Drainage Ratio Controls Phytoplankton Abundance in Urban Lakes

Abstract

Urban lakes located in densely populated regions are highly vulnerable freshwater ecosystems compared to lakes in rural areas due to intense anthropogenic activities. However, the impacts of intrinsic lake morphometry on the water quality of urban lakes remain unclear. In the present study, the water quality of 14 lakes and the underlying factors associated with such quality were explored in Wuhan City, China. Of these surveyed urban lakes, 92.9% were eutrophic or hypereutrophic; phytoplankton biomass ranged between 3.2 and 62.0 mg/L and was positively correlated with drainage ratio values (catchment area/lake area) during the phytoplankton bloom season. These results are consistent with the fact that small lakes associated with a large watershed area generally exhibit high levels of areal nutrient accumulation that rise with the drainage ratio, supporting phytoplankton growth. There were no significant differences in phytoplankton diversity among lakes (p > 0.05), remaining stable at the low Shannon index of 1.9–2.9, which is possibly due to high eutrophication pressure and similar local climatic conditions across the relatively limited study area. Overall, the results of this study will provide a valuable foundation for future efforts to improve water quality management efforts for urban lakes.

1. Introduction

Lakes are complex and productive biological ecosystems that provide a range of ecological benefits to their surrounding communities, including high levels of biodiversity, recreational opportunities, flood mitigation utility, and various industrial, agricultural, and domestic applications [1,2,3]. The urbanization of human societies has grown increasingly pronounced since the 20th century [4], with approximately 55% of the global population living in urban areas as of 2018 and a projected increase in this proportion to 68% as of 2050 [5]. The regions with the highest degree of urbanization include North America (82%), Latin America and the Caribbean (81%), and Europe (74%) [6]. The progressive urbanization of many developing nations is spurring an increase in the number and size of megacities, exacerbating environmental issues including changes in land cover and the production and flow regimes for pollution, all of which can have a substantial impact on nearby lakes [7,8,9].

While nutrients are essential to the integrity of lake ecosystems and the maintenance of bioactivity therein, excessive nutrient accumulation can contribute to adverse outcomes including eutrophication and the consequent development of odoriferous phytoplankton blooms, ultimately resulting in decreased water quality and a drop in overall biodiversity [10,11,12,13]. Ho et al. [14] found that peak summertime phytoplankton bloom intensity has risen in most global lakes, highlighting the marked exacerbation of these blooms in recent years. Wang et al. [15] determined that such eutrophication results in a marked loss of biodiversity and contributes to the development of cross-taxon congruence in lakes. A massive phytoplankton bloom in Taihu Lake in China that was observed in May of 2007 was sufficiently large to overwhelm local water treatment plants, thereby causing a severe drinking water crisis affecting over two million people for one week [16]. Unlike rural lakes, urban lakes tend to be small, shallow, and extremely artificial. These factors, combined with the high levels of anthropogenic activity to which they are exposed, have led to the classification of urban lakes as being among the most vulnerable freshwater ecosystems in the world [17]. Until now, the impacts of anthropogenic activities on urban lakes have been intensively studied [18,19,20]; however, it still remains unclear whether and how intrinsic lake morphometry influences urban lakes.

Lake morphometry (surface area, depth, volume, hydraulic residence time, etc.), catchment properties (geology, size, and land use), and hydrologic setting all influence the quantities of terrestrial substances that enter into lakes and govern how long it takes them to decompose, thereby strongly regulating lake water quality [21,22,23,24]. Small ponds, for example, are important contributors to inland water CO₂ and CH₄ emissions as they are very shallow, exhibit high levels of sedimentation, have larger edge-to-water ratios, and undergo frequent mixing [22]. Drainage ratio values are calculated by dividing the catchment area of a lake by the area of the lake itself, and are commonly used to evaluate hydrologic loads, hydrologic residence time, and substance loads [24,25]. Rasmussen et al. [26] reported a positive correlation between water color and drainage ratios in 337 lakes throughout the US and Canada. Cremona et al. [27] further demonstrated the value of drainage ratio as a robust predictor of allochthonous carbon budget in hemiboreal lakes. Based on these prior results, we hypothesized that drainage ratio may influence nutrient loads in urban lakes, thereby controlling the phytoplankton abundance in these vulnerable water bodies.

To test this hypothesis, the present study was designed to explore the effects of drainage ratio on the abundance of phytoplankton in 14 urban lakes in Wuhan City, China. Moreover, the correlation between land use and the eutrophication of these lakes was assessed. The overall goals of these analyses were to clarify the mechanisms underlying such eutrophication and to identify promising approaches to the management of water quality in urban lakes.

2. Materials and Methods

2.1. Study Area

The study area was located in the national Wuhan Economic and Technological Development Zone (WETDZ) in China, which has an administrative area of 489.7 km² and a population of nearly 400,000 (Figure 1). Wuhan, the capital of Hubei Province in China (113°41′–115°05′ E, 29°58′–31°55′ N), has the largest water surface coverage of all cities in China. These lakes range from 0.01 to 2255 km² in size and exhibit widely varying water quality and optical properties [28]. Rapid socioeconomic development in the WETDZ has subjected this area to a range of public health and ecological risks that threaten further sustainable development. According to a 2016 report from the local department of environmental protection, over 70% of lakes in the WETDZ are worse than Class IV based on the standards established by the State Environment Protection Bureau of China. The deterioration of water quality can harm lake ecosystems and degrade associated ecological functions.

2.2. Field Survey

In order to comprehensively understand the phytoplankton community, a field survey in urban lakes was conducted during the phytoplankton bloom season. Two field surveys of 14 lakes in the WETDZ were performed by several workgroups within several adjacent days in August 2017 and August 2018. Three sampling sites were selected per lake based on spatial heterogeneity considerations. Triplicate water samples were collected randomly at each site using a stainless-steel bucket. These samples were fully homogenized and then a portion of the homogenized sample was used as the representative study site sample. Of this sample, 500 mL was frozen in acid-washed PVC bottles for nutrient analyses, while 1000 mL was preserved with 1% Lugol’s solution and concentrated to a final volume of 30 mL, following sedimentation for 48 h to facilitate phytoplankton analyses.

2.3. Chemical Analyses

In situ measurements of water temperature (WT), dissolved oxygen (DO), and pH were made with a Yellow Springs Instruments (YSI) 556 MPS. Water samples were used to measure chemical oxygen demand (COD), biochemical oxygen demand (BOD), total nitrogen (TN), and total phosphorus (TP) levels. BOD and COD were analyzed as per standard protocols established by the State Environment Protection Bureau of China (2002) [29], while TN and TP were respectively assessed via alkaline potassium persulphate digestion ultraviolet spectrometry and potassium persulfate digestion-Mo-Sb-Vc colorimetric methods [30].

A Sedgwich-R counting chamber was used to assess phytoplankton density (magnification × 400), while phytoplankton species were identified as detailed previously by Hu and Wei (2006) [31]. The Shannon index, which is a function of the number of taxa identified in the community (S; taxa richness) and the relative biomass of each taxon, was calculated to assess phytoplankton diversity [32,33]:

$$Shannon index=-{\displaystyle \sum }_{i=1}^s{p}_i\times ln{p}_i$$

where s is the total number of phytoplankton types in a sample (richness), i is the total biomass of individuals of one type, and p_i is the proportion of biomass of type i relative to the total biomass across all types.

2.4. Lake Watershed Area and Land Use Analyses

DEM, land use, and satellite remote-sensing data were collected to evaluate land use and the watershed area associated with the analyzed urban lakes. DEM data were obtained from the Computer Network Information Center of the Chinese Academy of Sciences (projection coordinates: WGS8; resolution: 30 × 30 m). Land use data from 2015 were obtained from the Computer Network Information Center of the Chinese Academy of Sciences at a resolution of 30 × 30 m with the ALBERS projection of the Krasovsky ellipsoid. Satellite remote-sensing data were collected from the TM data of the US Land Resources Satellites Landsat 8 (projection coordinates: WGS8; resolution: 30 × 30 m). The WETDZ GRID map was generated with the ArcGis software based on DEM data. WETDZ river systems were extracted by filling in depressions, analyzing flow direction, and calculating cumulative flow. Lake watershed area was divided according to outlet locations, and adjusted based on pipeline alignment, urban layouts, and road distributions.

2.5. Statistical Analysis

Statistical analyses were performed using SPSS v22.0 (SPSS Inc., IL, USA). To ensure that the data better conformed to a normal distribution, results were subjected to logarithmic transformation. Results were compared using t-tests following the Kolmogorov-Smirnov and variance homogeneity tests, with p < 0.05 as the threshold of significance. Relationships between the phytoplankton biomass and lake drainage ratio as well as land use type were assessed through correlation analyses using simple linear regression.

3. Results and Discussion

3.1. Urban Lake Eutrophication

Lakes situated in urban regions provide higher levels of societal value and recreational benefits to their densely populated local communities as compared to rural lakes [34]. Appropriately managing water quality in these lakes, however, is challenging, owing to these high levels of population density and associated urban encroachment [35]. Overly high pollutant loads can subject urban lakes to a range of ecological and environmental challenges [34]. For example, Regnery and Püttmann [36] demonstrated that the toxic organophosphate levels in rural lakes were substantially lower than those in urban lakes, while Wu et al. [37] performed an analysis of 12 urban lakes in the Chinese capital of Beijing and found the vast majority of these lakes to be subject to substantial eutrophication. In the urban lakes of the WETDZ, the mean values of DO, COD_Mn, BOD, TN, and TP in the water were 11.5, 4.9, 2.7, 2.1, and 0.19 mg/L, respectively. Per the Chinese national water quality standards, these urban lakes fall in the fifth poorest quality category, as these lakes represent artificial ecosystems that are generally small and relatively shallow in addition to being subjected to high levels of socioeconomic development. The exact water quality values for these surveyed lakes varied, with DO, COD_Mn, BOD, TN, and TP ranges of 7.4–13.4 (standard deviation: 1.8), 2.7–8.0 (standard deviation: 1.7), 1.3–5.6 (standard deviation: 1.3), 0.5–9.8 (standard deviation: 2.3), and 0.02–0.96 (standard deviation: 0.23) mg/L, respectively. Per these Chinese national water quality standards, the ChuanJian, Long Hougua, Nantai, Wanjia, Wulang, Zhulin, Zhumu, and Zhuangyuan lakes exhibited the poorest water quality (fifth category), with TN and TP values of 1.53–9.8 and 0.02–0.96 mg/L, respectively, whereas the Guanliang, Shangwu, and Zhushan lakes exhibited the best water quality (third category), with TN and TP levels of 0.5–0.9 and 0.07–0.12 mg/L, respectively. As shown in

Table 1. The physicochemical properties of water in the urban lakes analyzed in this study.

Lake Name	Lat.	Lon.	Catchment Area (ha)	Lake Area (ha)	WT (°C)	pH	DO (mg/L)	CODMn (mg/L)	BOD (mg/L)	TN (mg/L)	TP (mg/L)	TLI
ChuanJiang	30.41	114.13	291	668	9.3	8.7	12.4	3.02	1.40	1.58	0.02	28.2
Long	30.37	114.13	35	168	9.6	8.5	11.0	2.70	1.90	1.72	0.07	42.1
Guanliang	30.38	114.05	1238	8082	9.3	8.3	10.3	3.58	1.80	0.51	0.08	43.5
Houguan	30.49	114.12	1812	61,215	9.5	8.9	11.0	3.89	2.80	2.41	0.06	40.3
Nantai	30.48	114.20	994	5357	10.5	8.9	8.4	5.25	2.50	3.41	0.29	57.8
Niuwei	30.41	114.09	34	258	5.0	8.2	12.8	6.17	1.70	0.90	0.19	53.1
Shangwu	30.41	114.10	54	279	3.8	8.1	12.5	4.47	1.57	0.71	0.12	48.0
Wanjia	30.46	114.20	511	1580	9.6	9.1	7.4	8.00	5.63	9.80	0.96	71.1
Xiashan	30.37	114.06	321	999	7.8	8.5	11.8	3.38	1.30	1.26	0.09	44.8
Wulang	30.41	114.09	82	660	11.1	8.4	12.6	7.51	4.70	1.61	0.22	54.7
Zhushan	30.43	114.11	2760	6690	9.9	8.8	12.7	3.65	2.90	0.93	0.07	42.1
Zhulin	30.43	114.15	270	345	9.8	8.5	12.1	4.24	3.90	1.79	0.14	49.7
Zhumu	30.37	114.08	68	342	3.4	8.2	13.4	6.72	2.70	1.53	0.16	51.2
Zhuangyuan	30.39	114.08	268	860	3.9	8.6	13.2	6.25	2.78	1.86	0.15	50.5

, the trophic level index (TLI) values for each lake were calculated as detailed by Wang et al. [38]. Based on these results, 92.9% of the analyzed urban lakes were eutrophic. ChuanJiang lake was oligotrophic, while Wanjia lake was supereutrophic and the others were lightly eutrophic or mesotrophic. Lakes are an essential component of urban ecosystems, and often produce outsized influence on urban ecosystem health. Urban lakes are, however, often overlooked due to their small size [39]. The prevailing poor water quality of urban lakes is certainly weakening their ecological functions. City officials need to pay more attention and try to address water quality problems in the future.

Nutrients are essential for phytoplankton growth, but the input of excessively high nutrient levels into a given body of water can result in adverse ecological outcomes including the rapid development of phytoplankton blooms [40,41]. Eutrophication and associated phytoplankton bloom formation can have a serious adverse impact on local water quality and ecological functionality [42]. The phytoplankton biomass in the surveyed lakes in this study was relatively high (mean: 30 mg/L), with substantial variation among the individual analyzed urban lakes in the WETDZ (range: 10–80 mg/L, standard deviation: 20 mg/L). The highest phytoplankton abundance was observed in Zhusan Lake (85 mg/L), with these levels being 5-fold higher than those in Wanjia Lake (15 mg/L) (Figure 2a). These urban lakes tended to exhibit low levels of phytoplankton diversity (range: 1.0–1.2) without any significant differences among the individual lakes (p > 0.05, t = 0.064, df = 13) (Figure 2b). The phytoplankton community showed high taxonomic similarity among these urban lakes with the dominant species of Chlorophyta (~60%). The other phytoplankton species includes Bacillariophyta, Cyanophyta, Cryptophyta, Euglenophyta, Pryrophyta, and Chrysophyta (Figure 3b). This may be attributable to high eutrophication pressure and similar local climatic conditions across the relatively limited study area. Eutrophication can decrease phytoplankton diversity in lakes [43], and climatic conditions can influence the structure of phytoplankton communities both directly through physiological changes and indirectly through changes in water column stratification and resource availability, thus altering light or nutrient availability and the intensity of grazing by heterotrophs [44].

3.2. The Relationships between Lake Morphometry and Eutrophication

Lake morphometry is closely linked to the accumulation of specific substances in lakes and the ecological processes that occur therein [45,46]. Zhou et al. [23] highlighted the high rates of eutrophication in shallow lakes, such as those often found in agricultural plains and lowland areas associated with high levels of population density. These shallow lakes are exposed to intensive human activity and high levels of anthropogenic nutrient input, unlike deeper lakes located in upland regions surrounded by primarily natural landscape features, where anthropogenic nutrient inputs are relatively minimal. Here, phytoplankton biomass was found to be positively correlated with the drainage ratio values with a correlation coefficient of 0.35 (p = 0.025) (Figure 3), with these values being calculated by dividing the catchment area by the associated lake area. The entry of terrestrial compounds from a large catchment area in small lakes generally results in high levels of areal substance accumulation, such that this accumulative capacity rises with lake drainage ratio values, ultimately providing nutrients to support higher levels of phytoplankton growth (Figure 2a).

To evaluate the effects of watershed properties on the abundance of phytoplankton in these urban lakes, their associated watershed land use types were next evaluated. This approach revealed that farmland and construction were the two dominant land use types, with farmland, dry land, woodland, grassland, marshland, bottomland, urban land, rural settlements, and construction accounting for 32.23%, 5.86%, 2.54%, 5.15%, 2.62%, 2.78%, 7.90%, 1.20%, and 39.69% of land use activity, respectively (Figure 4). Analyses of the correlative relationships between land use type and phytoplankton abundance revealed that these levels differed substantially as a function of land use type. Specifically, a positive correlation was observed between phytoplankton levels and farmland, construction land, rural settlements, urban land, and bottomland, whereas these levels were negatively correlated with dry land, woodland, grassland, and marshland (Figure 5a). The strength of the correlation coefficients for farmland, construction land, rural settlements, and bottomland were 0.27, 0.21, 0.14, 0.05, and 0.01, respectively (Figure 5b). In contrast to more traditional urban zones, Chinese economic and technological development zones often harbor higher levels of industrial activity but lower levels of population density. The relatively low levels of water pollution generated by the primary industry in the WETDZ, automobile production, which are largely confined to associated industrial parks, thus resulting in farmland being the main contributor to associated urban lake pollution [47].

3.3. Future Perspectives for the Management of Urban Lake Water Quality

While urban lakes serve as an important provider of ecosystem services to their surrounding communities to a greater extent than do rural lakes, they are highly sensitive to the direct effects of anthropogenic activity. The present results revealed that urban lakes exhibit high rates of eutrophication, with drainage ratio values having a strong influence on phytoplankton abundance in these lakes owing to the high levels of nutrients that accumulate in smaller lakes associated with a large catchment. These urban lakes are widely considered to represent artificial ecosystems, and efforts to reduce the associated drainage ratio via increasing lake area or decreasing the associated catchment area have the potential to help protect against severe eutrophication, for example, by drawing flow to nearby lakes with lower drainage ratios. This water diversion has been widely used to control water quality in inland waters [48,49]. Land use in the watershed regions associated with urban lakes can also influence the pollutant loads therein, and a range of strategies can be employed in an effort to lower watershed-derived nutrient loads including geo-engineering tools, wetland construction, or the construction or optimization of wastewater treatment plants and technologies [50,51,52]. Moreover, based on the preliminary correlation between lake morphometry and water quality in this study, a model can be further established using machine learning in the future to predict water quality after collecting more data [53,54]. Such a model would facilitate management of urban lakes.

4. Conclusions

In the present analysis, the water quality of 14 urban lakes in Wuhan City, China, was assessed and the impacts of lake morphometric factors including land use and drainage ratio on water quality. The major findings of this study included the following:

(1)

The majority of surveyed urban lakes exhibited poor water quality, with 92.9% being classified as eutrophic and hypereutrophic.

(2)

Significant differences in phytoplankton biomass were observed among these lakes, with a mean value of 23.6 mg/L and values ranging between 10 and 80 mg/L, whereas no corresponding significant differences in phytoplankton diversity were observed (p > 0.05).

(3)

Phytoplankton biomass was positively correlated with lake drainage ratio (R² = 0.35). Nutrient accumulation capacity rises with the drainage ratio, thereby providing nutrients that support greater levels of phytoplankton growth in these lake ecosystems.

(4)

More data need to be collected in the future to establish models to predict water quality using lake morphometry, which can be beneficial to urban lake management.