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Hydrology Predominates Over Harvest History and Landscape Variation to Control Water Quality and Disinfection Byproduct Formation Potentials in Forested Pacific Coast Watersheds
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  • Alyssa K. Bourgeois*
    Alyssa K. Bourgeois
    Department of Biological Sciences, University of Alberta, Edmonton T6G 2E9, Canada
    *Email: [email protected]
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    Orcidhttps://orcid.org/0009-0001-9376-4282
  • Suzanne E. Tank
    Suzanne E. Tank
    Department of Biological Sciences, University of Alberta, Edmonton T6G 2E9, Canada
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  • William C. Floyd
    William C. Floyd
    Department of Geography, Vancouver Island University, Nanaimo V9R 5S5, Canada
    Ministry of Forests, Nanaimo V9T 6E9, Canada
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  • Monica B. Emelko
    Monica B. Emelko
    Water Science, Technology & Policy Group, Department of Civil & Environmental Engineering, University of Waterloo, Waterloo N2L 3G1, Canada
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    Orcidhttps://orcid.org/0000-0002-8295-0071
  • Fariba Amiri
    Fariba Amiri
    Water Science, Technology & Policy Group, Department of Civil & Environmental Engineering, University of Waterloo, Waterloo N2L 3G1, Canada
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Cite this: ACS EST Water 2024, 4, 4, 1335–1345
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https://doi.org/10.1021/acsestwater.3c00471
Published March 18, 2024

Copyright © 2024 The Authors. Published by American Chemical Society. This publication is licensed under

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Abstract

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Despite the global importance of forested watersheds as sources of drinking water, few studies have examined the effects of forestry on drinking water treatability. Relatively little is known about how the interaction between landscape variation and flow impacts source water quality and what this interaction means for drinking water treatability. To address this knowledge gap, we examined variability in sediments, dissolved organic matter, and disinfection byproduct formation potentials (DBP-FPs) across a range of flow conditions in four small watersheds with contrasting forest harvest histories and soil characteristics on Vancouver Island. Storm event-driven change in streamflow was the primary driver of water quality and DBP-FPs at our sites, with greater changes during stormflow (e.g., a 3-fold increase in dissolved organic carbon concentrations) than those across contrasting watersheds. Flow-driven changes in water quality and DBP-FPs were not significantly different across watersheds with different harvest histories; muted responses may be attributed to widespread second growth forests (i.e., recent harvesting effects may be confounded by historical harvest), forestry practices (e.g., slash burning), or soils with low organic carbon storage. This study suggests that variation in hydrology predominates over harvest history and soil characteristics to drive water quality and DBP-FPs on the east coast of Vancouver Island.

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Synopsis

Hydrologic changes drive water quality and disinfection byproduct formation potentials across four small, second-order watersheds in Canada’s Pacific Maritime Region.

1. Introduction

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The efficiency of drinking water treatment is often challenged by shifts in turbidity, total suspended solids (TSS), dissolved organic matter carbon concentrations (DOM-[C]), and DOM composition. (1,2) DOM is a key driver of particle charge in natural water and thus affects chemical coagulant dosing requirements during drinking water treatment. (1,3) DOM is also the principal precursor in the formation of disinfection byproducts (DBPs): trihalomethanes (THMs) and haloacetic acids (HAAs) are the most common groups of DBPs that are produced through the reaction of DOM (especially higher molecular weight, aromatic DOM) with common chlorine-based disinfectants. (4,5) The concentrations of THMs and HAAs are regulated in treated drinking water because chronic exposure to DBPs may increase risks of some types of cancer. (5,6) In Canada, the maximum acceptable concentrations for THMs and HAAs are 100 and 80 parts per billion (ppb), respectively, while in the U.S., maximum acceptable concentrations are 80 and 60 ppb. (7−9) Chemical clarification processes, such as coagulation/flocculation/sedimentation or sand-ballasted flocculation, partly remove DOM in treated drinking water. (2) Techno-ecological nature-based solutions, such as biological filtration, are increasingly used for DOM removal; (10−14) however, they are less efficient in removing the humic acid fraction of DOM, a key precursor for regulated DBPs. (15) Landscape disturbances that result in high concentrations of aromatic DOM may increase the potential for DBP formation during drinking water treatment. (1,5,6) Therefore, identifying key conditions (e.g., wildfire and storm events) contributing to fluctuations in DOM-[C] and DOM composition is critical to informing source water protection and drinking water treatment strategic planning and practices.
Across this range of conditions, undisturbed forested watersheds may be important for the provision of safe drinking water because of their ability to regulate DOM export and sediment yield. (16) With forest harvesting and other disturbances, water quality may deteriorate due to changes in hydrological flow paths and biogeochemical processes. (17−19) Notably, however, forest harvesting has also been suggested as an important tool for managing drinking water treatability threats from landscape disturbances, such as wildfire, that can be exacerbated by climate change (20) and have long-term effects on treatability even at large basin scales. (21,22) Previous studies have shown that harvest intensity (23) and hydrologic connectivity (24) act concurrently to regulate water quality in temperate forested watersheds; for example, clear cutting usually increases turbidity and TSS and may also increase DOM-[C], (19) but this effect may be dampened under conditions of low hydrologic connectivity. (25) Thus, considering landscape disturbance – including harvest history – in conjunction with hydroclimatic variability is essential when assessing water quality and resultant treatability, including DBP formation potential (DBP-FP).
Storm event-driven changes in water quality are generally well understood, (26−28) with emerging research further exploring effects on DBP-FP and other aspects of treatability. (1,27) However, responses can be complex because of regional variation in seasonal temperatures, antecedent moisture conditions, hydroclimatic regimes, and disturbance history. (28−31) While prior studies have demonstrated that landscape attributes (e.g., land cover composition) can determine water quality responses to rainfall events, (32,33) others have reported that the magnitude and timing of rainfall are primary controls on water quality. (31,34) As a result, there is a need for research focused on characterizing storm responses on compositionally diverse landscapes and their consequent impacts on source water quality and treatability.
Although the effects of forestry on watershed hydrology have received much attention in the past, (17,18,25,35) little of this research has focused on the interaction of forest harvest and storm events on water quality and treatability. Given the extensive history of forest harvest, (36,37) high precipitation as rain and snow, (38) propensity for intense storm events, (31) and high reliance on surface water as a drinking water source on Canada’s Pacific Coast, (39,40) this region provides an ideal site for exploring variation in water quality and resultant DBP-FPs across storm and baseflow conditions in subwatersheds with varying harvest intensities. Here, we evaluate how water quality (i.e., turbidity, TSS, DOM-[C], and spectral characteristics to inform DOM composition) and DBP precursors (i.e., THM formation potential and HAA formation potential [THM-FP and HAA-FP], respectively) varied during storm events and between storm and baseflow conditions. This work occurred in watersheds with diverse harvest histories and soil characteristics in Canada’s Pacific Maritime ecozone. Our objectives were to: (1) investigate changes in water quality and DBP-FPs under contrasting flow conditions; (2) examine the combined and relative effects of forest harvest and storm events on water quality and DBP-FPs; and (3) identify leading drivers of DBP-FPs.

2. Methods

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2.1. Study Region

Our work occurred in four second-order subwatersheds of the Comox Lake watershed, which covers 461 km2 on the east coast of Vancouver Island (Figure 1) and occurs within the coastal western hemlock and mountain hemlock biogeoclimatic zones. (41) Similar to much of British Columbia, (39) the Comox Valley Regional District (CVRD) relies heavily on source waters that originate in forested watersheds, with 50,000 local residents depending on the Comox Lake watershed for drinking water. (40) Forest harvest represents the main anthropogenic land use in the Comox Lake watershed; harvesting has resulted in extensive clear-cut areas and a network of roads across subwatersheds. Forested subwatersheds were first harvested in the early 1900s, with recent harvests (since 1985) focusing on second growth forests. Most precipitation occurs in autumn and winter (mean annual precipitation = 2193 mm yr–1; autumn plus winter precipitation = 1798 mm yr–1; Figure 1 and Table S1). Mild, wet winters and cool to warm, dry summers characterize the local climate (mean annual temperature = 9.4 °C). (42)

Figure 1

Figure 1. (A) The Comox Lake watershed. Streams and harvested areas are shown on the map in addition to other relevant features. Sampling was performed under stormflow (n = 13–15, n = 5–6; November and December events) and baseflow (n = 4) conditions at four subwatershed sites (in red): Moat Creek (low harvest–shallow soil; LH-SS), Boston Creek (low harvest–deep soil; LH-DS), Toma Creek (high harvest–shallow soil; HH-SS), and Perserverance Creek (high harvest–deep soil; HH-DS). Rainfall data were collected from the nearest hydrometric station (in pink). (B) Total daily rainfall (mm) from 1 April 2019 to 31 March 2020, as measured at the “Cruikshank River Near the Mouth” Water Survey of Canada hydrometric station. Light blue bars correspond to sample collection dates; B indicates baseflow sample collection dates, while S represents storm events captured during the study period.

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The importance of Comox Lake as a forested drinking water source in a heavily managed landscape prompted us to investigate four tributary streams in the watershed (Figure 1A). Site selection was based on an initial assessment of 30 subwatershed sites, which were evaluated for their percent harvested area and average soil depth. From this range, we identified four study subwatersheds (the Perserverance, Toma, Boston, and Moat subwatersheds, ranging in size from 3.6 to 29.83 km2) that were representative of high and low harvest as well as deep and shallow soil. Since 1980, the highest percent area harvested was in the Perserverance (54.2%) and Toma (32.7%) subwatersheds, while the lowest was in Boston (12.7%) and Moat (6.5%; Table 1). (37) Notably, there were no accessible subwatershed sites in the study region that had not experienced recent forest harvest (i.e., no true “unharvested” sites). The Boston and Perserverance subwatersheds have thicker soils (1.7 to 1.8 m) and higher clay contents (9.1 to 14.7%) than the Moat and Toma subwatersheds (Table 1). (43,44) The study subwatersheds were therefore categorized as low harvest–shallow soil (LH-SS; Moat), low harvest–deep soil (LH-DS; Boston), high harvest–shallow soil (HH-SS; Toma), and high harvest–deep soil (HH-DS; Perserverance). The headwaters of LH-SS and LH-DS originate in protected subalpine and alpine environments. In addition, LH-SS has a lake (0.95 km2 of 29.83 km2 watershed area), and HH-DS has a small reservoir (0.17 km2 of 6.93 km2 watershed area) located in its headwaters. HH-DS is also known for significant erosion of silty clay streambanks, which can result in turbidity levels (>1 NTU) that exceed filtration exemption criteria (45) and can lead to the longer term need for intensive source water monitoring and management such as the turbidity control program in New York City (46) or the need to build a chemically assisted filtration plant or equivalent treatment. (45) Additional details on the study region are provided in Supplemental Text S1.
Table 1. Catchment Characteristics (Area, (87) Slope, (87) Elevation, (87) Soil Thickness, (43) Clay Content, (44) and Forest Cover (36)), Harvested Area (1985–2019), (37) and Dates of the Two Storms at Each of the Four Subwatershed Sites in the Comox Lake Watersheda
sitesubwatershedarea (km2)mean slope(° angle)mean elevation (m)mean soil depth (m)mean clay content (% soil)forest cover (% area)harvest 1985–2019 (% area)storm 1 (16–19 Nov. 2019)storm 2 (5–9 Dec. 2019)
LH-DSBoston9.2026.3801.71.79.185.012.743.2b 43c17.1b 19c
LH-SSMoat29.8324.21083.41.34.272.46.525.4b 41c14.2b 10c
HH-DSPerserverance6.9311.4379.21.814.745.854.253.8b 34c20.4b 9c
HH-SSToma3.6124.7952.31.14.167.332.782.2b 28c35.2b 8c
a

Both rainfall amounts and corresponding stream water level increases are noted for the two storm events. Note that areas harvested between 1985 and 2019 were not included in percent forest cover. Site abbreviations are as follows: low harvest–shallow soil (LH-SS), low harvest–deep soil (LH-DS), high harvest–shallow soil (HH-SS), and high harvest–deep soil (HH-DS).

b

Denotes rainfall (mm).

c

Denotes rise in the stream water level (cm).

2.2. Rainfall Data

Cumulative, 15 min rainfall data were obtained from four hydrometric stations located throughout the Comox Lake watershed (Figure 1A). A different station was chosen for each subwatershed site based on proximity; HH-DS was located 0.01 km from the nearest hydrometric station, LH-DS was 3.10 km, HH-SS was 5.16 km, and LH-SS was 9.92 km. Rainfall during our study period was variable across sites with contrasting topographies. A tipping bucket rain gauge was used to measure rainfall (mm), which comprised 99% of precipitation during the monitoring period (i.e., September to December 2019). (47)

2.3. Sampling Campaigns and Sample Collection

Between 6 November and 14 December 2019, high-frequency storm sampling was performed when rainfall events were forecasted to be greater than 25 mm in 24 h, following guidance on significant rainfall benchmarks generally (27) and for this specific region. (48) Storm water samples were collected via portable autosamplers (ISCO 6712) to capture the rising limb, peak, and falling limb of the storm hydrograph. Stream water levels were measured with a pressure transducer (KPSI 700, 0–300 cm range, 1% accuracy) and recorded at 5 min intervals on a CR300 Campbell Scientific data logger. During the monitoring period, we captured two storm events: one from 16–19 November (n = 13–15 samples, varying by subwatershed site) and another from 5–9 December (n = 5–6 samples). Grab samples were also collected approximately every 3 weeks from 3 September to 28 November 2019 (n = 4) as streamwater levels declined between periods of rainfall (Figure 1B; see Supplemental Text for specific dates). These “baseflow” (or “between-event”) conditions were delineated based on rainfall records, real-time water level data from pressure transducer sensors at the four subwatershed sites, and the “Cruikshank River Near the Mouth” Water Survey of Canada hydrometric station (Figure 1A).
Turbidity, TSS, DOM-[C], and spectral characteristics (to inform DOM composition) were evaluated in all storm and baseflow samples (raw data are provided in Tables S2, S3, and S4). Cations (Ca2+, K+, Mg2+, Na+, and dissolved Fe [dFe]), the oxygen isotopic composition of water (δ18O–H2O), and DBP-FPs were also analyzed in baseflow samples and storm samples from the 5–9 December storm event (Tables S2 and S3). Details of sample collection and processing can be found in Supplemental Text S2.

2.4. Stream Water Quality Analyses

Filters used for TSS analysis (mg L–1) were dried in an oven at 60 °C for 24 h and subsequently weighed. Dissolved cations (μmol L–1) were analyzed on an inductively coupled plasma–optical emission spectrometer (Thermo Scientific iCAP 6300). Turbidity (NTU) and DOM-[C] (mg L–1) were measured using a portable turbidimeter (Hach 2100Q) and a TOC-V analyzer (Shimadzu), respectively. δ18O–H2O (‰) was quantified on an L2130-i analyzer (Picarro). Fluorescence and absorbance were measured on an Aqualog spectrofluorometer (Horiba Scientific) and used to calculate DOM compositional indices. Specifically, fluorescent excitation–emission matrices (EEMs) were input into parallel factor (PARAFAC) analysis to determine individual components, (49) while absorbance was used to compute the Napierian absorption coefficient at 254 nm (a254; m–1), the specific ultraviolet absorbance at 254 nm (SUVA254, L mg-C–1 m–1; increases with DOM aromaticity), and the spectral slope coefficient from 275–295 nm (S275–295, nm–1; decreases with increasing DOM molecular weight). (50,51) To ensure accurate SUVA254 values, we measured dFe, (52) which was always less than 0.11 mg L–1 and often below detection, indicating negligible effects on SUVA254. Additional information on the calculation of DOM compositional metrics and PARAFAC analysis is provided in Supplemental Text S3.

2.5. Analysis of True Disinfection Byproduct Formation Potentials (DBP-FPs)

True DBP-FPs were assessed using Standard Method 5710 B. (53) While other formation potential tests such as uniform formation conditions better reflect the potential for DBP formation within drinking water distribution systems, (54) the true FP test assesses complete reactivity of DBP precursors and allows for cross-site comparisons. In treated drinking water, the four main constituents (trichloromethane [TCM], bromodichloromethane [BDCM], dibromochloromethane [DBCM], and tribromomethane [TBM]) of THMs are termed total THMs (TTHM; μg L–1). The sum of trichloroacetic acid (TCAA), dichloroacetic acid (DCAA), monochloroacetic acid (MCAA), monobromoacetic acid (MBAA), and dibromoacetic acid (DBAA) is known as HAA5 (μg L–1). Both TTHM and HAA5 were evaluated; detection limits for each compound are listed in Table S5. THM and HAA extracts were measured on a gas chromatograph with a mass spectrometer detector to derive true formation potentials. Additional details on the analysis of DBP-FPs, including detection limits, can be found in Supporting Information Text S4 and Table S5.

2.6. Data Treatment and Analyses

All statistical analyses were conducted using R (4.0.2). (55) Data were assessed for linearity, normality (Shapiro–Wilk test), independence, and skewness (>2.0) before analyses and log transformed for normality if required (packages stats and GGally). (55,56) For data analyses, major cations (Ca2+, K+, Mg2+, and Na+) were correlated and thus summed as a molar total (μmol L–1). In addition, individual THM and HAA species FPs were summed to yield total FP (i.e., TTHM-FP and HAA5-FP; μg L–1). For some analyses, TTHM-FP and HAA5-FP were normalized to DOM-[C] to assess specific reactivity. For DBP-FP scatterplots and ANOVAs (described below), initial stormflow samples were categorized as baseflow (see additional information in Supplemental Text S5).
To evaluate changes in water quality and DBP-FPs during stormflow and baseflow conditions, we created box plots, scatterplots, and hysteresis plots. (55,57,58) Hysteresis was evaluated for turbidity, DOM-[C], S275–295, a254, TTHM-FP, and HAA5-FP. We examined the slope of the concentration-stage relationship to assess whether solutes displayed a flushing (positive slope) or dilution (negative slope) response. We additionally examined concentration-stage relationships for the presence of hysteresis during storm events, where clockwise relationships indicate rapid flushing from proximate sources and counterclockwise responses indicate delayed transport from distal sources.
Two-way ANOVAs were used to assess the joint effect of subwatershed sites (i.e., forest harvest) and flow conditions (i.e., baseflow versus stormflow) on water quality and DBP-FPs. (55) Individual ANOVAs were constructed for major cations, δ18O–H2O, turbidity, TSS, DOM-[C], SUVA254, S275–295, PARAFAC components, TTHM-FP, and HAA5-FP. A 5% significance level (α = 0.05) was used to evaluate the main effects (i.e., site and flow) and interaction effects. Posthoc site comparisons were assessed using Tukey’s honestly significant difference tests. After finalizing the ANOVAs, diagnostic tests were performed to ensure that assumptions of residual normality and homogeneity were satisfied.
Multiple linear regression (backward elimination) models were used to identify key water quality indicators driving DBP-FPs. (55,59) In each DBP-FP model, initially considered indicators included DOM-[C], a254, SUVA254, and S275–295. Given that DOM-[C] was highly correlated with a254 (r = 0.901, p < 0.001), it was not analyzed further. To improve model fits, water quality indicators were standardized (i.e., data were scaled to establish the mean and standard deviation at zero and one, respectively). Significance values were computed using α = 0.05. Final models were validated via diagnostic tests confirming that assumptions of residual normality and multicollinearity were satisfied. Water quality indicators did not show issues of multicollinearity (VIFs < 2.0).

3. Results and Discussion

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3.1. Hydro-Meteorological Impacts on Water Sources, Flow Paths, and Stream Responses

Relative to the 1981–2019 climate normal (9.4 °C and 2193 mm yr–1 at Comox Lake; elevation: 314 m), the Comox Lake watershed was warmer (9.9 °C) and experienced less precipitation (1512 mm yr–1) in 2019. (47,60) Although dry conditions persisted throughout the year, with seasonal rainfall ranging from 154 mm (spring; normal = 241 mm) to 681 mm (autumn; normal = 965 mm), we were able to capture two storm events in autumn 2019 (Figure 1B). Total rainfall during the 16–19 November (5–9 December) event ranged between 28.8 and 82.2 mm (14.2 and 35.2 mm) across the watershed, resulting in a rise in the streamwater level at each subwatershed site, with the greatest increases observed at LH-DS (43 cm, 19 cm; November, December events), followed by LH-SS (41 cm, 10 cm), HH-DS (34 cm, 9 cm), and HH-SS (28 cm, 8 cm) (Table 1). Stage measurements also revealed that sites responded quickly to rainfall with steep rising limbs and a return to baseflow over several days (e.g., Figures 2 and 3).

Figure 2

Figure 2. Rainfall (mm), streamwater level (cm), and water quality (i.e., turbidity (NTU), DOM-[C] (mg L–1), and S275–295 (10–3 nm–1)) responses across subwatershed sites during the 16–19 November 2019 storm event (n = 13–15, varying by subwatershed site). Monthly baseflow samples (n = 4) collected during stable conditions are shown as box plots for comparison. Boxes comprise the 25th to 75th percentile, and whiskers represent the 5th and 95th percentiles. Streamwater level data were normalized to zero. Data for TSS (mg L–1) and SUVA254 (L mg-C–1 m–1) were collected but are not shown here (raw data are provided in Tables S2 and S4). Site abbreviations are as defined in Figure 1.

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Figure 3

Figure 3. Rainfall (mm), streamwater level (cm), water quality (i.e., major cations (μmol L–1) δ18O–H2O (‰), turbidity (NTU), DOM-[C] (mg L–1), and S275–295 (10–3 nm–1)), and DBP-FPs (i.e., TTHM-FP (μg L–1) and HAA5-FP (μg L–1)) responses across subwatershed sites during the 5–9 December 2019 storm event (n = 5–6, varying by subwatershed site). Monthly baseflow samples (n = 4) collected during stable conditions are shown as box plots for comparison. Boxes comprise the 25th to 75th percentile, and whiskers represent the 5th and 95th percentiles. Streamwater level data were normalized to zero and individual THM and HAA species FPs were summed to yield total FPs. Data for TSS (mg L–1) and SUVA254 (L mg-C–1 m–1) were collected but are not shown here (raw data are provided in Tables S2 and S4). Site abbreviations are as defined in Figure 1.

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3.2. Water Quality and DBP-FP Dynamics under Storm and Baseflow Conditions

Significant flow-related differences indicated that baseflow and stormflow water quality were distinct by individual subwatersheds (Table S6). Subwatersheds displayed more depleted δ18O–H2O (two-way ANOVA; F1,23 = 9.528, p < 0.01) and higher major cation concentrations (F1,23 = 9.814, p < 0.01) at stable baseflow conditions than during storm events (Figure 3 and Table S6). During high flow conditions, turbidity (F1,87 = 36.215, p < 0.001), TSS (F1,87 = 30.404, p < 0.001), and DOM-[C] (F1,86 = 114.666, p < 0.001) were universally higher when compared to baseflow (Figures 2, 3 and Table S6). Increases in DOM-[C] were also accompanied by a shift toward more aromatic, high molecular weight DOM (SUVA254: F1,86 = 51.574, p < 0.001; S275–295: F1,87 = 56.202, p < 0.001) during storms (Figures 2, 3 and Table S6).
PARAFAC analysis indicated that the DOM pool was comprised of humic-like (C1 and C2) and protein-like (C3 and C4) DOM (Figure S1; see additional information in Supplemental Text S4). The DOM compositional signature was mainly composed of C1 and C2 under both baseflow (79.8%) and stormflow (81.9%) conditions (Figure S2), with none of the four PARAFAC components changing significantly with flow (Table S6). Of the suite of DBPs assessed, only two THMs (BDCM and TCM) and two HAAs (DCAA and TCAA) were present at quantifiable concentrations; all other DBPs (TBM, DBCM, MCAA, MBAA, and DBAA) were below detection limits. TTHM-FP and HAA5-FP both exhibited a significant flow condition effect, with greater concentrations during stormflow (TTHM-FP: F1,31 = 11.926, p < 0.01; HAA5-FP: F1,31 = 10.386, p < 0.01) than during baseflow (Figure 3 and Table S6). Differences in DBPs with flow condition reflect those for DOM and DOM-[C] because DOM is a known THM and HAA precursor. This relationship is evident in the significant relationships between DOM and DBPs observed herein (Figure S3; see also Section 3.4). Given that true DBP-FP analysis involves chlorination at doses higher than those applied in drinking water treatment plants, DBP-FP concentrations are not representative of the extent of DBP formation that would be expected after typical drinking water treatment. (2) However, this method of analysis provides the greatest insight when comparing DOM oxidant demand and reactivity between sites.
Concentration-stage relationships and hysteresis patterns also suggest hydrologically driven changes in water quality and DBP-FPs across all subwatershed sites. Turbidity, DOM-[C], a254, TTHM-FP, and HAA5-FP displayed a flushing (positive concentration-stage) response coupled with clockwise (i.e., higher concentrations on the rising limb of the hydrograph) hysteresis during storm events (Figure 4). This overall response is consistent with the rapid delivery of materials from sources proximate to the stream. In contrast, S275–295 showed a negative concentration-stage response and counterclockwise hysteresis with increased values on the falling limb (Figure 4), consistent with the delayed delivery of low molecular weight DOM from distal sources, but flushing of proximate high molecular weight DOM. Increases in streamwater level, resultant water quality and DBP-FP changes, and hysteresis patterns were smaller during the more modest, December, event, when compared to the event in November (Figures 2 and 3).

Figure 4

Figure 4. Turbidity (NTU), DOM-[C] (mg L–1), S275–295 (10–3 nm–1), a254 (m–1), TTHM-FP (μg L–1), and HAA5-FP (μg L–1) versus changes in streamwater level (cm) across subwatershed sites during the 16–19 November and 5–9 December 2019 storm events (n = 13–15, n = 5–6; November, December events, varying by subwatershed site). The arrows represent the temporal direction of the storm from the rising to falling limb. Streamwater level data were normalized to zero and individual THM and HAA species FPs were summed to yield total FPs. Data for TSS (mg L–1) and SUVA254 (L mg-C–1 m–1) were collected but are not shown here (raw data are provided in Tables S2 and S4). Site abbreviations are as defined in Figure 1.

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Collectively, these results are consistent with increasing surficial flow activating new flow pathways that facilitate the transport of high molecular weight, aromatic DOM through shallow soil horizons during storm events. (28,32,61) Flow through shallower flow paths – as also evidenced by a diluting storm response for dissolved cations – results in leaching of humic DOM from recently produced, surficial, soil organic matter, and increased sediment entrainment. (62,63) Clockwise hysteresis patterns for DOM-[C] and turbidity indicate that these surficial flow paths: (1) rapidly transport near-stream DOM into the stream network upon reaching a critical soil saturation threshold; (64,65) and (2) quickly deliver sediments from channel banks to streams, likely in conjunction with in-stream sediment remobilization. (66) This consequently increases turbidity and DOM-[C] and the DOM pool shifts, becoming more aromatic with a higher molecular weight. (27,32) Hysteresis patterns further suggest that once shallower soil layers stop contributing to streamflow, deeper flow pathways become more dominant. (64) Deeper soil horizons are not major sources of sediment (66) and contain more processed DOM and less leachable DOM-[C]. (63,67) The loss of surficial flow paths therefore reduces streamwater turbidity, DOM-[C], and DOM aromaticity and molecular weight. (67) Given that storm events control the amount of DOM-[C] and DOM composition in streamwater, DBP-FPs are also affected. (1,68) An increase in DOM-[C] and more aromatic, high molecular weight DOM – including during stormflow – typically leads to greater TTHM-FP and HAA5-FP following chlorination. (27,29,69,70) Hysteresis patterns also suggest continued flushing of TSS, DOM-[C], and DBP-FPs with small changes in streamflow (e.g., due to modest storm events).
These results corroborate other studies showing strong effects of storm events on turbidity, DOM-[C], and DOM composition (1,28,34,62) and add to emerging research on storm DBP-FP responses. (27,29) Previous research has reported increases in turbidity, DOM-[C], and aromatic DOM during storm events in forested tropical, (71) subtropical, (30) temperate interior, (27,34) montane cordillera, (1) and coastal temperate (28,31,62) watersheds. Other research has reported increased DBP-FPs in stormflow across forested watersheds in temperate regions. (27,29)

3.3. Hydrology Predominates Over Cross-Catchment Differences in Harvest and Soils to Control Water Quality and DBP-FPs

Our statistical analyses indicated insignificant differences across sites for DOM-[C], SUVA254, S275–295, PARAFAC components, TTHM-FP, and HAA5-FP (p > 0.075; Table S6), irrespective of the amount of harvested area (ranging from 6.5 to 54.2% of watershed cover), mean soil depth (ranging from 1.1 to 1.8 m), mean soil clay content (ranging from 4.1 to 14.7% of the total soil composition), or other characteristics that varied among study subwatersheds (Table 1). Differences in turbidity and TSS were also insignificant across sites, except at HH-DS (mean soil depth = 1.8 m; mean clay content = 14.7%), where concentrations were significantly elevated (83 NTU, 17 NTU; November and December events) due to fine silty-clay streambanks (72) that result in enhanced erosion at this subwatershed site, relative to the three other sites (maximum concentration of 12–29 NTU in November and 3–5 NTU in December). Between-catchment differences in δ18O–H2O appear to reflect the well-known effect of elevation on the isotopic composition of precipitation, (73) with depleted δ18O–H2O at the high-elevation LH-SS, enriched δ18O–H2O at the low-elevation HH-DS, and intermediate δ18O–H2O at the two mid-elevation sites (Tables 1 and S2). Elevated cation concentrations at HH-SS align with high concentrations found within the larger watershed area downstream of this site, indicating potential lithologic variation throughout the Comox Lake watershed. (74)
Past studies have shown forest harvest to affect DOM and DOM-[C] in receiving stream systems, (15,19) particularly during high flow conditions. (24,25) The lack of a discernible harvesting effect on DOM and DOM-[C] in receiving streams in the present investigation may be attributable to subwatersheds that were largely comprised of second growth forest with low soil organic carbon storage. Typically, decreased DOM-[C] and altered DOM composition occur in managed (i.e., second growth) forests due to reductions in large woody debris (75,76) and increases in nutrients that stimulate soil biological activity and thus organic matter decomposition. (77) Second growth (i.e., regenerating) forests may therefore yield more processed (i.e., aliphatic, protein-like) DOM and lower DOM-[C] than old growth forest landscapes. In addition to the effects of past harvest, logging slash, which is usually a major source of DOM, (76) may be removed post-harvest. Slash (i.e., fine and coarse woody debris) is occasionally left to decompose in harvested areas, which increases organic matter leaching and thus elevates DOM-[C] and aromatic, humic-like DOM in stream waters. (16,35) In the Comox Lake watershed, slash was typically piled and burned within 1 or 2 years after harvest. Given that second growth watersheds generally have lower amounts of fine and coarse woody debris than mature or old forests, especially when logging slash is piled and burned post-harvest, (78,79) burning this material may have led to reduced organic inputs compared to other harvested watersheds. Slash removal, coupled with historical harvest and soils with low organic carbon storage, (80) may explain the lack of the effect of forest harvest on streamwater DOM in Comox Lake subwatersheds, and overall low DOM-[C] measured at these sites.
In addition to the lack of significant differences detected in DOM, DOM-[C], and DBP-FPs among the four subwatersheds, no significant interaction effects were detected between site and flow condition for any of the variables examined, indicating similar responses to differing flows across sites (p > 0.105, excluding PARAFAC component C2; Table S6). These results are consistent with previous work in the Midwestern U.S., which similarly found that watersheds displayed comparable storm responses relative to one another, regardless of land use. (34) In that work, the primary controls on water quality were precipitation and discharge. (34) Our findings suggest that hydrology may act as a key control on stormwater quality and DBP-FPs in the Comox Lake watershed, with variation in the soil water table and hydrologic flow paths regulating stream dynamics during storms. (35) Collecting additional samples from comparable watersheds (in landcover and watershed size) will be important to corroborate and increase confidence in these findings and generalizability across broader spatial scales.

3.4. Linkages and Key DOM Drivers of DBP-FPs

True DBP-FPs were directly linked to DOM and DOM-[C], following the role of DOM as a precursor of THMs and HAAs. (81−83) DBP-FPs increased with elevated DOM-[C] (TTHM-FP: R2 = 0.57, p < 0.001; HAA5-FP: R2 = 0.62, p < 0.001) but showed only a modest relationship with increasing SUVA254 (TTHM-FP: R2 = 0.16, p < 0.05; HAA5-FP: R2 = 0.20, p < 0.01) and S275–295 (TTHM-FP: R2 = 0.06, p > 0.1; HAA5-FP: R2 = 0.09, p < 0.1) (Figure S3). Normalizing DBP-FPs to DOM-[C] revealed a similar trend: per unit carbon, DBP-FPs showed only modest trends with both SUVA254 (TTHM-FP: R2 = 0.04, p = 0.253; HAA5-FP: R2 = 0.02, p = 0.450) and S275–295 (TTHM-FP: R2 = 0.16, p < 0.05; HAA5-FP: R2 = 0.20, p < 0.01) (Figure S4). The poor linear correlations between SUVA254 and S275–295 with DBP-FPs are consistent with previous reports, (29) suggesting that SUVA254 and S275–295 are weak indicators of regulated DBP-FPs. In our study, multiple linear regression (backward elimination) models showed a254 to be the best predictor of DBP-FPs (TTHM-FP: b = 0.439, p < 0.001; HAA5-FP: b = 0.399, p < 0.001; Table S7), with individual compositional measures (i.e., SUVA254 and S275–295) not significantly improving the model fit. Simple metrics indicative of total aromaticity (such as a254) thus remain the most informative for evaluating variation in DBP-FPs within forested subwatersheds, (29,81−83) which may be helpful to practitioners given the time and expense required for measurement of DOM-[C]. Notably, chlorinated DBP-FPs prevailed across all subwatershed sites; brominated TTHM-FP and HAA5-FP, which are more toxic than chlorinated byproducts, (5) did not form in our study basins due to low bromide concentrations (<detection limit of 0.02 mg L–1; data not shown) in the system.

4. Conclusions

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Our findings indicate that hydrologic shifts substantially increase turbidity, TSS, DOM-[C], and DBP-FPs and result in more aromatic, higher molecular weight DOM in small watersheds on the east coast of Vancouver Island, British Columbia. In contrast to event (hydrologic)-based variation, watershed-scale variation in recent forest harvest and soil characteristics caused only modest variation in the water quality parameters that we investigated. Increasing DOM-[C], and particularly a254, led to increases in DBP-FP, indicating that varying hydrology is an important consideration for understanding challenges to drinking water treatability. Hydrologic connectivity in Comox Lake subwatersheds may change in the future with climate-driven increases in the intensity, duration, and frequency of extreme high flow events, (84) coupled with the increased prevalence of drought. (85) Increased hydrologic connectivity may result in elevated turbidity, DOM-[C], aromatic DOM, and thus DBP-FP, while also causing faster shifts in each of these metrics during storms in harvested areas. In contrast, decreased hydrologic connectivity (e.g., during drought) may result in the opposite response. Continued evaluation of turbidity, DOM-[C], and DOM composition will be essential for monitoring and adapting management strategies for effective drinking water treatment, especially with changing hydroclimatic conditions in the future. Future research should explore how the responses we document may vary seasonally (86) and investigate their applicability in other regions with known differences in hydrologic seasonality, disturbance responses, and concentration–discharge relationships across diverse landscape types. An exploration of these processes across different forest management strategies and the interaction between climate change and other land uses will contribute valuable insight into the evolving challenges to drinking water treatability with global environmental change.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsestwater.3c00471.

  • Supplemental information on the study region; sample collection and processing; DOM composition calculation, PARAFAC analysis, and potential characteristics; analysis of true DBP-FPs; data treatment for analyses; statistical outputs and other supplemental data analyses, including ANOVA results, multiple linear regression outputs, and plots illustrating variation in DOM composition and DBP-FPs; all raw data used in this study (PDF)

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Author Information

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  • Corresponding Author
  • Authors
    • Suzanne E. Tank - Department of Biological Sciences, University of Alberta, Edmonton T6G 2E9, Canada
    • William C. Floyd - Department of Geography, Vancouver Island University, Nanaimo V9R 5S5, Canada;  Ministry of Forests, Nanaimo V9T 6E9, Canada
    • Monica B. Emelko - Water Science, Technology & Policy Group, Department of Civil & Environmental Engineering, University of Waterloo, Waterloo N2L 3G1, Canada;  Orcidhttps://orcid.org/0000-0002-8295-0071
    • Fariba Amiri - Water Science, Technology & Policy Group, Department of Civil & Environmental Engineering, University of Waterloo, Waterloo N2L 3G1, Canada
  • Author Contributions

    CRediT: Alyssa K. Bourgeois conceptualization, data curation, formal analysis, investigation, methodology, project administration, validation, visualization, writing-original draft, writing-review & editing; Suzanne E. Tank conceptualization, formal analysis, funding acquisition, methodology, project administration, resources, supervision, writing-review & editing; William C. Floyd formal analysis, funding acquisition, methodology, project administration, conceptualization, resources, supervision, writing-review & editing; Monica B. Emelko funding acquisition, writing-review & editing; Fariba Amiri investigation, writing-review & editing.

  • Funding

    This study was funded through grants from the following: (1) forWater NSERC Network for Forested Drinking Water Source Protection Technologies [NETGP-494312-16]; (2) the Campus Alberta Innovates Program; and (3) a Government of Canada Clean Tech Internship [C65-25].

  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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The authors thank Zoe Norcross-Nu’u for her assistance with site orientation and fieldwork, Sheetal Patel, Stewart Butler, Alison Bishop, and Alex Cebulski for their field, lab, and GIS assistance, and Mosaic Forest Management Corp. for granting land access.

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    Severe western Canadian wildfire affects water quality even at large basin scales
    Emmerton, Craig A.; Cooke, Colin A.; Hustins, Sarah; Silins, Uldis; Emelko, Monica B.; Lewis, Ted; Kruk, Mary K.; Taube, Nadine; Zhu, Dongnan; Jackson, Brian; Stone, Michael; Kerr, Jason G.; Orwin, John F.
    Water Research (2020), 183 (), 116071CODEN: WATRAG; ISSN:0043-1354. (Elsevier Ltd.)
    Wildfires can have severe and lasting impacts on the water quality of aquatic ecosystems. However, our understanding of these impacts is founded primarily from studies of small watersheds with well-connected runoff regimes. Despite the predominance of large, low-relief rivers across the fire-prone Boreal forest, it is unclear to what extent and duration wildfire-related material (e.g., ash) can be obsd. within these systems that typically buffer upstream disturbance signals. Following the devastating 2016 Fort McMurray wildfire in western Canada, we initiated a multi-faceted water quality monitoring program that suggested brief (hours to days) wildfire signatures could be detected in several large river systems, particularly following rainfall events greater than 10 mm. Continuous monitoring of flow and water quality showed distinct, pptn.-assocd. signatures of ash transport in rivers draining expansive (800-100,000 km2) and partially-burned (<1-22 percent burned) watersheds, which were not evident in nearby unburned regions. Yields of suspended sediment, nutrients (nitrogen, phosphorus) and metals (lead, others) from impacted rivers were 1.2-10 times greater than from those draining unburned regions. Post-fire suspended sediment concns. in impacted rivers were often larger than pre-fire 95% prediction intervals based on several years of water sampling. These multiple lines of evidence indicate that low-relief landscapes can mobilize wildfire-related material to rivers similarly, though less-intensively and over shorter durations, than headwater regions. We propose that uneven mixing of heavily-impacted tributaries with high-order rivers may partially explain detection of wildfire signals in these large systems that may impact downstream water users.
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    Variability of disinfection by-products at a full-scale treatment plant following rainfall events
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    The quality of drinking water sources can decrease when contaminants are transported by overland and subsurface flow and discharged into surface waters following rainfall events. Increases in org. contaminants such as road salts and org. matter may occur and potentially modify disinfection byproducts (DBPs) concn. and speciation. This study investigated the effects of various spring rainfall events on the quality of treated waters at a large water treatment plant through the implementation of intensive water quality monitoring of raw, filtered and treated waters during different rainfall events. DBPs (four trihalomethanes and six haloacetic acids) and their explanatory variables (pH, turbidity, water temp., specific UV absorbance, total and dissolved org. carbon, bromide and chlorine dose) were measured during four rainfall events. The results showed that water quality degrades during and following rainfall, leading to small increases in trihalomethanes (THM4) and haloacetic acids (HAA6) in treated waters. While THM4 and HAA6 levels remained low during the pre-rainfall period (<9 μg/L) for the four sampling campaigns, small increases in THM4 and HAA6 during and after spring rainfall events were obsd. During the rainfall and post-rainfall periods, concn. peaks corresponding to 3-fold and 2-fold increases (resp. 27.5 μg/L for THM4 and 12.6 μg/L for HAA6) compared to pre-rainfall levels were also measured. A slight decrease in harmful brominated THM and HAA proportion was also obsd. following rainfall events.
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    Different Responses of Dissolved Black Carbon and Dissolved Lignin to Seasonal Hydrological Changes and an Extreme Rain Event
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    Hydrol., esp. extreme hydrol. events, has been recognized as an important driver of the land-to-ocean export of terrigenous dissolved org. matter (tDOM). Nevertheless, how various types of tDOM that differ in source and reactivity respond to changes in hydrol. is not known. Seasonal and event exports of dissolved org. carbon (DOC), dissolved black carbon (DBC), and dissolved lignin were studied in a small subtropical river. We found that seasonal variations in DBC concn. were significantly related to hydrol., while DOC and dissolved lignin were not. In contrast, DOC, DBC, and dissolved lignin changed similarly during an extreme rain event. The variation magnitudes of DOC, DBC, and dissolved lignin concns. were in the lower end compared to other rivers, which may be related to the limited coverage of wetlands and riparian vegetation and poor development of org.-rich soil. Diln. effects were obsd. when the runoff exceeded 0.4 mm/h, and the fluxes of both DBC and dissolved lignin decreased during the runoff peak, which was caused by surface flow and potentially by removal processes during peak discharge. Our results suggest that the influence of hydrol. varies with tDOM source and reactivity and that high enough runoff (e.g., 0.7 mm/h in the Jiulong River) may not enhance the export rate of tDOM. However, our study was carried out in a small watershed with limited wetlands and riparian vegetation, and more studies are needed to verify whether this trend is consistent among global rivers.
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    In boreal regions, increased concns. of dissolved org. carbon (DOC) have been linked to extreme wet years; however, less is known about the extent to which pptn. events are altering DOC concn. and quality. We assessed the effects of rain events on a suite of six lakes in Maine, U.S.A., to better understand how events alter DOC quantity and quality. DOC concns. and DOC quality (measured as DOC-specific absorption coeffs. Specific UV Absorbance (SUVA254 (also a*254, a*320, and a*380)) were quantified 24 h before, and at three time points (24-48 h, 5-7 days, and 3 wk) after five different pptn. events. Our results revealed three types of responses across the lakes: (1) an initial spike in DOC concns. of 30-133% and in the three quality metrics of 20-86% compared to pre-storm levels, followed by return to pre-storm concns.; (2) a sustained increase in DOC concns. (by 4-23%) and an increase in the three DOC quality metrics (by 1-43%) through the second post-storm sampling, with concns. falling by the third post-storm sampling compared to pre-storm levels; and (3) no change during all sampling periods. Lake residence time was a key driver of changes in DOC concn. and DOC quality in response to storm events. Our research provides evidence that pptn. events contribute to short-term abrupt changes in DOC quantity and quality that are largely driven by key landscape and lake characteristics.
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    We present new global maps of the Koppen-Geiger climate classification at an unprecedented 1-km resolution for the present-day (1980-2016) and for projected future conditions (2071-2100) under climate change. The present-day map is derived from an ensemble of four high-resolution, topographically-corrected climatic maps. The future map is derived from an ensemble of 32 climate model projections (scenario RCP8.5), by superimposing the projected climate change anomaly on the baseline high-resolution climatic maps. For both time periods we calculate confidence levels from the ensemble spread, providing valuable indications of the reliability of the classifications. The new maps exhibit a higher classification accuracy and substantially more detail than previous maps, particularly in regions with sharp spatial or elevation gradients. We anticipate the new maps will be useful for numerous applications, including species and vegetation distribution modeling. The new maps including the associated confidence maps are freely available via www.gloh2o.org/koppen.
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    This paper describes the tech. development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resoln. (June 2016 update). SoilGrids provides global predictions for std. numeric soil properties (org. carbon, bulk d., Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven std. depths (0, 5, 15, 30, 60, 100 and 200 cm), in addn. to predictions of depth to bedrock and distribution of soil classes based on the World Ref. Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivs., climatic images and global landform and lithol. maps), which were used to fit an ensemble of machine learning methods-random forest and gradient boosting and/or multinomial logistic regression-as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10-fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall av. of 61%. Improvements in the relative accuracy considering the amt. of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resoln., range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in prepg. finer resoln. covariate layers and (3) to insertion of addnl. soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resoln.) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.
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    PARAllel FACtor anal. (PARAFAC) is increasingly used to decomp. fluorescence excitation emission matrixes (EEMs) into their underlying chem. components. In the ideal case where fluorescence conforms to Beers Law, this process can lead to the math. identification and quantification of independently varying fluorophores. However, many practical and anal. hurdles stand between EEM datasets and their chem. interpretation. This article provides a tutorial in the practical application of PARAFAC to fluorescence datasets, demonstrated using a dissolved org. matter (DOM) fluorescence dataset. A new toolbox for MATLAB is presented to support improved visualisation and sensitivity analyses of PARAFAC models in fluorescence spectroscopy.
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    Specific UV absorbance (SUVA) is defined as the UV absorbance of a water sample at a given wavelength normalized for dissolved org. carbon (DOC) concn. Our data indicate that SUVA, detd. at 254 nm, is strongly correlated with percent aromaticity as detd. by 13C NMR for 13 org. matter isolates obtained from a variety of aquatic environments. SUVA, therefore, is shown to be a useful parameter for estg. the dissolved arom. carbon content in aquatic systems. Expts. involving the reactivity of DOC with chlorine and tetramethylammonium hydroxide (TMAH), however, show a wide range of reactivity for samples with similar SUVA values. These results indicate that, while SUVA measurements are good predictors of general chem. characteristics of DOC, they do not provide information about the reactivity of DOC derived from different types of source materials. Sample pH, nitrate, and iron were found to influence SUVA measurements.
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    Fe is a source of interference in the spectroscopic anal. of dissolved org. matter (DOM); however, its effects on commonly used UV and visible (UV-vis) light adsorption and fluorescence measurements are poorly defined. We describe the effects of Fe(II) and Fe(III) on the UV-vis absorption and fluorescence of solns. contg. 2 DOM fractions and 2 surface water samples. In each case, regardless of DOM compn., UV-vis absorption increased linearly with increasing Fe(III). Correction factors were derived using Fe(III) absorption coeffs. detd. at wavelengths commonly used to characterize DOM. Fe(III) addn. increased specific UV absorbances (SUVA) and decreased the absorption ratios (E2:E3) and spectral slope ratios (SR) of DOM samples. Both Fe(II) and Fe(III) quenched DOM fluorescence at pH 6.7. The degree and region of fluorescence quenching varied with the Fe:DOC concn. ratio, DOM compn., and pH. Regions of the fluorescence spectra assocd. with greater DOM conjugation were more susceptible to Fe quenching, and DOM fluorescence indexes were sensitive to the presence of both forms of Fe. Analyses of the excitation-emission matrixes using a 7- and 13-component parallel factor anal. (PARAFAC) model showed low PARAFAC sensitivity to Fe addn.
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  1. Jaweria Shamshad, Rashid Ur Rehman. Innovative approaches to sustainable wastewater treatment: a comprehensive exploration of conventional and emerging technologies. Environmental Science: Advances 2025, 4 (2) , 189-222. https://doi.org/10.1039/D4VA00136B
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  • Abstract

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    Figure 1

    Figure 1. (A) The Comox Lake watershed. Streams and harvested areas are shown on the map in addition to other relevant features. Sampling was performed under stormflow (n = 13–15, n = 5–6; November and December events) and baseflow (n = 4) conditions at four subwatershed sites (in red): Moat Creek (low harvest–shallow soil; LH-SS), Boston Creek (low harvest–deep soil; LH-DS), Toma Creek (high harvest–shallow soil; HH-SS), and Perserverance Creek (high harvest–deep soil; HH-DS). Rainfall data were collected from the nearest hydrometric station (in pink). (B) Total daily rainfall (mm) from 1 April 2019 to 31 March 2020, as measured at the “Cruikshank River Near the Mouth” Water Survey of Canada hydrometric station. Light blue bars correspond to sample collection dates; B indicates baseflow sample collection dates, while S represents storm events captured during the study period.

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    Figure 2

    Figure 2. Rainfall (mm), streamwater level (cm), and water quality (i.e., turbidity (NTU), DOM-[C] (mg L–1), and S275–295 (10–3 nm–1)) responses across subwatershed sites during the 16–19 November 2019 storm event (n = 13–15, varying by subwatershed site). Monthly baseflow samples (n = 4) collected during stable conditions are shown as box plots for comparison. Boxes comprise the 25th to 75th percentile, and whiskers represent the 5th and 95th percentiles. Streamwater level data were normalized to zero. Data for TSS (mg L–1) and SUVA254 (L mg-C–1 m–1) were collected but are not shown here (raw data are provided in Tables S2 and S4). Site abbreviations are as defined in Figure 1.

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    Figure 3

    Figure 3. Rainfall (mm), streamwater level (cm), water quality (i.e., major cations (μmol L–1) δ18O–H2O (‰), turbidity (NTU), DOM-[C] (mg L–1), and S275–295 (10–3 nm–1)), and DBP-FPs (i.e., TTHM-FP (μg L–1) and HAA5-FP (μg L–1)) responses across subwatershed sites during the 5–9 December 2019 storm event (n = 5–6, varying by subwatershed site). Monthly baseflow samples (n = 4) collected during stable conditions are shown as box plots for comparison. Boxes comprise the 25th to 75th percentile, and whiskers represent the 5th and 95th percentiles. Streamwater level data were normalized to zero and individual THM and HAA species FPs were summed to yield total FPs. Data for TSS (mg L–1) and SUVA254 (L mg-C–1 m–1) were collected but are not shown here (raw data are provided in Tables S2 and S4). Site abbreviations are as defined in Figure 1.

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    Figure 4

    Figure 4. Turbidity (NTU), DOM-[C] (mg L–1), S275–295 (10–3 nm–1), a254 (m–1), TTHM-FP (μg L–1), and HAA5-FP (μg L–1) versus changes in streamwater level (cm) across subwatershed sites during the 16–19 November and 5–9 December 2019 storm events (n = 13–15, n = 5–6; November, December events, varying by subwatershed site). The arrows represent the temporal direction of the storm from the rising to falling limb. Streamwater level data were normalized to zero and individual THM and HAA species FPs were summed to yield total FPs. Data for TSS (mg L–1) and SUVA254 (L mg-C–1 m–1) were collected but are not shown here (raw data are provided in Tables S2 and S4). Site abbreviations are as defined in Figure 1.

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      A review, with 116 refs., on biol. processes in drinking water purifn., including biodegrdn. of carbonaceous materials; the removal of N, NH4+, NO3-, Fe, and Mn; and denitrification, microbial oxidn., limitations of biol. processes, and release of microorganisms.
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      Brown, J.; Upadhyaya, G.; Nyfennegger, J.; Pope, G.; Bassett, S.; Evans, A.; Carter, J.; Nystrom, V.; Black, S.; Alito, C.; Lauderdale, C. Biofiltration guidance manual for drinking water facilities (Project no. 4719); The Water Research Foundation: Denver, CO, 2020.
      There is no corresponding record for this reference.
    13. 13
      Emelko, M. B.; Huck, P. M.; Coffey, B. M.; Smith, E. F. Effects of media, backwash, and temperature on full-scale biological filtration. J. - Am. Water Works Assoc. 2006, 98 (12), 61– 73,  DOI: 10.1002/j.1551-8833.2006.tb07824.x
      13
      Effects of media, backwash, and temperature on full-scale biological filtration
      Emelko, Monica B.; Huck, Peter M.; Coffey, Bradley M.; Smith, E. Franklyn
      Journal - American Water Works Association (2006), 98 (12), 61-73CODEN: JAWWA5; ISSN:0003-150X. (American Water Works Association)
      Full-scale biofiltration expts. demonstrated that good removal of biodegradable org. matter (BOM) following ozonation could be achieved without compromising particle removal. BOM removal by granular activated carbon (GAC) filter adsorbers and dual-media filters was measured using total org. carbon (TOC) and certain BOM components (carboxylic acids). The authors investigated how filter backwashing with water, water and air scour, and water and air scour at collapse-pulsing conditions affect filter biomass, BOM removal, and particle removal. At 21-24°C, the media type did not affect BOM removal. At 1-3°C, GAC provided substantially better removal of oxalate and TOC than did anthracite. For both media types, cold water oxalate removals were significantly impaired, compared with those achieved in warm waters. BOM removal was more resilient than particle removal to changes in backwash protocol. Phospholipid biomass concn. was not directly related to BOM removal by filters.
    14. 14
      Kirisits, M. J.; Emelko, M. B.; Pinto, A. J. Applying biotechnology for drinking water biofiltration: Advancing science and practice. Curr. Opin. Biotechnol. 2019, 57, 197– 204,  DOI: 10.1016/j.copbio.2019.05.009
      14
      Applying biotechnology for drinking water biofiltration: advancing science and practice
      Kirisits, Mary Jo; Emelko, Monica B.; Pinto, Ameet J.
      Current Opinion in Biotechnology (2019), 57 (), 197-204CODEN: CUOBE3; ISSN:0958-1669. (Elsevier B.V.)
      A review. Drinking water biofiltration processes have evolved over time, moving from unintentional to deliberate, with careful filter media selection, nutrient and trace metal supplementation, oxidant amendment, and bioaugmentation of key microorganisms, to achieve improvements in water quality. Biofiltration is on the precipice of a revolution that aims to customize the microbial community for targeted functional outcomes. These outcomes might be to enhance or introduce target functional activity for contaminant removal, to avoid hydraulic challenges, or to shape beneficially the downstream microbial community. Moving from the foundational mol. techniques that are commonly applied to biofiltration processes, such as amplicon sequencing and quant., real-time polymerase chain reaction, the biofiltration revolution will be facilitated by modern biotechnol. tools, including metagenomics, metatranscriptomics, and metaproteomics. The application of such tools will provide a rich knowledge base of microbial community structure/function data under various water quality and operational conditions, where this information will be utilized to select biofilter conditions that promote the enrichment and maintenance of microorganisms with the desired functions.
    15. 15
      Blackburn, E. A.; Dickson-Anderson, S. E.; Anderson, W. B.; Emelko, M. B. Biological filtration is resilient to wildfire ash-associated organic carbon threats to drinking water treatment. ACS ES&T Water 2023, 3 (3), 639– 649,  DOI: 10.1021/acsestwater.2c00209
      There is no corresponding record for this reference.
    16. 16
      Berkowitz, J. F.; Summers, E. A.; Noble, C. V.; White, J. R.; DeLaune, R. D. Investigation of biogeochemical functional proxies in headwater streams across a range of channel and catchment alterations. Environ. Manage. 2014, 53, 534– 548,  DOI: 10.1007/s00267-013-0199-1
      There is no corresponding record for this reference.
    17. 17
      Erdozain, M.; Kidd, K.; Kreutzweiser, D.; Sibley, P. Linking stream ecosystem integrity to catchment and reach conditions in an intensively managed forest landscape. Ecosphere 2018, 9 (5), e02278  DOI: 10.1002/ecs2.2278
      There is no corresponding record for this reference.
    18. 18
      Jordan, P. The use of sediment budget concepts to assess the impact on watersheds of forestry operations in the southern interior of British Columbia. Geomorphology 2006, 79 (1–2), 27– 44,  DOI: 10.1016/j.geomorph.2005.09.019
      There is no corresponding record for this reference.
    19. 19
      Kreutzweiser, D. P.; Hazlett, P. W.; Gunn, J. M. Logging impacts on the biogeochemistry of boreal forest soils and nutrient export to aquatic systems: A review. Environ. Rev. 2008, 16, 157– 179,  DOI: 10.1139/A08-006
      19
      Logging impacts on the biogeochemistry of boreal forest soils and nutrient export to aquatic systems: A review
      Kreutzweiser, David P.; Hazlett, Paul W.; Gunn, John M.
      Environmental Reviews (Ottawa, ON, Canada) (2008), 16 (), 157-179CODEN: ENRVEH; ISSN:1181-8700. (National Research Council of Canada)
      A review. Logging disturbances in boreal forest watersheds can alter biogeochem. processes in soils by changing forest compn., plant uptake rates, soil conditions, moisture and temp. regimes, soil microbial activity, and water fluxes. In general, these changes have often led to short-term increases in soil nutrient availability followed by increased mobility and losses by leaching to receiving waters. Among the studies we reviewed, dissolved org. carbon (DOC) exports usually increased after logging, and nitrogen (N) mineralization and nitrification often increased with resulting increased N availability and exports to receiving waters. Similar processes and responses occurred for phosphorus (P), but to a lesser extent than for N. In most cases, base cations were released and exported to receiving waters after logging. Several studies demonstrated that stem-only or partial-harvest logging reduced the impacts on nutrient release and exports in comparison to whole-tree clear-cutting. Despite these logging-induced increases in soil nutrient availability and movement to receiving waters, most studies reported little or no change in soil chem. properties. However, responses to logging were highly variable and often site specific. The likelihood, extent and magnitude of logging impacts on soil nutrient cycling and exports in boreal forest watersheds will be dependent on soil types, stand and site conditions, hydrol. connectivity, post-logging weather patterns, and type and timing of harvest activities. Addnl., logging impacts can interact with, and be confounded by, atm. pollutant deposition and climate change. Further watershed-level empirical studies and modeling efforts are required to elucidate these interactions, to improve predictive capabilities, and to advance forest management guidelines for sustaining forest soil productivity and limiting nutrient exports.
    20. 20
      Emelko, M. B.; Sham, C. H. Wildfire Impacts on Water Supplies and the Potential for Mitigation: Workshop Report; Canadian Water Network and Water Research Foundation, Waterloo, ON, Canada, 2014.
      There is no corresponding record for this reference.
    21. 21
      Emmerton, C. A.; Cooke, C. A.; Hustins, S.; Silins, U.; Emelko, M. B.; Lewis, T.; Kruk, M. K.; Taube, N.; Zhu, D.; Jackson, B.; Stone, M. K.; Kerr, J.; Orwin, J. F. Severe western Canadian wildfire affects water quality even at large basin scales. Water Res. 2020, 183, 116071,  DOI: 10.1016/j.watres.2020.116071
      21
      Severe western Canadian wildfire affects water quality even at large basin scales
      Emmerton, Craig A.; Cooke, Colin A.; Hustins, Sarah; Silins, Uldis; Emelko, Monica B.; Lewis, Ted; Kruk, Mary K.; Taube, Nadine; Zhu, Dongnan; Jackson, Brian; Stone, Michael; Kerr, Jason G.; Orwin, John F.
      Water Research (2020), 183 (), 116071CODEN: WATRAG; ISSN:0043-1354. (Elsevier Ltd.)
      Wildfires can have severe and lasting impacts on the water quality of aquatic ecosystems. However, our understanding of these impacts is founded primarily from studies of small watersheds with well-connected runoff regimes. Despite the predominance of large, low-relief rivers across the fire-prone Boreal forest, it is unclear to what extent and duration wildfire-related material (e.g., ash) can be obsd. within these systems that typically buffer upstream disturbance signals. Following the devastating 2016 Fort McMurray wildfire in western Canada, we initiated a multi-faceted water quality monitoring program that suggested brief (hours to days) wildfire signatures could be detected in several large river systems, particularly following rainfall events greater than 10 mm. Continuous monitoring of flow and water quality showed distinct, pptn.-assocd. signatures of ash transport in rivers draining expansive (800-100,000 km2) and partially-burned (<1-22 percent burned) watersheds, which were not evident in nearby unburned regions. Yields of suspended sediment, nutrients (nitrogen, phosphorus) and metals (lead, others) from impacted rivers were 1.2-10 times greater than from those draining unburned regions. Post-fire suspended sediment concns. in impacted rivers were often larger than pre-fire 95% prediction intervals based on several years of water sampling. These multiple lines of evidence indicate that low-relief landscapes can mobilize wildfire-related material to rivers similarly, though less-intensively and over shorter durations, than headwater regions. We propose that uneven mixing of heavily-impacted tributaries with high-order rivers may partially explain detection of wildfire signals in these large systems that may impact downstream water users.
    22. 22
      Emelko, M. B.; Stone, M.; Silins, U.; Allin, D.; Collins, A. L.; Williams, C. H.; Martens, A. M.; Bladon, K. D. Sediment-phosphorus dynamics can shift aquatic ecology and cause downstream legacy effects after wildfire in large river systems. Global Change Biol. 2016, 22 (3), 1168– 1184,  DOI: 10.1111/gcb.13073
      There is no corresponding record for this reference.
    23. 23
      Schelker, J.; Öhman, K.; Löfgren, S.; Laudon, H. Scaling of increased dissolved organic carbon inputs by forest clear-cutting – What arrives downstream?. J. Hydrol. 2014, 508, 299– 306,  DOI: 10.1016/j.jhydrol.2013.09.056
      There is no corresponding record for this reference.
    24. 24
      Erdogan, B. U.; Gökbulak, F.; Serengil, Y.; Yurtseven, İ.; Özçelik, M. S. Changes in selected physical water quality characteristics after thinning in a forested watershed. Catena 2018, 166, 220– 228,  DOI: 10.1016/j.catena.2018.04.010
      There is no corresponding record for this reference.
    25. 25
      Schelker, J.; Eklöf, K.; Bishop, K.; Laudon, H. Effects of forestry operations on dissolved organic carbon concentrations and export in boreal first-order streams. J. Geophys. Res. 2012, 117.  DOI: 10.1029/2011JG001827
      There is no corresponding record for this reference.
    26. 26
      Coynel, A.; Seyler, P.; Etcheber, H.; Meybeck, M.; Orange, D. Spatial and seasonal dynamics of total suspended sediment and organic carbon species in the Congo River. Global Biogeochem. Cycles 2005, 19, 4.  DOI: 10.1029/2004GB002335
      There is no corresponding record for this reference.
    27. 27
      Delpla, I.; Rodriguez, M. J. Variability of disinfection by-products at a full-scale treatment plant following rainfall events. Chemosphere 2017, 166, 453– 462,  DOI: 10.1016/j.chemosphere.2016.09.096
      27
      Variability of disinfection by-products at a full-scale treatment plant following rainfall events
      Delpla, Ianis; Rodriguez, Manuel J.
      Chemosphere (2017), 166 (), 453-462CODEN: CMSHAF; ISSN:0045-6535. (Elsevier Ltd.)
      The quality of drinking water sources can decrease when contaminants are transported by overland and subsurface flow and discharged into surface waters following rainfall events. Increases in org. contaminants such as road salts and org. matter may occur and potentially modify disinfection byproducts (DBPs) concn. and speciation. This study investigated the effects of various spring rainfall events on the quality of treated waters at a large water treatment plant through the implementation of intensive water quality monitoring of raw, filtered and treated waters during different rainfall events. DBPs (four trihalomethanes and six haloacetic acids) and their explanatory variables (pH, turbidity, water temp., specific UV absorbance, total and dissolved org. carbon, bromide and chlorine dose) were measured during four rainfall events. The results showed that water quality degrades during and following rainfall, leading to small increases in trihalomethanes (THM4) and haloacetic acids (HAA6) in treated waters. While THM4 and HAA6 levels remained low during the pre-rainfall period (<9 μg/L) for the four sampling campaigns, small increases in THM4 and HAA6 during and after spring rainfall events were obsd. During the rainfall and post-rainfall periods, concn. peaks corresponding to 3-fold and 2-fold increases (resp. 27.5 μg/L for THM4 and 12.6 μg/L for HAA6) compared to pre-rainfall levels were also measured. A slight decrease in harmful brominated THM and HAA proportion was also obsd. following rainfall events.
    28. 28
      Fellman, J. B.; Hood, E.; Behnke, M. I.; Welker, J. M.; Spencer, R. G. M. Stormflows drive stream carbon concentration, speciation and dissolved organic matter composition in coastal temperate rainforest watersheds. J. Geophys. Res.: Biogeosci. 2020, 125, e2020JG005804  DOI: 10.1029/2020JG005804
      There is no corresponding record for this reference.
    29. 29
      Bahramian, S.; Emelko, M. B.; Silins, U.; Stone, M.; Shams, S.; Williams, C. H. S. Preliminary assessment of contemporary forest harvesting impacts on NOM and disinfection by-product formation potential. In AWWA Water Quality Technology Conference (WQTC): Toronto, ON, Canada, 2018.
      There is no corresponding record for this reference.
    30. 30
      Bao, H.; Niggemann, J.; Huang, D.; Dittmar, T.; Kao, S. Different responses of dissolved black carbon and dissolved lignin to seasonal hydrological changes and an extreme rain event. J. Geophys. Res.: Biogeosci 2019, 124, 479– 493,  DOI: 10.1029/2018JG004822
      30
      Different Responses of Dissolved Black Carbon and Dissolved Lignin to Seasonal Hydrological Changes and an Extreme Rain Event
      Bao, Hongyan; Niggemann, Jutta; Huang, Dekun; Dittmar, Thorsten; Kao, Shuh-Ji
      Journal of Geophysical Research: Biogeosciences (2019), 124 (3), 479-493CODEN: JGRBBS; ISSN:2169-8953. (Wiley-Blackwell)
      Hydrol., esp. extreme hydrol. events, has been recognized as an important driver of the land-to-ocean export of terrigenous dissolved org. matter (tDOM). Nevertheless, how various types of tDOM that differ in source and reactivity respond to changes in hydrol. is not known. Seasonal and event exports of dissolved org. carbon (DOC), dissolved black carbon (DBC), and dissolved lignin were studied in a small subtropical river. We found that seasonal variations in DBC concn. were significantly related to hydrol., while DOC and dissolved lignin were not. In contrast, DOC, DBC, and dissolved lignin changed similarly during an extreme rain event. The variation magnitudes of DOC, DBC, and dissolved lignin concns. were in the lower end compared to other rivers, which may be related to the limited coverage of wetlands and riparian vegetation and poor development of org.-rich soil. Diln. effects were obsd. when the runoff exceeded 0.4 mm/h, and the fluxes of both DBC and dissolved lignin decreased during the runoff peak, which was caused by surface flow and potentially by removal processes during peak discharge. Our results suggest that the influence of hydrol. varies with tDOM source and reactivity and that high enough runoff (e.g., 0.7 mm/h in the Jiulong River) may not enhance the export rate of tDOM. However, our study was carried out in a small watershed with limited wetlands and riparian vegetation, and more studies are needed to verify whether this trend is consistent among global rivers.
    31. 31
      Mistick, E.; Johnson, M. S. High-frequency analysis of dissolved organic carbon storm responses in headwater streams of contrasting forest harvest history. J. Hydrol. 2020, 590, 125371,  DOI: 10.1016/j.jhydrol.2020.125371
      There is no corresponding record for this reference.
    32. 32
      Coch, C.; Juhls, B.; Lamoureux, S. F.; Lafrenière, M. J.; Fritz, M.; Heim, B.; Lantuit, H. Comparisons of dissolved organic matter and its optical characteristics in small low and high Arctic catchments. Biogeosciences 2019, 16 (23), 4535– 4553,  DOI: 10.5194/bg-16-4535-2019
      There is no corresponding record for this reference.
    33. 33
      Warner, K. A.; Saros, J. E. Variable responses of dissolved organic carbon to precipitation events in boreal drinking water lakes. Water Res. 2019, 156, 315– 326,  DOI: 10.1016/j.watres.2019.03.036
      33
      Variable responses of dissolved organic carbon to precipitation events in boreal drinking water lakes
      Warner, Kate A.; Saros, Jasmine E.
      Water Research (2019), 156 (), 315-326CODEN: WATRAG; ISSN:0043-1354. (Elsevier Ltd.)
      In boreal regions, increased concns. of dissolved org. carbon (DOC) have been linked to extreme wet years; however, less is known about the extent to which pptn. events are altering DOC concn. and quality. We assessed the effects of rain events on a suite of six lakes in Maine, U.S.A., to better understand how events alter DOC quantity and quality. DOC concns. and DOC quality (measured as DOC-specific absorption coeffs. Specific UV Absorbance (SUVA254 (also a*254, a*320, and a*380)) were quantified 24 h before, and at three time points (24-48 h, 5-7 days, and 3 wk) after five different pptn. events. Our results revealed three types of responses across the lakes: (1) an initial spike in DOC concns. of 30-133% and in the three quality metrics of 20-86% compared to pre-storm levels, followed by return to pre-storm concns.; (2) a sustained increase in DOC concns. (by 4-23%) and an increase in the three DOC quality metrics (by 1-43%) through the second post-storm sampling, with concns. falling by the third post-storm sampling compared to pre-storm levels; and (3) no change during all sampling periods. Lake residence time was a key driver of changes in DOC concn. and DOC quality in response to storm events. Our research provides evidence that pptn. events contribute to short-term abrupt changes in DOC quantity and quality that are largely driven by key landscape and lake characteristics.
    34. 34
      Vidon, P.; Wagner, L. E.; Soyeux, E. Changes in the character of DOC in streams during storms in two Midwestern watersheds with contrasting land uses. Biogeochemistry 2008, 88 (3), 257– 270,  DOI: 10.1007/s10533-008-9207-6
      There is no corresponding record for this reference.
    35. 35
      Dai, K. H.; Johnson, C. E.; Driscoll, C. T. Organic matter chemistry and dynamics in clear-cut and unmanaged hardwood forest ecosystems. Biogeochemistry 2001, 54 (1), 51– 83,  DOI: 10.1023/A:1010697518227
      There is no corresponding record for this reference.
    36. 36
      Canadian Council of Forest Ministers. Satellite forest information for Canada, 2015. https://opendata.nfis.org/mapserver/nfis-change_eng.html.
      There is no corresponding record for this reference.
    37. 37
      Hansen, M. C.; Potapov, P.; Moore, R.; Hancher, M.; Turubanova, S.; Tyukavina, A.; Thau, D.; Stehman, S.; Goetz, S.; Loveland, T.; Kommareddy, A.; Egorov, A.; Chini, L.; Justice, C. O.; Townshend, J. High-resolution global maps of 21st-century forest cover change. Science (New York, NY) 2013, 342, 850– 853,  DOI: 10.1126/science.1244693
      There is no corresponding record for this reference.
    38. 38
      Schnorbus, M. A. Climate change impacts on hydrology for the Comox Lake watershed: Final report , 2018.
      There is no corresponding record for this reference.
    39. 39
      Government of British Columbia. Community watershed guidebook, 1996. https://www.for.gov.bc.ca/ftp/hfp/external/!publish/FPC%20archive/old%20web%20site%20contents/fpc/fpcguide/WATRSHED/Watertoc.htm.
      There is no corresponding record for this reference.
    40. 40
      Comox Valley Regional District. Protecting our water: Water quality and management, 2019. https://www.comoxvalleyrd.ca/sites/default/files/docs/Projects-Initiatives/2wtp_backgrounder1.pdf.
      There is no corresponding record for this reference.
    41. 41
      MacKinnon, A.; Meidinger, D.; Klinka, K. Use of the biogeoclimatic ecosystem classification system in British Columbia. Forestry Chronicle 1992, 68 (1), 100– 120,  DOI: 10.5558/tfc68100-1
      There is no corresponding record for this reference.
    42. 42
      Beck, H. E.; Zimmermann, N. E.; McVicar, T. R.; Vergopolan, N.; Berg, A.; Wood, E. F. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci. Data 2018, 5 (1), 180214,  DOI: 10.1038/sdata.2018.214
      42
      Present and future Koppen-Geiger climate classification maps at 1-km resolution
      Beck Hylke E; Vergopolan Noemi; Berg Alexis; Wood Eric F; Zimmermann Niklaus E; Zimmermann Niklaus E; McVicar Tim R; McVicar Tim R
      Scientific data (2018), 5 (), 180214 ISSN:.
      We present new global maps of the Koppen-Geiger climate classification at an unprecedented 1-km resolution for the present-day (1980-2016) and for projected future conditions (2071-2100) under climate change. The present-day map is derived from an ensemble of four high-resolution, topographically-corrected climatic maps. The future map is derived from an ensemble of 32 climate model projections (scenario RCP8.5), by superimposing the projected climate change anomaly on the baseline high-resolution climatic maps. For both time periods we calculate confidence levels from the ensemble spread, providing valuable indications of the reliability of the classifications. The new maps exhibit a higher classification accuracy and substantially more detail than previous maps, particularly in regions with sharp spatial or elevation gradients. We anticipate the new maps will be useful for numerous applications, including species and vegetation distribution modeling. The new maps including the associated confidence maps are freely available via www.gloh2o.org/koppen.
    43. 43
      Hengl, T.; Mendes de Jesus, J.; Heuvelink, G. B. M.; Ruiperez Gonzalez, M.; Kilibarda, M.; Blagotić, A.; Shangguan, W.; Wright, M. N.; Geng, X.; Bauer-Marschallinger, B.; Guevara, M. A.; Vargas, R.; MacMillan, R. A.; Batjes, N. H.; Leenaars, J. G. B.; Ribeiro, E.; Wheeler, I.; Mantel, S.; Kempen, B.; Bond-Lamberty, B. SoilGrids250m: Global gridded soil information based on machine learning. PLoS One 2017, 12 (2), e0169748  DOI: 10.1371/journal.pone.0169748
      43
      SoilGrids250m: global gridded soil information based on machine learning
      Hengl, Tomislav; de Jesus, Jorge Mendes; Heuvelink, Gerard B. M.; Gonzalez, Maria Ruiperez; Kilibarda, Milan; Blagotic, Aleksandar; Shangguan, Wei; Wright, Marvin N.; Geng, Xiaoyuan; Bauer-Marschallinger, Bernhard; Guevara, Mario Antonio; Vargas, Rodrigo; MacMillan, Robert A.; Batjes, Niels H.; Leenaars, Johan G. B.; Ribeiro, Eloi; Wheeler, Ichsani; Mantel, Stephan; Kempen, Bas
      PLoS One (2017), 12 (2), e0169748/1-e0169748/40CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)
      This paper describes the tech. development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resoln. (June 2016 update). SoilGrids provides global predictions for std. numeric soil properties (org. carbon, bulk d., Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven std. depths (0, 5, 15, 30, 60, 100 and 200 cm), in addn. to predictions of depth to bedrock and distribution of soil classes based on the World Ref. Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivs., climatic images and global landform and lithol. maps), which were used to fit an ensemble of machine learning methods-random forest and gradient boosting and/or multinomial logistic regression-as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10-fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall av. of 61%. Improvements in the relative accuracy considering the amt. of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resoln., range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in prepg. finer resoln. covariate layers and (3) to insertion of addnl. soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resoln.) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.
    44. 44
      Government of Canada. Soils of British Columbia, 2013. http://sis.agr.gc.ca/cansis/soils/bc/soils.html.
      There is no corresponding record for this reference.
    45. 45
      British Columbia Ministry of Health. Design Guidelines for Drinking Water Systems in British Columbia. Version 1.0, 2023. https://www2.gov.bc.ca/assets/gov/environment/air-land-water/water/waterquality/how-drinking-water-is-protected-in-bc/dwog_part_b_-_17_design_guidelines_for_drinking_water.pdf.
      There is no corresponding record for this reference.
    46. 46
      National Academies of Sciences, Engineering, and Medicine. Review of the New York City department of environmental protection operations support tool for water supply, 2019. https://www.nationalacademies.org/our-work/review-of-the-new-york-city-department-of-environmental-protection-operations-support-tool-for-water-supply
      There is no corresponding record for this reference.
    47. 47
      Wang, T.; Hamann, A.; Spittlehouse, D.; Carroll, C. Locally downscaled and spatially customizable climate data for historical and future periods for North America. PLoS One . 2016, 11, e0156720.  DOI: 10.1371/journal.pone.0156720
      There is no corresponding record for this reference.
    48. 48
      City of North Vancouver Stream and Drainage System Protection Bylaw, 2003, No. 7541; The Corporation of The City of North Vancouver, 2020.
      There is no corresponding record for this reference.
    49. 49
      Murphy, K. R.; Stedmon, C. A.; Graeber, D.; Bro, R. Fluorescence spectroscopy and multi-way techniques. PARAFAC. Anal. Methods 2013, 5 (23), 6557– 6566,  DOI: 10.1039/c3ay41160e
      49
      Fluorescence spectroscopy and multi-way techniques. PARAFAC
      Murphy, Kathleen R.; Stedmon, Colin A.; Graeber, Daniel; Bro, Rasmus
      Analytical Methods (2013), 5 (23), 6557-6566CODEN: AMNEGX; ISSN:1759-9679. (Royal Society of Chemistry)
      PARAllel FACtor anal. (PARAFAC) is increasingly used to decomp. fluorescence excitation emission matrixes (EEMs) into their underlying chem. components. In the ideal case where fluorescence conforms to Beers Law, this process can lead to the math. identification and quantification of independently varying fluorophores. However, many practical and anal. hurdles stand between EEM datasets and their chem. interpretation. This article provides a tutorial in the practical application of PARAFAC to fluorescence datasets, demonstrated using a dissolved org. matter (DOM) fluorescence dataset. A new toolbox for MATLAB is presented to support improved visualisation and sensitivity analyses of PARAFAC models in fluorescence spectroscopy.
    50. 50
      Helms, J. R.; Stubbins, A.; Ritchie, J. D.; Minor, E. C.; Kieber, D. J.; Mopper, K. Absorption spectral slopes and slope ratios as indicators of molecular weight, source, and photobleaching of chromophoric dissolved organic matter. Limnol. Oceanogr. 2008, 53 (3), 955– 969,  DOI: 10.4319/lo.2008.53.3.0955
      There is no corresponding record for this reference.
    51. 51
      Weishaar, J. L.; Aiken, G. R.; Bergamaschi, B. A.; Fram, M. S.; Fujii, R.; Mopper, K. Evaluation of specific ultraviolet absorbance as an indicator of the chemical composition and reactivity of dissolved organic carbon. Environ. Sci. Technol. 2003, 37 (20), 4702– 4708,  DOI: 10.1021/es030360x
      51
      Evaluation of Specific Ultraviolet Absorbance as an Indicator of the Chemical Composition and Reactivity of Dissolved Organic Carbon
      Weishaar, James L.; Aiken, George R.; Bergamaschi, Brian A.; Fram, Miranda S.; Fujii, Roger; Mopper, Kenneth
      Environmental Science and Technology (2003), 37 (20), 4702-4708CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)
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  • Supporting Information

    Supporting Information

    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsestwater.3c00471.

    • Supplemental information on the study region; sample collection and processing; DOM composition calculation, PARAFAC analysis, and potential characteristics; analysis of true DBP-FPs; data treatment for analyses; statistical outputs and other supplemental data analyses, including ANOVA results, multiple linear regression outputs, and plots illustrating variation in DOM composition and DBP-FPs; all raw data used in this study (PDF)


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