State and parameter update of a hydrodynamic-phytoplankton model using ensemble Kalman filter

Gao, Junfeng; Liu, Jutao; Zhang, Yinjun

doi:10.1016/j.ecolmodel.2013.04.022

Cited by 34 publications

(21 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Forecasting algal blooms in lakes is relatively new (Kim et al, 2014) but is increasingly becoming a requirement for lake and reservoir managers (Huang et al, 2013;Recknagel et al 2014;Xiao et al, 2017) to help inform decisions regarding timely and cost-effective management interventions. The fact that limmnology is rapidly becoming data-rich (Marcé et al, 2016;Xiao et al, 2014) means that effective realtime forecasts are increasingly more feasible.…”

Section: Introductionmentioning

confidence: 99%

“…There are still relatively few studies for operational lake forecasting systems and various approaches have been taken such as using: Ensemble Kalman Filter (EnKF; Evensen, 1994) schemes and physically-based simulation models (e.g. Allen et al, 2003, Huang et al 2013and Kim et al, 2014; evolutionary computation (Recknagel et al, 2014;Ye et al, 2014); Lagrangian particle tracking model methods (Rowe et al, 2016); and a combination of wavelet analysis and neural networks (Luo et al, 2011;Xiao et al, 2017). The EnKF has been developed to deal with highly non-linear model dynamics which cannot be represented well using the traditional Kalman Filter.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive forecasting of phytoplankton communities

et al. 2018

View full text Add to dashboard Cite

The global proliferation of harmful algal blooms poses an increasing threat to water resources, recreation and ecosystems. Predicting the occurrence of these blooms is therefore needed to assist water managers in making management decisions to mitigate their impact. Evaluation of the potential for forecasting of algal blooms using the phytoplankton community model PROTECH was undertaken in pseudo-real-time. This was achieved within a data assimilation scheme using the Ensemble Kalman Filter to allow uncertainties and model nonlinearities to be propagated to forecast outputs. Tests were made on two mesotrophic lakes in the English Lake District, which differ in depth and nutrient regime. Some forecasting success was shown for chlorophyll a, but not all forecasts were able to perform better than a persistence forecast. There was a general reduction in forecast skill with increasing forecasting period but forecasts for up to four or five days showed noticeably greater promise than those for longer periods. Associated forecasts of phytoplankton community structure were broadly consistent with observations but their translation to cyanobacteria forecasts was challenging owing to the interchangeability of simulated functional species.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive forecasting of phytoplankton communities

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Lawson et al [43] have used adjoint method and also given a description of how the adjoint technique is combined with optimization techniques. Recently, Huang et al [52] has discussed the parameter identification of hydrodynamic-phytoplankton model. Parameter estimation of a Lotka-Volterra system using experimental data can be found in [53].…”

mentioning

confidence: 99%

Dynamical analysis of a prey–predator model with Beddington–DeAngelis type function response incorporating a prey refuge

2014

View full text Add to dashboard Cite

This paper discusses a prey-predator model with reserved area. The feeding rate of consumers (predators) per consumer (i.e., functional response) is considered to be Beddington-DeAngelis type. The Beddington-DeAngelis functional response is similar to the Holling type II functional response but contains an extra term describing mutual interference by predators. We investigate the role of reserved region and degree of mutual interference among predators in the dynamics of system. We obtain different conditions that affect the persistence of the system. We also discuss local and global asymptotic stability behavior of various equilibrium solutions to understand the dynamics of the model system. The global asymptotic stability of positive interior equilibrium solution is established using suitable Lyapunov functional. It is found that the Hopf bifurcation occurs when the parameter corresponding to reserved region (i.e., m) crosses some critical value. Our result indicates that the predator species exist so long as prey reserve value (m) does not cross a threshold value and after this value the predator species extinct. To mimic the real-world scenario, we also solve the inverse problem of estimation of model parameter (m) using the sampled data of the system. The results can also be interpreted in different contexts such as resource conservation, pest management and

show abstract

“…One way to overcome such difficulties is to assimilate either in situ or satellite-derived data to guide and tune the coupled model. Indeed, data assimilation has been increasingly used to improve the model performance [32,[34][35][36][37][38][39][40][41].…”

Section: Introductionmentioning

confidence: 99%

An EOF-Based Algorithm to Estimate Chlorophyll a Concentrations in Taihu Lake from MODIS Land-Band Measurements: Implications for Near Real-Time Applications and Forecasting Models

Duan

et al. 2014

Remote Sensing

View full text Add to dashboard Cite

For near real-time water applications, the Moderate Resolution Imaging Spectroradiometers (MODIS) on Terra and Aqua are currently the only satellite instruments that can provide well-calibrated top-of-atmosphere (TOA) radiance data over the global aquatic environments. However, TOA radiance data in the MODIS ocean bands over turbid atmosphere in east China often saturate, leaving only four land bands to use. In this study, an approach based on Empirical Orthogonal Function (EOF) analysis has been developed and validated to estimate chlorophyll a concentrations (Chla, μg/L) in surface waters of Taihu Lake, the third largest freshwater lake in China. The EOF approach analyzed the spectral variance of normalized Rayleigh-corrected reflectance (Rrc) data at 469, 555, 645, and 859 nm, and subsequently related that variance to Chla using 28 concurrent MODIS and field measurements. This empirical algorithm was then validated using another 30 independent concurrent MODIS and field measurements. Image analysis and radiative transfer simulations indicated that the algorithm appeared to be tolerant to aerosol perturbations, with unbiased RMS uncertainties of <80% for Chla ranging between 3 and 100 μg/L. Application OPEN ACCESSRemote Sens. 2014, 6 10695 of the algorithm to a total of 853 MODIS images between 2000 and 2013 under cloud-free conditions revealed spatial distribution patterns and seasonal changes that are consistent to previous findings based on floating algae mats. The current study can provide additional quantitative estimates of Chla that can be assimilated in an existing forecast model, which showed improved performance over the use of a previous Chla algorithm. However, the empirical nature, relatively large uncertainties, and limited number of spectral bands all point to the need of further improvement in data availability and accuracy with future satellite sensors.

show abstract

State and parameter update of a hydrodynamic-phytoplankton model using ensemble Kalman filter

Cited by 34 publications

References 51 publications

Adaptive forecasting of phytoplankton communities

Adaptive forecasting of phytoplankton communities

Dynamical analysis of a prey–predator model with Beddington–DeAngelis type function response incorporating a prey refuge

An EOF-Based Algorithm to Estimate Chlorophyll a Concentrations in Taihu Lake from MODIS Land-Band Measurements: Implications for Near Real-Time Applications and Forecasting Models

Contact Info

Product

Resources

About