay and growth rates of pathogens in beach habitats impede robust modeling. Climatic variability adds further complexity to predictive modeling because extreme weather events, warming water, and sea level change may increase human exposure to waterborne pathogens and alter relationships between FIB and pathogens. In addition, population growth and urbanization will exacerbate contamination events and increase the potential for human exposure. The cumulative effects of anthropogenic changes will alter microbial population dynamics in beach habitats and the assumptions and relationships used in quantitative microbial risk assessment (QMRA) and process-based models. Here, we review our current understanding of microbial populations and transport dynamics across the sand-water continuum at beaches, how these dynamics can be modeled, and how global change factors (e.g., climate and land use) should be integrated into more accurate beachscape-based models.

The impact of socioeconomic system on the river system in a heavily disturbed basin

The quantitative assessment of the impact of socioeconomic development on river water environment is important to the scientific management of river basins. However, current methods have high data requirements or are difficult to deal with the impact between systems (which is defined by a collection of indicators). This paper first uses canonical correlation analysis (CCA) to understand the relationship between socialeconomic system (defined by a set of indicators reflecting socioeconomic development) and river system (defined by a set of indicators reflecting river water environment), and then proposes a method to assess the impact of socioeconomic system on river system by integrating CCA and the degrees of influence of river system indicators. The proposed method and framework are applied to the Shaying River Basin with the characteristics of multi-sluices, high pollution, and dense population based on data from 2000 to 2015. Results indicate that socioeconomic and river systems are highly related to each other with the average influence degree of greater than 0.9, indicating very close relationships between socioeconomic and river systems. The changes of influence degree vary between 0.19 and 0.79 with a turning point in 2010. Most of the influence levels are "moderate" (influence degree between 0.4 and 0.6) or "high" (influence degrees between 0.6 and 0.8) before 2010 but become to "low" (influence degrees between 0.2 and 0.4) since then. In addition, the influence degree shows a significant increase from upstream to downstream with Zhoukou Station as the turning point, meaning that the stronger the human activity is, the greater the impact of the socioeconomic system on the river system is. The main influential factors are population density and sewage treatment rate. The proposed method contributes to the research in river management with limited data availability and the results can serve as an important reference for basin management.

The impact of socio-economic development and climate change on E. coli loads and concentrations in Kabul River, Pakistan

Microbial pollution is a major problem worldwide. High concentrations of Escherichia coli have been found in Kabul River in Pakistan. E. coli concentrations vary under different socio-economic conditions, such as population and livestock densities, urbanisation, sanitation and treatment of wastewater and manure, and climate-change aspects, such as floods and droughts. In this paper, we assess potential future E. coli loads and concentrations in the Kabul River using the Soil and Water Assessment Tool with scenarios that are based on the most recent Shared Socio-economic Pathways and Representative Concentration Pathways (SSPs and RCPs) developed for the Intergovernmental Panel on Climate Change (IPCC). Scenario_1 considers moderate population and livestock density growth, planned urbanisation and strongly improved wastewater and manure treatment (based on SSP1, "Sustainability"), and moderate climate change (RCP4.5, moderate greenhouse gas (GHG) emissions). Scenario_2 considers strong population and livestock density growth, moderate urbanisation, slightly improved wastewater treatment, no manure treatment (based on SSP3, "Regional rivalry") and strong climate change (RCP8.5, high GHG emissions). Simulated E. coli responses to Scenario_2 suggest a mid-century increase in loads by 111% and a late century increase of 201% compared to baseline loads. Similarly, simulated E. coli loads are reduced by 60% for the mid-century and 78% for the late century compared to the baseline loads. When additional treatment is simulated in Scenario_1, the loads are reduced even further by 94%, 92% and 99.3% compared to the baseline concentrations when additional tertiary treatment, manure treatment or both have been applied respectively. This study is one of the first to apply combined socio-economic development and climate change scenario analysis with an E. coli concentration model to better understand how these concentrations may change in the future. The scenario analysis shows that reducing E. coli concentrations in Pakistan's rivers is possible, but requires strongly improved waste water treatment and manure management measures.