Climate change and land use drivers of fecal bacteria in tropical hawaiian rivers

Village Settlements in Mountainous Tropical Areas, Hotspots of Fecal Contamination as Evidenced by Escherichia coli and Stanol Concentrations in Stormwater Pulses

Fecal bacteria in surface water may indicate threats to human health. Our hypothesis is that village settlements in tropical rural areas are major hotspots of fecal contamination because of the number of domestic animals usually roaming in the alleys and the lack of fecal matter treatment before entering the river network. By jointly monitoring the dynamics of Escherichia coli and of seven stanol compounds during four flood events (July-August 2016) at the outlet of a ditch draining sewage and surface runoff out of a village of Northern Lao PDR, our objectives were (1) to assess the range of E. coli concentration in the surface runoff washing off from a village settlement and (2) to identify the major contributory sources of fecal contamination using stanol compounds during flood events. E. coli pulses ranged from 4.7 × 104 to 3.2 × 106 most probable number (MPN) 100 mL-1, with particle-attached E. coli ranging from 83 to 100%. Major contributory feces sources were chickens and humans (about 66 and 29%, respectively), with the highest percentage switching from the human pole to the chicken pole during flood events. Concentrations indicate a severe fecal contamination of surface water during flood events and suggest that villages may be considered as major hotspots of fecal contamination pulses into the river network and thus as point sources in hydrological models.

A comparison of soil Staphylococcus aureus and fecal indicator bacteria concentrations across land uses in a Hawaiian watershed

Staphylococcus aureus, methicillin-resistant S. aureus (MRSA), and fecal indicator bacteria (FIB; Enterococcus spp., Clostridium perfringens) concentrations increase in Hawaiian streams and estuaries following storms and pose a health threat to recreational water users. To reduce this risk, watershed bacteria sources need to be identified for management actions. This study's goals were to identify soil bacteria sources among different land uses and to determine if their concentrations were associated with different soil properties. Soil samples were collected three times on 24 d between October 2017 and November 2018 at urban, agriculture, and native-forest land uses in the Hilo Bay watershed, Hawai'i Island, Hawai'i. Soil bacteria concentrations were quantified using culturing techniques with selective media. Staphylococcus aureus, MRSA, and FIB were present in soil from all land uses. Bacteria concentrations were highest in urban soils and lowest in native-forest soils, with up to three orders of magnitude differences among land uses. Staphylococcus aureus, MRSA, and FIB soil concentrations were positively correlated with each other and with soil temperature and pH, but inversely correlated with soil moisture and organic matter content. Our results demonstrate that soils are a watershed bacteria source and that some soil properties affect their concentrations. Identifying these sources is critical for implementing management actions to reduce pathogen loads to estuaries and transmission to recreational water users.

Modelling the influence of short-term climate variability on drinking water quality in tropical developing countries: A case study in Tanzania

Climate change is expected to increase the prevalence of water-borne diseases especially in developing countries. Climate-resilient drinking water supplies are critical to protect communities from faecal contamination and thus against increasing disease risks. However, no quantitative assessment exists for the impacts of short-term climate variability on faecal contamination at different drinking water sources in developing countries, while existing understanding remains largely conceptual. This critical gap limits the ability to predict drinking water quality under climate change or to recommend climate-resilient water sources for vulnerable communities. This study aims to provide such quantitative understanding by investigating the relationships between faecal contamination and short-term climate variability across different types of water sources. We collected a novel dataset with over 20 months' monitoring of weather, Escherichia coli (E. coli) and total coliforms, at 233 different water sources in three climatically different regions in Tanzania. We then took a rigorous statistical analysis with Bayesian hierarchical models, to relate both contamination occurrence and amount to climate variability. The model results explained the temporal variability in drinking water faecal contamination using climate predictors, and also revealed the climate sensitivity of faecal contamination for individual water sources. We found that: a) short-term climate variability and baseline contamination levels can explain about half the observed variability in faecal contamination (R² ≥ 0.44); b) increased contamination was most consistently related to recent heavy rainfall and high temperature across different water sources; c) unimproved water sources such as the unprotected dug wells have substantially higher climate sensitivity. Based on these results, we can expect substantial increases in drinking water contamination risks across tropical Sub-Saharan Africa and South-East Asian developing countries under a warmer climate, which highlight the urgent need of protecting vulnerable communities from the severe climate impacts.

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.

A REVIEW OF WATER QUALITY RESPONSES TO AIR TEMPERATURE AND PRECIPITATION CHANGES 2: NUTRIENTS, ALGAL BLOOMS, SEDIMENT, PATHOGENS

In this paper we review the published, scientific literature addressing the response of nutrients, sediment, pathogens and cyanobacterial blooms to historical and potential future changes in air temperature and precipitation. The goal is to document how different attributes of water quality are sensitive to these drivers, to characterize future risk, to inform management responses and to identify research needs to fill gaps in our understanding. Results suggest that anticipated future changes present a risk of water quality and ecosystem degradation in many U.S. locations. Understanding responses is, however, complicated by inherent high spatial and temporal variability, interactions with land use and water management, and dependence on uncertain changes in hydrology in response to future climate. Effects on pollutant loading in different watershed settings generally correlate with projected changes in precipitation and runoff. In all regions, increased heavy precipitation events are likely to drive more episodic pollutant loading to water bodies. The risk of algal blooms could increase due to an expanded seasonal window of warm water temperatures and the potential for episodic increases in nutrient loading. Increased air and water temperatures are also likely to affect the survival of waterborne pathogens. Responding to these challenges requires understanding of vulnerabilities, and management strategies to reduce risk.

Collaboration Across Worldviews: Managers and Scientists on Hawai'i Island Utilize Knowledge Coproduction to Facilitate Climate Change Adaptation

Complex socio-ecological issues, such as climate change have historically been addressed through technical problem solving methods. Yet today, climate science approaches are increasingly accounting for the roles of diverse social perceptions, experiences, cultural norms, and worldviews. In support of this shift, we developed a research program on Hawai'i Island that utilizes knowledge coproduction to integrate the diverse worldviews of natural and cultural resource managers, policy professionals, and researchers within actionable science products. Through their work, local field managers regularly experience discrete land and waterscapes. Additionally, in highly interconnected rural communities, such as Hawai'i Island, managers often participate in the social norms and values of communities that utilize these ecosystems. Such local manager networks offer powerful frameworks within which to co-develop and implement actionable science. We interviewed a diverse set of local managers with the aim of incorporating their perspectives into the development of a collaborative climate change research agenda that builds upon existing professional networks utilized by managers and scientists while developing new research products. We report our manager needs assessment, the development process of our climate change program, our interactive forums, and our ongoing research products. Our needs assessment showed that the managers' primary source of information were other professional colleagues, and our in-person forums informed us that local managers are very interested in interacting with a wider range of networks to build upon their management capacities. Our initial programmatic progress suggests that co-created research products and in-person forums strengthen the capacities of local managers to adapt to change.

Modeling the Impact of Land Use Change on Basin-scale Transfer of Fecal Indicator Bacteria: SWAT Model Performance

Land use change from annual crops to commercial tree plantations can modify flow and transport processes at the watershed scale, including the fate and transport of fecal indicator bacteria (FIB), such as . The Soil and Water Assessment Tool (SWAT) is a useful means for integrating watershed characteristics and simulating water and contaminants. The objective of this study was to provide a comprehensive assessment of the impact of land use change on microbial transfer from soils to streams using the SWAT model. This study was conducted for the Houay Pano watershed located in northern Lao People's Democratic Republic. Under the observed weather conditions, the SWAT model predicted a decrease from 2011 to 2012 and an increase from 2012 to 2013 in surface runoff, suspended solids, and transferred from the soil surface to streams. The amount of precipitation was important in simulating surface runoff, and it subsequently affected the fate and transport of suspended solids and bacteria. In simulations of identical weather conditions and different land uses, fate and transport was more sensitive to the initial number of than to its drivers (i.e., surface runoff and suspended solids), and leaf area index was a significant factor influencing the determination of the initial number of on the soil surface. On the basis of these findings, this study identifies several limitations of the SWAT fertilizer and bacteria modules and suggests measures to improve our understanding of the impacts of land use change on FIB in tropical watersheds.

Human Bacteroides and total coliforms as indicators of recent combined sewer overflows and rain events in urban creeks

Combined sewer overflows (CSOs) are a known source of human fecal pollution and human pathogens in urban water bodies, which may present a significant public health threat. To monitor human fecal contamination in water, bacterial fecal indicator organisms (FIOs) are traditionally used. However, because FIOs are not specific to human sources and do not correlate with human pathogens, alternative fecal indicators detected using qPCR are becoming of interest to policymakers. For this reason, this study measured correlations between the number and duration of CSOs and mm of rainfall, concentrations of traditional FIOs and alternative indicators, and the presence of human pathogens in two urban creeks. Samples were collected May-July 2016 and analyzed for concentrations of FIOs (total coliforms and E. coli) using membrane filtration as well as for three alternative fecal indicators (human Bacteroides HF183 marker, human polyomavirus (HPoV), pepper mild mottle virus (PMMoV)) and nine human pathogens using qPCR. Four of the nine pathogens analyzed were detected at these sites including adenovirus, Enterohemorrhagic E. coli, norovirus, and Salmonella. Among all indicators studied, human Bacteroides and total coliforms were significantly correlated with recent CSO and rainfall events, while E. coli, PMMoV, and HPoV did not show consistent significant correlations. Further, human Bacteroides were a more specific indicator, while total coliforms were a more sensitive indicator of CSO and rainfall events. Results may have implications for the use and interpretation of these indicators in future policy or monitoring programs.

A geospatial analysis of land use and stormwater management on fecal coliform contamination in North Carolina streams

Although non-point source (NPS) pathogen pollution is a leading cause of stream impairment in the United States, the sources of NPS pollution are often difficult to ascertain. While previous studies have employed land use regression methods to develop a greater understanding of the sources and dynamics of microbial NPS pollution, little work has explicitly considered the effects of local, state, and federal stormwater management policies on water quality across multiple watersheds or at larger spatial scales. How do land use and stormwater management efforts collectively influence fecal coliform (FC) levels at a regional or multiple-watershed scale? We construct a unique spatial regression model of stream FC pollution (n=327 monitoring stations) throughout the state of North Carolina (USA), incorporating both land cover and urban development variables. We then use a subset of our data (n_bmp=80 monitoring stations) to incorporate local stormwater control measures and stormwater management policies. Results demonstrate that the inclusion of policy and management variables improves the explanatory capacity for FC levels (R²=0.4412 versus R²=0.5323). Locally, this model can be used to better target stream restoration and water quality mitigation actions and investments, as well as help to predict FC levels at unmonitored locations throughout North Carolina's stream network. More generally, the novel structure of this model can also help examine the large-scale effects of stormwater regulations on surface water pathogen levels, helping researchers and planners better predict water quality in the absence of extensive monitoring station data.

Significance of beach geomorphology on fecal indicator bacteria levels

Large databases of fecal indicator bacteria (FIB) measurements are available for coastal waters. With the assistance of satellite imagery, we illustrated the power of assessing data for many sites by evaluating beach features such as geomorphology, distance from rivers and canals, presence of piers and causeways, and degree of urbanization coupled with the enterococci FIB database for the state of Florida. We found that beach geomorphology was the primary characteristic associated with enterococci levels that exceeded regulatory guidelines. Beaches in close proximity to marshes or within bays had higher enterococci exceedances in comparison to open coast beaches. For open coast beaches, greater enterococci exceedances were associated with nearby rivers and higher levels of urbanization. Piers and causeways had a minimal contribution, as their effect was often overwhelmed by beach geomorphology. Results can be used to understand the potential causes of elevated enterococci levels and to promote public health.

Modeling the interannual variability of microbial quality metrics of irrigation water in a Pennsylvania stream

Knowledge of the microbial quality of irrigation waters is extremely limited. For this reason, the US FDA has promulgated the Produce Rule, mandating the testing of irrigation water sources for many farms. The rule requires the collection and analysis of at least 20 water samples over two to four years to adequately evaluate the quality of water intended for produce irrigation. The objective of this work was to evaluate the effect of interannual weather variability on surface water microbial quality. We used the Soil and Water Assessment Tool model to simulate E. coli concentrations in the Little Cove Creek; this is a perennial creek located in an agricultural watershed in south-eastern Pennsylvania. The model performance was evaluated using the US FDA regulatory microbial water quality metrics of geometric mean (GM) and the statistical threshold value (STV). Using the 90-year time series of weather observations, we simulated and randomly sampled the time series of E. coli concentrations. We found that weather conditions of a specific year may strongly affect the evaluation of microbial quality and that the long-term assessment of microbial water quality may be quite different from the evaluation based on short-term observations. The variations in microbial concentrations and water quality metrics were affected by location, wetness of the hydrological years, and seasonality, with 15.7-70.1% of samples exceeding the regulatory threshold. The results of this work demonstrate the value of using modeling to design and evaluate monitoring protocols to assess the microbial quality of water used for produce irrigation.

Spatial and temporal microbial pollution patterns in a tropical estuary during high and low river flow conditions

Spatial and temporal patterns of coastal microbial pollution are not well documented. Our study examined these patterns through measurements of fecal indicator bacteria (FIB), nutrients, and physiochemical parameters in Hilo Bay, Hawai'i, during high and low river flow. >40% of samples tested positive for the human-associated Bacteroides marker, with highest percentages near rivers. Other FIB were also higher near rivers, but only Clostridium perfringens concentrations were related to discharge. During storms, FIB concentrations were three times to an order of magnitude higher, and increased with decreasing salinity and water temperature, and increasing turbidity. These relationships and high spatial resolution data for these parameters were used to create Enterococcus spp. and C. perfringens maps that predicted exceedances with 64% and 95% accuracy, respectively. Mapping microbial pollution patterns and predicting exceedances is a valuable tool that can improve water quality monitoring and aid in visualizing FIB hotspots for management actions.

Influence of Climate Extremes and Land Use on Fecal Contamination of Shallow Tubewells in Bangladesh

Climate extremes in conjunction with some land use practices are expected to have large impacts on water quality. However, the impacts of land use and climate change on fecal contamination of groundwater has not been well characterized. This work quantifies the influences of extreme weather events and land use practices on Escherichia coli presence and concentration in groundwater from 125 shallow wells, a dominant drinking water resource in rural Bangladesh, monitored over a 17 month period. The results showed that E. coli presence was significantly associated with the number of heavy rain days, developed land and areas with more surface water. These variables also had significant impacts on E. coli concentration, with risk ratios of 1.38 (95% CI = 1.16, 1.65), 1.07 (95% CI: 1.05, 1.09), and 1.02 (95% CI = 1.01, 1.03), respectively. Significant synergistic effects on E. coli presence and concentration were observed when land use and weather variables were combined. The findings suggest that climate extremes and land use practices, particularly urbanization, might promote fecal contamination of shallow well water, thus increasing the risk of diarrheal diseases.

Rainfall intensity effects on removal of fecal indicator bacteria from solid dairy manure applied over grass-covered soil

The rainfall-induced release of pathogens and microbial indicators from land-applied manure and their subsequent removal with runoff and infiltration precedes the impairment of surface and groundwater resources. It has been assumed that rainfall intensity and changes in intensity during rainfall do not affect microbial removal when expressed as a function of rainfall depth. The objective of this work was to test this assumption by measuring the removal of Escherichia coli, enterococci, total coliforms, and chloride ion from dairy manure applied in soil boxes containing fescue, under 3, 6, and 9cmh(-1) of rainfall. Runoff and leachate were collected at increasing time intervals during rainfall, and post-rainfall soil samples were taken at 0, 2, 5, and 10cm depths. Three kinetic-based models were fitted to the data on manure-constituent removal with runoff. Rainfall intensity appeared to have positive effects on rainwater partitioning to runoff, and removal with this effluent type occurred in two stages. While rainfall intensity generally did not impact the parameters of runoff-removal models, it had significant, inverse effects on the numbers of bacteria remaining in soil after rainfall. As rainfall intensity and soil profile depth increased, the numbers of indicator bacteria tended to decrease. The cumulative removal of E. coli from manure exceeded that of enterococci, especially in the form of removal with infiltration. This work may be used to improve the parameterization of models for bacteria removal with runoff and to advance estimations of depths of bacteria removal with infiltration, both of which are critical to risk assessment of microbial fate and transport in the environment.

A short review of fecal indicator bacteria in tropical aquatic ecosystems: knowledge gaps and future directions

Given the high numbers of deaths and the debilitating nature of diseases caused by the use of unclean water it is imperative that we have an understanding of the factors that control the dispersion of water borne pathogens and their respective indicators. This is all the more important in developing countries where significant proportions of the population often have little or no access to clean drinking water supplies. Moreover, and notwithstanding the importance of these bacteria in terms of public health, at present little work exists on the persistence, transfer and proliferation of these pathogens and their respective indicator organisms, e.g., fecal indicator bacteria (FIB) such as Escherichia coli and fecal coliforms in humid tropical systems, such as are found in South East Asia or in the tropical regions of Africa. Both FIB and the waterborne pathogens they are supposed to indicate are particularly susceptible to shifts in water flow and quality and the predicted increases in rainfall and floods due to climate change will only exacerbate the problems of contamination. This will be furthermore compounded by the increasing urbanization and agricultural intensification that developing regions are experiencing. Therefore, recognizing and understanding the link between human activities, natural process and microbial functioning and their ultimate impacts on human health are prerequisites for reducing the risks to the exposed populations. Most of the existing work in tropical systems has been based on the application of temperate indicator organisms, models and mechanisms regardless of their applicability or appropriateness for tropical environments. Here, we present a short review on the factors that control FIB dynamics in temperate systems and discuss their applicability to tropical environments. We then highlight some of the knowledge gaps in order to stimulate future research in this field in the tropics.