Vulnerability of Beloslav and Varna Lakes to Eutrophication
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TENTH INTERNATIONAL CONFERENCE ON MARINE SCIENCES AND TECHNOLOGIES VULNERABILITY OF BELOSLAV AND VARNA LAKES TO EUTROPHICATION Valentina DONCHEVA, Snejana MONCHEVA, Nataliya SLABAKOVA ABSTRACT The main goal of the study is to assess vulnerability of Varna and Beloslav Lakes to eutrophication based on the screening models applied for water column and sediment characteristics. Simplified ‘screening’ models that have been applied for assessment the status of the lakes are Comprehen- sive Studies Task Team (CSTT)model (1994, 1997) for the water column status, and biogeochemical indicators for the sediment quality (Viaroli et al, 2004). According to applied models Beloslav and Varna lakes could be classified as hypereutrophic with high turbidity where the phytoplankton is light limited due to self-shading effect of the high biomass. Based on up- take of available nutrients by phytoplankton the resulting biomass characterizes the lakes as hypereutrophic. A reduction of the phytobiomass in the lake would require more than 20 times decrease of WWTP discharge. The sediments are defined as of high to excessive vulnerability risk. Key-words: eutrophication, Beloslav Lake, Varna Lake, screening model, CSTT, chlorophyll, sediment. INTRODUCTION from a sampling grid of nine stations in the lakes Understanding the increased eutrophication pres- (Regional Inspectorate of Ministry of Environment) sure over the coastal systems has challenged the need and additionally, our own data for chlorophyll and for integration of many complex processes. Screening nutrients (IO-BAS - Varna) were used (Fig. 2). The models are designed to provide an overview of the background station 301 is selected from the monitor- trophic status based on a few diagnostic variables [1], ing grid of IO-BAS. The Varna wastewater treatment to act as a link between data collection, interpretation plant (WWTP), which discharges about 1800 l/s into and coastal management. the Varna Lake from Varna city (more than 300000 in- The goal of the present paper is to assess vulnerabil- habitants), is included in the balance as a source. Water ity to eutrophication of system Beloslav Lake - Varna mass and nutrients balances were estimated according Lake based on screening models, applied to the water to [4]. PAR (photosynthetic available radiation) data column and upper sediment layer. was obtained from [5]. Material AND METHODS The CSTT is a simple model for identifying the waters that were at risk of eutrophication. (Fig.1). The model calculates the maximum phytoplankton chlorophyll concentration that could occur in summer for a given nutrient loading, based on uptake of avail- able nitrogen and phosphorus by phytoplankters. This concentration than is compared to a predetermined threshold to determine trophic state. The model was proposed by the UK’s Compre- hensive Studies Task Team [2, 3] in conformity to the requirement of the Urban Waste Water Treatment Directive (UWWTD) implementation. Fig. 1 Schematic presentation of the CSTT’s The input data for nutrient concentrations are based model for eutrophication-after [1] on averaged data for the 10-year period (1992-2002) Assoc. Res. PhD Valentina Doncheva, Assoc. Prof. PhD Snejana Moncheva, Assoc. Res. Natalia SLABAKOVA, Institute of Oceanology, tel.370 485 e-mail: [email protected], [email protected], [email protected] 261 TENTH INTERNATIONAL CONFERENCE ON MARINE SCIENCES AND TECHNOLOGIES Tentative assessment of the potential vulnerability level (PVL) of transitional waters based on integrated measurement of status variables in the surficial sediment (upper 5 cm). (1) modified from [6, 7] Table1 Vulnerability low Moderate high excessive Individual Rank 3 2 1 0 PVL 12 8 4 0 Fig. 2. Sampling stations in the system Beloslav Water Retention < 1 1-7 7-15 > 15 lake-Varna Lake - Varna Bay. Time (WRT, d) Granulometry (G) sand sandsilt siltclay Clay Total Organic Car- As major variables to monitor sediment character- bon (TOC, % dw) < 0.5 0.5 - 2.5 2.5 - 5 > 5 istics biogeochemical indicators were employed, inte- upper 5 cm (1) Carbone (CaCO , grated in index according to the criteria of UNESCO/ 3 > 40 20 - 40 5 - 20 < 5 % dw) IOC and [6, 7]. Originally the index of vulnerability is a sum of individual ranks of 6 parameters - Water Retention Time, Granulometry (G), Total Organic Results AND DISCUSSION Carbon (TOC, % dw) in the upper 5 cm, Carbonate The main CSTT procedure is relevant for zones in (CaCO , % dw), Reactive Fe (μmol cm-3), Acid Volatile 3 which discharged nutrients have residence times of a Sulphide (AVS, mol cm-3). Each rank is ranging from few days, sufficiently long to influence phytoplankton 3 - low vulnerability to 0 - excessive vulnerability and growth and biomass under of favorable conditions. the maximal value of the index is 18. Due to lack of Beloslav Lake has a residence time 6 days, Varna Reactive Fe and Acid Volatile Sulphide data, the index Lake 17.5 days and if unified in 1 box about 15 days is modified for 4 parameters - the maximal value for in average. index for low potential vulnerability level (PVL) is 12 In the CSTT eutrophication model applied the (Tbut able 1). parameters used to convert nutrients into worst case The data for sediment characteristics were obtained chlorophyll enrichment are according to [1, 2, 3]. from Environmental Impact Assessment Reports [8, There are three key steps in calculation of the 9, 10, 11] and new data collected within the project vulnerability of an area under investigation to eutro- TWReference net (Fig. 3.). phication [12]. The first step is to calculate the equilibrium con- centration of nutrients in the area that will result from a specified discharge, taking into account other nutrient inputs, and given the rate at which receiving-waters exchange with the sea (containing a known concentra- tion of nutrient) 1. S eq = S o + (s i /(E.V)) Fig. 3. Location of the stations for sediment sampling. Where S o - boundary or background concentration of nutrient; si is the local input of nutrient (in mmol d-1 from rivers, WWTP discharges, etc.; E: exchange or dilution rate; V: volume Next step is to calculate the concentration of chloro- phyll that would result if all nutrients were completely used during the phytoplankton growth, the chlorophyll concentration in the water coming from the adjacent sea, and consider if the total exceeds a threshold: 262 TENTH INTERNATIONAL CONFERENCE ON MARINE SCIENCES AND TECHNOLOGIES 2. X max =X o + q.S eq ((maximum) chlorophyll Thus based on uptake of available nutrients by concentration.); phytoplankton the resulting biomass characterizes the lakes as hypereutrophic (Table 2). The models results Xo: summer concentration of chlorophyll in sea:q are close to the measured concentrations in the area. In coefficients converting phytoplankton at yield of chlo- a number of cases the reported phytoplankton biomass rophyll per mmole of nitrate or phosphate; q = 1.1 mg expressed as Chl. a exceeded 100 mg.m-3 [14, 15]. chl (mmol N)-1; q = 30 mg chl (mmol P)-1; The maximal summer values measured in the canal, Finally it was determined if algae can in fact use these connecting Varna Lake and Varna Bay for the period nutrients - if receiving waters are too turbid to not allow 2000-2003 varied within the range between 10 and 50 plant growth, or diluted too fast to sustain an increase mg.m-3, in average 33 mg.m-3. in the abundance of phytoplankton. During the late spring 2001 the maximal value of chlorophyll was 90.64 mg.m-3, and during the summer 3. μ(I) = αb.(I-Ic) of 2005 - 52.8 mg.m-3. The maximal concentration measured in spring 2002 was 72.53 mg.m-3. Where :μ(I) is light-controlled phytoplankton growth; αB=0.006 is photosynthetic efficiency per day per ir- Input data and model results with and without radiance unit (d-1I-1) at low illumination. Photosynthetic WWTP input estimation (denominator) efficiency is the ratio of the rate of photosynthetic for- Table 2 mation of organic carbon for the available PAR Parameter Symbol Nitrogen Phosphates I is Photosynthetically Available Radiation (PAR) aver- volume box m3.106 V 195.5 195.5 aged over 24 h for a typical summer’s exchange rate per day E 0.04 0.04 _2 Ic 5 mE m s is compensation PAR, the illumination at nutrient input [kmol/ 70.61 0.9 si which photosynthesis and respiration are in balance day] /231.34 /21.05 when totalled over 24 h [1]. seawater concentra- S 8 0.3 The average illumination of the vertically mixed tion [mmol/m3] 0 Seq = S0 layer within which phytoplankton grow was calculated equilibrium concen- 17.03 0.42 + tration [mmol/m3] /37.58 /2.99 from: (si/(E*V)) -kD.h I=m.I0.(1-e )//kD.h≈m=I0/kD.h chlorophyll yield h : thickness of the surface mixed layer, metres (from N and P) q 1.1 30 [mgChl mmol nutri- I0 : 24-hr mean photosynthetically available radiation (PAR) at sea-surface, μE m-2 s-1 ent] seawater chlorophyll X0 5.5 5.5 kD: diffuse attetuation of (downwards) PAR in the conc. mg/m3 mixed layer, m-1 maximum chlorophyll Xmax = X0 24.2/ 18 m : correction for surface reflection and additional conc. mg/m3 + q*Seq 46.8 /95.3 near-surface losses rough estimate of the coefficient maximum permitted EQS 10 10 may be made from: chlorophyll mg/m3 kD = f/zS Where zS is the Secchi disc depth (metres), and the fac- tor f can be (taken) assumed as 1.4 typical for turbid Optic characteristic of Beloslav and Varna Lakes coastal water [13]. Table 3 Secchi disk depth data is averaged from monitor- Parameter Symbol Value Units average PAR ing data of IO-BAS, and a depth of 1 m is accepted I 20.5 μE m-2s-1 for the Lakes.