**4. The trophic status assessment**

### **4.1. Simple lake characterizations**

Trophic state of a lake can be determined by simply observing its basic characteristics (**Table 1**). More profound approaches of trophic state require analysis of key parameters such as phosphorus, nitrogen, chlorophyll *a*, and Secchi depth [65–68]. **Table 1** shows the trophic state classification based on simple lake characterization [69, 70].


**Table 1.** Trophic state classification based on simple lake characteristics [69].

### **4.2. Trophic state per nutrients, primary productivity and Secchi disc parameters**

Ecosystems can be described at different trophic states using grow-limiting nutrients, primary productivity and Secchi disc parameters. **Table 2** shows the average characteristics of lakes, streams, and coastal marine waters of different trophic states.


**Table 2.** Average characteristics of lakes [66], streams [67], and coastal marine waters [68] of different trophic states [13].

To increase the efficiency of a lake management program is used a more sophisticate trophic state index to provide more and complete information about the water state. The characteri‐ zation of trophic status has been conducted using the following: the Carlson's trophic state index, the TSI (Carlson's index).

### **4.3. Carlson's trophic state index**

**Characteristic Eutrophic state**

Characteristic fish Deep-dwelling cold water fish such

as trout, salmon, and cisco

Secchi depth 7.5 m 1.5 m

**Table 1.** Trophic state classification based on simple lake characteristics [69].

streams, and coastal marine waters of different trophic states.

Total aquatic plant production

30 Water Stress in Plants

Number of algae species

Characteristic algae groups

Oxygen in hypolimnion

[13].

index, the TSI (Carlson's index).

**Oligotrophic Eutrophic**

Parse Abundant

**4.2. Trophic state per nutrients, primary productivity and Secchi disc parameters**

**Water body Tropic state TN, mg m−3 TP, mg m−3 CHL, mg m−3 SD, m** Lakes Oligotrophic <350 <10 <3.5 >4

Streams Oligotrophic <700 <25 <10 <20

Streams Oligotrophic <260 <10 <1 >6

Mesotrophic 350–650 10–30 3.5–9 2–4 Eutrophic 650–1200 30–100 9–25 1–2 Hypertrophic >1200 >100 >25 <1

Mesotrophic 700–1500 25–75 10–30 20–70 Eutrophic >1200 >75 >30 >70

Mesotrophic 260–350 10–30 1–3 3–6 Eutrophic 350–400 30–40 3–5 1.5–3 Hypertrophic >400 >40 >5 <1.5

**Table 2.** Average characteristics of lakes [66], streams [67], and coastal marine waters [68] of different trophic states

To increase the efficiency of a lake management program is used a more sophisticate trophic state index to provide more and complete information about the water state. The characteri‐ zation of trophic status has been conducted using the following: the Carlson's trophic state

Ecosystems can be described at different trophic states using grow-limiting nutrients, primary productivity and Secchi disc parameters. **Table 2** shows the average characteristics of lakes,

Surface-dwelling, warm water fish such as pike, perch, and bass; also bottom-dwellers such as

Suspended CHL, mg m−3 Benthic CHL, mg m−3

Suspended CHL, mg m−3 SD, m

catfish and carp

Present Absent

Low High

Many Few

The trophic state is an absolute scale which describes the biological condition of the water body. The trophic state (TSI) is defined as the total weight of living biological material (*biomass*) in a water body at a specific location and time, a biological response to forcing factors such as nutrient additions [71]. The TSI is the interrelationship between the varia‐ bles which can be used to identify certain conditions in the lake which are related to the factors limiting the phytoplankton biomass [72]. The effect of nutrients is modified by factors such as season, grazing, mixing depth, etc. For characterizing the trophic state of lakes independent of climate exchange, there were defined the trophic state index (TSI)— Carlson's index Secchi depth, chlorophyll *a*, and total phosphorus; these are three varia‐ bles which can therefore be used to classify the water body [73]. Three linear regression models are used to calculate the trophic state index and the classified water body: the Secchi disk, TSI(SD); chlorophyll pigments, TSI(CHL); and total phosphorus, TSI(TP). The simpli‐ fied equation used is presented below [73]:

$$\text{TSI(SD)} = 60 - 14.41 \ln(\text{SD}) \tag{5}$$

$$\text{TSI(CHL)} = 9.81 \ln(\text{CHL}) \text{ + 30.6} \tag{6}$$

$$\text{TSI(TP)} = \text{l4.42 } \ln\text{(TP)} + \text{4.15} \tag{7}$$

where TSI(SD) is the trophic state index depending on the Secchi depth, the values of SD is in meters;

TSI(CHL) is the trophic state index depending on the chlorophyll *a* concentration, CHL (μg/l); TSI(TP) is the trophic state index depending on the total phosphorus concentration, TP (μg/l).


**Table 3.** Assessment criteria for lake Trophic status (SD, TP, CHL, TSI) [9].

More used is the averaging TSI value, which characterizes the central tendency of the trophic state [73–75]. **Table 3** shows the assessment criteria for the lake trophic status regarding the averaging TSI, the Secchi depth, chlorophyll *a*, and total phosphorus concentration [8].


**Table 4.** Carlson's trophic state index values and classification of lakes [76].

TSI results could be analyzed using Carlson's scale. This is divided into four steps regarding lake productivity: oligotrophic (least productive), mesotrophic (moderately productive); eutrophic (very productive), and hypereutrophic (extremely productive). In natural condition at largely variation of meteorological parameters, a simple interpretation of trophic state of lake water is not enough.

**Figure 8.** A representation of possible explanations of deviations of the trophic [74].

For complex characterization of natural water must to account of systematic deviations of the simple presentation like in **Table 4**, reported of Carlson in 1992. **Figure 8** illustrates the deviations of TSI(CHL) − TSI(TP) and TSI(CHL) − TSI(SD), and are simultaneously plotted on a single graph, that completes the interpretation of trophic state of natural water. The possi‐ bilities are illustrated in **Figure 8** [74]

### **4.4. Case study: Snagov Lake trophic stage assessment**

**TSI values Trophic status Attributes**

32 Water Stress in Plants

lake water is not enough.

<30 Oligotrophic Clear water, oxygen throughout the year in the hypolimnion 30–40 Oligotrophic A lake will still exhibit oligotrophy, but some shallower lakes

40–50 Mesotrophic Water moderately clear, but increasing probability of anoxia during the summer 50–60 Eutrophic Decreased transparency, warm-water fisheries only

60–70 Eutrophic Dominance of blue-green algae, algal scum probable, extensive macrophyte problems 70–80 Hypereutrophic Heavy algal blooms possible throughout the summer >80 Hypereutrophic Algal scum, summer fish killing, few macrophytes

**Table 4.** Carlson's trophic state index values and classification of lakes [76].

**Figure 8.** A representation of possible explanations of deviations of the trophic [74].

will become anoxic during the summer

TSI results could be analyzed using Carlson's scale. This is divided into four steps regarding lake productivity: oligotrophic (least productive), mesotrophic (moderately productive); eutrophic (very productive), and hypereutrophic (extremely productive). In natural condition at largely variation of meteorological parameters, a simple interpretation of trophic state of

The Snagov Lake is a natural lake located at 25–30 km North from Bucharest, in Ilfov County, Romania. It is an important natural lagoon on the inferior Ialomita river course with its 5.75 km2 surface, 16 km length, and 9 m maximum depth, it is included in national patrimony as natural reservation (**Figure 9**).

The lake water sources are the underground waters and in small part snow and rain waters. As consequence, the water level is relatively constant except in winter and autumn [77].

Samples were collected in 2015 during three annual campaigns: April, July, and October. The duplicate of samples were collected from three sampling points than were chosen to monitor the Snagov Lake: input of Lake-Antena Tancabesti, middle of lake—Complex Pacea and output of lake Santu Floresti (**Figure 9**).

**Figure 9.** Sampling sites to Snagov Lake: input-Antena Tancabesti, middle-Complex Pacea, and output-Santu Floresti [74].

There were analyzed temperature (*T*), pH, transparency Secchi depth (SD), total nitrogen (TN), total phosphorus (TP), chlorophyll *a* (CHL), dissolved oxygen (DO), turbidity (Tr), total suspended matter (Ts) (**Table 5**).

We calculated the trophic state index (Carlson's index), TSI(SD), TSI(CHL), and TSI(TP) using Eqs. (5)–(7) and there average values TSI and using **Figure 7** and **Table 4** the state of lake was characterized. **Table 6** shows the characterization of Snagov Lake in time in sampling points.

**Table 6** shows the evolution of water quality of Snagov Lake in time and in space, at input loaded with nutrient in organic and inorganic matter like smaller particles that involve an excessive development of algae and inorganic matter sedimentation in the middle zone of lake until output when the biological activity slowly decreasing and water quality is slightly improvement, all of this in the eutrophic-hypertrophic state of lake. With this evaluation system can identify the status of the lake and can take necessary measures to improve water quality.


**Table 5.** Average parameter values for Snagov Lake characterization.


There were analyzed temperature (*T*), pH, transparency Secchi depth (SD), total nitrogen (TN), total phosphorus (TP), chlorophyll *a* (CHL), dissolved oxygen (DO), turbidity (Tr), total

We calculated the trophic state index (Carlson's index), TSI(SD), TSI(CHL), and TSI(TP) using Eqs. (5)–(7) and there average values TSI and using **Figure 7** and **Table 4** the state of lake was characterized. **Table 6** shows the characterization of Snagov Lake in time in sampling points.

**Table 6** shows the evolution of water quality of Snagov Lake in time and in space, at input loaded with nutrient in organic and inorganic matter like smaller particles that involve an excessive development of algae and inorganic matter sedimentation in the middle zone of lake until output when the biological activity slowly decreasing and water quality is slightly improvement, all of this in the eutrophic-hypertrophic state of lake. With this evaluation system can identify the status of the lake and can take necessary measures to improve water

**Parameter Input Antena Tancabest Middle Complex Pacea Output Santu Floresti Data Data Data**

*T*, °C 15 29 16 14 28 17 16 29 16

pH 8.4 8.7 7.9 8.3 7,86 7.74 8,5 8,1 7,6

Ts, mg/l, 21.6 32.2 60.8 21.6 19.6 55.2 23.4 40.2 45.2

SD, m 0.5 0.5 0.5 0.8 0.9 0.9 2 0.45 0.9

Tr, NTU 10 51 32 10.9 5.5 11 18 45 8

DO, mg/l 14.8 21.1 16.8 8.7 10.9 9.4 11.0 9.3 11.5

TN, mg/l 1.7 1.99 0.43 1.47 1.41 0.37 1.85 1.9 0.37

TP, mg/l 0.14 0.23 0.09 0.08 0.14 0.05 0.14 0.08 0.06

TN/TP 12 8.7 4.8 18.8 10.1 7.4 13.2 13.8 6.2

CHL, μg/l 2.4 65.2 58.5 3.6 28.4 22.9 2.37 23.5 11.7

TSI(SD) 70 70 70 63.2 61.5 61.5 50 71.5 61.5

TSI(TP) 75.7 82.5 68.2 67.3 75.4 60.6 75.4 67.3 63.2

TSI(CHL) 39 71.6 69.4 43.2 63.4 61.3 53.8 61.6 54.7

TSI 61.6 74.7 69.2 57.9 66.7 61.1 60 66.8 60

**Table 5.** Average parameter values for Snagov Lake characterization.

**April July October April July October April July October**

suspended matter (Ts) (**Table 5**).

quality.

34 Water Stress in Plants

**Table 6.** Values of trophic state index (TSI) (Carlson's index), the state of lake, and characterization of it to input of lake Antena Tâncăbeşti, middle of Lake Complex Pacea, and output of lake Santu Floresti.
