Qiandao Lake Research Articles

A fault-tolerant algorithm of AUV formation based on reconfiguration map

Aiming at the fault occurrence of AUV formation members during sailing, a fault tolerance algorithm of AUV formation based on reconfiguration was proposed. Firstly, the cost matrix is designed based on the reconfiguration and Hungarian algorithm to solve the problem of assigning target points under the fault condition. Then, based on Bezier curves, the dynamic constraints of AUV are designed parametrically. The nonlinear optimization problem satisfies the constraints through the characteristics of spline curves, and the adaptive particle swarm optimization algorithm is used to solve the tracking trajectory. The comparison and simulation experiment of a particle swarm algorithm based on a reconfiguration map (RMPSO) was carried out. The simulation results show that under the same planned path, the total tracking path of the following AUV is shorter, the turning radius is smaller, and the heading Angle is more stable. Finally, field tests are carried out in Qiandao Lake to verify the effectiveness of the algorithm for formation faults.

Study on the interaction characteristics of hull-propeller-appendages of autonomous underwater vehicle based on unsteady conditions

In order to improve the hydrodynamic performance of autonomous underwater vehicle (AUV), a new method is proposed to study the AUV hull-propeller-appendages interaction in coupled mode, considering the coupling effect between the AUV hull, propeller and appendages, and to predict the self-thrust point. Based on the Reynolds mean Navier-Stokes (RANS) solver and the RNG k−ε turbulence model, the hydrodynamic performance of the propeller and AUV is predicted. The error between the predicted results and the experimental results is within 5%, which verified the correctness of the modeling method based on CFD. Finally, the thrust and torque generated by the open-water propeller and the propeller after the boat, the hydrodynamic characteristics of the naked AUV and the AUV with appendages, and the interaction between hull-propeller-appendages under different working conditions are studied. Experiments are carried out in Qiandao Lake, Zhejiang Province, China. The numerical simulation results of AUV at 1.76 m/s are compared with the experimental results of 1.5 m/s, and the correctness of the proposed interaction method is verified. The research results not only provide theoretical guidance for the design and operation of AUV, but also have important significance for improving the performance and reliability of AUV in complex underwater environments.

Comparing diversity and structure of freshwater fish assemblages using environmental DNA and gillnetting methods: A case study of a large deep reservoir in East China

Environmental DNA (eDNA) technology, as an alternative to traditional gillnet surveys, has attracted widespread attention. However, comparisons between eDNA and traditional methods regarding biodiversity and community structure have not yet been fully elucidated. This study compared the ability of eDNA and gillnets for fish monitoring in a large deep reservoir (Qiandao Lake) in East China. The results showed that eDNA exhibited higher taxonomic resolution and detection rates, and significantly larger species diversity and richness indices compared with traditional gillnetting methods. Using abundance and biomass datasets from gillnets revealed significant differences in fish community composition between gillnetting and eDNA survey methods. Gillnet abundance was dominated by small-sized fish species, while gillnet biomass was dominated by larger-sized ones, and the prevailing species detected in eDNA reads included the dominant species from gillnet abundance and biomass, as well as a medium-sized invasive alien fish (Lepomis macrochirus). Non-metric multidimensional scaling (NMDS) showed that the spatial distribution in abundance of fish species sampled by gillnetting was more dispersed than that using eDNA. The explanatory power with the gillnet abundance and biomass together as predictor variables of the eDNA reads increased moderately compared with taking them separately, and the fitting degree of quadratic functions was also improved somewhat compared to linear equations when using biomass to predict eDNA reads. Furthermore, the key environmental factors affecting fish communities differed between the two methods. Current research indicates that eDNA has advantages over gillnets in detecting fish species diversity, and it is recommended to combine it with traditional sampling methods. Under natural aquatic ecosystem conditions, the eDNA reads may comprehensively reflect the biomass and abundance information obtained through gillnetting, but their relationship is complex and requires further research. This study will provide guidance for biodiversity monitoring.

Color-restoring and energy-saving imaging monitoring for intelligent offshore engineering

Images play a crucial role in artificial intelligence (AI) for offshore engineering, which provide a large amount of data for machine intelligence to ensure the safe operation and maintenance of offshore structures. However, due to the attenuation of sunlight in water or monitoring at nighttime, underwater imaging monitoring systems need a light source, which consumes a lot of energy and impacts the load capacity of an offshore monitoring system. In addition, due to the nonlinearity of attenuation at different wavelengths, underwater images generally suffer from color deviation, tending to be blue and green, which decreases the accuracy of machine learning and intelligent recognition in unmanned offshore engineering. In order to reduce energy consumption and enhance color restoration, we proposed and designed a three-detector underwater imaging system (TD&TP-UIS) based on a prism, in which three detectors were used to enhance the utilization efficiency of light, and a gated band coating was designed on the prism to enhance the color reproduction. A series of experiments were carried out in water tanks, pools, Qiandao Lake, and other places to verify the advantage of color restoration and energy saving using the TD&TP-UIS.

Effects of filter-feeding fish faeces on microbial driving mechanism of lake sediment carbon transformation

Silver carp (Hypophthalmichthys molitrix) can filter the carbon in the food taken up by phytoplankton and plays an important role in carbon fixation. In this study, the faeces of silver carp, the dominant fish species in Qiandao Lake, China, were collected and subjected to a closed incubation and transformation experiment for three months. The physical and chemical indices of water and sediment mixture, carbon metabolic enzyme activity, and microbial sequences were analyzed to identify the key microbial strains that affect carbon transformation as well as the main factors influencing carbon transformation. The results showed maximum CO2 and CH4 emission fluxes on day 15 of fish faeces and sediment interaction. In the faeces addition group, the contents of soluble organic carbon, soluble inorganic carbon, SO42−, and PO43− were significantly increased, while the dissolved oxygen content was significantly decreased. Furthermore, the pH, total carbon content, volatile suspended solids content, and activities of four carbon-metabolizing enzymes were significantly increased in the faeces addition group. The 16sRNA analysis of methanogenic and methane-oxidizing bacteria showed that Euryarchaea and Pseudomonas accounted for the highest proportion respectively. The most significant differences expression were found for Methylbacterium in the methanogenic bacteria and Methylobacter in the methane oxidizing bacteria. Structural variance model showed that interaction of fish faeces and sediments mainly caused changes in sulfate content, leading to variations in methanogens and methanotrophs and promotion of CH4 emission. The results of this study can provide a theoretical reference for the mechanism of carbon reduction and emission reduction of lake filter-feeding fish.

Evaluation of the efficacy of implementing Ecosystem-Based Management (EBM) strategies within fisheries across the middle and lower Yangtze River basin lakes in China

To mitigate the decline of fishery resources and the exacerbation of water pollution in Chinese lakes and to enhance the potential and sustainable use of lake fisheries, the Chinese government has actively implemented principles and models of ecosystem-based lake fishery management. This includes promoting ecological aquaculture techniques and the “retiring pens to restore lakes” policy. To assess the effects of ecosystem-based management on Chinese lake fisheries, data from 2007 to 2020 were collected for the Qiandao Lake, Tai Lake, Hongze Lake, Luoma Lake, and Gaobao Lake in the middle and lower reaches of the Yangtze River. The study employed Data Envelopment Analysis (DEA) to assess fishing efficiency through a static input-output efficiency model. Additionally, the Malmquist index and distance functions were used for a dynamic comparison of total factor productivity (TFP) across the five lake management models. The results indicate that trends in technological progress, scale efficiency, and TFP were consistent across the lakes from 2013 to 2020. Qiandao Lake, Tai Lake, and Hongze Lake showed a positive average annual growth rate in TFP, with Qiandao Lake having the highest average annual growth rate of 13.2%. In contrast, Gaobao and Luoma Lakes experienced a negative growth rate in TFP. Furthermore, Qiandao Lake exhibited significantly higher technical efficiency than the other four lakes, effectively achieving an efficient state, followed by Hongze Lake. The study demonstrates that technological progress and variations in scale efficiency are the primary factors driving the increase in TFP in fisheries. Promoting ecosystem-based “fishing for water conservation” aquaculture techniques and restricting aquaculture scale through the “retiring pens to restore lakes” policy contribute to enhancing TFP in ecological fisheries.

Exploring the relationship between cultural ecosystem services and human well-being of Qiandao Lake in China: insights from tourists and residents

Abstract Landscapes of lakes have a significant impact on people's perceptions of Cultural Ecosystem Services (CES), as well as on their overall sense of well-being. However, there is limited understanding of how best to manage land landscapes and how different approaches influence these perceptions. To explore these questions, a case study of China's Qiandao Lake was conducted, using a survey of 416 tourists and residents based on the Millennium Ecosystem Assessment (MA) framework. The relationship between CES and Human Well-Being (HWB) was examined using Structural Equation Modeling (SEM), followed by the application of the Importance-Performance Analysis (IPA) method to identify which aspects should be targeted in management strategies. The results revealed several key findings. Firstly, there were significant differences in satisfaction with CES between tourists and residents. Tourists showed higher satisfaction levels in spiritual service, aesthetic service, inspiration, and education and science aspects. In contrast, residents prioritized cultural heritage and sense of place, indicating a deeper connection to the cultural and historical elements of their environment. Secondly, age, education, and income levels played important roles in shaping perceptions of CES. Thirdly, the study underscored the impact of CES on HWB, with aesthetic service having the greatest influence on tourists' HWB, and spiritual service having the most impact on residents' HWB. Lastly, using the IPA model, indicators with low satisfaction but high importance were identified, suggesting areas for improvement, particularly in cultural integration and unique environmental features. These research findings provide scientific and theoretical support for the management and landscape planning of lake ecosystems.

A hybrid water quality prediction model based on variational mode decomposition and bidirectional gated recursive unit.

Water quality predicted accuracy is beneficial to river ecological management and water pollution prevention. Owing to water quality data has the characteristics of nonlinearity and instability, it is difficult to predict the change of water quality. This paper proposes a hybrid water quality prediction model based on variational mode decomposition optimized by the sparrow search algorithm (SSA-VMD) and bidirectional gated recursive unit (BiGRU). First, the sparrow search algorithm selects fuzzy entropy (FE) as the fitness function to optimize the two parameters of VMD, which improves the adaptability of VMD. Second, SSA-VMD is used to decompose the original data into several components with different center frequencies. Finally, BiGRU is employed to predict each component separately, which significantly improves predicted accuracy. The proposed model is validated using data about dissolved oxygen (DO) and the potential of hydrogen (pH) from the Xiaojinshan Monitoring Station in Qiandao Lake, Hangzhou, China. The experimental results show that the proposed model has superior prediction accuracy and stability when compared with other models, such as EMD-based models and other CEEMDAN-based models. The prediction accuracy of DO can reach 97.8% and pH is 96.1%. Therefore, the proposed model can provide technical support for river water quality protection and pollution prevention.

Heterogeneous vehicle scheduling with precedence constraints

The problem of heterogeneous vehicle scheduling with precedence constraints is inspired by the transportation service in tourism areas. Tourists must take the shuttle vehicles provided by the areas because of the long distances between the scenic spots. The scheduling of vehicles in tourism areas is complicated because the transportation requests of tourists are precedence-constrained temporally and spatially. The problem optimises both the cost of using vehicles and the waiting time of tourists. A mixed-integer linear programming model is formulated according to the description of a graph. An adaptive large neighbourhood search algorithm with several specialised operators is designed to solve the problem. Experiments based on randomly generated instances validate the mathematical model and the algorithm. A real-size instance based on Qiandao Lake in China is also analysed. The results indicate that the algorithm outperforms the model. The sensitivities of key parameters are analysed with managerial insights presented.

On the importance of mooring cable dynamics in response analysis of submerged floating tunnel using quasi-static and fully coupled dynamic models

Submerged floating tunnels are considered an economical alternative to those conventional bridges in crossing deep and long-span water bodies. The development of accurate modeling methods and simulation tools is the primary requirement for the safe design of submerged floating tunnels. Mooring cables are the primary source of stability of submerged floating tunnels against hydrodynamic loadings, and are commonly modelled using the computationally efficient quasi-static catenary approach. The dynamics of mooring cables can be of significant importance in dynamic responses of the submerged floating tunnel. Therefore, in this study, a discrete catenary element is presented with the aim of its implementation in the fully coupled dynamic analysis of submerged floating tunnels. To study the effect of mooring cable dynamics, the prototype of Qiandao Lake submerged floating tunnel has been used in a comparative study between quasi-static and fully coupled dynamic models. The numerical examples show differences in displacements and cable tensions due to the mooring cable dynamics. Furthermore, the mooring cables dynamics have significant effect on the tunnel shear forces and bending moments. The quasi-static coupled modeling significantly underestimates the tunnel internal forces.

Epitypification and emended description of Cyclotella hubeiana, a centric diatom from Central China, with remarks on its distribution and ecology

Since its description by Chen and Zhu in 1985 from samples collected in a river and reservoir from Hubei Province (Central China), Cyclotella hubeiana has been reported from several sites in central and southern China. Only line drawings were provided with the original description and the same drawings were used in the subsequent diatom floras from China. The more recent reports of this species come from limnological studies which generally do not provide illustrations. There is therefore a need to better illustrate this taxon. As the type material could not be retrieved, new material was collected from the type locality (Xionghe Reservoir) to elucidate its ultrastructure using light and electron microscopy. The figures published by Chen and Zhu in 1985 are designed as lectotype and the new material as epitype to the lectotype. Characteristics of the valve such as the position of the rimoportula (on a costa, within the ring of marginal fultoportulae) and the absence of central fultoportulae on the valve face suggest that this species is best placed within the genus Cyclotella as presently defined. Its morphology is compared with similar species of Cyclotella and Pantocsekiella. In addition, in a study on Qiandao Lake, a reservoir from Zhejiang Province (eastern China), a large population of this taxon was found in down-core assemblages within 20 years of the reservoir being impounded. This abundant material allowed a better assessment of the size range and morphological variability of this species. Besides emending the description and validating the taxonomic status of this species, this study also discusses its ecology and distribution.

Revealing the Diversity of Thin Filamentous Cyanobacteria, with the Discovery of a Novel Species, Pegethrix qiandaoensis sp. nov. (Oculatellaceae, Oculatellales), in a Freshwater Lake in China

During the study of diversity in filamentous cyanobacteria in China, two strains (WZU0719 and WZU0723) with the form of thin filaments were isolated from the surface of Qiandao Lake, a large freshwater lake in Zhejiang Province, China. A comprehensive analysis was conducted, incorporating morphological, ecological, and molecular data. The morphological examination provided an initial identification as a Leptolyngbya-like cyanobacterium. Genetic characterization was also performed by amplifying the 16S rRNA gene and the 16S-23S rRNA internal transcribed spacer (ITS) region. The phylogenetic grouping based on the 16S rRNA gene demonstrates that the examined strain is unequivocally assigned to the Pegethrix genus. However, it possesses distinct phylogenetic divergence from the six described Pegethrix species. Additionally, discrepancies in habitat further differentiate it from other members of this genus. Employing the polyphasic approach, we present a comprehensive account of the newly discovered taxa: Pegethrix qiandaoensis sp. nov. The novel taxonomic finding in this research significantly contributes to enhancing the comprehension of Pegethrix diversity across various habitats.

Robust Positioning Estimation for Underwater Acoustics Targets with Use of Multi-Particle Swarm Optimization

With the extensive application of sensor technology in scientific ocean research, ocean resource exploration, underwater engineering construction, and other fields, underwater target positioning technology has become an important support for the ocean field. This paper proposes a robust positioning algorithm that combines the disadvantages of distributed estimation and particle swarm optimization, which can solve the large localization error problem caused by uncertainties in underwater acoustic communication and sampling processes. Considering the presence of ranging anomalies and sampling packet loss in underwater acoustic measurements, a weighted coupling filling method is used to correct the outliers in an underwater acoustic ranging signal. Based on the mapping model from the element array to the underwater acoustic responder, an unconstrained optimization algorithm for one-time localization estimation of underwater acoustic targets was established. Based on the one-time localization estimation results of underwater acoustic targets, an improved multi-particle swarm optimization estimation based on interactive search is proposed, which improves the accuracy of underwater target localization. The numerical results show that the positioning accuracy of the proposed algorithm can be effectively enhanced in cases of distance measurement errors and azimuth measurement errors. Compared with the positioning error before optimization, the positioning error can be reduced after optimization. Additionally, the experiment was carried out in the underwater environment of Hangzhou Qiandao Lake, which verified the positioning performance of the proposed algorithm.

Diving dynamics identification and motion prediction for marine crafts using field data

Ensuring accurate parameter identification and diving motion prediction of marine crafts is essential for safe navigation, optimized operational efficiency, and the advancement of marine exploration. Addressing this, this paper proposes an instrumental variable-based least squares (IVLS) algorithm. Firstly, aiming to balance complexity with accuracy, a decoupled diving model is constructed, incorporating nonlinear actuator characteristics, inertia coefficients, and damping coefficients. Secondly, a discrete parameter identification matrix is designed based on this dedicated model, and then a IVLS algorithm is innovatively derived to reject measurement noise. Furthermore, the stability of the proposed algorithm is validated from a probabilistic point of view, providing a solid theoretical foundation. Finally, performance evaluation is conducted using four depth control datasets obtained from a piston-driven profiling float in Qiandao Lake, with desired depths of 30 m, 40 m, 50 m, and 60 m. Based on the diving dynamics identification results, the IVLS algorithm consistently shows superior performance when compared to recursive weighted least squares algorithm and least squares support vector machine algorithm across all depths, as evidenced by lower average absolute error (AVGAE), root mean square error (RMSE), and maximum absolute error values and higher determination coefficient (R2). Specifically, for desired depth of 60 m, the IVLS algorithm achieved an AVGAE of 0.553 m and RMSE of 0.655 m, significantly outperforming LS-SVM with AVGAE and RMSE values of 8.782 m and 11.117 m, respectively. Moreover, the IVLS algorithm demonstrates a remarkable generalization capability with R2 values consistently above 0.95, indicating its robustness in handling varied diving dynamics.

Research on ocean-current-prediction-based virtual mooring strategy for the portable underwater profilers

The Argo Global Ocean Observing Network has remained the preeminent ocean observation network worldwide. Since the Argo buoys lack freedom of lateral movement, their wave-following working characteristics prevent them from completing the long-term observations in the designated sea area. Long-term monitoring of designated waters is often required, for example, to study the impacts of seabed mining on the marine environment in the surrounding sea area. To solve this problem, a portable underwater profiler (PUP) that combines the functionalities of profiling buoys and underwater gliders was devised. The PUP employs a center of gravity adjustment mechanism utilizing the double-weight block approach, enabling the pitch angle adjustment within -90° to 0°. Remarkably, the PUP weighs only 11.25 kg, meeting the requirements for rapid deployment. Furthermore, the prediction method of the ocean current velocity was optimized by employing the full-depth-averaged ocean current velocity instead of the depth-averaged ocean current velocity. To ensure continuous observation operations of the PUP within designated sea areas, a horizontal displacement correction strategy (HDCS) based on the virtual mooring concept is proposed. The effectiveness of the HDCS has been preliminarily validated through simulations and further confirmed through lake trials conducted in Qiandao Lake.

Extrinsic information based enhanced Doppler compensation for high-speed underwater acoustic mobile communication

In high-speed underwater acoustic mobile communication, achieving robust Doppler compensation is crucial due to the unpredictable changes in the Doppler factor. Due to the difficulty in optimizing Doppler estimation in turbo equalization through closed-form methods, a joint design of Doppler compensation, channel equalization, and decoding, is proposed to improve the accuracy of the Doppler compensation through integrated methods. Specifically, the proposed scheme utilizes extrinsic information provided by the decoder to evaluate the effectiveness of Doppler compensation because the extrinsic information indirectly reflects the accuracy of Doppler estimation. The proposed algorithm performs parallel Doppler resampling through multiple joint Doppler compensation, equalization, and decoding to optimize Doppler estimation by searching for the best extrinsic information. With iterative Doppler compensation and channel equalization, the accuracy of Doppler estimation is enhanced, leading to improved signal detection performance. The proposed algorithm was verified by underwater test data collected in Qiandao Lake, Hangzhou, China in May 2016. The results of this evaluation provide practical validation and demonstrate the effectiveness of the proposed algorithm in real-world underwater acoustic communication scenarios.

Integrating ecosystem services closely related to human well-being into the restoration and management of deep lakes facing multiple stressors: Lessons from long-term practice in Qiandao Lake, China

Deep-lake (reservoir) ecosystems provide valuable ecosystem services (ES) and generate significant ecosystem service values (ESV); however, reservoir ecosystems have suffered great losses from environmental changes and human activities. Currently, studies on ES and its correlations with stressors remain insufficient and the integration of ES into ecological restoration and management poses numerous challenges. Here, we combined four types of stressors with six ES closely related to human well-being to discuss their interactions in Qiandao Lake (a representative deep lake in China). Our results indicate that all ESV showed a consistent growth trend throughout the study period, reaching 5203.8 million CNY in 2018, and the cultural service value surpassed the provisioning service value for the first time in 2004. Almost all the ESV were limited during the cyanobacterial bloom in Qiandao Lake. Redundancy analysis and partial least squares structural equation modeling jointly revealed that socioeconomic development was the most important direct driver of the increase in ESV (0.770) and that hydro-meteorological conditions (0.316) and pollutant loads (0.274) positively affected ESV by mediating lake trophic status. The trophic status of the lake is the result of the interaction of multiple stressors, which has a negative impact on ESV. Therefore, to continuously protect the provisioning and cultural service values of deep-lake ecosystems from damage, the government must rationally formulate SED goals and reduce pollutant loads during lake development, operation, and utilization. This work provides valuable insights into the interactions between ES, which are closely related to human well-being, and stressors in deep-lake ecosystems.

An iterative subblock-based receiver for SC-FDE systems in time-varying underwater acoustic channels

Traditional single-carrier frequency domain equalization (SC-FDE) systems assume time-invariant channels that are difficult to realize in underwater acoustic (UWA) communication over block-based durations, leading to inter-frequency interference (IFI). Currently available approaches to resolving this issue involve shortening the block or inserting frequent training sequences at the cost of additional information from the channel and reduced spectral efficiency. This paper proposes an iterative subblock-based receiver algorithm that divides each time-varying block into multiple quasi-static subblocks. The designed receiver has a two-step structure consisting of block processing and cascaded subblock processing, where the former generates prior symbolic knowledge and the latter iteratively weakens IFI. We consider smoothly variant channels between adjacent subblocks and track them using a Kalman filter, leading to a more accurate estimation of the IFI and better equalization. The proposed algorithm was tested through simulations and experiments in Qiandao Lake and the Yellow Sea using blocks of different lengths and numbers of subblocks and elements in the array. The results provide a low bit error rate.

Classification and Identification of Non-point Source Nitrogen Pollution in Surface Flow of the Shangwu River Watershed in the Qiandao Lake Region

Accurate quantification of non-point source pollution is an important step for non-point source pollution control and management at the watershed scale. Considering the non-point source pollution from baseflow, an improved export coefficient model (IECM) on a weekly scale was established based on the traditional export coefficient model (ECM), which was then used to estimate the surface flow non-point source total nitrogen (TN) loads contributed by different land use types of the Shangwu River watershed in the Qiandao Lake Region. The results showed that IECM performed well for the predictions of TN loads in the studied watershed, with the Nash-Sutcliffe efficiency coefficient (NSE) and R2values of 0.82 and 0.77 (P<0.01) for the calibration period and 0.87 and 0.84 (P<0.01) for the validation period, respectively. The IECM estimated TN exports through surface flow and baseflow were 5.74 kg·(hm2·a)-1and 9.85 kg·(hm2·a)-1 from the Shangwu River watershed in the period of Nov. 2020 to Oct. 2021, which accounted for 36.80% and 63.20% of the corresponding streamflow TN load, respectively. Without consideration of the baseflow non-point source TN pollution, the ECM-estimated surface flow TN loading was 54.21% higher than that estimated by IECM. Obviously, attributing baseflow non-point source pollution to surface flow directly would lead to a serious load overestimation of surface flow. According to IECM, the estimated TN export intensity through surface flow from paddy fields, grasslands, woodlands, rainfed croplands, and residential lands was 10.95, 5.42, 5.20, 12.34, and 2.77 kg·(hm2·a)-1, respectively, which accounted for 5.80%, 4.00%, 26.55%, 0.38%, and 0.03% of the corresponding total streamflow TN loads. Therefore, the future management of non-point source nitrogen pollution in the studied watershed should focus mainly on the prevention and management of groundwater non-point source pollution and control of load export from surface flow on cultivated land (paddy fields and rainfed croplands).

Multitask Sparse Bayesian Channel Estimation for Turbo Equalization in Underwater Acoustic Communications

In this article, a multitask sparse Bayesian learning channel estimation based on factor graphs (MT-SBL-FG) for turbo equalization (TEQ) in underwater acoustic (UWA) communications is proposed. Based on the framework of multitask sparse Bayesian learning, the received data are divided into subblocks and the channel estimation (CE) of each subblock is regarded as a task. Considering the time-varying channel in UWA communications and the CE error in turbo equalization, a factor graph is proposed for the multitask CE of the subblocks. Based on the factor graph, a message-passing algorithm with weighting factor is derived. The performance of channel estimation is improved by utilizing the temporal correlation between the subblocks and the sparsity of the UWA channel. The proposed algorithm has been tested by the underwater trial data collected in an experiment conducted in Qiandao Lake, Hangzhou, China, in May 2016. We have verified that the proposed algorithm outperforms other CE algorithms in terms of the bit error rate (BER).