Abstract

We investigated whether recent springtime water temperature increases in a shallow eutrophic lake affected bottom sediment temperature and fluxes of ammonia (NH4+) and phosphate (PO43−) from the sediment. We conducted a lake-wide survey of Lake Kasumigaura, Japan, and analyzed the relationship between water temperature increases in spring and NH4+ and PO43− release fluxes. We also developed a numerical model to analyze how water temperature increase affects sediment temperature. Water temperature in May increased during 2010–2019 at a rate of 1.8–3.2 °C decade−1. The numerical simulation results showed that the water temperature increase was accompanied by a sediment temperature increase from a minimum of 18.3 °C in 2011 to a maximum of 21.6 °C in 2015. Despite the substantial difference in the observed sediment temperature (2.9 °C), no significant differences in NH4+ and PO43− fluxes in May between 2013/2014 and 2015 were found. These results suggest that both water and sediment temperatures are increasing in Lake Kasumigaura in spring, but it is unclear whether this warming has affected NH4+ and PO43− releases from the sediment. However, because a nonlinear response to sediment temperature was observed, future springtime warming may accelerate NH4+ and PO43− releases.

HIGHLIGHTS

  • A water temperature increase was observed in spring by a trend analysis.

  • Sediment temperature also increased with the increase of water temperature.

  • Ammonia and phosphate releases from bottom sediment were little changed by warming.

Graphical Abstract

Graphical Abstract
Graphical Abstract

INTRODUCTION

Climate warming increases atmospheric temperature, which could also increase the water temperature in lakes (Woolway et al. 2019; Woolway et al. 2020; Maberly et al. 2020) through changing the heat fluxes on the lake surface (Livingstone 2003). Under the RCP8.5 scenario of the Intergovernmental Panel on Climate Change (IPCC 2014), the atmospheric temperature will increase by 4.8 °C by 2100. In deep, well-stratified lakes, an atmospheric temperature increase leads to an increase in epilimnion temperatures (Niedrist et al. 2018), whereas in shallow, polymictic lakes, it could increase the whole water column. Therefore, shallow lake sediments are more likely affected by temperature increases than deep lake sediments. For example, O'Reilly et al. (2015) have reported that lake surface temperatures around the world have been increasing during 1985 and 2009 (O'Reilly et al. 2015).

Sediment temperature is one of the most important parameters for nutrient cycling in lacustrine environments. An increase in sediment temperature, thereby increasing microbial decomposition of organic matter, can accelerate the release of ammonia (NH4+) and phosphate (PO43−) from the sediment (Rydin et al. 2017). Such internal nutrient loading of NH4+ and PO43− promotes phytoplankton blooms in the lake (Yang et al. 2020). Release rates of phosphorus (P) from lake sediments are usually highest in summer (Wang et al. 2019), but increases in lake water temperatures have been also observed seasonality (Winslow et al. 2017). For example, Li et al. (2019) observed long-term water temperature in shallow lakes in China during 1979 and 2017. They found that increases in water temperatures are largest during spring and the water temperature increase is associated with an increase in solar radiation (Li et al. 2018). A water temperature increase in spring might be expected to enhance effluxes of NH4+ and PO43− from sediment to the overlying water, as given the effects of temperatures on PO43− release (Holdren & Armstrong 1980; Jensen & Andersen 1992). However, despite many studies of water temperature increases due to global warming (Chikita et al. 2018; Chikita et al. 2019), little information is available about how spring warming is changing sediment temperature and consequent releases of NH4+ and PO43− from sediment.

This study addressed the following questions about the effects of a water temperature increase on bottom sediments of shallow lakes: (1) Have increased water temperatures been changing sediment temperatures, thereby making the release of nutrients from lake sediments into the overlying water more likely? and (2) How do N and P releases from bottom sediments respond to water temperature increases? If springtime warming increases the NH4+ and PO43− release rates, the duration of the NH4+ and PO43− releases period could be extended and accelerate eutrophication.

We hypothesized that (1) the long-term water temperature increase in spring has increased the sediment temperature; and (2) the sediment temperature increase is enhancing nitrogen (N) and P fluxes from sediments. To test these hypotheses, we studied springtime water and sediment temperature trends and NH4+ and PO43− fluxes from the bottom sediment in Lake Kasumigaura, Japan. Lake Kasumigaura is a shallow, hypereutrophic lake, and P released from the bottom sediment accounts for approximately half of the total P loading. In the lake, empirically, water temperature is highest in summer, more than 30 °C every year, and NH4+ and PO43− also exhibit maximum releases during summer. First, we analyzed water temperature changes in the lake from 2010 to 2019 to clarify whether and how much water temperature increased during this period. Next, we developed a one-dimensional numerical model to analyze how sediment temperature has been changing in Lake Kasumigaura from 2010 to 2019 in response to the water temperature increase. We simulated sediment temperatures and compared them between the years in which the minimum and maximum water temperatures were recorded in the lake. Finally, we analyzed the relationship between observed sediment temperatures and NH4+ and PO43− fluxes from the sediment to the water during three consecutive years (2013–2015) and examined whether the increase in sediment temperature also increased NH4+ and PO43− releases. The loadings from the inflow rivers as well as the factors changing the NH4+ and PO43− releases in August were also discussed.

METHODS

Lake Kasumigaura

Lake Kasumigaura is the second largest lake in Japan, with an area of 171 km2, a mean depth of approximately 4 m, and a maximum depth of 7.4 m (Figure 1). This lake is a polymictic lake, showing vertical mixing every day in the water column. The average water residence time is approximately 200 days. More than 900,000 people live in the lake's watershed (1,577 km2), and the lake is the source of drinking water for about 660,000 people. Land use in the watershed is 30% forest, 25% paddy field, 25% ploughed field, 10% residential, and 10% other. Extremely high loads of organic matter and nutrients have caused eutrophication of the lake, which has mean concentrations of total nitrogen (TN) and total phosphorus (TP) of 0.78 mgN L−1 and 0.08 mgP L−1, respectively, as measured at the center of the lake in 2018.

Figure 1

Map of Lake Kasumigaura and locations of sediment sampling stations, Stn. A, B, and C. Water temperatures At Stn. B and Stn. C, water temperatures were monitored at positions very close to the sediment sampling sites.

Figure 1

Map of Lake Kasumigaura and locations of sediment sampling stations, Stn. A, B, and C. Water temperatures At Stn. B and Stn. C, water temperatures were monitored at positions very close to the sediment sampling sites.

Sediment and water sampling and sediment temperature measurements

Sediment samples were collected monthly from December 2012 to December 2015 at three sampling stations (Stns. A, B, and C; Figure 1), each in a different area of the lake (Matsuoka et al. 1986). The sediment samples were collected under calm conditions with low wind speed. At Stn. A, water depth 4.0 m, is in organic-rich sediments derived from the inflow of the Koise River. At Stn. B, water depth 2.0 m, the sediments include coarser particles derived from dredging (Tsuchiya et al. 2020). At Stn. C, in the center of the lake, the water depth is 6.0 m; thus, it was the deepest sampling site. The detailed physical properties of the sediments at each station are described in the supporting information (Supplementary Material, Table S1).

A gravity core sampler (ϕ = 11 cm) was used for collecting sediment samples. Just after each sediment core was collected, we used a syringe to collect a water sample just above the bottom sediment for later analysis of NH4+ and PO43−. In addition, at each station, we measured the sediment temperature at 1.5, 4.5, 7.5, 10.5, 13.5, 16.5, 19.5, 22.5, 25.5, 28.5, and 31.5 cm depth below the sediment surface with a digital thermometer (TX10–01, Yokogawa, Tokyo, Japan). A duplicate core was taken to the laboratory as soon as possible for analysis of NH4+ and PO43− concentrations in the surface sediment.

We measured dissolved oxygen (DO), and pH in situ at a point just above the lake bottom with a multiparameter water quality sonde (Hydrolab DS5, HydroMet, Loveland, Colorado, USA). We also collected water samples for analysis of chlorophyll a (Chl-a) in a well-washed, 2-m column sampler (Rigo Co., Tokyo, Japan). The collected water samples were transported to our laboratory within ∼2 h.

The water samples of the two major inflow rivers (the Sakura and Koise Rivers) were also collected monthly from January 2014 to December 2015. The sampling point of the Sakura River was approximately 10 km upstream from Lake Kasumigaura. The sampling point of the Koise River was 9.5 km upstream from Lake Kasumigaura. We collected surface water by using a well-washed container (5 L) from the bridge. The collected water was stored in an acid-washed polycarbonate container (2 L) and carried to our laboratory as soon as possible (∼2 h).

In the laboratory, each sediment core (0–1.5 cm depth) was sliced at a depth of 0.75 cm under an N2 atmosphere for analysis of NH4+ and PO43− in the porewater. We centrifuged (relative centrifugal force, 2,278 g) each sample for 15 min at 4 °C and filtered the supernatant through a GF/F glass fiber filter (nominal pore size: 0.70 μm) under an N2 atmosphere. The filtrates were then frozen (–20 °C) and stored until analysis. Each water sample (200 mL) for Chl-a analysis was immediately filtered through a GF/F glass fiber filter, and then the filter was frozen and stored at –20 °C until analysis.

Water temperature and river flow rate data

Hourly water temperature data were downloaded from the Water Information System of the Ministry of Land, Transportation, and Tourism (http://www1.river.go.jp/). Our sediment sampling point at Stn. A was a distance of 2.4 km from the water temperature observation site (Figure 1), but we expected the difference in water temperature between the two sites to be small, based on our observations. We used water temperature data from 2010 to 2019 for analyzing the change in monthly averaged water temperature. The flow rates (m3 s−1) from the Sakura and Koise Rivers were provided by the Ministry of Land, Transportation, and Tourism.

Chemical analysis

NH4+ and PO43− concentrations were analyzed with an auto-analyzer (QuAAtro 2-HR, BLTec, Tokyo, Japan) according to the manufacturer's instructions. Briefly, the NH4+ concentration was analyzed by a phenate method (4,500–NH3 F; APHA 2005), and the PO43− concentration was analyzed by a molybdenum blue method (Murphy & Riley 1962). The minimum detection limits (3σ of the 6 blanks) of NH4+ and PO43− were 1.0 μgN L−1 and 0.8 μgP L−1, respectively. Chl-a was extracted by methanol, and the optical densities were determined by spectrophotometer (UV–2500PC, Shimadzu, Kyoto, Japan). The data were opened online at the Kasumigaura Database of the National Institute for Environmental Studies.

N and P release from sediment to the overlying water

In the present study, molecular diffusion from the sediment to the water was assumed to occur with little physical disturbance. Although Lake Kasumigaura is a shallow lake, the collection of sediment samples was not under any strong physical disturbance (Matsuzaki et al. 2021). We calculated the NH4+ and PO43− release flux J from the N and P data of the bottom water (+0 cm) and the porewater (0.75 cm depth) using the following equation (Klump & Martens 1981):
formula
(1)
where ϕ is porosity (dimensionless), D is the tortuosity-corrected diffusion coefficient (cm2 s−1), C is the NH4+ or PO43− concentration (μg cm3), and z is sediment depth. D was calculated as follows (Reddy & DeLaune 2008):
formula
(2)
where Dm is the molecular diffusion coefficient (cm2 s−1). For the Dm values of NH4+ and PO43− in Equation (2), we used the values for 18 °C of 1.68 × 10−5 and 7.15 × 10−6 cm2 s−1, respectively, determined by Li & Gregory (1974). We then used the Stokes-Einstein relationship to calculate the diffusion coefficients at temperatures other than 18 °C:
formula
(3)
where μ1 and μ2 are viscosities, and D1 and D2 are molecular diffusion coefficients at temperatures T1 and T2 (K), respectively.

Numerical modeling of sediment temperature

The sediment temperature simulation model was based on one-dimensional diffusion following (Pivato et al. 2018):
formula
(4)
where T is sediment temperature (°C), t is time (s), λ is thermal conductivity (W cm−1 K−1), ρ is the density of the water or sediments (g cm−2), and c is the specific heat of sediment (J g−1 K−1). The values of ρ (for the sediments) and λ are given in the supporting information (Supplementary Material, Table S1). Thermal conductivity was set at 0.25 × 10−2 W cm−1 K−1 or 0.30 × 10−2 W cm−1 K−1 (Hipsey et al. 2019), based on the organic-rich sediments of Lake Kasumigaura. An implicit finite difference scheme was used to solve Equation (4). The calculations were conducted for the sediment layer from 0 to 31.5 cm depth at depth intervals (Δz) of 0.25 cm. For the boundary condition at the top of the sediment, we used the monthly water temperature data collected at each station. We compared the hourly data with observed water temperature data (Supplementary Material, Figure S1), and the regression equation was applied to the boundary conditions. The time interval (Δt) of the calculation was 1,800 s.
To validate the model, we used the temperatures measured in December 2012 and December 2013 and calculated the root mean square error (RMSE) between the calculated and observed values as follows:
formula
(5)
where n is the number of data, xcal is the calculated temperature, and xobs is the observed sediment temperature (°C).
To calculate the heat flux between sediment and water, we used the following equation (Fang & Stefan 1996):
formula
(6)
where HG is the heat flux (W m−2) between sediment and the water column, Tw and Ts are water and sediment temperatures (°C), respectively, and Δz is the depth interval in the model (0.25 cm).

Numerical calculation of cool and warm years

We calculated the differences in sediment temperature and heat flux between 2011, when water temperatures were relatively cool, and 2015, when they were warm (see section Long-term water temperatures). The initial conditions were set as constant values of water temperature, and the model spin-up period was 2 months. Missing data were linearly interpolated using the data collected before and after.

Statistical analysis

For long-term trend analyses and validation of the numerical simulations, we used the Pearson product moment correlation coefficient. We used paired t-tests to assess differences in sediment temperature and the release fluxes of NH4+ and PO43−. A type I error (α) of less than 0.05 was regarded as significant. We used Microcal Origin ver. 8.5.1.J software for the statistical analyses.

RESULTS

Long-term water temperatures

Monthly mean water temperatures at the three stations are shown in Figure 2. Note that water temperatures recorded in February are not shown, because many data were missing. Spring water temperatures (March–May) increased at rates of 1.8–3.2 °C decade−1 from 2010 to 2019 (Figure 2 and Supplementary Material, Figure S2). In particular, the water temperature in May increased at all three stations. The monthly mean water temperature in May was lowest in 2011 (Stn. A: 19.6 °C, Stn. B: 18.9 °C, and Stn. C: 19.0 °C) and highest in 2015 (Stn. A: 22.9 °C, Stn. B: 22.1 °C, and Stn. C: 21.4 °C). Therefore, these years were used to represent cool and warm years, respectively, in this study.

Figure 2

Monthly mean water temperature fluctuations in Lake Kasumigaura at (a) Stn. A, (b) Stn. B, and (c) Stn. C. The colored circles are values for months showing statistically significant relationships between water temperature and year. The correlation coefficient (r) and the p-values are also shown.

Figure 2

Monthly mean water temperature fluctuations in Lake Kasumigaura at (a) Stn. A, (b) Stn. B, and (c) Stn. C. The colored circles are values for months showing statistically significant relationships between water temperature and year. The correlation coefficient (r) and the p-values are also shown.

Numerical model validation and analysis

The developed one-dimensional numerical model successfully simulated the sediment temperature of Lake Kasumigaura during 2012–2013 (Supplementary Material, Figure S3). The measured and calculated sediment temperatures differed only slightly (Stn. A, RMSE = 0.98 °C; Stn. B, RMSE = 1.1 °C; Stn. C, RMSE = 1.1 °C), and the correlation coefficient for the relation between the observed and simulated values was high at all stations (Supplementary Material, Figure S4; Stns. A–C: r= 0.99, p < 0.001).

Differences in sediment temperatures between 2011 and 2015 were simulated by the numerical model (Figure 3), and particularly for those in May of both years (Figure 4). The monthly mean water temperature difference in May between 2011 and 2015 was 3.3 °C at Stn. A, 3.2 °C at Stn. B, and 2.4 °C at Stn. C. The calculated sediment temperature at 0.75 cm depth in May increased from 18.3 to 21.4 °C at Stn. A, 18.6 to 21.6 °C at Stn. B and 18.9 to 20.1 °C at Stn. C between 2011 and 2015 (Figure 4). The 25-h running mean of the heat flux between sediment and water ranged between –12 and 14 W m−2 in both 2011 and 2015 (Figure 3(j)–3(l)).

Figure 3

(a–c) Water temperature fluctuations in 2011 (black lines) and 2015 (red lines), simulation results for sediment temperatures (color scale, °C) in (d–f) 2011 and (g–i) 2015, and (j–l) heat fluxes (25 h running mean) in 2011 (black lines) and 2015 (red lines) at stations A–C. The positive values mean the downward flux. Please refer to the online version of this paper to see this figure in colour: http://dx.doi/10.2166/wcc.2021.145.

Figure 3

(a–c) Water temperature fluctuations in 2011 (black lines) and 2015 (red lines), simulation results for sediment temperatures (color scale, °C) in (d–f) 2011 and (g–i) 2015, and (j–l) heat fluxes (25 h running mean) in 2011 (black lines) and 2015 (red lines) at stations A–C. The positive values mean the downward flux. Please refer to the online version of this paper to see this figure in colour: http://dx.doi/10.2166/wcc.2021.145.

Figure 4

Time series of sediment temperature (color scale, °C) in May of (a–c) 2011 and (d–f) 2015 at station A–C. (g–i) Time series of sediment temperature at 0.75 cm depth at Stn. A–C. Please refer to the online version of this paper to see this figure in colour: http://dx.doi/10.2166/wcc.2021.145.

Figure 4

Time series of sediment temperature (color scale, °C) in May of (a–c) 2011 and (d–f) 2015 at station A–C. (g–i) Time series of sediment temperature at 0.75 cm depth at Stn. A–C. Please refer to the online version of this paper to see this figure in colour: http://dx.doi/10.2166/wcc.2021.145.

Changes in temperature and N and P releases from sediment during 2013–2015

The release rates of NH4+ and PO43− ranged from 0.59 to 95 mgN m−2 d−1 for NH4+ and from –0.02 to 11 mgP m−2 d−1 for PO43− (Figure 5). The fluxes increased with increasing sediment temperature, and the correlation coefficients between fluxes and sediment temperature were high (Supplementary Material, Table S2). The response of the release rates to sediment temperature differed among the stations, and remarkably the response of the NH4+ flux was linear except at Stn. A. By contrast, at all stations, the PO43− flux from the sediment did not begin to increase until the sediment temperature exceeded 15–20 °C (Figure 5).

Figure 5

Time series of (a) NH4+ and (b) PO43− fluxes from December 2012 to December 2015. Relationships between (c) NH4+ and (d) PO43− fluxes from sediment and sediment temperature in Lake Kasumigaura at stations A–C.

Figure 5

Time series of (a) NH4+ and (b) PO43− fluxes from December 2012 to December 2015. Relationships between (c) NH4+ and (d) PO43− fluxes from sediment and sediment temperature in Lake Kasumigaura at stations A–C.

Comparison of the NH4+ and PO43− fluxes in May between 2013/2014 and 2015 by paired t-tests showed no significant difference in either the NH4+ or the PO43− flux between 2013/2014 and 2015, even though the sediment temperature was significantly higher, by 2.9 °C, in 2015 compared with 2013/2014 (Table 1).

Table 1

Results of paired t-tests comparing sediment temperature with NH4+ and PO43− fluxes between May 2013/2014 and May 2015

Temperature (°C)
NH4+ flux (mgN m−2 d−1)
PO43− flux (mgP m−2 d−1)
Year201320152013201520132015
Average 17.7 20.6 15.5 10.8 0.23 0.2 
t-test t = 4.3, p< 0.001 t = 4.3, p= 0.47 t = 4.3, p = 0.77 
Year201420152014201520142015
Average 17.7 20.6 15.9 10.8 0.33 0.2 
t-test t = 4.3, p< 0.001 t = 4.3, p= 0.47 t = 4.3, p = 0.50 
Temperature (°C)
NH4+ flux (mgN m−2 d−1)
PO43− flux (mgP m−2 d−1)
Year201320152013201520132015
Average 17.7 20.6 15.5 10.8 0.23 0.2 
t-test t = 4.3, p< 0.001 t = 4.3, p= 0.47 t = 4.3, p = 0.77 
Year201420152014201520142015
Average 17.7 20.6 15.9 10.8 0.33 0.2 
t-test t = 4.3, p< 0.001 t = 4.3, p= 0.47 t = 4.3, p = 0.50 

The averaged values of Stns. A, B, and C are shown.

Sediment temperature better explained the NH4+ and PO43− fluxes from the sediment to the overlying water than the other measured parameters, including phytoplankton biomass (Chl-a concentration) and the DO concentration and pH at the lake bottom, as indicated by the high correlation coefficients between sediment temperature and both fluxes (Table 2). Chl-a, DO, and pH all varied greatly during 2012–2015 (Figure 6), but DO concentrations were high (>7.2 mg L−1) in May at all stations.

Table 2

Correlation coefficients for the relationship between PO43− and NH4+ fluxes and chlorophyll a (Chl-a), dissolved oxygen (DO), or pH and sediment temperature (**p < 0.001)

Chl-aDOpHTemperature
PO43− flux 0.29** –0.68** –0.01 0.79** 
NH4+ flux 0.18 –0.51** –0.09 0.63** 
Chl-aDOpHTemperature
PO43− flux 0.29** –0.68** –0.01 0.79** 
NH4+ flux 0.18 –0.51** –0.09 0.63** 

Note that the natural logarithm of the PO43− flux was compared with sediment temperature (see Supplementary Material, Table S2).

Figure 6

Time series of (a) chlorophyll a (Chl-a), (b) dissolved oxygen (DO), and (c) pH in the bottom water at Stns. A–C from December 2012 to December 2015.

Figure 6

Time series of (a) chlorophyll a (Chl-a), (b) dissolved oxygen (DO), and (c) pH in the bottom water at Stns. A–C from December 2012 to December 2015.

PO43− and NH4+ fluxes from the inflow rivers

The flow rates of the Sakura and Koise Rivers and the NH4+/PO43− concentrations during 2014 and 2015 are shown in Figure 7. The NH4+ concentrations were, on average, 0.06 mgN L−1, and the averaged PO43− concentration was 0.009 mgP L−1 in the Sakura River. In the Koise River, the concentrations were higher than the Sakura River. The averaged NH4+ concentration was 0.24 mgN L−1, whereas the averaged PO43− concentration was 0.019 mgP L−1.

Figure 7

The daily flow rates from the inflow river (the Sakura and Koise Rivers) and NH4+ and PO43− concentrations in the inflow river from 2014 to 2015.

Figure 7

The daily flow rates from the inflow river (the Sakura and Koise Rivers) and NH4+ and PO43− concentrations in the inflow river from 2014 to 2015.

We calculated the fluxes of NH4+ and PO43− from the inflow rivers by using these values in May. Because the basin area of Stn. A was 23 km2 (Matsuoka et al. 1986), the estimated NH4+ and PO43− fluxes from the Koise River in May 2014 were 1.73 mgN m−2 d−1 and 0.23 mgP m−2 d−1, respectively. By contrast, the fluxes from the Sakura River (the area: 49.3 km2) in May 2014 were 0.60 mgN m−2 d−1 for NH4+ and 0.15 mgP m−2 d−1. From the Koise River, the fluxes in 2015 were 1.63 mgN m−2 d−1 for NH4+ and 0.24 mgP m−2 d−1 for PO43−. The fluxes from the Sakura River were 1.39 mgN m−2 d−1 for NH4+ and 0.17 mgP m−2 d−1 for PO43−. The NH4+ flux from the sediment at Stn.A were 8.4 times greater than from the Koise River, whereas the NH4+ flux from the Sakura River was 7.8 times greater than from the sediment at Stn. B during 2014 and 2015. The PO43− flux from the sediment at Stn. A was 3.2 times greater than from the Koise River, whereas it was 1.6 times greater Stn. B than from the Sakura River. However, in 2015, discharges of total N and total P into the lake from rivers (e.g., 34.9 mgN m−2 d−1 and 1.37 mgP m−2 d−1 from the Koise River at Stn. A) were much greater than the fluxes of NH4+ (10.8 mgN m−2 d−1) and PO43− (0.20 mgP m−2 d−1) from the bottom sediment in May.

DISCUSSION

The most striking finding of this study is that in Lake Kasumigaura, although springtime water temperatures increased, the increase had no effect or only a limited effect on N and P effluxes from the sediment. The water temperature increase in spring is consistent with observations at other shallow lakes in temperate regions (Li et al. 2019), but to our knowledge this is the first study to assess the effects of lake water warming on sediment N and P in the spring season. Summertime warming is often considered (O'Reilly et al. 2015), but our study observed springtime warming of water temperature and the effects on the sediment.

Our simulation results also indicated warming of sediment temperature in spring, but the increase was too small to affect N and P release fluxes from the sediment to the overlying water, as shown by the lack of significant changes in NH4+ and PO43− fluxes in May between 2013 or 2014 and May 2015 (Figure 5; Table 1). The NH4+ and PO43− releases from sediment were much smaller than the fluxes of total N and total P from the inflow river.

The limited effect of warmer springtime temperatures on the releases of N and P from sediment has several possible explanations. First, acceleration of microbial decomposition of organic P may have been insufficient. Decomposition of organic P, especially DNA-P, is mainly responsible for the release of P from sediment to the overlying water (Reitzel et al. 2007; Ishii et al. 2010). Second, oxidation and reduction potentials affect the acceleration. P in sediment, which is often adsorbed onto metal oxyhydroxides, is released under reductive conditions (Chen et al. 2018). However, the observed DO concentrations in the water column in May (7.2 mg L−1; Figure 6) indicate oxidative conditions.

The effects of warmer springs on NH4+ and PO43− fluxes are still unclear, but the nonlinear increase in the PO43− flux in relation to sediment temperature suggests that a further increase in temperature might accelerate the flux. Gudasz et al. (2010) have reported that warming of water temperature in lakes accelerates the decomposition and mineralization of organic matter (Gudasz et al. 2010). The PO43− supply to sediment porewater depends not only on the mineralization of organic P but also on the presence or absence of electron acceptors (Schindler 2012) and sulfate-reducing bacteria (Caraco et al. 1989). Sediment temperature should also affect these reactions related to PO43− and organic P.

Masunaga & Komuro (2019) have reported that heat fluxes at the lake surface cannot fully explain water temperatures in Lake Kasumigaura (Masunaga & Komuro 2019). They suggested that the sediment acts as a heat buffer and that the heat flux between sediment and water can be as large as 100 W m−2 in summer. However, our numerical simulation results for sediment temperature are inconsistent with this suggestion (Figure 3). A heat flux of 14 W m−2 resulted in an increase of the water temperature of Lake Kasumigaura of approximately 0.072 °C per day (∼2.2 °C per month). This increase is too small, compared to the heat flux at the water surface, to account for the water temperature changes in Lake Kasumigaura (Sugita et al. 2020). The small heat flux between the sediment and the water column was consistent with the other lakes (Fang & Stefan 1996).

Several factors may account for the changing water temperature of Lake Kasumigaura. An increase in solar radiation, possibly associated with global brightening and dimming (Wild et al. 2005; Tanaka et al. 2016), may explain increases in water temperature globally (Fink et al. 2014) and also in Lake Kasumigaura. Sugita et al. (2014) have shown that wind direction and speed change the latent heat flux, which can cause water temperature fluctuations (Sugita et al. 2014). In this study, a water temperature in May of around 20 °C was the turning point for the release of P from sediment (Figure 5); this result implies that a further increase of water temperature in spring may cause greater releases of NH4+ and PO43− from the sediment.

We could not determine whether spring warming has been observed in other lakes, but global brightening and dimming have been observed all over the world (Wild 2009; Cermak et al. 2010). Global brightening and dimming could be caused by the decrease in aerosol (Wild et al. 2005) and such brightening also increases shortwave radiation on the lake surface (Fink et al. 2014). The future meteorology, including air temperature and precipitation, is unclear now, but for a more comprehensive understanding of spring warming, the factors responsible for the changing water temperature in other lakes in the world in May must be clarified so that future water temperatures in May can be predicted.

In this study, the mechanisms causing the changes in NH4+ and PO43− fluxes with the changes in surface water and sediment temperatures were not examined. The relationship between PO43− releases and sediment temperature, which differed among the stations (Figure 5), may depend on sediment characteristics. For example, the sandy sediment at Stn. B had a lower organic matter content than the sediment at the other stations (Tsuchiya et al. 2020; Supplementary Material, Table S1) and release rates of NH4+ and PO43− there were low, even at high temperatures. Furthermore, the relationship between SO42− and PO43− needs further investigation. The clear decrease in SO42− concentration with the sediment depth suggests that SO42− reduction and pyrite formation could occur in the sediments (Gächter & Müller 2003) because pyrite was also detected in Lake Kasumigaura (Supplementary Material, Figures S5 and S6). Pyrite does not adsorb PO43− onto the sediment solids (Gächter & Müller 2003). SO42− and PO43− should be addressed in the future work because they could be involved in the P release from the bottom sediments (Sinkko et al. 2011).

The higher temperature could also change N cycling in the lake, such as denitrification (Veraart et al. 2011). In the case of Lake Kasumigaura, the undetectable level of NO3 concentrations in the sediment porewater could have resulted from denitrification in the bottom sediments regardless of the seasons (Supplementary Material, Figure S5). Further investigation is warranted about the impacts of temperature increase on N cycles in the watershed.

CONCLUSION

We analyzed the effect of increases in water temperature in spring on bottom sediment temperature and the potential impact on the release of NH4+ and PO43− from the sediment to the overlying water. Water temperature in spring has been increasing in Lake Kasumigaura. We used a numerical model to examine changes in sediment temperature due to the warming of the water during 2010–2019 and found that sediment temperature in May was approximately 3.1 °C higher in 2015, a warm year, compared with 2011, a relatively cool year. At Lake Kasumigaura, the PO43− flux did not start to increase until the sediment temperature reached 15–20 °C. The impact of an increase of sediment temperature in spring is thus still obscure. However, the nonlinear response of the PO43− flux to sediment temperature suggests that future warming in spring may accelerate the release of PO43− from sediment. Although the total N flux from the bottom sediment was less than the inflow river, the amount of NH4+ flux from the bottom sediment was, in particular, 8.4 times greater than that from the Koise River. Such a large amount of flux could mitigate the N limitation in particular at Stn. A (Matsuzaki et al. 2018). A better understanding of the effects of spring warming will require intensive monitoring of meteorology and water/sediment temperatures during spring.

ACKNOWLEDGEMENTS

This research was financially supported by KAKENHI (19K04629). We also thank laboratory members Noriko Sugiyama and Yasushi Yakabe for their support in analyzing the ammonia and phosphate concentrations in the sediment porewater. We also thank Shin-ichiro Matsuzaki for the fruitful discussion we exchanged.

DATA AVAILABILITY STATEMENT

All relevant data are available from an online repository or repositories (https://db.cger.nies.go.jp/gem/moni-e/inter/GEMS/database/kasumi/index.html).

REFERENCES

APHA
2005
Standard Methods for the Examination of Water and Wastewater
.
American Public Health Association (APHA)
,
Washington, DC
,
USA
.
Caraco
N.
,
Cole
J.
&
Likens
G.
1989
Evidence for sulphate-controlled phosphorus release from sediments of aquatic systems
.
Nature
341
(
6240
),
316
318
.
Cermak
J.
,
Wild
M.
,
Knutti
R.
,
Mishchenko
M. I.
&
Heidinger
A. K.
2010
Consistency of global satellite-derived aerosol and cloud data sets with recent brightening observations
.
Geophysical Research Letters
37
(
21
),
L21704
.
Chen
M.
,
Ding
S.
,
Chen
X.
,
Sun
Q.
,
Fan
X.
,
Lin
J.
,
Ren
M.
,
Yang
L.
&
Zhang
C.
2018
Mechanisms driving phosphorus release during algal blooms based on hourly changes in iron and phosphorus concentrations in sediments
.
Water Research
133
,
153
164
.
Chikita
K. A.
,
Oyagi
H.
,
Aiyama
T.
,
Okada
M.
,
Sakamoto
H.
&
Itaya
T.
2018
Thermal regime of a deep temperate lake and its response to climate change: Lake Kuttara, Japan
.
Hydrology
5
(
1
),
17
.
Chikita
K.
,
Ochiai
Y.
,
Oyagi
H.
&
Sakata
Y.
2019
Geothermal linkage between a hydrothermal pond and a deep lake: Kuttara Volcano, Japan
.
Hydrology
6
(
1
),
4
.
Fang
X.
&
Stefan
H. G.
1996
Dynamics of heat exchange between sediment and water in a lake
.
Water Resources Research
32
(
6
),
1719
1727
.
Fink
G.
,
Schmid
M.
,
Wahl
B.
,
Wolf
T.
&
Wüest
A.
2014
Heat flux modifications related to climate-induced warming of large European lakes
.
Water Resources Research
50
(
3
),
2072
2085
.
Gudasz
C.
,
Bastviken
D.
,
Steger
K.
,
Premke
K.
,
Sobek
S.
&
Tranvik
L. J.
2010
Temperature-controlled organic carbon mineralization in lake sediments
.
Nature
466
(
7305
),
478
481
.
Hipsey
M. R.
,
Bruce
L. C.
,
Boon
C.
,
Busch
B.
,
Carey
C. C.
,
Hamilton
D. P.
,
Hanson
P. C.
,
Read
J. S.
,
De Sousa
E.
&
Weber
M.
2019
A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)
.
Geoscientific Model Development
12
,
473
523
.
Holdren
G. C.
&
Armstrong
D. E.
1980
Factors affecting phosphorus release from intact lake sediment cores
.
Environmental Science & Technology
14
(
1
),
79
87
.
IPCC
2014
Climate Change 2013: the Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change
.
Cambridge University Press
.
Ishii
Y.
,
Harigae
S.
,
Tanimoto
S.
,
Yabe
T.
,
Yoshida
T.
,
Taki
K.
,
Komatsu
N.
,
Watanabe
K.
,
Negishi
M.
&
Tatsumoto
H.
2010
Spatial variation of phosphorus fractions in bottom sediments and the potential contributions to eutrophication in shallow lakes
.
Limnology
11
(
1
),
5
16
.
Klump
J. V.
&
Martens
C. S.
1981
Biogeochemical cycling in an organic rich coastal marine basin – II. Nutrient sediment-water exchange processes
.
Geochimica et Cosmochimica Acta
45
(
1
),
101
121
.
Li
Y.-H.
&
Gregory
S.
1974
Diffusion of ions in sea water and in deep-sea sediments
.
Geochimica et Cosmochimica Acta
38
(
5
),
703
714
.
Li
X.
,
Peng
S.
,
Deng
X.
,
Su
M.
&
Zeng
H.
2019
Attribution of lake warming in four shallow lakes in the Middle and Lower Yangtze River basin
.
Environmental Science & Technology
53
(
21
),
12548
12555
.
Maberly
S. C.
,
O'Donnell
R. A.
,
Woolway
R. I.
,
Cutler
M. E.
,
Gong
M.
,
Jones
I. D.
,
Merchant
C. J.
,
Miller
C. A.
,
Politi
E.
&
Scott
E. M.
2020
Global lake thermal regions shift under climate change
.
Nature Communications
11
(
1
),
1
9
.
Masunaga
E.
&
Komuro
S.
2019
Stratification and mixing processes associated with hypoxia in a shallow lake (Lake Kasumigaura, Japan)
.
Limnology
21
,
173
186
.
Matsuoka
Y.
,
Goda
T.
&
Naito
M.
1986
An eutrophication model of Lake Kasumigaura
.
Ecological Modelling
31
(
1–4
),
201
219
.
Matsuzaki
S. S.
,
Suzuki
K.
,
Kadoya
T.
,
Nakagawa
M.
&
Takamura
N.
2018
Bottom-up linkages between primary production, zooplankton, and fish in a shallow, hypereutrophic lake
.
Ecology
99
(
9
),
2025
2036
.
Matsuzaki
S. S.-i.
,
Tanaka
A.
,
Kohzu
A.
,
Suzuki
K.
,
Komatsu
K.
,
Shinohara
R.
,
Nakagawa
M.
,
Nohara
S.
,
Ueno
R.
&
Satake
K.
2021
Seasonal dynamics of the activities of dissolved 137Cs and the 137Cs of fish in a shallow, hypereutrophic lake: links to bottom-water oxygen concentrations
.
Science of the Total Environment
761
,
143257
.
Murphy
J.
&
Riley
J. P.
1962
A modified single solution method for the determination of phosphate in natural waters
.
Analytica Chimica Acta
27
,
31
36
.
O'Reilly
C. M.
,
Sharma
S.
,
Gray
D. K.
,
Hampton
S. E.
,
Read
J. S.
,
Rowley
R. J.
,
Schneider
P.
,
Lenters
J. D.
,
McIntyre
P. B.
&
Kraemer
B. M.
2015
Rapid and highly variable warming of lake surface waters around the globe
.
Geophysical Research Letters
42
(
24
),
10,773
10,781
.
Pivato
M.
,
Carniello
L.
,
Gardner
J.
,
Silvestri
S.
&
Marani
M.
2018
Water and sediment temperature dynamics in shallow tidal environments: the role of the heat flux at the sediment-water interface
.
Advances in Water Resources
113
,
126
140
.
Reddy
K. R.
&
DeLaune
R. D.
2008
Biogeochemistry of Wetlands: Science and Applications
.
CRC Press
,
Baco Raton, FL
.
Reitzel
K.
,
Ahlgren
J.
,
DeBrabandere
H.
,
Waldebck
M.
,
Gogoll
A.
,
Tranvik
L.
&
Rydin
E.
2007
Degradation rates of organic phosphorus in lake sediment
.
Biogeochemistry
82
(
1
),
15
28
.
Rydin
E.
,
Kumblad
L.
,
Wulff
F.
&
Larsson
P.
2017
Remediation of a eutrophic bay in the Baltic Sea
.
Environmental Science & Technology
51
(
8
),
4559
4566
.
Schindler
D. W.
2012
The dilemma of controlling cultural eutrophication of lakes
.
Proceedings of the Royal Society B: Biological Sciences
279
(
1746
),
4322
4333
.
Sinkko
H.
,
Lukkari
K.
,
Jama
A. S.
,
Sihvonen
L. M.
,
Sivonen
K.
,
Leivuori
M.
,
Rantanen
M.
,
Paulin
L.
&
Lyra
C.
2011
Phosphorus chemistry and bacterial community composition interact in brackish sediments receiving agricultural discharges
.
PLoS One
6
(
6
),
e21555
.
Sugita
M.
,
Ikura
H.
,
Miyano
A.
,
Yamamoto
K.
&
Zhongwang
W.
2014
Evaporation from Lake Kasumigaura: annual totals and variability in time and space
.
Hydrological Research Letters
8
(
3
),
103
107
.
Tanaka
K.
,
Ohmura
A.
,
Folini
D.
,
Wild
M.
&
Ohkawara
N.
2016
Is global dimming and brightening in Japan limited to urban areas?
Atmospheric Chemistry and Physics
16
(
21
),
13969
.
Tsuchiya
K.
,
Komatsu
K.
,
Shinohara
R.
,
Imai
A.
,
Matsuzaki
S. i. S.
,
Ueno
R.
,
Kuwahara
V. S.
&
Kohzu
A.
2020
Variability of benthic methane-derived carbon along seasonal, biological, and sedimentary gradients in a polymictic lake
.
Limnology and Oceanography
65
(
12
),
3017
3031
.
Veraart
A. J.
,
De Klein
J. J.
&
Scheffer
M.
2011
Warming can boost denitrification disproportionately due to altered oxygen dynamics
.
PLoS One
6
(
3
),
e18508
.
Wang
M.
,
Xu
X.
,
Wu
Z.
,
Zhang
X.
,
Sun
P.
,
Wen
Y.
,
Wang
Z.
,
Lu
X.
,
Zhang
W.
&
Wang
X.
2019
Seasonal pattern of nutrient limitation in a Eutrophic lake and quantitative analysis of the impacts from internal nutrient cycling
.
Environmental Science & Technology
53
(
23
),
13675
13686
.
Wild
M.
2009
Global dimming and brightening: a review
.
Journal of Geophysical Research: Atmospheres
114
(
D10
),
D00D16
.
Wild
M.
,
Gilgen
H.
,
Roesch
A.
,
Ohmura
A.
,
Long
C. N.
,
Dutton
E. G.
,
Forgan
B.
,
Kallis
A.
,
Russak
V.
&
Tsvetkov
A.
2005
From dimming to brightening: decadal changes in solar radiation at Earth's surface
.
Science
308
(
5723
),
847
850
.
Winslow
L. A.
,
Read
J. S.
,
Hansen
G. J.
,
Rose
K. C.
&
Robertson
D. M.
2017
Seasonality of change: summer warming rates do not fully represent effects of climate change on lake temperatures
.
Limnology and Oceanography
62
(
5
),
2168
2178
.
Woolway
R. I.
,
Weyhenmeyer
G. A.
,
Schmid
M.
,
Dokulil
M. T.
,
de Eyto
E.
,
Maberly
S. C.
,
May
L.
&
Merchant
C. J.
2019
Substantial increase in minimum lake surface temperatures under climate change
.
Climatic Change
155
(
1
),
81
94
.
Woolway
R. I.
,
Kraemer
B. M.
,
Lenters
J. D.
,
Merchant
C. J.
,
O'Reilly
C. M.
&
Sharma
S.
2020
Global lake responses to climate change
.
Nature Reviews Earth & Environment
1
,
388
403
.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).

Supplementary data