Article Hydrological Variability Impact on in a Large Romanian Border Reservoir, Stanca–Costesti

Gabriela Elena Dumitran 1 , Liana Ioana Vuta 1,*, Bogdan Popa 1 and Florica Popa 2

1 Department of Hydraulic, Hydraulic Machines and Environmental Engineering, University Politehnica of Bucharest, 060042 Bucharest, Romania; [email protected] (G.E.D.); [email protected] (B.P.) 2 Department of Electronics, Telecommunications and Energy Engineering, University Valahia of Targoviste, 130004 Targoviste, Romania; fl[email protected] * Correspondence: [email protected]

 Received: 24 September 2020; Accepted: 30 October 2020; Published: 1 November 2020 

Abstract: Climate change represents one of the major challenges of our century with great potential to alter , and hence, find suitable solutions becomes a must. Stanca–Costesti reservoir is one of the most important in Romania and one of the most affected by the hydrologic variability. The studies regarding the trophic state of this reservoir are few, even if there are some environmental issues in its hydrological basin that could be further investigated. According to the National Administration “Apele Romane” (ANAR) yearly reports, the Stanca–Costesti reservoir is, from the trophic state point of view, an oligotrophic . The current research is based on chemical and some biological data collected over 10 years (ANAR) for the trophic state of the Stanca–Costesti reservoir, using the Carlson index. The research investigates the hydrological data and spans over 10 years that were classified into three categories, namely: wet year, normal year, and dry year and the influences generated by the contrasting weather (flow and temperature changes) on the trophic state of the lake. The research findings show that the trophic state of the lake is directly influenced by the hydrological variability, namely evolving to a hypertrophic status due to concentrations of nutrients. Moreover, over the years, according to ANAR data, the water quality in the reservoir alternated. Hence, at times, the quality of the water was poor, with possible negative influences on water usage. As a consequence, we proposed that the water quality be verified monthly, and this should be done by means of a more reliable method, such as a multiparameter index or multicriteria analysis.

Keywords: hydrological variability; lake eutrophication; Romanian water resources; Stanca–Costesti reservoir

1. Introduction Water is a natural renewable resource dramatically affected by activity; therefore, its usage must be carefully controlled. Since freshwater represents only 2.7% of the global sources of water, this natural resource around the world is limited. Therefore, its efficient use is one of the greatest challenges of contemporary society [1]. The scientific research confirms that global warming is a direct result of human activities, causing the change in global atmosphere composition, which is added to natural climate variability [2]. However, hydrological variability cannot be viewed solely as a result of climate change since it is influenced by so many more factors: heterogeneity of watershed properties, changes in the channel network geometry, river bed geometry alterations, and changes in land-use [3,4]. Climate change is reflected in the gradual change in statistical meteorological models valid for a certain region for a period of at least 30 years. Thus, from one year to another, the weather is contrasting [5]. Climate change leads to the increase in the average temperature with significant variations at regional level, diminishing the water resources used by human populations, reducing

Water 2020, 12, 3065; doi:10.3390/w12113065 www.mdpi.com/journal/water Water 2020, 12, x FOR PEER REVIEW 2 of 23 Water 2020, 12, 3065 2 of 23 variations at regional level, diminishing the water resources used by human populations, reducing the volume of ice caps and thus, raising the sea level, changing the hydrological cycle, increasing the the volume of ice caps and thus, raising the sea level, changing the hydrological cycle, increasing thefrequency frequency and and the theintensity intensity of ofextreme extreme weather weather events events (excessive (excessive heat, heat, droughts, droughts, floods), floods), etc. etc. [ [66].]. Regarding the air temperature at the European level, the Intergovernmental Panel on Climate Change Regarding the air temperature at the European level, the Intergovernmental Panel on Climate Change (IPCC) remarked an approximately 1 °C increase. The forecast for the next one hundred years is an (IPCC) remarked an approximately 1 ◦C increase. The forecast for the next one hundred years is an increase in air temperature up to 6.3 °C in Europe, 5.5 °C for Romania [7,8]. In addition, according to increase in air temperature up to 6.3 ◦C in Europe, 5.5 ◦C for Romania [7,8]. In addition, according to data published by the European Environment Agency [9], water resources for the people of south data published by the European Environment Agency [9], water resources for the people of south and and southeastern Europe will diminish in the coming years. Although Romania is situated in southeastern Europe will diminish in the coming years. Although Romania is situated in southeastern southeastern Europe, characterized by a temperate climate, and its climate change follows the global Europe, characterized by a temperate climate, and its climate change follows the global warming trend, warming trend, some particularities appear due to the Carpathian Mountains [10]. In terms of some particularities appear due to the Carpathian Mountains [10]. In terms of rainfall, the forecast rainfall, the forecast shows a decrease in precipitation quantities for the summer period with a shows a decrease in precipitation quantities for the summer period with a maximum in July (91%). maximum in July (91%). Furthermore, the annual maximum precipitation will be registered once in Furthermore, the annual maximum precipitation will be registered once in March and once around March and once around November [7,10]. November [7,10]. Climate change influences aquatic ecosystems through the action of two main factors: Climate change influences aquatic ecosystems through the action of two main factors: temperature temperature and precipitation (Figure 1). Thus, the impact of these factors on the surface water and precipitation (Figure1). Thus, the impact of these factors on the surface water quality is practically quality is practically manifested by drought or floods [11]. Moreover, the changes in water quality manifested by drought or floods [11]. Moreover, the changes in water quality are determined by water are determined by water temperature increase, which affects the biogeochemical processes operation temperature increase, which affects the biogeochemical processes operation rate [12]. Some of these rate [12]. Some of these effects are the change in flow volumes, which alter residence time and effects are the change in flow volumes, which alter residence time and dilution, increased atmospheric dilution, increased atmospheric CO2 concentration, which affects its dissolution rate in water, and CO2 concentration, which affects its dissolution rate in water, and finally, changed chemical inputs to finally, changed chemical inputs to the catchments, which disturb the streams’ water chemistry. In the catchments, which disturb the streams’ water chemistry. In the case of and reservoirs, all the case of lakes and reservoirs, all these processes lead to changes in the trophic state. these processes lead to changes in the trophic state.

Figure 1. Climatic change effects effects on the quality of lakes and reservoirs Plus and minus signs indicate increases and decreases,decreases, respectively,respectively, ofof aa phenomenon)phenomenon) [[12]12]..

EEutrophicationutrophication was recognized as a problem in European and North American lakes and reservoirsreservoirsin in the the mid-20th mid-20th century, century, being being one one of the of mostthe most serious serious problems problems that a ffthatect wateraffect qualitywater qualitynowadays nowadays [13,14]. [1 The3,14 eutrophication]. The eutrophication process process generally generally refers torefers the to loading the loading of nutrients of nutrients to lakes to lakesand reservoirs and reservoirs at rates at highratesenough high enough to increase to increase the potential the potential of biological of biological production, production, decrease decrease water volume,water volume and deplete, and deplete dissolved dissolved oxygen oxygen (DO) [15(DO]. Human) [15]. Human activities activities can accelerate can accelerate the rate the at rate which at whichnutrients nutrients enter ecosystemsenter ecosystems by the by release the release in the in watershed the watershed from from agricultural agricultural or urban or urban sources sources [16]. The[16]. mainThe main effects effects of eutrophication of eutrophication consist consist of an of increase an increase in , in turbidity, changes changes in color, in color, smell, smell and, andtaste taste of water, of water, dissolved dissolved oxygen depletion,oxygen depletion and a phytoplankton, and a phytoplankton biomass increase biomass [17 ].increase Furthermore, [17]. Furthermorestimulation of, stimulation the primary productionof the primary can generate production ecological can generate effects such ecological as biodiversity effects decrease,such as biodiversitychanges in species decrease, composition changes in and species dominance, composition and toxicity and dominance, effects [18 ,and19]. toxicity effects [18,19].

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The intensity of the eutrophication process is directly correlated with the hydrodynamics [20]. Generally, water quality in reservoirs tends to improve due to important outflow, which causes a mixing process with direct consequences on thickness and depth [21]. Thus, the trophic state of the lake is improved by reducing the appearance of anaerobic processes in [22–24]. Numerous studies have investigated the relationship between reservoir trophic status, water quality, nutrients load, hydrological variability, and so on [12,19,25]. In Romania, the National Administration “Apele Romane” (ANAR) is the national authority in charge of water management and the only one that classifies the water bodies from the water quality point of view. This study aims to verify if the ANAR classification of the Stanca–Costesti reservoir as an oligotrophic lake is still valid, when the Carlson index is used. The classification of water bodies made by ANAR is according to Regulation 161/2006, Table1[26].

Table 1. Values of eutrophication indicators according to Regulation 161/2006 [26].

Total Phosphorus Total Nitrogen Phytoplanktonic Biomass Chlorophyll a Trophic Status mg/L oligotrophic <0.01 <0.4 <3 <2.5 mesotrophic 0.001–0.03 0.4–0.65 3–5 2.5–8 eutrophic 0.03–0.1 0.65–1.5 5–10 8–25 hypertrophic >0.1 >1.5 >10 >25

The most sensitive issue related to this classification is that it is done using yearly data, and thus, it is difficult to assess water quality if some indices classify water as being in a certain trophic status, whereas others do in another one. The Carlson is the most well-known and still used, even if there are numerous other classification schemes available [27]. To assess the trophic state of the reservoir, based on available data (biochemical, inflow, and reservoir water level), the trophic state indices (α) values have been computed. Based on the monthly values of the reservoir water level and inflows for the period 2010 to 2017, data were classified into three groups, namely: wet year, normal year, and dry year and the influences generated by the hydrologic variability (flow and temperature changes) on the trophic state of the lake were investigated.

2. Materials and Methods Most of the Romanian hydrological network is collected by the Danube river and flows into the Black Sea, apart from some small rivers which flow directly into the sea. The most important water resources in Romania are the surface , which consist of inland rivers and the Danube river, bordering the southern part of the country, and both resources are vulnerable to climate variability. To optimize water supplies around the country, more than 1900 reservoirs were created. These ecosystems are quantitatively and qualitatively dependent on direct human influences, as well as on variations of the climate. Related to the quality of the large lakes and reservoirs in Romania, in terms of trophic state degree, the monitoring of 94 reservoirs regarding nutrient concentrations reveals that 61.7% have a good ecological status/potential, while 38.3% do not meet the required quality objective [28], mostly due to eutrophication. Romania’s target is to achieve a good status for all surface water and groundwater and good ecological potential for heavily modified water bodies until 2027. In Romania, there are still major issues regarding compliances with EU regulations, and several hotspots have been identified: lower Danube, the river basins of Arges–Vedea and Buzau–Ialomita, and the north of the Prut–Barlad basin (border with Moldova) [29]. Prut river basin is located in the northeastern part of the Danube basin, and it is bordered by three major basins, i.e., the Tisa to the northwest, the Siret to the west, and the Dnestr to the northeast, occupying the eastern part of Romania. The Stanca–Costesti reservoir lies on the middle course of Prut River and collects tributaries from Romania, Ukraine, and the Republic of Moldova. Water 2020, 12, 3065 4 of 23

This paper analyzes the effects of hydrologic variability on the Stanca–Costesti reservoir, which, in terms of water volume and covered area, is the second-largest reservoir in Romania and the first in the Republic of Moldova. It was created after the completion of a dam built on the Prut River during 1972–1975, and now it is a border crossing point between the two countries. Prut river has its source in the Ukrainian Carpathians and flows into the Danube, crossing the Moldavian Plateau and the Romanian Plain. It has 248 tributaries, and its hydrographic basin is elongated, with an average width of approximately 30 km. It is the second-longest river in Romania, having a length of 952.9 km in Romania and 711 km in the Republic of Moldova. The catchment area is relatively symmetrical and is 27,820 km2, and 10,990 km2 (40%) is on the Romanian territory [30]. The drainage network has a length of 11,000 km (33% corresponding to permanent streams while the rest of 67% are due to intermittent streams with temporary discharge), which leads to a density of the drainage network of 0.41 km/km2, higher than the average value for the Romanian territory (0.33 km/km2). In terms of land use, 21.4% of the area represents forests, 57% arable land, 1.19% water surface, 13.3% perennial crops [31]. The Stanca–Costesti reservoir has a watershed of approximately 12,000 km2 (located on the territory of Romania, the Republic of Moldova, and Ukraine), a volume of 1400 million m3, a maximum depth of 43 m, a length of 90 km, covering an area of 590 km2 and mean inflow of 81 m3/s. It has a complex use, allowing the flood attenuation, generation of hydroelectricity at the Stanca–Costesti hydropower plant, water supply for population and industry and irrigation. In addition, it is an integral part of the European ecological network—Natura 2000—in Romania starting in 2004 and in 2007 was declared as a special avifauna protection area. There are numerous studies presenting the hydrological variability/floods on the Prut River [32–35], but the studies regarding the trophic state of this reservoir are scarce. The Stanca–Costesti reservoir is a heavily modified water body, according to National Administration Romanian Waters (ANAR). Its physical characteristics have been substantially changed, and to achieve good surface water status, it is necessary to change its hydromorphological characteristics, which would have a significant adverse impact on the water environment [28]. The main pressures in the basin are related to insufficiently treated industrial and municipal waters, trespass of water protected zones, accumulation of heavy metals, illegal waste dumping, and inappropriate agricultural practices, which represent up to 65% of the diffuse sources of pollution/emissions in the Romanian part of the reservoir. According to the Danube River Basin District Management Plan, Stanca–Costesti fails the chemical status criterion. Its general physical and chemical conditions are poor, and it does not have a high status for hydromorphology [36]. In the reservoir area, the climate is tempered with large thermal variations, low rainfall, and long periods of drought. The average annual temperature varies between 7 and 9 ◦C, the minimum daily temperature being 3.2 C and the maximum between 38 and 40 C. The climatic element with an important − ◦ ◦ role in triggering erosion processes is precipitation, whose annual average varies between 500 and 550 mm/year. At the Botosani hydrometric station, a maximum annual value of 964 mm/year was registered in 1912. The distribution of precipitation is represented by approximately 70% rain and 30% snow, with an important quantitative increase in March–June, when 75–90% of the precipitation occurs. Throughout a single year, in the Stanca–Costesti reservoir area, the dominant wind blows from north and northwest direction, with a maximum speed of approximately15 m/s, and the mean speed ranging from 3 to 5 m/s. Numerous studies reveal that extreme hydrological phenomenon, e.g., drought, flood and flash-flood episodes are very common within the Prut river basin, even during the same year [32–35,37]. Likewise, changes in regional hydrological cycles can be foreseen: earlier snowmelt due to higher air temperature will lead to a different timing of peak streamflow, lower available surface water quantities during summer, increased rainfall variability, and an overall drop in rainfall [32,38]. Therefore, it must be mentioned that in the last 15 years, in the Stanca–Costesti area, three catastrophic floods have taken place in 2005, late July 2008, and in September 2010 [29]. Those events occurred on the Prut River, upstream of the Stanca–Costesti reservoir, generating floods in Romania as well as in the Republic of Moldova, with major damage and even loss of life. Water 2020, 12, 3065 5 of 23

InWater the 20 aftermath20, 12, x FOR PEER of the REVIEW same climatic changes, in 2009 and 2012, an increased level of temperature5 of 23 in the warm season was registered. The countryIn the aftermath is ranked of the in thesame EU climatic just after changes, Poland, in 2009 the and Slovak 2012, Republic, an increased and level the of Czech temperature Republic in in the warm season was registered. terms of floods risks. Annual floods in different parts of the country between 2002–2013 were estimated The country is ranked in the EU just after Poland, the Slovak Republic, and the Czech Republic to have incurred economic losses of more than 6.3 billion euros (the two catastrophic floods in 2005 in terms of floods risks. Annual floods in different parts of the country between 2002–2013 were and 2010estimated caused to have more incurred than 100 economic deaths losses and of total more economic than 6.3 billion losses euros of 2.4 (the billion two catastrophic euros). The floods average annualin cost2005 ofand floods 2010 wascaused estimated more than at 100 150 deaths million and euros total for economic the 2000–2015 losses of period 2.4 billion [29]. euros). The Theaverage experimental annual cost dataof floods used was in estimated this research at 150 are million the integrated euros for the samples 2000–2015 collected period [ between29]. 2008 and 2017The based experimental on four characteristic data used in thi pointss research of the are reservoir: the integrated the dam samples (A), collected the intake between (B), the 2008 middle (C), andand the2017 tail based (D) on (Figure four 2characteristic). The frequency points of of measurementthe reservoir: the of dam physicochemical (A), the intake and (B), biologicalthe middle data was according(C), and the to tail European (D) (Figure norms 2). The and frequency was made of measurement by ANAR [ 39of ].physicochemical To study the hydrochemicaland biological data regime, the waterwas according samples to are European analyzed norms during and the was spring made by and ANAR summer [39]. floodsTo study and the shallow hydrochemical waters regime, in summer the water samples are analyzed during the spring and summer floods and shallow waters in summer and winter. In the upper part of the reservoir, the water samples are taken from the surface (0.2–0.5 m) and winter. In the upper part of the reservoir, the water samples are taken from the surface (0.2–0.5 and inm) the and dam in the area dam at area three at points:three points: 0.2 m 0.2 and m and 0.6 m0.6 depthm depth and and from from the the bottom. bottom.

FigureFigure 2. Map 2. Map of of the the Stanca–Costesti Stanca–Costesti reservoir and and the the measurement measurement sections sections..

The evaluationThe evaluation of theof the trophic trophic state state of of the the reservoirsreservoirs was was made made based based on onthe thefollowing following elements: elements: total phosphorus,total phosphorus, total total mineral mineral nitrogen, nitrogen, chlorophyll chlorophyll a, and phytoplankton phytoplankton biomass biomass [28] [.28 ]. In thisIn study,this stud they, the actual actual trophic trophic state state of of the the Stanca–CostestiStanca–Costesti reservoi reservoirr was was evaluated evaluated in relation in relation to the recent severe climatic events in the geographical area of the reservoir, based on experimental to the recent severe climatic events in the geographical area of the reservoir, based on experimental data. In the case of the Stanca–Costesti reservoir, it was supposed that the trophic state is given by data. In the case of the Stanca–Costesti reservoir, it was supposed that the trophic state is given by the the biological response to forcing factors, thus using the trophic state indices (TSI). biologicalThe response ecological to forcing status of factors, the lakes thus and using reservoirs the trophic is generally stateindices assessed (TSI). according to Carlson’s Theindex. ecological The quantities status of nitrogen, of the lakes phosphorus, and reservoirs and other is biologically generally useful assessed nutrients according are the toprimary Carlson’s index.determinants The quantities of aquatic of nitrogen, systems phosphorus,’ TSI. Carlson and’s index other is one biologically of the most useful used nutrientstrophic indices are the, and primary it determinantsuses the algal of aquatic biomass systems’ as an objective TSI. Carlson’s classifier of index lakes isand one reservoirs’ of the most trophic used status trophic [27]. indices, and it uses the algalThe determination biomass as an of objective TSI is based classifier on the ofalgal lakes bio andmass, reservoirs’ nutrients concentrations trophic status (phosphorus [27]. Theand nitrogen) determination, and Secchi of TSI transparency is based on. TSI the provide algal biomass, a way to nutrientsrate and compare concentrations lakes according (phosphorus to and nitrogen),their level of and biological Secchi activity transparency. on a range TSI of provide “0” (corresponding a way to rate to an and ultraoligotrophic compare lakes lake) according to 100 to (corresponding to a hypereutrophic lake). A trophic state below 60 indicates lakes with good water their level of biological activity on a range of “0” (corresponding to an ultraoligotrophic lake) to 100 quality (oligotrophic through mesotrophic), and values above 60 but below 70 correspond to a highly (correspondingproductive lake to a with hypereutrophic fair water quality lake). (mesotrophic A trophic statethrough below eutroph 60 indicatesic). TSI greater lakes than with 70 goodis for a water qualityhypertrophic (oligotrophic lake through with a poor mesotrophic), water quality and [39]. values above 60 but below 70 correspond to a highly productive lake with fair water quality (mesotrophic through eutrophic). TSI greater than 70 is for a hypertrophic lake with a poor water quality [39]. Water 2020, 12, 3065 6 of 23

Water 2020, 12, x FOR PEER REVIEW 6 of 23 In this study, TSI values were determined by using the following equations: In this study, TSI values were determined by using the following equations: TSIChl = 16.8 + [14.4 ln(Chl)], (1) TSIChl = 16.8 + [14.4·‧ln(Chl)], (1)

TSITN1 = 56 + [19.8 ln(TN)], (2) TSITN1 = 56 + [19.8·‧ln(TN)], (2) TSI = 10 [5.96 + 2.15 ln(TN + 0.001)], (3) TN2 · TSITN2 = 10 [5.96 + 2.15‧ln(TN + 0.001)], (3) TSI = [18.6 ln(TP 1000) 18.4], (4) TP1 · · − TSI TSI=TP110 = [2.36[18.6‧ln(ln(TP‧1000)1000) − 18.4],2.38], (4) (5) TP2 · · − TSITSITotalTP2 == 10( TSI[2.36Chl‧ln(+TPTSI‧1000)NUTRI −) /2.38],2, (5) (6) where: TSITotal = (TSIChl + TSINUTRI)/2, (6) TN TP TSI TSI if /whe>re:30 then NUTRI = TP2, if TN/TP < 10 then TSINUTRI = TSITN2 and if TN/TP > 30 then TSINUTRI = TSITP2, if 10 < TN/TP < 30 then TSINUTRI = (TSITP1+ TSITN1)/2, if TN/TP < 10 then TSINUTRI = TSITN2 and with TN,if 10 < TP, TN and/TP < Chl 30 then measured TSINUTRI the = (TSI valuesTP1+ TSI ofTN1 total)/2, nitrogen, total phosphorus, and chlorophyll a in the reservoir. with TN, TP, and Chl measured the values of total nitrogen, total phosphorus, and chlorophyll a in 3. Resultsthe reservoir.

According3. Results to the hydrological data, the flow with 1% insurance for the Stanca–Costesti reservoir 3 3 is 2850 mAccording/s, and the to the mean hydrological inflow for data, the the period flow with 1988–2018 1% insurance was79 for m the/ s,Stanca with–Costesti the highest reservoir average 3 3 monthlyis 2850 inflow m3/s in, and April, the mean 133.6 minflow/s, and for the period lowest 198 one8– in201 January,8 was 79 40.2m3/s, m with/s. Forthe highest the studied average period, 2008–2017,monthly the inflow highest in April average, 133.6 monthly m3/s, and inflow the lowest was one in July,in January, 155.2 m40.23/s, m and3/s. For the the lowest studied in period, November, 38.6 m20083/s.–2017, This shiftthe highest regarding average the monthly highest inflow value was between in July, April 155.2 and m3/s, July and wasthe lowest determined in November, by the two floods38.6 registered m3/s. This in shift July, regarding in the years the highest 2008 and value 2010. between April and July was determined by the two Figurefloods 3registered shows the in July, hydrograph in the years of the2008 average and 2010. monthly flows for the period 2008–2017. The time is expressedFigure in months, 3 shows the where hydrogr 1st monthaph of the is Januaryaverage monthly 2008, while flows month for the 120period is December 2008–2017. 2017.The time is expressed in months, where 1st month is January 2008, while month 120 is December 2017.

FigureFigure 3. Hydrograph 3. Hydrograph of the of average the average monthly monthly flows flows of the of Prutthe Prut River, River, upstream upstream from from the Stanca–Costestithe Stanca– Reservoir,Costesti for Reservoir the period, for 2008–2017. the period 2008–2017.

Figure 4 illustrates, on the same graph, the average monthly flows for each year of the period, and it can be observed that, normally, the maximum inflow corresponded to April. Water 2020,, 12,, xx FORFOR PEERPEER REVIEWREVIEW 7 of 23

Figure 4. illustrates, on the same graph, the average monthly flows for each year of the period, Water Figure2020, 12, 4. 3065 illustrates, on the same graph, the average monthly flows for each year of the period7 of 23, and it can be observed that, normally, the maximum inflow corresponded to April.

Figure 4. AAverageverage monthly monthly flow flowss of of the the Prut Prut river, river, upstream from the Stanca Stanca–Costesti–Costesti Reservoir Reservoir,,, superposed, for the period 2008-2017.2008-2017.. According to the hydrographs and the variation of the water levels in the reservoir, collected According to the hydrographs and the variation of the water levels in the reservoir, collected between 2008–2017,2008–2017, the time-lapsetime-lapse of the 10 years targeted were classifiedclassified intointo three categories based between 2008–2017, the time-lapse of the 10 years targeted were classified into three categories3 based on thethe abundanceabundance of of precipitation: precipitation: wet wet years, years, with with average average annual annual flows flows between between 40 and 40 59and m 59/s, m 20083/s, on the abundance of precipitation: wet years, with average annual flows between 40 and 359 m /s, and2008 2010,and 2010, years years with normalwith normal precipitation precipitation with averagewith average annual annual flows flows between between 60 and 60 89 and m 89/s, m 20093/s, 2008 and 2010, years with normal precipitation with average annual3 flows between 60 and 89 m /s, and 2013, and dry years with average annual flows higher than 90 m /s: 2011,3 2012, 2014 to 2017. 2009 and 2013, and dry years with average annual flows higher than 90 m3/s: 2011, 2012, 2014 to 2017. However, as compared to the values recorded between 1988–2017, in the last decade, there were However, as compared to the values recorded between 1988–2017, in the last decade,, there were considerable deviations from these values, so that for July there was an increase in the multiannual considerable deviations from these values, so that for July there was an increase in the multiannual average monthly flow values of about 68%, while for September, a decrease of 46% can be noted. In average monthly flow values of about 68%, while for September,, a decrease of 46% can be noted.. InIn fact, significant decreases in these values of inflows were observed for the whole period of summer’s fact, significant decreases in these values of inflows were observed for the whole period of summer’s end and autumn, whereas in August, there were decreases of approximately 36%, in September of 46%, end and autumn, whereas in August,, there were decreases of approximately 36%, in September of and in November of 30%. Figure5 shows the variation of water levels in the reservoir for the study 46%,, and in November of 30%. Figure 5 shows the variation of water levels in the reservoir for the period; a good correlation with the hydrograph can be observed. study period; a good correlation with the hydrograph can be observed.

Figure 5. Monthly variation of water levels in the Stanca–CostestiStanca–Costesti r reservoir,eservoir,, superimposed,supersuperimimposed, for the period 2008–2017.2008–2017..

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Figure 66 showsshows the evolution evolution of of the the water water level level,, in inflows,flows, and and live live storage storage in inthe the reservoir reservoir for forthe periodthe period 2010 2010–2017.–2017. In this In representati this representation,on, the flows the flows and levels and levels are represented are represented as a function as a function of time, of intime, which in which January January 2010 2010is marked is marked with with 1 and 1 and December December 2017 2017 with with number number 96. 96. There There was was a a good connection between inflowsinflows and water level level,, with a correlation coefficient coefficient of 0.6, justified justified by the ma majorjor influenceinfluence of lake entrance flowsflows onon thethe dynamicsdynamics ofof thethe lake.lake.

Figure 6.6. AverageAverage monthly monthly flows flows of theof the Prut Prut River River upstream upstream from thefrom Stanca–Costesti the Stanca–Costesti reservoir, reservoir, average averagemonthly monthly levels of levels the reservoir, of the reservoir and live, storageand live (2010–2017). storage (2010–2017).

The physical physical–chemical–chemical indicators analyzed so as to estimate the degree of eutrophication in the StancaStanca–Costesti–Costesti reservoirreservoir are are temperature, temperature, dissolved dissolved oxygen, oxygen, nutrients—total nutrients nitrogen—total and nitrogen phosphorus, and phosphorusand chlorophyll, anda .chlorophyll The values a of. The these values parameters of these were parameters measured were by measured ANAR. by ANAR. Changes inin thethe waterwater temperature temperature regime regime can can fundamentally fundamentally alter alter water water quality. quality. The The duration duration and anddepth depth of temperature of temperature stratification stratification can also can a alsoffect affect the time the and time volume and volume of water of thatwater is isolatedthat is isolated during duringthe summer, the summer, influencing influencing anoxia and anoxia ammonia and production ammonia and production accumulation and in accumulation the hypolimnion. in the hypolimnion.Values of the water temperatures recorded for the study period ranged between 0.8 ◦C (January 2008Values and February of the water 2012) temperatures and 29 ◦C (July recorded 2012) [for10], the which study allowed period ranged the consideration between 0.8 that °C from(January the 2008thermal and point February of view, 2012) the and Stanca–Costesti 29 °C (July 2012) reservoir [10], fluctuateswhich allow withined the the consideration normal variation that limitsfrom t forhe thermaldimictic point lake ecosystems of view, the in Stanca the temperate–Costesti areasreservoir (Figure fluctuate7). s within the normal variation limits for dimicticThe lake evolution ecosystems of the in dissolved the temperate oxygen areas concertation (Figure 7). in the Stanca–Costesti reservoir has shown greatThe variations evolution correlated of the dissolved mainly withoxygen water concertation temperature in the evolution Stanca–Costesti (Figure7 reservoir). Thus, thehas valuesshown greatrecorded variations ranged correlated within a minimum mainly with value water in August temperature 2015, 2.8 evolution mg/L, and (Figure a maximum 7). Thus, of 12.7 the mg values/L in recordedMarch 2008. ranged Moreover, within thea minimum evolution value of the in phytoplanktonAugust 2015, 2. density8 mg/L, inand the a maximum Stanca–Costesti of 12.7 reservoir mg/L in Marchrecorded 2008. a maximum Moreover value, the evolution of 1.77 mil of ex. the/L inphytoplankton September 2009 density in the in tail the of Stanca the reservoir–Costesti section. reservoir recorded a maximum value of 1.77 mil ex./L in September 2009 in the tail of the reservoir section.

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(a)

(b)

Figure 7. Cont.

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(c)

(d)

FigureFigure 7. TimeTime evolution evolution of of measured measured values values of of water water temperature temperature,, di dissolvedssolved oxygen, and and phytoplanktonphytoplankton density density:: ( (aa)) Dam Dam section section—A;—A; ( (bb)) Intake Intake section section—B;—B; ( (cc)) Middle Middle reservoir reservoir section section—C;—C; ((dd)) Tail Tail reservoir section—D.section—D.

ForFor the study period,period, thethe totaltotal phosphorus phosphorus concentration concentration recorded recorded values values between between 0.009 0.009 mg mg/L/L for forthe the dam dam section section in Octoberin October 2008 2008 and and 0.246 0.246 for for the the middle middle reservoir reservoir section section in in October October 2015 2015 (Figure (Figure7). 7)This. This means means that that most most of them of them were were within within the permissible the permissible limit limit (0.1 mg (0.1/L) mg/L) for good for ecologicalgood ecological status. status.The quantities of nitrogen, phosphorus, and chlorophyll a are the primary determinants of aquaticThe systemsquantities trophic of nitrogen, state index phosphorus, (TSI). The and abundance chlorophyll of nitrogen a are the in the primary reservoir determinants is justified byof aquaticthe regeneration systems trophic of this compoundstate index in(TSI). water The mass abundance by decomposing of nitrogen organic in the matter reservoir or the is contributionjustified by theof anthropogenicregeneration of sources. this compound As for in nitrogen, water mass it usually by decomposing decreases duringorganic summermatter or due the contribution to biological ofconsumption anthropogenic and sources. sedimentation. As for However,nitrogen, nitrogenit usually concentrations decreases during were summer largely consistent due to biological with the consumption and sedimentation. However, nitrogen concentrations were largely consistent with the average monthly flow of the Prut river. Thus, the greatest values were recorded at the intake and

Water 2020, 12, 3065 11 of 23 Water 2020, 12, x FOR PEER REVIEW 11 of 23 lake’saverage tail monthly measurement flow of stations, the Prut where, river. Thus, at the the end greatest of summer values inwere 2016, recorded the value at was the 2.9 intake mg/L and (Figure lake’s 8tail). measurement stations, where, at the end of summer in 2016, the value was 2.9 mg/L (Figure8).

(a)

(b)

Figure 8. Cont.

Water 2020, 12, 3065 12 of 23 Water 2020, 12, x FOR PEER REVIEW 12 of 23

(c)

(d)

FigureFigure 8.8. TimeTime evolutionevolution ofof biochemicalbiochemical data:data: (a)) DamDam section—A;section—A; ((b)) IntakeIntake section—B;section—B; ((cc)) MiddleMiddle reservoirreservoir section—C;section—C; ((dd)) TailTail reservoirreservoir section—D. section—D.

ForFor the intake measurement section, chlorophyll a data were not available over the study period. ForFor thethe restrest ofof thethe measurementmeasurement sections,sections, thethe contentcontent ofof chlorophyllchlorophyll aa determineddetermined inin thethe reservoirreservoir variedvaried betweenbetween 00 andand 1515 µμgg/L/L (Figure(Figure8 ).8). The The multiannual multiannual average average monthly monthly valuesvalues ofof chlorophyll chlorophyll aa concentrationconcentration recordedrecorded a a substantial substantia increasel increase in in 2010. 2010. Thus, Thus, for for 2010 2010 the the greatest greatest value value was was recorded recorded in thein the June–August June–August period period due due to anto an extensive extensive algal algal bloom. bloom. TheThe TSITSI valuesvalues forfor thethe nutrientsnutrients andand chlorophyllchlorophyll aa obtainedobtained forfor thethe Stanca–CostestiStanca–Costesti reservoirreservoir (Figure(Figure9 9)) indicateindicate thatthat thethe lake is is in in large large proportion proportion in in mesotrophic mesotrophic status. status. Thus, Thus, the the resulting resulting TSI values for the nutrient concentration shows that the lake was placed in the eutrophic category

Water 2020, 12, 3065 13 of 23

Water 2020, 12, x FOR PEER REVIEW 13 of 23 TSI values for the nutrient concentration shows that the lake was placed in the eutrophic category throughoutthroughout the the period period 2008–2017. 2008–2017. However, However, looking looking at at the the chlorophyll chlorophylla variation,a variation, the the lake lake fitted fitted into into thethe oligotrophic oligotrophic stage stage during during 2008 2008 and and 2017. 2017.

(a)

(b) Figure 9. Cont.

Water 2020, 12, 3065 14 of 23 Water 2020, 12, x FOR PEER REVIEW 14 of 23

(c)

(d)

FigureFigure 9. 9.The The computed computed trophic trophic state state indices indices (TSI) (TSI) component component between between 2008 2008 and and 2017: 2017: ( a()a Dam) Dam section—A;section—A; (b ()b Intake) Intake section—B; section—B; (c )(c Middle) Middle reservoir reservoir section—C; section—C; (d ()d Tail) Tail reservoir reservoir section—D. section—D.

ToTo compute compute the the total total TSI, theTSI, limiting the limiting elements elemen in thets lake in andthe thelake available and the data available were considered. data were Thus,considered. for the Thus, intake for section, the intake when section, calculating when thecalc totalulating TSI, the the total values TSI, ofthe chlorophyll values of chlorophylla were not a considered.were not considered. As previously As mentioned, previously for mentioned, the four measurement for the four sections, measurement there were sections, months there with were no recordingsmonths with available no recordings for the eutrophication available for the indicators, eutrophi socation that inindicators, Figure 10 so, there that arein Figure discontinuities 10, there inare thediscontinuities computed values. in the computed values.

Water 2020, 12, x FOR PEER REVIEW 15 of 23 Water 2020, 12, 3065 15 of 23 Water 2020, 12, x FOR PEER REVIEW 15 of 23

Figure 10. The computed total TSI for the study period, 2008–2017. Figure 10. The computed total TSI for the study period, 2008–2017. Figure 10. The computed total TSI for the study period, 2008–2017. To allow a more accurate analysis of the total TSI values, these values were represented separatelyTo allow for a moreeach accuratemeasurement analysis section of the (Figure total TSI 11), values, which these allowed values a were better represented classification separately of the To allow a more accurate analysis of the total TSI values, these values were represented forreservoir each measurement from the trophic section state (Figure point 11of), view. which allowed a better classification of the reservoir from theseparately trophic state for pointeach measurement of view. section (Figure 11), which allowed a better classification of the reservoir from the trophic state point of view.

(a)

Figure 11.(a)Cont .

Water 2020, 12, 3065 16 of 23 Water 2020, 12, x FOR PEER REVIEW 16 of 23

(b)

(c)

(d)

FigureFigure 11. 11.The The computed computed totaltotal TSITSI forfor the the study study period, period, 2008–2017:2008–2017: ((aa)) DamDam section—A;section—A; ((bb)) IntakeIntake section—B;section—B; ( c()c) Middle Middle reservoir reservoir section—C; section—C; ( d(d)) Tail Tail reservoir reservoir section—D. section—D.

WaterWater 20202020,, 1122,, x 3065 FOR PEER REVIEW 1717 of of 23 23

For an easier comparison and correlation of the reservoir’s levels and total TSI values, Figure 12 For an easier comparison and correlation of the reservoir’s levels and total TSI values, Figure 12 presents the TSI values for all four measurement sections. The values are represented according to presents the TSI values for all four measurement sections. The values are represented according to the number of the day, 1 January 2010 being day number 1, 31 December 2010 is the day 365, and 31 the number of the day, 1 January 2010 being day number 1, 31 December 2010 is the day 365, and 31 December 2017 is the day number 3612, considering the leap years. December 2017 is the day number 3612, considering the leap years.

FigureFigure 12. 12. ComputedComputed TSI and TSI water and level water for level the Stanca for the–Costesti Stanca–Costesti reservoir, for reservoir, the study forperiod, the 2008 study– 2017period,. 2008–2017.

4.4. Discussion Discussion WithWith regard regard to to the the studied period, period, 2008 2008–2017,–2017, in in the the Stanca Stanca–Costesti–Costesti reservoir, reservoir, t thehe water water temperaturetemperature varied between 0.50.5◦ °CC andand 29 29◦ C,°C, having having the the biggest biggest gap gap for for the the measurement measurement section section (C), (C),middle middle of the of reservoir.the reservoir The. concentrationThe concentration of dissolved of dissolved oxygen oxygen varied varied between between 2.8 mg /L2.8 in mg/L summer in summer2015 and 2015 15.5 and mg/ L15.5 in wintermg/L in 2010. winter Regarding 2010. Regarding the time the evolution time evolution of nutrient of content,nutrient itcontent, was observed it was observedthat the totalthat the mineral total mineral nitrogen nitrogen concentration concentration varied varie betweend between 0.25 and 0.25 2.92 and mg 2.92/L, mg/ whileL, while the total the totalphosphorus phosphorus concentration concentration varied varie fromd 0.0035 from to 0.0 0.025035 mgto /L.0.0 Moreover,25 mg/L. theMoreover chlorophyll, the achlorophyllconcentration a concentrationvaried between varie 0 andd between 15 mg/L during0 and summer,15 mg/L havingduring maximum summer, valueshaving at maximum the measurement values sectionat the measurementD, tail of the reservoir.section D, A tail drastic of the reduction reservoir. in A dissolved drastic reduction oxygen concentrationin dissolved oxygen was observed concentration during wasJune–August observed (betweenduring June 2.8– mgAugust/L at the(between intake 2.8 section mg/L and at 4.1the mgintake/L at section the tail and lake 4.1 section). mg/L at the tail lake section).The eutrophication development was analyzed for the Stanca–Costesti reservoir: the evolution of nutrientThe eutrophica concentrationtion development and biomass was in relation analyzed to f climateor the Stanca change–Costesti (temperature reservoir and: the precipitation) evolution ofalready nutrient recorded concentration in this and region. biomass This in may relation be given, to climate on the change one hand, (temperature by the low and di ffprecipitation)usion of this alreadyelement recorded in water and,in this on region. the other This hand, may by be higher given, consumption on the one inhand, the decayby the processes low diffusion at the bottomof this elementof the lake. in water It results and, thaton the the other temperature hand, by increase higher consumption as an effect of in climate the decay changes processes may fundamentally at the bottom ofalter the thelake. habitat It results of the that aquatic the temperature organisms increase and largely as an depends effect of on climate internal changes heat transfermay fundamentally by turbulent alterand convectivethe habitat processesof the aquati [40c,41 organisms]. and largely depends on internal heat transfer by turbulent and convectiveAs for the processes Stanca–Costesti [40,41] dam,. the maximum flow that can be discharged during floods is about 3 3 3 2834As m f/ors. the From Stanca that,– 1560Costesti m / sd canam, bethe discharged maximum throughflow that the can surface be discharged spillway, during 1144 m floods/s through is about the 3 2834bottom m3/s. outlet, From and that, 130 1560 m / sm through3/s can be the discharged turbines of through the hydropower the surface plant. spillway, During 1144 the m two3/s floodsthrough in thethe bottom summers outlet of 2008, and and 130 2010,m3/s thethrough discharged the turbines flow from of the the hydropower Stanca–Costesti plant reservoir. During the using two the floods three 3 indischarge the summers ways simultaneouslyof 2008 and 2010, was the up discharged to 2310 m /flows. Because from the of the Stanca two– catastrophicCostesti reservoir floods, using the water the threequality disc worsened.harge ways This simultaneously is due to the increase was up into the2310 decomposition m3/s. Because processof the two and catastrophic the organic floods, matter andthe water quality worsened. This is due to the increase in the decomposition process and the organic

Water 2020, 12, 3065 18 of 23 phosphorus concentrations because of the lake surface layer extension, fueling phytoplankton growth and leading to algal blooms. It was expected that with the important discharge of water, especially by the bottom outlet, the water quality would improve as a direct result of the lake destratification. However, this did not happen, and after the transit of the flood, the dissolved oxygen concentration in the lake decreased to 5.5–7 mg/L, while the phosphorus concentration at the dam section increased up to 0.023 mg/L. Hydrological variability tends to generate stronger lakes/reservoirs stratification [42]. This may alter vertical mixing in low-altitude lakes. Lake mixing, however, is especially important to provide oxygen to the deep water and to nutrients from the hypolimnion to the [43], preventing nutrient accumulation in the deep water. Furthermore, regular and frequent vertical mixing prevents the build-up of anoxic, reducing conditions in the hypolimnion, which could, in turn, modify the interactions between water and sediments [42]. Stanca–Costesti is a low-altitude reservoir with multi-annual regulation so that the residence time of water is high. Water stagnation in reservoirs favors the release of nutrients from the sediment layer. Thus, the increase in nutrient loading causes a negative impact on the trophic status of the lake. In the flood periods of 2008 and 2010, the transit of a significant water volume through the bottom outlet of the dam was approved, thereby reducing nutrient loading. This did not happen in 2009, and in March, a substantial increase in nutrient concentration in the lake was observed, especially at the tail (D) and middle (C) reservoir measurement sections. The largest values of nutrient concentration in the lake may be explained by the accumulation of soluble phosphorus and ammonium by the release of nutrients in the hypolimnion layer. These processes depend on thermocline depth, hypolimnetic temperature, microbial decomposition, and oxygen concentration [44,45]. In the case of the dam section (A), the situation was better as the outflow of the hydroelectric power plant allowed a local mixing of the water mass. In the following period, the nutrients were strongly assimilated by plants in the epilimnion layer. According to measured data, it is worth mentioning that during floods, an accentuated increase in total phosphorus appears. Those high values frequently lead to TSI total values greater than 60, which implies a surface water body in an eutrophic state. During floods, the runoff on the surface of the catchment is emphasized, and, as a result, supplementary quantities of phosphorus from agricultural activities are driven. On the other hand, a large amount of water enters the reservoir and intensifies the vertical mixing of water, moving phosphorous from the bottom of the reservoir (hypolimnion) to the epilimnion. Immediately after the flood, an increase in chlorophyll a concentration is noticed, directly related to the higher quantity of nutrients available in the reservoir [44,45]. Pearson’s correlation analysis of water quality parameters was conducted to determine how the eutrophication indicators were correlated with the TSI in the reservoir [46]. Pearson’s correlation analysis revealed a strong positive and negative relationship between the water quality indicators and total TSI of the Stanca–Costesti reservoir (Table2). The correlation between total TSI and TN was positive moderate, with values of Pearson coefficients r = 0.09 0.56 with the strongest correlation ÷ for the tail reservoir section (r = 0.56). The correlation between total TSI and TP was positive and negative weak/moderate with values in the domain (r = 0.09 0.69), with the strongest correlation − ÷ for the middle reservoir section (r = 0.69). For correlation between the total TSI and Chl, it was not possible to determine r for the intake section due to lack of data, and for the other measuring sections, it resulted in a moderate correlation, negative for the middle reservoir section and positive for the dam and tail reservoir sections. Therefore, we obtained a correlation coefficient between (r = 0.45 0.56) ÷ with maximum values for the dam and middle sections. Water 2020, 12, 3065 19 of 23

Table 2. Pearson’s correlation coefficients between total trophic state indices (TSI) and total nitrogen (TN), total phosphorous (TP), and Chlorophyll a (Chl).

TN TP Chl Measurement Section r Values r Values r Values Intake 0.32 0.09 - − Dam 0.09 0.51 0.56 Middle 0.31 0.69 0.45 − Tail 0.56 0.02 0.54

Throughout the entire study period, 2008–2017, Pearson’s correlation coefficients between Chl and TN and TP were weak, around 0.3. For the dam and middle of the reservoir sections, Chl was correlated with TN, while, for the tail of the reservoir section, it was correlated with TP. This shift in the influencing factor, TN or TP, is probably related to different species of existing in the measurement sections, the tail of the reservoir being highly influenced by inflows. When considering the different hydrological type of years, Pearson’s correlation coefficient varied from 0.07 to 0.95, as can be seen in Table3. Globally, Pearson’s coe fficients show a strong correlation during wet years and a weak correlation during dry years. Regarding normal years, the correlation coefficient was strong for the dam and middle reservoir section; however, for the tail of the reservoir section, it was not correlated at all.

Table 3. Pearson’s correlation coefficients between Chl and TN and TP.

Dam Middle of the Reservoir Tail of the Reservoir Hydrologic Year TN TP TN TP TN TP Wet 0.6 0.65 0.9 0.67 0.95 0.35 Normal 0.8 0.63 0.62 0.23 0.07 0.08 Dry 0.36 0.32 0.43 0.32 0.32 0.50

As shown in Figures9–11, the total TSI values obtained for the four measurement sections have quite different values. Thus, for the dam, middle, and tail of the reservoir sections, the reservoir can be framed for almost the entire study period in good status (oligotrophic through mid-eutrophic). For the intake section, most of the data frame the reservoir in the poor status (eutrophic through hypertrophic). Table4 presents the values of correlation coe fficients between total TSI and reservoir water level. It must be specified that for the years 2010 and 2011, experimental data for the dam section were not available. Total TSI values were well correlated with the reservoir water level, the best results being obtained for the dam section. In addition, if we examine the incidence of good correlations for the three types of hydrological years, the best correlations were the values for the dry years 2015 and 2017, and the weakest correlation was for the year 2013, which is considered normal from a hydrological point of view. It must be specified that for the years 2010 and 2011, available experimental data from the dam section were not available.

Table 4. Values of correlation coefficients between reservoir water level and total TSI.

Year Type/Section Dam Intake Middle Tail 2010 Wet - 0.14 0.77 0.92 2011 Dry - 0.34 0.61 0.66 2012 Dry 0.93 0.50 0.28 0.74 2013 Normal 0.99 0.29 0.16 0.40 2014 Dry 0.89 0.08 0.69 0.32 2015 Dry 0.67 0.40 0.86 0.92 2016 Dry 0.72 0.15 0.99 0.10 2017 Dry 0.74 0.36 0.84 0.66 Water 2020, 12, 3065 20 of 23

Apart from the contributions, when considering the lack of data, the limitations of the current study are obvious. However, for assessing the trophic state of any surface water body (including reservoirs), multiparameter indexes, or multicriteria analysis is clearly a better solution. Our study considered only the hydrological variability (e.g., the inflows and water level) and some water quality indicators data. A complete study of eutrophication of surface water bodies requires systematic data to assess all the transformations taking place in the water properly: monthly data related to water quality (physicochemical indicators—temperature, DO, TN, TP, etc. and biological indicators—algal biomass, characteristics, and density, etc.) and catchment characteristics, land use, pollution sources, water uses, hydrodynamic conditions, evaporation, precipitation, atmospheric humidity, etc.

5. Conclusions The current study aimed to compare the present method used for the characterization of surface water bodies based on Regulation 161/2006, as employed by ANAR, with a method based on the Carlson index. We analyzed rainy periods, with floods on the Prut river, and dry periods, with droughts. Thus, it has been noted how an increased hydrologic variability (as one of the climate change consequences), in terms of floods and droughts, influenced water quality in the Stanca–Costesti reservoir. Due to the prolonged form and geomorphological structure of this catchment, the Prut River is prone to flooding. According to the results of our study, for the period 2008–2017, the general classification of the Stanca–Costesti reservoir is in the mesotrophic–eutrophic stage. Hence, sometimes, the Stanca–Costesti reservoir experiences changes in the water quality, mainly during the summer periods, and is in the eutrophic state for short periods, with poor water quality and possible negative influences for water usage. The method presented in this study can be applied to any surface water body and provide a better indication of the trophic state than the currently used method in Romania. It is relatively simple to apply based on measurements made by ANAR and can help to adequately manage the use of water considering its trophic status at different times of the year. Thus, it would be beneficial to consider the possibility of conducting systematic measurements and classifying surface water bodies by using a multiparameter index, such as the Carlson index, or multicriteria analysis, as a more reliable method. In terms of reservoir management, several actions, universally valid, can be implemented to improve water quality in the Stanca–Costesti reservoir: a reduction in nutrient loading entering the reservoir; regular use of the bottom outlet to induce water mixing in the reservoir; active monitoring of water quality and environmental factors; a web platform containing all the monitoring data, used not only by the national authorities and other government agencies involved in water management, agricultural activities, energy sector, and so on but also by researchers and the local community; social awareness actions, to educate citizens and to involve them in the protection of water quality, etc. Further studies containing detailed temporal analysis on TSI and DO, including correlations between the reservoir water quality and catchment characteristics, land use, etc. must be developed to properly assess the trophic state and the water quality of the Stanca–Costesti reservoir.

Author Contributions: G.E.D. and L.I.V.: data processing, conceptualization, writing, editing, and review; B.P. and F.P.: methodology, editing, and review. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Acknowledgments: The authors are grateful for data and support provided by National Administration Romanian Waters. Conflicts of Interest: The authors declare that they have no conflicts of interest. Water 2020, 12, 3065 21 of 23

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