water

Article Exploring the Effects of Hydraulic Connectivity Scenarios on the Spatial-Temporal Salinity Changes in Bosten Lake through a Model

Ying Liu 1,2,3,4 and Anming Bao 1,2,3,4,* 1 State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; [email protected] 2 Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China 3 Key Laboratory of GIS & RS Application Xinjiang Uygur Autonomous Region, Urumqi 830011, China 4 University of Chinese Academy of Sciences, Beijing 100049, China * Correspondence: [email protected]; Tel.: +86-991-7885378



Received: 9 October 2019; Accepted: 18 December 2019; Published: 20 December 2019


Abstract: Lake water salinization in arid areas is a common problem and should be controlled for the better use of freshwater of lakes and for the protection of the environment around lakes. It is well known that the increasing of hydraulic connectivity improves water quality, but for a lake, understanding how hydraulic connectivity changes its water quality in terms of spatial aspects is of great significance for the protection and utilization of different regions of the lake water body. In this paper, the impacts of three connectivity scenarios on the spatial-temporal salinity changes in Bosten Lake were modeled through the three-dimensional (3D) hydrodynamic model, Environmental Fluid Dynamics Code (EFDC). The constructed Bosten Lake EFDC model was calibrated for water level, temperature, and salinity with acceptable results. As for the Bosten Lake, three connectivity scenarios were selected: (1) the increasing of the discharge water amount into the lake from the Kaidu River, (2) the transferring of 1 million cubic meter freshwater to the southwestern part of the lake (the Huangshuigou region of the lake), and (3) the changing of the outflow position from the southwestern part of the lake (the Kongque river) to the southeastern of the lake (the Caohu region). Through the simulations, we found that the region of the lake mainly influenced by the three scenarios presented here were different, and of the three scenarios, scenario 3 was the best means of controlling the overall lake salinity. On the basis of the salinity distribution results gained from the simulations, decision-makers can choose the ways to mitigate the salinity of the lake according to which region they want to improve the most in terms of economic efficiency and preserve in terms of ecological balance.

Keywords: Bosten Lake; Kaidu River; connectivity; salinity; Environmemnt Fluid Dynamics Code (EFDC)

1. Introduction Lakes are important components in the terrestrial system. They provide vital water sources for the development of the regional ecology and economy [1,2]. This is particularly true in arid and semi-arid regions, where regional development depends on water availability [3]. Moreover, in arid and semi-arid regions, lakes are important for the survival and development of their surrounding and internal living organisms and for the preservation of species diversity, also generally carrying cultural value and providing enormous economic, recreational, and aesthetic benefits to citizens [4]. Hence, lake scientific management is very important to sustainable development in arid and semi-arid regions.

Water 2020, 12, 40; doi:10.3390/w12010040 www.mdpi.com/journal/water Water 2020, 12, 40 2 of 22

It is a common problem that water is salinized with time in arid and semi-arid areas [5,6]. In Central Asia, many freshwater lakes have changed to oligosaline or saline lakes due to anthropogenic activities and climate change [7]. Lake Qarun, southwest of Cairo, Egypt, a formerly freshwater lake, has become a saline lake due to agricultural drainage [8]. The water salinity of the Aral Sea and Lake Chad has increased due to river regulation and diversions [9]. In arid and semi-arid regions, lake water salinization has been attributed primarily to high water evaporation rates, low rainfall rates, limited recharge and inflow water diversion for irrigation, among other uses [10–12]. The impacts of water salinization are manifold, adverse, and have largely irreversible environmental, economic, and social costs [8]. Many studies [13–17] demonstrate that the high salinity in lake water has harmful effects on water quality and the health of people, plants, and animals, hence restricting the utilization of water and damaging the integrity of ecosystems. It is well known that water connectivity is important for controlling water quality and improving ecological environment. The river loop connection, existing prior to 1965, between the Keelung River and Danshuei River in northern Taiwan, had important effects on the residual transport and the salinities of the rivers [18]. Enhanced hydrological connectivity led to an improved water environment of the seasonal lakes in the Poyang Lake floodplains, China [19]. Greater hydrological connectivity to stream surface water increased inflows of allochthonous nutrients in the Piedmont physiographic province of Virginia [20]. In the wet season from February to April 2011, the surficial hydrological connectivity was a key factor dominating change in total dissolved nitrogen (TDN) and dissolved organic carbon (DOC) in small, seasonal wetlands in the upper Piedmont and lower Blue Ridge ecoregions of South Carolina, USA [21]. The community composition of bacterioplankton among floodplain lakes in the Middle Basin of the Biebrza River, Northeastern Poland, was different because of the variation of hydrological connectivity with the main river [22]. Reconnecting a lake group with the Yangtze River significantly changed the lake circulation patterns, increased the lake water replacement rate, and greatly enhanced the water exchange between sub-lakes [23]. Hydrological connectivity was a key factor influencing both physico-chemical conditions of water, mainly water trophy, and the qualitative and quantitative faunal structure related to Stratiotes aloides L. in oxbow lakes (North Poland) [24]. The hydrological connectivity alteration changed the interactions and synergistic processes between rivers and their floodplains, and clearly affected the distribution of wintering waterbirds in the Poyang Lake region [25]. Facilitating hydrologic connectivity by engineered and natural geomorphic features would have expanded the habitat of alligator gar in the Lower Mississippi River floodplain [26]. Total stormflow and peak streamflow were influenced by maximum subsurface connectivity in small headwater watersheds in the Swiss pre-Alps and the Italian Dolomites [27]. It has been shown that the water quality in Bosten Lake is largely impacted by the hydraulic connectivity between the lake and the upstream tributaries [28]. In this paper, in order to control the salinization of Bosten Lake, the largest lake in the arid area of Xinjiang, the impacts of different water connectivity on the spatial-temporal changes of water salinity of Bosten Lake were studied. Three water connectivity scenarios were selected: (1) the increasing of the inflow from the Kaidu River into the lake, (2) the transferring of freshwater to the Huangshuigou region, and (3) the changing of the outflow position from the Kongque River to the Caohu region. Water connectivity in the lake can be represented by increasing inflow and outflow and finding the proper location of the outflow. The impacts of the Kaidu River discharge on the salinity distribution of Bosten Lake were studied previously through a three-dimensional numerical model, the terrain-following estuarine, coastal, and ocean modeling system with sediments (ECOMSED) [29], which is studied here again to take it as one connectivity scenario and then comparing it with other two scenarios because the Kaidu River is the primary recharge of the lake. Bosten Lake is a flow-through lake, but both its inflow and outflow positions are in the southwestern corner of the lake. For a lake that is around 1000 km2, the only intense exchange happens at one corner of the lake, and even under wind force the circulation is weak. The Caohu region is at the southeastern corner of the lake, where there is weak water circulation, and thus in this region the salinity is high; the outflow of the Kongque Water 2020, 12, 40 3 of 22

River is near the southwestern corner, and we want to know how changing the outflow position to the Caohu region will influence the water salinity of the lake. In order to maintain the lake as a freshwater lake, the government wants to transfer 1 million cubic meters of fresh water through the Huangshuigou region to the lake. We are sure it will improve the salinity of the region, but the extent of the region it will influence, as well as how much it will reduce the salinity of the lake, needs to be studied. The objectives of this research are (1) to quantify the influence of the three connectivity scenarios on the spatial-temporal salinity changes of the lake, and (2) to compare the three scenarios to see which one is better for controlling the salinization of the lake. To achieve this objective, firstly, a hydrodynamic model was set up. Then, the influence of three scenarios of inflow and outflow on lake water salinity was analyzed on the basis of the hydrodynamic model. Finally, we quantitatively assessed the effects of three scenarios on lake water salinity. We investigated the influence of increasing the flow quantity and recharging freshwater and changing the outflow position on the water salinity of Bosten Lake through the three-dimensional (3D) hydrodynamic model, Environmental Fluid Dynamics Code (EFDC). The simulation of the changes in water salinity under the three connectivity scenarios in this study can be used as a guidance for hydraulic engineering control and to assist the water resource management and planning for Bosten Lake. The results can heighten our comprehending of the effects of different hydraulic engineering activities on the lake water salinity and provide meaningful information on how to arrange hydraulic engineering activities to control water salinization. Our results can provide quantity information for lake water salinity control. Combined with water control objectives, the region to be controlled in terms of salinity, and the salinity value that is to be maintained, among others, it could be chosen by decision-makers using which engineering method from the three to control the water salinity, or integrating the three.

2. Methods

2.1. The Study Area

Bosten Lake (41◦560 N–42◦140 N, 86◦400 E–87◦260 E) is situated in southern Xinjiang, the arid and semi-arid region in northwest China. It is the biggest lake in Xinjiang and was previously the biggest inland freshwater lake in China that has evolved into an oligosaline (subsaline) lake in the previous 60 years [7,30]. Bosten Lake is rich in fish, reeds, and waterfowls. The lake was referred to as the “Oriental Hawaii of Xinjiang” due to its distinct lush scenery enclosed by the rough Gobi Desert. The lake held natural outflow conditions in history until an artificial pumping station was constructed in 1983. Then, via a channel, the water of the lake has been pumped out to the Kongque River. The lake is at the beginning of the Kongque River (KQR) and the terminal of the Kaidu River (KDR) (Figure1). The mean width and length of the lake is around 20–25 km from south to north and 55 km from east to west, respectively. When the water level is 1048 m a.m.s.l.(above mean sea level), the lake has an average and maximum water depth of 8.1 and 15 m, respectively, a water surface area of 1160 km2, and storage capacity of 8.41 109 m3. The lake is very shallow close to the shores and the deepest × part is in its east-central region with a dissymmetrical bottom topography [31]. The Kaidu River is the main perennial tributary stream of the lake, accounting for 83.4% of its total inflow. The annual ≈ runoff volume of the Kaidu River, on average, is 3.412 109 m3. The Huangshuigou, the Qing-Shui × River, and the Wu-La-Si-Te River are the other important tributary streams [32]. The Caohu region is the southeastern corner of the lake. The climate here is labeled as dry with a hot summer and cold winter. The annual precipitation is only 68.2 mm, mostly falling during the summer months, and the annual potential evaporation rate reaches up to approximately 1800–2000 mm, and the mean annual air temperature is 8.4 ◦C[33]. Winds principally come from the southwest, presenting the most important effect of the westerlies in the summer season. There are 14 monitoring sites for spatial salinity surveys (Figure1). Site 1 is situated to the lake southwest, and in front of the lake water outflow. Sites 7–12 are situated close to the agricultural wastewater discharge and tourist sites on the western lakeside. Water 2020, 12, 40 4 of 22

Bosten Lake is very important for the region. It plays an important part in preventing floods from the Kaidu River and supplying water for the Kongque River basin and the downstream of Tarim River. It plays a significant part in wild reed and fish production, as well as wildlife breeding, and Waterprovides2020, 12precious, 40 but limited water resources for industry, drinking consumption water for about4 of 22 1.3 million people, around 190,000 ha of agriculture irrigation, and more than 50,000 km2 downstream basin ecosystem. The lake water resource is of great importance for the societal stability and economic Sitedevelopment 13 and 14 of are southern situated Xinjiang, near the as Kaidu well River,as the which ecological supplies restoration the lake of a the considerable lower reaches amount of the of freshTarim water. River Thewate fivershed other [6,17,34]. sites are situated in the center of the lake.

Figure 1. The schematic map of Bosten Lake (in which black sold circles represent the observed sites; Figure 1. The schematic map of Bosten Lake (in which black sold circles represent the observed sites; KDR, KQR, HSG, CH, YQ, and BH stand for the Kaidu River, the Kongque River, the Huangshuigou KDR, KQR, HSG, CH, YQ, and BH stand for the Kaidu River, the Kongque River, the Huangshuigou region, the Caohu region, and Yanqi and Bohu stations, respectively; the black stars represent the inlets region, the Caohu region, and Yanqi and Bohu stations, respectively; the black stars represent the of KDR and HSG, the outlets of KQR and CH; the black arrows show the schematic flow direction of the inlets of KDR and HSG, the outlets of KQR and CH; the black arrows show the schematic flow inlet and outlet; the bathymetry was described by Kriging interpolation used for EFDC (Environmental direction of the inlet and outlet; the bathymetry was described by Kriging interpolation used for Fluid Dynamics Code) modeling). EFDC (Environmental Fluid Dynamics Code) modeling). Bosten Lake is very important for the region. It plays an important part in preventing floods from the KaiduHowever, River the and lake supplying has been water threatened for the Kongqueby water Riversalinization basin and because the downstream of the reduction of Tarim of water River. Itinflow plays and a significant the increment part in of wild salt reedinflow. and The fish lake production, water salinity as well has aswildlife been commonly breeding, over and provides1.0 g L−1 precious[35,36] and but the limited lake waterhas turned resources into fora slight industry, brac drinkingkish lake consumptionsince 1958 [37]. water The for Bosten about Lake 1.3 million water people,salinity aroundwent through 190,000 three haof change agriculture periods irrigation, because andof the more combined than 50,000 effects km of2 climatedownstream change basin and ecosystem.anthropogenic The activities lake water in resourcethe past isseveral of great decades importance [38,39]. for Specifically, the societal the stability lake andwater economic salinity developmentindicated an obvious of southern upward Xinjiang, trend as from well the as thefirst ecological observation restoration (0.39 g/L) of [38], the lowerstarting reaches in 1956 of and the Tarimrising Riverto its watershedhighest recorded [6,17,34 ].salinity (1.87 g/L) in 1987. Then, the lake water salinity showed a successiveHowever, downward the lake trend has been and threatened fell to its lowest by water record salinization (1.17 g/L) because in 2003. of theThereafter, reduction the of water salinity rose dramatically from 2002 to 2010 and increased to 1.45 g/L in 2010. Increasing1 lake inflow and the increment of salt inflow. The lake water salinity has been commonly over 1.0 g L− [35,36] andevaporation the lake hasresulted turned in intothe asuccessive slight brackish increase lake in since lake 1958 water [37 salinity]. The Bosten from Lake1958 to water 1987. salinity Increasing went throughlake inflow three and change human-controlled periods because lake outflow of the combined together eresultedffects of in climate the decrease change in and lake anthropogenic water salinity activitiesfrom 1988 in to the 2002. past During several 2003 decades to 2010, [38,39 the]. Specifically,lake water thesalinity lake increased water salinity sharply indicated because an the obvious lake upwardinflow significantly trend from the reduced first observation due to a drop (0.39 in g/ L)precipitation; [38], starting meanwhile, in 1956 and risingthe water to its supply highest project recorded of salinitytransferring (1.87 water g/L) in from 1987. Bosten Then, Lake the lake to Tarim water River salinity resulted showed in athe successive growing downward of the lake trendoutflow. and The fell tosalinization its lowest recordof the lake (1.17 is g /L)controlled in 2003. Thereafter,by various theelements, water salinity including rose the dramatically inflow, outflow, from 2002 and to water 2010 andlevel increased of the lake, to 1.45as well g/L as in 2010.the salt Increasing carried by lake agricultural evaporation drainage resulted into in the the successive lake [6]. increase in lake waterWater salinity salinization from 1958 harmfully to 1987. Increasing influences lake lake inflow water andsystems, human-controlled local eco-environments, lake outflow and together water resulteduse, and inhas the turned decrease into in a lakesevere water environmental salinity from problem 1988 to 2002.in Bosten During Lake. 2003 Salinity to 2010, was the found lake waterto be salinitythe dominant increased factor sharply that contro becauselled the the lake sedimentary inflow significantly abundance reduced of Betaproteobacteria due to a drop and in precipitation; the bacterial meanwhile, the water supply project of transferring water from Bosten Lake to Tarim River resulted in the growing of the lake outflow. The salinization of the lake is controlled by various elements, including the inflow, outflow, and water level of the lake, as well as the salt carried by agricultural drainage into the lake [6]. Water 2020, 12, 40 5 of 22

Water salinization harmfully influences lake water systems, local eco-environments, and water use, and has turned into a severe environmental problem in Bosten Lake. Salinity was found to be the dominant factor that controlled the sedimentary abundance of Betaproteobacteria and the bacterial community composition in the oligosaline Lake Bosten [7,40]. The spatial distribution of bacterial abundance was affected by the water salinity in Lake Bosten [41]. Its water salinization should be managed to supply enough water resources for the surrounding arid area, and for protecting the environment of the lake and its surroundings [6].

2.2. Model Description In this paper, we implemented the EFDC Explorer 7, a widely used model developed by Dynamic Solutions International (DSI), for the hydrodynamic modeling of Bosten Lake. The EFDC model was originally developed by Hamrick (1992) [42] from the Virginia Institute of Marine Science, and afterwards was financed by the United States Environmental Protection Agency (U.S. EPA). It is capable of modelling one-, two-, and three-dimensional flow; transport; and biogeochemical evolutions in surface water systems. It models topographically and density-induced circulation; wind-driven flows; and temporal and spatial layouts of temperature, salinity, and conservative/non-conservative tracers. Its reliability and validity in hydrodynamic modeling has been extensively tested in various aquatic systems at numerous sites worldwide, including reservoirs, lakes, rivers, wetlands, estuaries, and coastal ocean regions contributing to environmental management and assessment [43,44]. The hydrodynamic portion of EFDC uses the three-dimensional continuity, vertically-hydrostatic, free-surface Reynolds-averaged Navier Stokes equations formulated using the turbulent-averaged motion equations for a changeable-density fluid with the Boussinesq approximation and Mellor–Yamada [45] turbulence closure [42,46]. The level 2.5 turbulence closure scheme of Mellor–Yamada is applied to calculate the vertical turbulent viscosity and diffusivity [45,47]. The code works out scalar transport equations in the aquatic column (e.g., salinity, temperature). Density-dependent vertical flows are simulated by ensuring mass conservation at every grid with a given flow boundary condition at the surface due to evaporation/condensation and precipitation, as well as at the bottom due to groundwater exchange. Horizontal flows are modelled by momentum equations without flow boundary conditions at lateral walls. The EFDC hydrodynamic model includes equations of continuity, momentum, state, and transport for salinity and temperature (see the AppendixA for equations). Details of the hydrodynamic model and mathematical schemes of the EFDC model are documented by Hamrick (1992; 2007a; 2007b) [42–44] and Hamrick and Wu (1997) [46]. The model of Bosten Lake was built with a curvilinear, orthogonal horizontal coordinate system and a sigma vertical coordinate system. The horizontal plane contained 3737 active cells with a grid size of 500 500 m. Vertical sigma coordinate could model the bottom terrain better. The vertical × sigma layers number was fixed and set to a constant and equal fraction within the whole model domain, whereas the regional thickness of every layer varied with the bathymetry of the model. The bathymetry data of the model from field measured water depth were applied to the model grids by kriging interpolation (Figure1). Ten equal thickness vertical layers were set to form the bathymetry. The simulation was performed from 1 April to 30 September 2005. EFDC is forced by atmospheric conditions (e.g., wind shear, evaporation, and precipitation) and tributary inflow/outflows, among other factors. Hourly meteorological data of 2005 at Yanqi weather station (Figure1) in the vicinity of Bosten Lake, including air temperature, wind speed and direction, atmospheric pressure, cloud cover, relative humidity, pan evaporation, and precipitation, were obtained from the China Meteorological Administration. The wind rose map of the station is presented in Figure2. Due to the absence of solar radiation observations at Yanqi Station, or neighboring areas in 2005, solar radiation was calculated by the method of Rosati and Miyakoda (1988) [48] and presumed to be the same in the whole model area. The solar attenuation coefficient was set as 0.45. The model flow boundary conditions included two inflows from the main stream, the Kaidu River at the southwest and agriculture drainage at the Huangshuigou region at the northwest, and one outflow to the Kongque Water 2020, 12, 40 6 of 22

River at the southwest of the lake (Figure1). Daily volumetric flow rate of river (Figure3) and water Watertemperature 2020, 12, 40 data specified for the inflow of the Kaidu River at Yanqi hydrological station and outflow6 of 22 of the Kongque River at Tashidian (TSD) hydrological station were acquired from the Hydrological acquiredYearbook from of the the People’s Hydrological Republic Yearbook of China of [the49]. Peop Thele’s time Republic series of of the China Kaidu [49]. River The discharge time series was of thetaken Kaidu as the River inflow discharge discharge was into taken the as Bosten the inflow Lake. di Inscharge 2005, theinto Kaidu the Bosten River Lake. discharges In 2005, varied the Kaidu from 13.2River to discharges 341 m3/s, havingvaried from a mean 13.2 of to 67.1 341 m m3/s.3/s, The having time a series mean of of the 67.1 Kongque m3/s. The River time discharge series of wasthe Kongqueset as the River outflow discharge discharge was out set of as the the Bosten outflow Lake. disc Toharge simulate out of the the real Bosten inflow Lake. and To outflow simulate of the reallake, inflow some factorsand outflow were of applied the lake, to thesome river factors inflow were and applied outflow. to the Salinity river ofinflow the inflows and outflow. was set Salinity by the ofdata the obtained inflows fromwas interpolationset by the data of severalobtained monthly from interpolation observations acquiredof severa atl monthly a nationally-managed observations acquiredenvironmental at a nationally-managed monitoring station. environmental monitoring station.

NORTH

15%15%

10%10%

5%5%

WEST EASTEAST

Wind speed (m/s) 10 - -12 12 8 -- 10 10 6 -- 8 8 4 -- 6 6 2 -- 4 4

0 -- 22 SOUTH Figure 2. Wind rose map at the Yanqi station during the simulation period. Figure 2. Wind rose map at the Yanqi station during the simulation period. The initial conditions involving water temperature and water salinity, and water level were set as The initial conditions involving water temperature and water salinity, and water level were set constant values. The lake water surface was assumed to be horizontally flat. The initial water level was as constant values. The lake water surface was assumed to be horizontally flat. The initial water level specified as 1047.5 m of the daily value of the Bohu hydrological station on 1 April 2005. The initial was specified as 1047.5 m of the daily value of the Bohu hydrological station on 1 April 2005. The water flow rate was specified as zero. initial water flow rate was specified as zero. Parameters associated with the Mellor–Yamada turbulence model [45] were specified as the Parameters associated with the Mellor–Yamada turbulence model [45] were specified as the suggested values that was used in the Princeton Ocean Model [50]. Similarly, the dimensionless suggested values that was used in the Princeton Ocean Model [50]. Similarly, the dimensionless horizontal viscosity in the Smagorinsky equation [51] was specified as a given value of 0.1 [52]. Bottom horizontal viscosity in the Smagorinsky equation [51] was specified as a given value of 0.1 [52]. roughness (Z0) was specified as a representative value of 0.0036 m [42,50] for water level calibration. Bottom roughness (Z0) was specified as a representative value of 0.0036 m [42,50] for water level Critical wet and dry depth were specified as 0.1. calibration. Critical wet and dry depth were specified as 0.1. A two-time level explicit finite-difference scheme was used in the time integration of the model. A two-time level explicit finite-difference scheme was used in the time integration of the model. Through an internal/external mode-splitting procedure, the internal shear (or baroclinic mode computed Through an internal/external mode-splitting procedure, the internal shear (or baroclinic mode across each sigma layer) separated from the external free-surface gravity wave (or barotropic mode computed across each sigma layer) separated from the external free-surface gravity wave (or computed on the depth average). The model was executed using a 25 s time step to meet the needs of barotropic mode computed on the depth average). The model was executed using a 25 s time step to the stability criterion of Courant–Fredrichs–Lewy condition. meet the needs of the stability criterion of Courant–Fredrichs–Lewy condition. Model calibration and verification was dependent on water level data observed at Bohu hydrological Model calibration and verification was dependent on water level data observed at Bohu station, as well as water temperature and salinity measures from 14 sites across the lake (Figure1). hydrological station, as well as water temperature and salinity measures from 14 sites across the lake The 2005 daily averaged water levels were obtained from hydrologic yearbooks of the People’s Republic (Figure 1). The 2005 daily averaged water levels were obtained from hydrologic yearbooks of the of China. The water surface elevation varied substantially within a year, with the highest value of People’s Republic of China. The water surface elevation varied substantially within a year, with the 1047.46 m during the winter, and the lowest value of 1046.87 m during the summer. The observations highest value of 1047.46 m during the winter, and the lowest value of 1046.87 m during the summer. of lake spatial salinity and temperature were obtained from the Xinjiang Environmental Protection The observations of lake spatial salinity and temperature were obtained from the Xinjiang Academy of Science for 14 sites on 11 May, 10 June, 7 July, 5 August, and 3 September of 2005. Of these Environmental Protection Academy of Science for 14 sites on 11 May, 10 June, 7 July, 5 August, and sites, sites 13 and 14 are situated near the Kaidu River, the freshwater region. The other sites are 3 September of 2005. Of these sites, sites 13 and 14 are situated near the Kaidu River, the freshwater region. The other sites are situated in oligosaline regions, where they are under the impact of human activities in terms of tourism or agriculture. Site 1 is situated to the southwest of the lake. Sites 7–12 are impacted by eutrophic and saline agriculture wastewater drainage from the western lakeshore and tourist sites on the western lakeside. Sites 5 and 4 are close to the tourist region of the northern lakeshore (Figure 1).

Water 2020, 12, 40 7 of 22 situated in oligosaline regions, where they are under the impact of human activities in terms of tourism or agriculture. Site 1 is situated to the southwest of the lake. Sites 7–12 are impacted by eutrophic and saline agriculture wastewater drainage from the western lakeshore and tourist sites on the western Water 2020, 12, 40 7 of 22 lakeside. Sites 5 and 4 are close to the tourist region of the northern lakeshore (Figure1).

FigureFigure 3. 3.The The flow flow rate rate of of hydrological hydrological stationsstations ofof thethe Kaidu River River (KDR), (KDR), the the Huangshuigou Huangshuigou region region (HSG),(HSG), and and the the Kongque Kongque River River (KQR) (KQR) taken taken from from the Hydrologicalthe Hydrological Yearbook Yearbook [48] was[48] appliedwas applied in forcing in theforcing Bosten the Lake Bosten model Lake during model simulation during simulation period from period 00:00 from 1 April 00:00 to 1 00:00 April 30 to September 00:00 30 September 2005. 2005. Because we are concerned with the impact of the hydraulic connectivity on the spatial-temporal salinityBecause changes we in Bostenare concerned Lake, three with numericalthe impact experiments of the hydraulic (Table connectivity1) were carried on the out spatial-temporal for studying the impactssalinity of changes the hydrological in Bosten Lake, connectivity three numerical scenarios experiments on the salinity (Table distribution 1) were carried of the out lake. for studying They were A2—thethe impacts increasing of the ofhydrological the inflow connectivity of the Kaidu scenarios River intoon the the salinity lake, A3—thedistribution transferring of the lake. of They some freshwaterwere A2—the to the increasing Huangshuigou of the inflow region, of and the A4—theKaidu River changing into the of lake, the outflow A3—the positon transferring from of the some outlet of thefreshwater Kongque to the River Huangshuigou to the Caohu region, region. and The A4—the simulation changing A1 of was the outflow driven bypositon actual from observed the outlet data andof wasthe Kongque subsequently River consideredto the Caohu as region. the control The simu run.lation In simulation A1 was driven A1, theby actual model observed was initialized data usingand averagewas subsequently water temperature considered and as salinitythe control on run. 5 April, In simulation and driven A1, by the hourly model mean was surfaceinitialized heat fluxusing and average wind stress, water andtemperature daily average and salinity flows on of 5 the April, rivers. and Indriven total by there hourly were mean four surface simulations. heat flux and wind stress, and daily average flows of the rivers. In total there were four simulations. Experiments A2–A4 were hydraulic connectivity scenarios. From simulations A1–A4, the influence of Experiments A2–A4 were hydraulic connectivity scenarios. From simulations A1–A4, the influence three connectivity scenarios on the salinity distribution of Bosten Lake can be found. of three connectivity scenarios on the salinity distribution of Bosten Lake can be found.

Table 1. The different hydraulic connectivity scenarios and their conditions.

Scenarios Conditions A1 The validation model under real conditions. A2 The same as A1, however, the Kaidu River discharge was risen by 50%. A3 The same as A1, however, 1 × 108 m3/a freshwater was transferred into the Huangshuigou region of the lake.

Water 2020, 12, 40 8 of 22

Table 1. The different hydraulic connectivity scenarios and their conditions.

Scenarios Conditions A1 The validation model under real conditions. Water 2020A2, 12, 40 The same as A1, however, the Kaidu River discharge was risen by 50%. 8 of 22 A3 The same as A1, however, 1 108 m3/a freshwater was transferred into the Huangshuigou × A4 The same as A1, however, the outflowregion ofpositon the lake. of the lake was changed from the A4 The sameoutlet as A1, however,of the Kongque the outflow River positon to the of outlet the lake of was the changedCaohu region. from the outlet of the Kongque River to the outlet of the Caohu region. 3. Results and Discussion 3. Results and Discussion 3.1. Model Validation 3.1. Model Validation The model was calibrated by comparing the modelled results of water level, salinity, and The model was calibrated by comparing the modelled results of water level, salinity, and temperature temperature with the observed water level of Bosten hydrological station and salinity and with the observed water level of Bosten hydrological station and salinity and temperature of different temperature of different sites within the lake. Generally, the simulated values were in agreement with sites within the lake. Generally, the simulated values were in agreement with the observed data the observed data (Figures 4–6). Here, we only showed the calibration results of S2, S8, and S11, as (Figures4–6). Here, we only showed the calibration results of S2, S8, and S11, as they were distributed they were distributed in the typical places of the lake and can represent the whole lake condition (See in the typical places of the lake and can represent the whole lake condition (See the AppendixA for the Appendix A for the calibration results of other sites). The modelled water level was almost equal the calibration results of other sites). The modelled water level was almost equal to the observed to the observed data (Figure 4), which demonstrated that the model could model water surface data (Figure4), which demonstrated that the model could model water surface variations considering variations considering changes in wind, freshwater discharge, evaporation, and precipitation. The changes in wind, freshwater discharge, evaporation, and precipitation. The water level of Bosten water level of Bosten Lake presented a concave change during the simulation period, and was mainly Lake presented a concave change during the simulation period, and was mainly influenced by the influenced by the lake evaporation and the inflow and outflow discharges. However, the predicted lake evaporation and the inflow and outflow discharges. However, the predicted salinity was slightly salinity was slightly different from the observed data, which may have been due to the neglecting of different from the observed data, which may have been due to the neglecting of the impact of the the impact of the resuspended and dissolved bottom salt sediments. The predicted temperature was resuspended and dissolved bottom salt sediments. The predicted temperature was also a little higher also a little higher than the observations, which may have been due to the neglecting of the spatial than the observations, which may have been due to the neglecting of the spatial heterogeneity of the heterogeneity of the meteorological conditions, as well as the neglecting of the heat exchange between meteorological conditions, as well as the neglecting of the heat exchange between the bottom water the bottom water and lakebed. and lakebed.

1047.8 Simulated Observed 1047.6

1047.4

1047.2 Water(m) level 1047.0

1046.8

2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Figure 4. Comparison between observed and simulated daily average water level at Bosten hydrological Figure 4. Comparison between observed and simulated daily average water level at Bosten station from 1 April 2005 to 30 September 2005. hydrological station from 1 April 2005 to 30 September 2005. The root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) were applied to evaluate the average1.9 simulation error. The agreement between the 1.6 Simulated Simulated 2-Observed simulated and measured water level at Bohu hydrological1.8 station 8-Observed (Figure1) was reasonable, with an MAE1.4 value of 0.02 m, an RMSE value of 0.03 m, and an MAPE value of 0%, which meant the 1.7 simulated1.2 and measured water levels were almost same (Figure4, Table2). The agreement between the measured and simulated water salinity at S2, S8,1.6 and S11 was satisfactory, with MAE values of 0.24,1.0 0.17, and 0.19 g/L; RMSE values of 0.45, 0.19, and1.5 0.31 g/L; and MAPE values of 16.24%, 10.36%, 0.8 1.4 Salinity (g/L) Salinity Salinity (g/L) Salinity

0.6 1.3 1.2 0.4 1.1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

Water 2020, 12, 40 8 of 22

A4 The same as A1, however, the outflow positon of the lake was changed from the outlet of the Kongque River to the outlet of the Caohu region.

3. Results and Discussion

3.1. Model Validation The model was calibrated by comparing the modelled results of water level, salinity, and temperature with the observed water level of Bosten hydrological station and salinity and temperature of different sites within the lake. Generally, the simulated values were in agreement with the observed data (Figures 4–6). Here, we only showed the calibration results of S2, S8, and S11, as they were distributed in the typical places of the lake and can represent the whole lake condition (See the Appendix A for the calibration results of other sites). The modelled water level was almost equal to the observed data (Figure 4), which demonstrated that the model could model water surface variations considering changes in wind, freshwater discharge, evaporation, and precipitation. The water level of Bosten Lake presented a concave change during the simulation period, and was mainly influenced by the lake evaporation and the inflow and outflow discharges. However, the predicted salinity was slightly different from the observed data, which may have been due to the neglecting of the impact of the resuspended and dissolved bottom salt sediments. The predicted temperature was also a little higher than the observations, which may have been due to the neglecting of the spatial heterogeneity of the meteorological conditions, as well as the neglecting of the heat exchange between the bottom water and lakebed.

1047.8 Simulated Observed 1047.6

1047.4

Water 2020, 12, 40 1047.2 9 of 22 Water(m) level 1047.0 and 11.68%, respectively (Figure5, Table2). The agreement between the simulated and measured 1046.8 water temperature at S2, S8, and S11 was satisfactory, with MAE values of 3.53, 4.56, and 3.14 ◦C;

RMSE values of 4.43, 5.86, and 4.082005/4/1◦C; 2005/5/1and MAPE 2005/6/1 values 2005/7/1of 2005/8/1 18.48%, 2005/9/1 25.30%, and 15.94%, respectively (FigureWater 20206, Table, 12, 402 ). The model has the possibility of simulatingDate water level, temperature, and salinity9 of 22 with reasonable accuracy, which nonetheless needs to be improved. Overall, the model results are Figure 4. Comparison between observed and simulated daily average water level at Bosten acceptable and can be used to1.7 analyze Simulated the salinity change due to different connectivity scenarios hydrological station from 1 April 2005 11-Observed to 30 September 2005. expressed by different inflows1.6 and outflows. 1.5 1.9 1.6 Simulated Simulated 2-Observed 1.4 1.8 8-Observed 1.4 1.3 1.2 1.7 1.2 Salinity (g/L) 1.1 1.6

1.0 1.0 1.5 0.9 0.8 1.4 Salinity (g/L) Salinity 0.8 (g/L) Salinity 0.6 2005/4/1 2005/5/1 2005/6/1 2005/7/11.3 2005/8/1 2005/9/1 Date1.2 0.4 Water 2020, 12, 40 1.1 9 of 22 2005/4/1Figure 5. 2005/5/1 Comparison 2005/6/1 between 2005/7/1 2005/8/1observed 2005/9/1 and simulated2005/4/1 daily average 2005/5/1 2005/6/1water salinity 2005/7/1 at 2005/8/1 sites 2, 2005/9/1 8, and 11 from 1 April 2005 to 30Date September 2005. Date 1.7 Simulated The root mean squared error 11-Observed(RMSE), mean absolute error (MAE), and mean absolute 1.6 percentage error (MAPE) were applied to evaluate the average simulation error. The agreement 1.5 between the simulated and measured water level at Bohu hydrological station (Figure 1) was 1.4 reasonable, with an MAE value of 0.02 m, an RMSE value of 0.03 m, and an MAPE value of 0%, which 1.3 meant the simulated and measured water levels were almost same (Figure 4, Table 2). The agreement 1.2 between the measured and simulated water salinity at S2, S8, and S11 was satisfactory, with MAE values of 0.24, 0.17, and 0.19 Salinity (g/L) g/L;1.1 RMSE values of 0.45, 0.19, and 0.31 g/L; and MAPE values of 16.24%, 10.36%, and 11.68%, respectively1.0 (Figure 5, Table 2). The agreement between the simulated and measured water temperature0.9 at S2, S8, and S11 was satisfactory, with MAE values of 3.53, 4.56, and 3.14 °C; RMSE values of 4.43,0.8 5.86, and 4.08 °C; and MAPE values of 18.48%, 25.30%, and 15.94%, 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 respectively (Figure 6, Table 2). The model has the possibility of simulating water level, temperature, Date and salinity with reasonable accuracy, which nonetheless needs to be improved. Overall, the model Figure 5. Comparison between observed and simulated daily average water salinity at sites 2, 8, and 11 resultsFigure are acceptable5. Comparison and between can be observed used to andanalyze simulated the salinity daily average change water due salinity to different at sites connectivity2, 8, and from 1 April 2005 to 30 September 2005. scenarios11 from expressed 1 April 2005 by differentto 30 September inflows 2005. and outflows. 35 35 Simulated The root Simulated mean squared error (RMSE), mean absolute 8-Observed error (MAE), and mean absolute 2-Observed 30 percentage30 error (MAPE) were applied to evaluate the average simulation error. The agreement 25 between25 the simulated and measured water level at Bohu hydrological station (Figure 1) was C) C) 。

。 20 reasonable,20 with an MAE value of 0.02 m, an RMSE value of 0.03 m, and an MAPE value of 0%, which meant the simulated and measured water levels were 15almost same (Figure 4, Table 2). The agreement 15 between the measured and simulated water salinity at S2, S8, and S11 was satisfactory, with MAE 10 values10 of 0.24, 0.17, and 0.19 g/L; RMSE values of 0.45, 0.19, and 0.31 g/L; and MAPE values of 16.24%, 5 5

10.36%, and 11.68%, respectively (Figure 5, Table Water temperature( 2). The agreement between the simulated and Water temperature ( measured0 water temperature at S2, S8, and S11 was satisfactory,0 with MAE values of 3.53, 4.56, and 3.14 °C; RMSE values of 4.43, 5.86, and 4.08 °C; and MAPE values of 18.48%, 25.30%, and 15.94%, -5 -5 respectively2005/4/1 2005/5/1 (Figure 2005/6/1 6, Table2005/7/1 2). The 2005/8/1 model 2005/9/1 has the possibility2005/4/1 2005/5/1 of simulating 2005/6/1 2005/7/1 water 2005/8/1level, temperature, 2005/9/1 and salinity with reasonableDate accuracy, which nonetheless needs to be improved.Date Overall, the model results are acceptable and can be used to analyzeFigure 6. theCont. salinity change due to different connectivity scenarios expressed by different inflows and outflows. 35 35 Simulated Simulated 30 8-Observed 30 2-Observed 25 25 C) C) 。

。 20 20 15 15 10 10 5 5 Water temperature( Water temperature ( 0 0

-5 -5 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

WaterWater2020 2020, 12, ,12 40, 40 10 of10 22 of 22

35 Simulated 11-Observed 30

25 C) 。 20

15

10

5 Water temperature( 0

-5 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Figure 6. Comparison between observed and simulated daily average water temperature at sites 2, 8, Figure 6. Comparison between observed and simulated daily average water temperature at sites 2, 8, and 11 from 1 April 2005 to 30 September 2005. and 11 from 1 April 2005 to 30 September 2005. Table 2. Statistics on water salinity and temperature at sites 2, 8, and 11 and water level at Bohu hydrologicalTable 2. Statistics station on (BH)—observation water salinity and against temperature simulation. at sites MAE: 2, 8, meanand 11 absolute and water error, level MAPE: at Bohu mean absolutehydrological percentage station error, (BH)—observation RMSE: root mean against squared simulation. error. MAE: mean absolute error, MAPE: mean absolute percentage error, RMSE: root mean squared error. Mean Mean MAPE Sites—Variable MAE RMSE Sites—Variable Mean SimulatedSimulated MeanObserved Observed MAE (%) MAPE (%) RMSE 2—Salinity (g/L) 1.28 1.38 0.24 16.24 0.45 2—Salinity (g/L) 1.28 1.38 0.24 16.24 0.45 8—Salinity8—Salinity (g/L) (g /L) 1.55 1.60 1.60 0.17 0.17 10.36 10.36 0.19 0.19 11—Salinity11—Salinity (g/L) (g /L) 1.38 1.51 1.51 0.19 0.19 11.68 11.68 0.31 0.31 2—Temperature2—Temperature (°C) (◦ C) 19.27 20.33 20.33 3.53 3.53 18.48 18.48 4.43 4.43 8—Temperature8—Temperature (°C) (◦ C) 16.94 20.17 20.17 4.56 4.56 25.30 25.30 5.86 5.86 11—Temperature11—Temperature (°C) (◦ C) 19.51 20.17 20.17 3.14 3.14 15.94 15.94 4.08 4.08 BH—WaterBH—Water level level (m) (m) 1047.15 1047.14 1047.14 0.02 0.02 0.00 0.00 0.03 0.03

3.2.3.2. The The Influences Influences of of Hydraulic Hydraulic Connectivity Connectivity onon WaterWater Salinity

3.2.1.3.2.1. The The Spatial Spatial Distribution Distribution of of Water Water SalinitySalinity ThroughThrough Figure Figure7 7salinity salinity distribution,distribution, we we can can see, see, compared compared to the to thevalidation validation value value (A1), (A1),the theincreasing increasing of of the the inflow inflow quantity quantity of ofthe the Kaidu Kaidu River River (A2), (A2), the the transferring transferring of offreshwater freshwater to tothe the HuangshuigouHuangshuigou region region (A3), (A3), and and the the changingchanging ofof the outflow outflow position position from from the the outlet outlet of ofthe the Kongque Kongque RiverRiver to theto the Caohu Caohu region region (A4) (A4) influenced influenced the regionthe region more more where where the changes the changes occurred. occurred. Under Under scenario A3,scenario due to theA3, limited due to quantity the limited of the quantity freshwater of inflow,the freshwater only the salinityinflow, ofonly the Huangshuigouthe salinity of regionthe deceasedHuangshuigou significantly, region but deceased that of the significantly, other regions but changed that of little.the other In the regions scenarios changed A2 and little. A4, In the the high salinityscenarios region A2 decreasedand A4, the and high low salinity salinity region region decreased increased and in low the salinity lake. The region increasing increased of in the the inflow lake. of theThe Kaidu increasing River andof the the inflow change of the of Kaidu the position River and of outflowthe change to of the the Caohu position region of outflow had similar to the Caohu impacts region had similar impacts on lake salinity, except that the salinity of the region of Caohu decreased on lake salinity, except that the salinity of the region of Caohu decreased a large amount under A4. a large amount under A4. The increasing of the inflow of the Kaidu River mainly influenced the The increasing of the inflow of the Kaidu River mainly influenced the southeastern corner and east southeastern corner and east region of the lake. The changing of the outflow position to the Caohu region of the lake. The changing of the outflow position to the Caohu region decreased the salinity of region decreased the salinity of the Caohu region. Our simulation to some extent reflects other the Caohu region. Our simulation to some extent reflects other scholars’ results in that the freshwater scholars’ results in that the freshwater inflows influenced the scope of the freshwater region in this inflowslake [53], influenced changing the the scope salinit ofy the gradient freshwater of the region lake [40]. in this lake [53], changing the salinity gradient of the lake [40].

Water 2020, 12, 40 11 of 22 Water 2020, 12, 40 11 of 22

Figure 7. Water surface salinity distribution on 15 August 2005 under different simulations: (A1) real Figure 7. Water surface salinity distribution on 15 August 2005 under different simulations: (A1) real condition, (A2) KDR inflow increase by 50%, (A3) 1 108 m3/a freshwater transfer into HSG, and (A4) condition, (A2) KDR inflow increase by 50%, (A3) 1 ×× 108 m3/a freshwater transfer into HSG, and (A4) changechange of of the the outflow outflow from from KQR KQR to to CHCH (in(in which KDR, KDR, KQR, KQR, HSG, HSG, and and CH CH stand stand for for the the Kaidu Kaidu River, River, thethe Kongque Kongque River, River, the the Huangshuigou Huangshuigou region, region, andand thethe Caohu region, respectively). respectively). 3.2.2. The Temporal Changes of Water Salinity 3.2.2. The Temporal Changes of Water Salinity The salinity of the lake changed with time and place. At sites east of the lake, such as 1, 6, 7, 8, 9, The salinity of the lake changed with time and place. At sites east of the lake, such as 1, 6, 7, 8, 9, 10,10, 11, 11, 12, 12, and and 13, 13, the the salinity salinity first first increased increased andand then decreased. In In the the sites sites in in the the center center of ofthe the lake, lake, suchsuch as as 2, 2, 3, 3, 4, 4, and and 5, 5, the the salinity salinity increased increased constantlyconstantly during the the study study period. period. The The time time of ofreaching reaching maximummaximum salinity salinity of theof the sites sites was was diff erent.different. At theAt regionthe region of the of Kaiduthe Kaidu River River input, input, it appeared it appeared around Julyaround 9, such July as 9, at such sites as 1 at and sites 13. 1 Atand sites 13. At 2, sites 3, 4, 2, and 3, 4, 5, and it was 5, it around was around September September 27. At27. theAt the other other sites, it wassites, around it was around August August 28. From 28. From the salinity the salinity temporal temporal changes changes of diof ffdifferenterent sites sites (Figure (Figure8), 8), it it can can be seenbe thatseen set that conditions set conditions for scenario for scenario A3 only A3 influenced only influenced the sites the around sites thearound Huangshuigou the Huangshuigou Region—6, 7, 8,Region—6, 9, and 10. 7, The8, 9, salinityand 10. The time salinity series time of these series sites of these under sites A3 under were diA3ff erentwere different from those from under those A1. Theunder change A1. of The the change outflow of positionthe outflow from position the Kongque from the River Kongque to the River Caohu to regionthe Caohu and region the increasing and the of theincreasing amount ofof thethe inflowamount of of thethe Kaiduinflow Riverof the decreasedKaidu River the decreased salinity the of disalinityfferent of sites. different At many sites. At sites, themany change sites, of the outflowchange of position the outflow (A4) decreasedposition (A4) the decreased salinity similarly the salinity to thesimilarly 50% increase to the 50% of the inflowincrease of the of the Kaidu inflow River of the (A2). Kaidu However, River (A2). the A4However, scenario the did A4 not scenario need costdid not addition need cost fresh addition water to decreasefresh water the laketo decrease salinity, the and lake thus salinity, it is and the thus optimum it is the way optimum to obtain way/ preserveto obtain/preserve freshwater freshwater lakes and savelakes water and resources save water in resources arid regions. in arid In scenarioregions. In A2, scenario the 50% A2, increase the 50% of increase the inflow of the of the inflow Kaidu of the River decreasedKaidu River the salinitydecreased of dithefferent salinity sites of moredifferent than si thetes othermore than two scenariosthe other becausetwo scenarios the discharge because ofthe the discharge of the Kaidu River is freshwater and the inflow amount of water is high (annual value of Kaidu River is freshwater and the inflow amount of water is high (annual value of 20.95 108 m3). 20.95 × 108 m3). ×

Water 2020, 12, 40 12 of 22 Water 2020, 12, 40 12 of 22

Figure 8. Cont.

Water 2020, 12, 40 13 of 22 Water 2020, 12, 40 13 of 22

FigureFigure 8. 8.Salinity Salinity temporal temporal changeschanges atat sitessites 1–14 from 1 1 April April 2005 2005 to to 30 30 September September 2005 2005 (in (in which which 8 3 simulations are A1—real condition, A2—KDR inflow increase by 50%, A3—1 108 m3 /a freshwater simulations are A1—real condition, A2—KDR inflow increase by 50%, A3—1 ×× 10 m /a freshwater transfertransfer into into HSG, HSG, and and A4—change A4—change of of thethe outflowoutflow from KQR KQR to to CH; CH; KDR, KDR, KQR, KQR, HSG, HSG, and and CH CH stand stand forfor the the Kaidu Kaidu River, River, the Kongque the Kongque River, theRiver, Huangshuigou the Huangshuigou region, andregion, the Caohuand the region, Caohu respectively). region, respectively). 3.2.3. The Amount of the Water Salinity Change under Different Scenarios 3.2.3.For The quantifying Amount of the the change Water Salinity of water Change salinity under due Different to different Scenarios scenarios, the mean difference of salinityFor between quantifying the scenario the change and theof water validation salinity simulation due to different over the scenarios, study period the mean was calculateddifference withof the following equation: salinity between the scenario and the validation simula tion over the study period was calculated with the following equation: diff = mean SIJ OJ (1) − where SIJ represents different scenarios,difOJf is=mean𝑆 the validation −𝑂 simulation, and I is scenario. I = (1)1, 2, 3 represents A2, A3, and A4, respectively. J is time (days). where 𝑆 represents different scenarios, 𝑂 is the validation simulation, and I is scenario. I = 1, 2, 3 representsThe A3 scenarioA2, A3, and was A4, mainly respectively. influenced J is time the (days). Huangshuigou region. In the transferring of fresh 1 water to the Huangshuigou region, the salinity of site 7 decreased extremely for around 1.4 g L− (68%) 0.2 1 (Figure9, Table3). At sites 8 and 9, the salinity decreased around 0.1 g L − . At sites 2, 6, 10, 11, 12, and 0.0 1 13 the salinity decreased around 0.01 g L− . At sites 1, 3, 4, and 5, the salinity only decreased around 1 0.003 g L− . The A2 and A4 scenarios-0.2 influenced the east part sites and not the center sites. At sites 3, 4, 1 and 5 under A2 and A4, the salinity-0.4 decreased only 0.02 g L− . At sites 1, 2, 8, 9, 10, 11, and 12, under 1 A2 and A4, the salinity decreased-0.6 around 0.1 g L− . At sites 6 and 13, the salinity decreased around 1 1 0.04 g L− . At site 7 under A2 and-0.8 A4, the salinity decreased 0.24 and 0.07 g L− (Figure9). The higher the salinity of the region, the more-1.0 obvious it changed. For the lower salinity region, the changes in salinity were not obvious. -1.2 A2 -1.4 A3 Mean salinity difference (g/L) A4 Table 3. The mean percentage-1.6 difference (%) of salinity between the scenario and the validation simulation (A1—real condition) over1234567891011121314 the study period at sites 1-14 (in which simulations are A2—KDR inflow increase by 50%, A3—1 108 m3/a freshwaterSites transfer into HSG, and A4—change of the × outflow from KQR to CH; KDR, KQR, HSG, and CH stand for the Kaidu River, the Kongque River, theFigure Huangshuigou 9. The mean region, difference and theof salinity Caohu between region, respectively). the scenario and the validation simulation at sites 1-14 (A1—real condition) over the study period (in which simulations are A2—KDR inflow increase bySimulations 50%, A3—1 × 10 18 m3/a freshwater 2 3 transfer 4 5 into 6HSG, 7and A4—change 8 9 10of the 11outflow 12 from 13 KQR 14 to CH; KDR,A2 KQR, HSG,6 and5 CH 3stand 1for the1 Kaid3u River,11 the6 Kongque6 5River,7 the Huangshuigou6 4 2 − − − − − − − − − − − − − − region,A3 and the Caohu 0 region, 0 respectively). 0 0 0 1 68 7 4 1 0 1 1 5 − − − − − − − − A4 6 4 2 1 1 2 3 4 4 4 5 5 5 6 − − − − − − − − − − − − − − Water 2020, 12, 40 13 of 22

Figure 8. Salinity temporal changes at sites 1–14 from 1 April 2005 to 30 September 2005 (in which simulations are A1—real condition, A2—KDR inflow increase by 50%, A3—1 × 108 m3/a freshwater transfer into HSG, and A4—change of the outflow from KQR to CH; KDR, KQR, HSG, and CH stand for the Kaidu River, the Kongque River, the Huangshuigou region, and the Caohu region, respectively).

3.2.3. The Amount of the Water Salinity Change under Different Scenarios For quantifying the change of water salinity due to different scenarios, the mean difference of salinity between the scenario and the validation simulation over the study period was calculated with the following equation:

diff =mean𝑆 −𝑂 (1)

Waterwhere2020 𝑆,12 ,represents 40 different scenarios, 𝑂 is the validation simulation, and I is scenario. I =14 1,of 2, 22 3 represents A2, A3, and A4, respectively. J is time (days).

0.2 0.0 -0.2 -0.4 -0.6 -0.8 -1.0 -1.2 A2 -1.4 A3 Mean salinity difference (g/L) A4 -1.6 1234567891011121314 Sites Figure 9. The mean difference of salinity between the scenario and the validation simulation at sites Figure 9. The mean difference of salinity between the scenario and the validation simulation at sites 1-14 (A1—real condition) over the study period (in which simulations are A2—KDR inflow increase by 1-14 (A1—real condition) over the study period (in which simulations are A2—KDR inflow increase 50%, A3—1 108 m3/a freshwater transfer into HSG, and A4—change of the outflow from KQR to CH; by 50%, A3—1× × 108 m3/a freshwater transfer into HSG, and A4—change of the outflow from KQR to KDR, KQR, HSG, and CH stand for the Kaidu River, the Kongque River, the Huangshuigou region, CH; KDR, KQR, HSG, and CH stand for the Kaidu River, the Kongque River, the Huangshuigou and the Caohu region, respectively). region, and the Caohu region, respectively). 4. Conclusions

The hydraulic connectivity influences on water salinity of Bosten Lake were studied in terms of controlling the water salinization of Bosten Lake, providing information for hydraulic engineering control activities. This research obtained the spatial information of salinity in different situations, instead of a single value, for one whole spatial heterogeneous lake. Its findings can be used so that decision-makers can make more targeted decisions regarding different regions of a big lake, especially for those in a water shortage area. A 50% increase of the quantity of the inflow from the Kaidu River, the transferring of freshwater to the Huangshuigou region of the lake, and the changing of the outflow position from the outlet of the Kongque River to the Caohu region, all decreased the salinity of the lake. The different hydraulic connectivity scenarios had different impacts in different regions of the lake. The transferring of 1 million cubic meters of freshwater to the Huangshuigou region mainly influenced the Huangshuigou region of the lake, which is useful mainly for the decrease of salinity in the northwestern region of the lake but not for the entire lake. If we want to control the lake salinity, adjusting hydraulic connectivity through changing the amount and position of the inflow and outflow of the lake is an alternative. A combination of all the three scenarios could be the best way to optimally decrease the salinity of Bosten Lake.

Author Contributions: Y.L. constructed the Bosten Lake EFDC model and wrote the first draft. A.B. was in charge of this work. All authors have read and agreed to the published version of the manuscript. Funding: This study was funded by the National Key Research and Development Program of China, grant number 2017YFC0404501; the Strategic Priority Research Program of Chinese Academy of Sciences, grant number XDA20060303; Tianshan Innovation Team Project of Xinjiang Department of Science and Technology, grant number Y744261; National Natural Science Foundation of China (NSFC), grant number 41101040; and “Western Light” Talents Training Program of Chinese Academy of science (CAS), grant number XBBS201005. Acknowledgments: We are extremely grateful to the editors Cici Hu, Evelyn Ning, and Cora Zheng and two anonymous reviewers for providing many important suggestions that were very helpful in the improvement of this paper. Conflicts of Interest: All authors state no conflicts of interest. Water 2020, 12, 40 15 of 22

Water 2020, 12, 40 15 of 22 Appendix A The Calibration Results of Sites 1-14 and Hydrodynamic Model Equations Are as FollowsAppendix A. The Calibration Results of Sites 1-14 and Hydrodynamic Model Equations are as Follows.

1.6 Simulated 1.6 Simulated 1-Observed 2-Observed 1.4 1.4

1.2 1.2

1.0 1.0 0.8 0.8 Salinity(g/L) Salinity(g/L) 0.6 0.6 0.4 0.4 0.2 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

1.8 1.7 Simulated Simulated 3-Observed 4-Observed 1.6 1.6 1.5 1.4 1.4 1.2 1.3

Salinity (g/L) 1.0 (g/L) Salinity 1.2

1.1 0.8 1.0 0.6 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

Simulated 1.65 1.65 Simulated 5-Observed 6-Observed 1.60 1.60

1.55 1.55

1.50 1.50

1.45 1.45 Salinity (g/L) Salinity Salinity (g/L) Salinity 1.40 1.40

1.35 1.35

1.30 1.30 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date Figure A1. Cont.

Water 2020, 12, 40 16 of 22 Water 2020, 12, 40 16 of 22

2.8 1.9 Simulated Simulated 7-Observed 2.6 1.8 8-Observed

2.4 1.7

2.2 1.6

2.0 1.5

1.8 1.4 Salinity (g/L) Salinity (g/L) Salinity 1.6 1.3

1.4 1.2

1.2 1.1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

1.9 Simulated Simulated 9-Observed 1.8 10-Observed 1.8

1.7 1.6 1.6 1.4 1.5

1.4 1.2 Salinity (g/L) 1.3 Salinity (g/L)

1.2 1.0

1.1 0.8 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

1.7 Simulated Simulated 11-Observed 1.6 1.6 12-Observed 1.4 1.5 1.4 1.2

1.3 1.0 1.2 0.8 Salinity (g/L) 1.1 (g/L) Salinity 0.6 1.0 0.9 0.4

0.8 0.2 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

1.6 Simulated 13-Observed 1.6 Simulated 1.4 14-Observed 1.4 1.2 1.2 1.0 1.0 0.8 0.8 Salinity(g/L) 0.6 Salinity (g/L) 0.6

0.4 0.4

0.2 0.2

2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

Figure A1. Comparison between observed and simulated daily average water salinity at sites 1-14 from 1 April to 30 September 2005. Water 2020, 12, 40 17 of 22

Table A1. Statistics on water salinity at sites 1-14: observation against simulation.

Sites Mean Simulated (g/L) Mean Observed (g/L) MAE (g/L) MAPE RMSE (g/L) 1 1.07 1.35 0.31 20.99 0.49 2 1.28 1.38 0.24 16.24 0.45 3 1.44 1.45 0.13 9.02 0.20 4 1.47 1.47 0.08 5.05 0.10 5 1.50 1.51 0.10 6.21 0.14 6 1.48 1.51 0.10 6.20 0.13 7 2.08 1.69 0.58 34.26 0.61 8 1.55 1.60 0.17 10.36 0.19 9 1.48 1.52 0.18 12.28 0.22 10 1.38 1.54 0.20 12.04 0.31 11Water 2020, 12, 40 1.38 1.51 0.19 11.68 0.3117 of 22 12 1.07 1.41 0.34 25.17 0.38 13Figure A1. 0.91 Comparison between observed 1.15 and simulated daily 0.42average water 46.98salinity at sites 1-14 0.45 14from 1 April 0.78 to 30 September 2005. 1.00 0.48 79.61 0.55

35 Simulated 35 Simulated 1-Observed 30 2-Observed 30 25 25 C) C) 。 。 20 20 15 15 10 10

5 5 Water temperature ( Water temperature ( Water temperature 0 0

-5 -5 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date 35 Simulated Simulated 30 4-Observed 3-Observed 30 25 25 C) C) 20 。 。 20

15 15

10 10

5 5 Water temperatureWater ( Water temperature ( 0 0

-5 -5 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date 35 35 Simulated Simulated 30 5-Observed 30 6-Observed

25 25 C) C) 。 20 。 20

15 15

10 10

5 5 Water temperature ( Watertemperature ( 0 0

-5 -5 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date Figure A2. Cont.

Water 2020, 12, 40 18 of 22 Water 2020, 12, 40 18 of 22

35 Simulated 30 Simulated 7-Observed 30 8-Observed 25 25 C) C) 。 。 20 20

15 15

10 10 5 Water temperature ( 5 Watertemperature ( 0 0 -5 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

35 Simulated 35 Simulated 30 9-Observed 10-Observed 30 25 25 C) C) 。 20 。 20 15 15

10 10

5 5 Watertemperature ( Water temperature ( temperature Water 0 0

-5 -5 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

35 Simulated 35 11-Observed Simulated 30 30 12-Observed

25 25 C) 。 C) 20 。 20

15 15

10 10

5 5 Water temperature ( Water temperature ( 0 0

-5 -5 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

Simulated Simulated 30 35 14-Observed 13-Observed 30 25

25 C) C) 。 20 。 20 15 15

10 10

5 temperatureWater ( 5 Watertemperature ( 0 0 -5 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 2005/4/1 2005/5/1 2005/6/1 2005/7/1 2005/8/1 2005/9/1 Date Date

Figure A2. Comparison between observed and simulated daily average water temperature at sites 1-14 from 1 April to 30 September 2005. Water 2020, 12, 40 19 of 22

Table A2. Statistics on water temperature at sites 1-14: observation against simulation.

Sites Mean Simulated (°C) Mean Observed (°C) MAE (°C) MAPE RMSE (°C) 1 18.97 20.50 3.55 18.41 4.51 2 19.27 20.33 3.53 18.48 4.43 3 18.53 20.33 3.61 18.82 3.94 4 18.59 20.50 3.71 19.44 3.92 5 18.53 19.80 3.19 16.38 3.43 6 18.77 20.50 3.84 20.53 4.31 7 13.52 20.50 7.86 41.70 8.78 8 16.94 20.17 4.56 25.30 5.86 9 17.30 20.00 3.46 20.02 5.16 10 19.51 20.33 3.31 17.39 4.12 11 19.51 20.17 3.14 15.94 4.08 12 17.10 20.17 4.08 23.30 5.47 13 18.17 19.00 3.87 21.20 4.99 14 15.50 18.67 5.09 27.69 6.11

Table A3. Statistics on water level at Bohu hydrological station (BH): observation against simulation.

Hydrological Mean Mean RMSE MAE (m) MAPE Station Simulated (m) Observed (m) (m) BH 1047.15 1047.14 0.02 0.00 0.03

The EFDC hydrodynamic model includes equations of continuity, momentum, state and transport for salinity and temperature shown below.   ∂t(mH) + ∂x myHu + ∂y(mxHv) + ∂z(mω) = Qh (A1)     ∂t(mHu) + ∂x myHuu +∂y(mxHvu) + ∂z(mωu) m f + v∂xmy u∂ymx Hv − − = myH∂x(gζ + p + Patm) my(∂xh z∂xH)∂zp − − − (A2)  1   1   1  +∂x mymx− HAH∂xu + ∂y mxmy− HAH∂yu + ∂z mH− Av∂zu p 2 2 mcpDPu u + v + Qu −     ∂t(mHv) + ∂x myHuv +∂y(mxHvv) + ∂z(mωv) m f + v∂xmy u∂ymx Hu −  −  = mxH∂y(gζ + p + Patm) mx ∂yh z∂yH ∂zp − − − (A3)  1   1   1  +∂x mymx HAH∂xv + ∂y mxmy HAH∂yv + ∂z mH− Av∂zv p− − 2 2 mcpDPv u + v + Qv − 1 ∂zp = gH(ρ ρ )ρ − = gHb (A4) − − 0 0 −   ∂t(mζ) + ∂x myHu + ∂y(mxHv) + ∂z(mω) = 0 (A5)

Z 1 ! Z 1 ! ∂t(mζ) + ∂x myH udz + ∂y mxH vdz = 0 (A6) 0 0 ρ = ρ(p, S, T) (A7)

 1 1   1 1  ω = ω∗ z ∂tζ + umx− ∂xζ + vmy− ∂yζ + (1 z) umx− ∂xh + vmy− ∂yh (A8) − −    1  ∂t(mHS) + ∂x myHuS + ∂y(mxHvS) + ∂z(mωS) = ∂z mH− Ab∂zS + Qs (A9)

   1  ∂t(mHT) + ∂x myHuT + ∂y(mxHvT) + ∂z(mωT) = ∂z mH− Ab∂zT + QT (A10) Water 2020, 12, 40 20 of 22 where, u and v are the horizontal velocity components in the curvilinear, orthogonal coordinates x and y (m/s); z is the sigma coordinate (dimensionless); t is time (s); mx, my are the square roots of the diagonal components of the metric tensor (m); m = mxmy is the Jacobian or square root of the metric tensor determinant; ω is the vertical velocity component in sigma coordinate (m/s), and ω∗ is the physical vertical velocity (m/s); H = h + ζ, is the total water depth; h is the water depth bellow the vertical reference level (m); ζ is the water surface elevation above the vertical reference level (m); f is 2 the Coriolis coefficient (1/s); AH is the horizontal momentum and mass diffusivity (m /s); Av is the 2 2 vertical turbulent or eddy viscosity coefficient (m /s); Ab is the vertical turbulent diffusivity (m /s); cp is the vegetation resistance coefficient (dimensionless); DP is the dimensionless projected vegetation area normal to the flow per unit horizontal area (dimensionless); Qh is the source/sink terms for the mass 3 conservation equation (m /s); Qu and Qv are the source/sink terms for the horizontal momentum in the 2 2 x and y directions, respectively (m /s ); Qs and QT are the horizontal diffusion and thermal sources and sinks; ρ is the disturbance density, generally a function of temperature and salinity; ρ0 is the reference water density (kg/m3); p is the physical pressure in excess of the reference density hydrostatic pressure 2 2 (m /s ); Patm is the barotropic pressure (Pa); b is buoyancy; T is the water temperature (◦C); S is the water salinity (g/L).

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