The Shakujii River Basin has an average annual rainfall of 1368 mm over 43 years. The average maximum daily rainfall is 121 mm and the average maximum hourly rainfall is 40.4 mm (Japan Meteorological Agency). The source of the water in the Shakujii River (Fig. 1b) is Kogane City, Tokyo. The watershed area is 61.6 km², the river length is 25.2 km, and the estuary length is approximately 1.4 km (Fig. 2b). The elevation difference of the watershed is 85 m, and the average topographic gradient is approximately 1/340. The river features concrete-lined channels in the urban and residential downstream areas, with a width of approximately 20 m shore protection height of approximately 7 m, and 154 combined sewer outfall chambers draining domestic and storm water runoff.

The Sumida River estuary is located on the west side of Tokyo Bay and flows through the deltaic lowland of central Tokyo. It receives fresh water from the Arakawa River, Shingashi River, Shakujii River and Kanda River, which all empty into Tokyo Bay. The location of the upstream and downstream edges of the river, with a length of 20.4 km, is near the Iwabuchi sluice gate and around the lower area of Tsukiji Market, respectively (Fig. 1b). The drainage basin covers approximately 690 km², receiving water from various tributaries including the Shingashi River, Kanda River, and Shakujii River. The Sumida River is characterized by a general river slope (Fig. 2a) that promotes stagnant areas and a large effect of sea water that goes landward, and 60% of the river water is from treated sewage water (Taniguchi 1999; Japan River Restoration Network (JRRN) 2012). The confluence of the Shakujii River and the Sumida River is located 16.5 km from Tokyo Bay.

This study was conducted in the Shakujii River upstream (Sh-U) and midstream (Sh-M) stations and in the Sumida River upstream (Su-U) and downstream (Su-D) stations (Fig. 2). The riverbed elevations of the stations were as follows: Sh-U is -2.68 A.P. m, Sh-M is -3.34 A.P. m, Su-U is -4.88 A.P. m, and Su-D is -3.58 A.P. m. The upstream Sumida River station has a deeper riverbed elevation than the downstream station. Additionally, the intertidal zone in the Shakujii River estuary faces a steep slope like a wall near Sh-U where high tide is not transited, and the length of the waterbody does not change from low tide to high tide.

Figure 1. 

(a) Location of the Shakujii and Sumida Rivers relative to Tokyo Bay (b) Location of the Nerima weather station and Iwabuchi sluicegate weather station (c) Water quality monitoring stations: Shakujii upstream (Sh-U), Shakujii midstream (Sh-M), Sumida upstream (Su-U) and Sumida downstream (Su-D).

Figure 2. 

Station location and longitudinal topography in Arakawa Peil (A.P., m) elevation of the (a) Sumida River and (b) Shakujii River.

Water quality parameters were monitored at three observation stations: Sh-M, Su-U and Su-D (Fig. 2c). Data were measured at 10 minutes interval using a water level sensor (HOBO, U-20 water level logger), salinity sensor and DO sensor (JFE Advantech, Infinity-ACTW, ACLW, AROW). The sensors were attached to the revetment wall 1 m from the riverbed. The data used for the Sh-U station were obtained from the Kita Government Office. The data from Aug. in the summer of 2017 to Oct. in autumn of 2017 were used for the analysis. The rainfall intensity (mm/hr) used in this study were the average of the data from the Iwabuchi (Ministry of Land, Infrastructure, Transport and Tourism, MLIT) and Nerima (Japan Meteorological Agency) weather stations.

The water surface in Sh-U, located upstream of the tidal area, is monitored for several reasons by the Kita City Office, Tokyo using a fixed video camera. A fixed camera allows daily monitoring of the scum occurrence in a location, evaluation of alternative technologies or management practices in terms of their effectiveness in reducing odor impacts, documentation of specific events or episodes that may provide significant information regarding scum and odor occurrence, identification of specific odor sources within a community or a particular facility, and verification of complaints.

In this study, an area of 25 m in length and 20 m in width was divided into 100 grids of 2.5 × 2 m (Fig. 3). The percentage of the area covered by scum in a grid was identified visually for an interval of one hour. Then, scum coverage was obtained as the total percentage of each grid. The scum coverage data in Sh-U from June to October 2017 were analyzed. The scum coverage data were classified according to DO ranges of 0­–1 mg/L, 1–2 mg/L, 2–4 mg/L, 4–6 mg/L and > 6 mg/L. A boxplot was made to determine the descriptive statistics as follows: minimum, median, maximum, lower quartile and upper quartile values. The scum probability for each DO range was also computed using Eq. (1).

Scum probability = n⁄N (1)

where n is the number of events with scum in a particular DO range, and N is the total number of populations or data with and without scum in the DO range.

Figure 3. 

Fixed camera image of 5% scum coverage in Sh-U on September 20, 2017 overlaid with a 25 m × 20 m scum coverage counting grid.

The temporal variations in rainfall, water level, salinity, DO, and scum coverage are shown in Fig. 5. Neap tides occurred on Aug. 31, Sep. 15 and Sep. 29, while spring tides took place on Aug. 23, Sep. 7, Sep. 21 and Oct. 5, all in the year 2017. There were five rainfall events with intensities greater than 5 mm/hr. The highest daily rainfall, recorded on Sep. 17, had a peak intensity of 12 mm/hr and a total amount of 65 mm. The effects of the tides and rainfall on the water quality parameters were analyzed.

Figure 5. 

Time series from Aug. 18 to Oct. 7, 2017, showing: (a) water depth (A.P., m) in Su-D and average rainfall value (mm/hr) from Iwabuchi and Nerima weather stations; DO (mg/L) and salinity at stations: (b) Sh-U, (c) Sh-M, (d) Su-U, and (e) Su-D; and (f) scum coverage (%) at Sh-U.

The salinity in the estuaries increased during neap tide and decreased during spring tide, which is a common estuarine condition (Uncles 2002). Salinity was minimal during intermediate tide following the spring tide in the two rivers. Salinity during neap tide was highest in Su-D, followed by Sh-M and Sh-U, and was lowest in Su-U (Fig. 6b–e). The lengths of the stations from the river mouth were 14.7 km in Su-D, 16.65 km in Sh-M, 17.15 km in Sh-U and 18.3 km in Su-U (Fig. 2). The salinity decreased with the distance of the stations from the river mouth. Two salinity peaks were observed in Su-D during neap tide due to the semidiurnal nature of these tides. However, three salinity peaks occurred in Su-U, Sh-U and Sh-M during neap tide in the semidiurnal tidal cycle. The probable sources of salinity were saltwater from Tokyo Bay and residual salinity at the confluence of the Shakujii and Sumida Rivers.

Figure 6. 

Time series of (a) tidal level in Su-D and rainfall; salinity and DO in (b) Sh-U, (c) Sh-M, (d) Su-U, and (e) Sh-U on the Sep. 2, 2017 neap tide. Spans 1, 2, 3 and 4 are indicated in red, blue, yellow and red, respectively. (f) The residual salinity in the confluence and the saltwater from Tokyo Bay.

The intrusion of unoxygenated saltwater from Tokyo Bay is important to investigate. The hypoxic conditions (< 2 mg/L) at the bottom depth may contribute to odor occurrence. Salinity was notably higher one or two days after neap tide (Okuyama et al. 2018) and decreased as tidal range increased (Fig. 5). The salinity sensors measured the bottom layer salinity. Therefore, it is estimated that a stratified salt wedge was formed by the vertical density stratification of salinity and freshwater. In the Chikugo River, the salinity was stratified during neap tide, and salinity intrusion occurred at tidal ranges of less than 1.5 m. The peak salinity occurred two days after neap tide, and the stratification changed, with waters becoming well mixed at spring tide (Somsook et al. 2020). Studies in the Sumida River on September 2008 (Nihei et al. 2009) and July 2017 (Casila et al. 2019a) observed a salt wedge during neap tide and well mixed salinity during spring tide, suggesting that seawater from Tokyo Bay formed a salt wedge during neap tide, which flowed through the Sumida River, causing salinity intrusion to the Shakujii River.

Fig. 6 shows the temporal variation in salinity at the four stations during Sep. 2 neap tide. Span 1 (in red for all stations) occurred during high tide, indicating high salinity after saltwater intrusion from Tokyo Bay, carrying water with low DO. The first high tide started at approximately 0:00 in the Sumida River. Salinity intrusion was evident at high tide with a peak value of 19.0 in Su-D at 02:30, 2 hours after high tide. In Su-U, salinity increased at 00:30 and peaked with a value of 8.6 at 05:00. In Sh-M, salinity increased rapidly at 01:00, with a peak value of 17.1 at 03:30. In Sh-U, salinity increased rapidly at 0:00, with the highest salinity value of 14.2 recorded at 03:00. Span 2 (in blue), which occurred during ebb to low tide, showed the influx of freshwater with high DO and low salinity after rainfall. Higher DO levels were observed upstream at Sh-U and Su-U. Saltwater was transported seaward during low tide at 9:00 in Su-D. The lowest salinity value in Su-D was 4.9 at approximately 12:00, 3 hours after low tide. In Su-U, Sh-M and Sh-U, salinity decreased during low tide due to freshwater influx.

Span 3 (shown in yellow in Sh-U, Sh-M and Su-U and in red in Su-D) indicates the first salinity peak during the flood tide of the next tidal cycle. In Sh-U, Sh-M and Su-U, salinity started to increase at approximately 11:00 due to the residual salinity moving landward. The peak salinity values were 7.4 at 12:00 in Sh-U, 9.9 at 11:30 in Sh-M, and 9.9 at 14:00 in Su-U. The values of peak salinity in Sh-M and Su-U were the same. Sh-M had an earlier peak because it was closer to the confluence. The confluence has the deepest bed elevation of -5.36 A.P. m, which caused salt retention. The Sh-U has a bed elevation of -2.68 A.P. m, while Sh-M has a bed elevation of -3.34 A.P. m. The bed slope is inversely graded from Su-D to areas upstream with a bed elevation of -4.88 A.P. m for Su-U and -3.58 A.P. m for Su-D (Fig. 2). Therefore, it is estimated that at the moment of change from ebb tide to flood tide, the direction of the flow changed in span 3. A pressure wave towards the upstream direction occurred and pushed the salinity that remained at the lowest point (Fig. 6f). In Su-D, there is no span 3, which means that residual salinity does not exist. Salinity increased and reached a peak value of 13.3 at 18:00, 2 hours after high tide. The time difference in peak salinity at Su-D and that of the other stations for Span 3 suggests that Su-D is largely affected by the salt wedge from Tokyo Bay. The lag time for salinity intrusion in Su-D may have also been because the low velocity during neap tide caused the salt wedge to move slowly. Span 4 (in red) showed a second salinity peak. The peak salinity in Sh-U was 9.4 at 18:00, 11.1 at 17:30 in Sh-M and 7.7 at 16:00 in Su-U. At the three stations, it was observed that salinity peaked two times for one tidal cycle during other neap tide events with or without rainfall (Fig. 5). Salinity moves seaward during ebb tide. It is noteworthy that the start and end times for Spans 3 and 4 in Sh-U and Sh-M were the same.

From the results, two salinity peaks were observed for one tidal cycle in the Shakujii River tidal area where scum is mainly generated. The channel slope from Sh-U to Sh-M is almost zero. This unique topography is a significant contributing factor to scum development. Sh-U also faces a steep wall that does not allow water transit during high tide. These factors could promote stagnant water conditions, which are conducive to scum generation

Higher salinity brings higher hydrogen sulfide which could be generated from the reduction of sulfate from seawater. This inhibits methane formation causing stronger odor but less scum formation. The odor index and odor concentration will be discussed in the succeeding section. Good estuary mixing is therefore favorable to avoid scum formation.

Among the four water quality monitoring stations, DO was consistently lowest in Su-D (Figs 5e, 6). Hypoxic water of less than 2 mg/L was observed in Su-D during neap tide except when there was an influx of freshwater after rainfall (Fig. 6e). In Su-U, the DO level was approximately 4 mg/L most of the days, but levels decreased to less than 2 mg/L when salinity increased during neap tide. The same trend was also observed in Sh-U and Sh-M. The DO levels in the Shakujii River can exceed 8 mg/L, but the levels decrease to less than 2 mg/L during neap tide. The factors that contribute to the decline in DO in the Shakujii River are rainfall and tidal level. The DO in Sh-U decreased from 5 mg/L to 1 mg/L for 12 hours after rainfall on Sep. 18 and from 6 mg/L to 1 mg/L for 24 hours from Sep. 23 to 24 (Fig. 5b). The DO increased due to rainfall and decreased thereafter during the two rainfall events on Sep. 18 and Sep. 23. DO must have been consumed for the decomposition of organic matter, which was similar to the findings of a study conducted in the Shakujii River (Casila et al. 2017).

The semidiurnal tidal cycle caused recurrent DO fluctuations in the Sumida and Shakujii Rivers, which were evident as repeating DO trends. Although both rivers are affected by tide, the DO trend in the Shakujii River was different from that in the Sumida River. The DO was low (in Su-D and Su-U) during high tide due to saltwater intrusion, while DO was high (in Su-D and Su-U) during low tide due to freshwater influx from upstream tributaries. The DO fluctuated largely during neap, spring and intermediate tides in the Shakujii River (Fig. 5b, c).

From Sep. 20 to 26, scum appeared 3 days following heavy rainfall with a total of 64.75 mm and a maximum intensity of 3.75 mm/hr (Fig. 5). On Sep. 20, the hourly scum coverage ranged between 0.5 and 12.9% (Fig. 3). Scum tends to appear two or three days after rainfall (Miura et al. 2018). Rainfall is therefore the main precursor to scum generation. The current data set indicates minimal scum coverage (less than 1%) when rainfall was 30 mm and 65 mm. Odor detection during field observation was heightened when scum coverage exceeded 5%. The water surface exhibited large portions of scum when the coverage surpassed 10%.

Scum in the Sh-U station started to appear on Sep. 2 (DO = 0.83–5.18 mg/L and salinity = 0.5–11.4) during neap tide, 2 days after rainfall, but the coverage remained under 1% (Fig. 5). Other instances of less than 1% scum coverage occurred on Sep. 3 (DO = 1.6–2.07 mg/L and salinity = 5.5–5.2) and Oct. 1 (DO = 2.82–6.97 mg/L and salinity = 0.2–1.8) during neap tide. Scum becomes more apparent when coverage exceeds 1%. The events with more than 1% coverage were observed from Sep. 20 during spring tide (DO = 1.04–2.66 mg/L and salinity = 0.2–0.3) to Sep. 26 during intermediate tide (DO = 2.15–4.02 mg/L and salinity = 0.1). Minimal salinity levels in the Shakujii River were recorded during the intermediate tide following the spring tide. Higher scum coverage was apparent when DO and salinity were low, typically occurring in the Shakujii River during spring tide. The low DO levels were likely due to OM decomposition, with high levels of OM possibly discharged from the combined sewer systems. Higher salinity resulted in reduced scum coverage, suggesting a limiting effect of salinity on scum and odor production.

The relationship between DO, scum coverage, and scum probability is shown in Fig. 7. The data gathered from June to Oct. 2017 at the Sh-U station where scum presence was apparent, indicated higher scum coverage at lower DO levels. Under hypoxic conditions of 0–1 and 1–2 mg DO/L, the median and upper quartiles (50–75% events) showed a scum coverage exceeding 1%. At approximately 0–1 mg/L DO, under anoxic conditions, the scum probability reached 75%. The scum probability was nearly identical for DO concentrations of 2–4 mg/L and 4–6 mg/L, which were 24% and 22%, respectively. It was observed that scum generation is inhibited with increasing DO levels, as scum probability decreased to 12% when DO exceed 6 mg/L. Additionally, the DO range of > 6% had the narrowest interquartile range compared to other DO ranges. It is recommended that DO levels ≥ 5 mg/L for Class B and C rivers, or ≥ 7.5 mg/L for Class A rivers, be strictly mandated to protect the environment. Most research on scum and odor has focused on wastewater treatment plants (Wang et al. 2016; Akcaalan et al. 2022), single rivers (Müezzinoğlu et al. 2000; Guo et al. 2021), and shallow eutrophic lakes (Xu et al. 2007; Wu et al. 2024b), with limited quantitative studies and on-site estuarine dynamics related to scum generation and odor.

Figure 7. 

Scum probability and relationship between scum coverage (%) and DO (mg/L) in Sh-U for 2017 data.

The results of odor analysis for scum, sediment and water samples are presented in Table 1. The scum sample from July 5, 2017 closely resembles the common brown and buoyant anaerobic sludge, serving as basis for comparison. The sediment and water samples were collected on the Aug. 23, 2017, during spring tide. The odor index was highest for scum, followed sediment and water. The Sh-U sediment had the highest similarity to scum, followed by Su-D sediment. The odor concentrations reported by the panelists ranked similarly, with scum at the highest, followed by sediment and water. The conditions in Sh-U on July 5 included a salinity of 0.1 and DO levels ranging from 1.6–6.7 mg/L, averaging4.2 mg/L at the time of scum appearance. Scum was not present in Sh-U on Aug. 23, despite the DO ranging from 6.6–9 mg/L and salinity of 0.1, likely because there was no rainfall 2 to 3 days prior.

Fig. 8 shows the odor components of the July 5 scum sample from Sh-U and the Aug. 23 sediment samples from Sh-U, Su-U and Su-D. The prominent components of the odor from scum and sediment samples in the Shakujii River (Sh-U) were organic acid and hydrogen sulfide. This was followed by aldehyde type, ester type and sulfur type compounds out of the 9 reference gases. Organic acid and sulfur compounds were prominent in Su-U and Su-D sediments. These odor components resemble those from sanitary sewage discharged by combined sewer systems during heavy rainfall. Organic acid comes from automobile emissions and anthropogenic sources such as wood, agricultural waste and fossil fuels (Sun et al. 2016). Ester is derived from acids like animal fat or vegetable oil. Hydrogen sulfide is generated from the reduction of sulfate from seawater and anaerobic decomposition of sulfur-containing proteins and organic matter. The sulfur compounds in the scum primarily come from sulfur-containing organics in the wastewater from restaurants, households, and other facilities (Ma et al. 2016). This finding was similar to the findings of Guo et al. 2021 where odor-causing compounds particularly sulfides where identified and related to marshy odor. Scum did not usually appear in the Sumida River stations. This was probably because the area had higher salinity than Sh-U. This may also explain the lower odor strength values of the Sumida River stations. Salinity during spring tide was higher in the Sumida River than in Sh-U (Fig. 5). High salinity inhibits the generation of methane, which is an anaerobic gas that is highly associated with scum generation (Miura et al. 2018). Scum coverage is usually high when salinity is low.

Figure 8. 

Strength of odor components from scum and sediments from Sh-U, Su-U and Su-D.

The authors have declared that no competing interests exist.

No ethical statement was reported.

This study was supported by the River Fund of The River Foundation, Japan. This research was supported in part by the project entitled “Study on guerrilla rainstorm, flood, and water pollution in megacity urban watersheds” funded by the Tokyo Metropolitan Government.

Conceptualization, J.C.C., R.O., K.Y.; methodology, J.C.C., R.O., K.Y.; software, R.O., K.Y.; validation, J.C.C., R.O., K.Y.; formal analysis, J.C.C., R.O., K.Y.; investigation, J.C.C., R.O., K.Y.; resources, K.Y.; data curation, J.C.C., R.O., K.Y.; writing—original draft preparation, J.C.C., R.O., K.Y.; writing—review and editing, J.C.C., R.O., K.Y.; visualization, J.C.C., R.O., K.Y.; supervision, K.Y.; project administration, K.Y.; funding acquisition, K.Y. All authors have read and agreed to the published version of the manuscript.

Joan Cecilia Casila  https://orcid.org/0000-0001-6319-8999

Katsuhide Yokoyama  https://orcid.org/0000-0003-1576-6239

All of the data that support the findings of this study are available in the main text.