www.nature.com/scientificreports OPEN Estimating the ecological water levels of shallow lakes: a case study in Tangxun Lake, China Wei Yang1,2*, Mingxiang Xu1, Ruiqing Li1, Liping Zhang2* & Qiuliang Deng1 Water level management is an efective tool for the ecological restoration of shallow lakes. In this study, we developed an ecologically-based approach to estimate the monthly suitable ecological water levels (EWLs). This approach took both the lake topographic features and aquatic plants’ growth characteristics into account. The aquatic vegetation coverage was used to characterize the degree of the lake ecological restoration. The relationship between water level and vegetation coverage was established. We chose the Tangxun Lake as a testbed, and the recommended lowest EWL was 16.6 m, as the minimum threshold for water level regulations. The results revealed that the predicted vegetation coverage decreased with the rise of water level during the germination period (February and March). To achieve the vegetation coverage goal of 30% and 50%, the lake’s water levels must be lowered to 17.1 m and 16.8 m respectively during germination. The EWLs were recommended to be low in spring and high in summer, which was matched with the natural water level regimes. The proposed approach can provide a reliable reference for water level regulation of shallow lakes especially the lakes with insufcient data. Lake is an important part of the natural ecosystem and plays a vital role in human’s survival and development. In the past decades, the hydrological regime of lakes has changed signifcantly in China due to the synergies of human activities and climate change, leading to a series of ecological problems, such as water environment dep- ravation, eutrophication aggravation and lakeside habitat destruction1–3. To address these problems, the govern- ment has tried numerous measures including strict control of point source pollution and some bioremediation technologies. Additionally, water level manipulation can be considered an efective tool for wetland restoration4,5. Water level is an important characteristic index to refect the lakes’ hydrological regime, as well as a key factor infuencing the distribution and diversity of aquatic plants in shallow lakes6,7. To maintain the lakes’ basic ecolog- ical functions, the concept of lake ecological water level (EWL) was developed. And it was defned as the optimal water level for maintaining the ecosystem integrity, protecting the biodiversity, improving the environmental quality and ensuring the ecosystem stability8,9. A thorough understanding of EWL is critical to restoring the lake ecosystems10. Tere has been an increasing number of studies on the EWL of lakes, and these studies mainly focus on two aspects: (1) the infuences of water level fuctuations on the establishment and development of biological com- munities in lakes; (2) the active or passive responses of biological communities to the water level fuctuations of lakes. Water level fuctuations, especially their extent, frequency and duration, have great efects on the lake’s physical environment and biological communities6,11. Particularly, since aquatic plants play a vital role in the maintenance of lake ecosystem health, much research has been undertaken to investigate the impacts of water level fuctuations on aquatic plants by using ecological indicators such as biodiversity and coverage12–14. It has been found that minor changes in water levels could produce huge alterations in plant communities15. Moreover, the rates of water level change are also dominant forces afecting the growth and development of aquatic plants. Aquatic plants gradually adapt to the natural hydrological regime in the long process of evolution, and they have diferent water level requirements at diferent growth stages16. Based on this, many countries have attempted to formulate water level manipulation schemes to restore natural water level regimes and ensure the species diversity and ecosystem stability of lake wetlands. 1Hubei Provincial Water Resources and Hydropower Planning Survey and Design Institute, Wuhan, 430064, China. 2State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China. *email: [email protected]; [email protected] SCIENTIFIC REPORTS | (2020) 10:5637 | https://doi.org/10.1038/s41598-020-62454-5 1 www.nature.com/scientificreports/ www.nature.com/scientificreports How to determine the appropriate EWLs in shallow lakes has become a new research hotspot. Since the end of the 20th century, a variety of methods have been developed for calculating the EWLs. Te scope of the EWLs assessment methods has gradually broadened from the hydrological analyses, towards more comprehen- sive approaches. Commonly used methodologies fall into four categories: historical fow record methodolo- gies, hydraulic rating methodologies, habitat rating methodologies, and holistic methodologies17. Te historical fow record methodologies and the hydraulic rating methodologies rely heavily on the availability of reliable long-term hydrological data9,18. Tese two methodologies are based on the concept that water levels below the natural water levels will destroy the ecosystem integrity19. Te habitat rating methodologies were derived from the hydraulic rating methodologies and were widely used in recent years. Tey draw on the ecological require- ments of indicator species to assess the suitability for ecosystem processes. And the common approaches include the Physical Habitat Simulation Model20, the Minimum Biological Space Requirements Method21, the Instream Flow Incremental Methodology22 and the Habitat Analysis Method23. Te holistic methodologies are comprehen- sive multidisciplinary approaches considering both hydrological and ecological indicators. Since the interaction mechanism between hydrological factors and ecological factors is extremely complicated, the research of this methodology is still at its initial period24. Among the existing methodologies, most of them were developed to determine the environmental fow requirements of rivers, while they could not directly applicable to lake wet- lands. Moreover, the primary focuses of these methods have been on the lowest EWLs, with less emphasis on the efects of dynamic water level fuctuations on the aquatic species. However, a single EWL value could not meet the water level requirements at diferent growth stages of aquatic species25,26. Te extent, frequency and duration of water levels are more worthy of attention. Terefore, further studies are still necessary to develop the methods for EWLs calculation in lakes that could meet the water level requirements at diferent growth stages of aquatic species. In this study, we developed an approach for calculating the suitable monthly EWLs of shallow lakes. Te essence of this approach was to regulate the water level based on the water level requirements of aquatic plants. Te vegetation coverage was used as an indicator of ecological health in this approach. Te lowest EWL was cal- culated as the minimum threshold for water level regulation using three approaches. Te principle and procedure of this method were introduced in detail, and then the methodology was applied to the Tangxun Lake. Materials and Methods Study area. In this study, we selected the Tangxun Lake in China as the study area. It is the largest urban lake in China and located in the middle and lower reaches of the Yangtze River (Fig. 1). Te Tangxun Lake has a water surface area of 52.19 km2 and drains a watershed area of 240.38 km2. It is a typical subtropics shallow lake with an average water depth of 1.85 m. It serves as the main water source of drinking, irrigation and aquaculture for Wuhan, the capital city of Hubei Province. Te Tangxun Lake used to be the largest original ecological lake in Wuhan. However, in recent years, the increase of population and economic development in the basin, especially the construction of industrial parks and development zones around the basin since 1996, has discharged a large amount of pollutant load that exceeds the environmental capacity of the water body, resulting in water pollution and eutrophication in the lake. As a result, the biological diversity and the aquatic vegetation coverage are sharply reduced, which poses a serious threat to the health of the surrounding residents. Traditional methods for estimating EWLs. Te lowest EWLs are generally emphasized in traditional methods of estimating the EWLs, and are usually estimated through the following approaches. Lake morphological analysis method (LMAM). Te LMAM was proposed by Xu et al. and was widely used in China27. In this method, water level is used as the index of lake topography and hydrological condition, and lake area is used as the index of lake function. Based on the measured water level and lake area data, the relation curve between water level and lake area can be established. Te change rate of lake area is the frst derivative of the rela- tion function between lake area and water level. Te water level corresponding to the maximum change rate of the lake area is treated as the lowest EWL of the lake. A major assumption of this method is that if the water level is lower than the lowest ecological water level, the surface area of the lake will be signifcantly reduced and the lake function will be seriously degraded. Tis method can be expressed as: Ff= ()H (1) ∂2F = 0 ∂H2 (2) where F is lake area (m2); H is water level (m). Te lowest EWL can be obtained by solving the equations. Natural water level statistics (NWLS). Some researchers demonstrated that the annual and inter-annual changes in water level cause disturbance to the lake ecosystem under natural conditions21. Te premise of the NWLS is that the lake ecosystem has adapted to the disturbance of lake level during the long ecological evolution28. Te long-term daily water level data is required in this method, then the water level guarantee rate curve can be plot- ted. Te water level with guarantee rate of 95% is generally considered as the lowest EWL29,30. Biological living space requirement method (BLSRM). Te aquatic organisms in lakes include phytoplankton, emergent plants, zooplankton, fshes and so on.