Numerical Study And Application Of A Marine Ecosystem Dynamical Model With Adjoint Assimilation Method

One typical feature of ecosystems is nonlinearity. Even small perturbations can beamplified through nonlinear interactions. Therefore, parameter values cansignificantly affect the model results in the simulation of marine ecosystem dynamics.However, it is very difficult to estimate parameter values accurately. Not only becauseare there very high correlations between some parameters, but also that someparameters are not constant. Parameter values in different sea areas are not same dueto different environmental factors, such as temperature, light intensity and so on. Evenwithin the same sea area, environmental factors such as temperature, light intensitymay change over time, indicating that the values of the parameter changes over time,too. In previous studies, there always has been a large discrepancy between simulationresults and observations because most researchers treated ecological parameters asconstant, and this difficult problem can not be solved by increasing the complexity ofthe model.In this paper, a typical3-dimension nutrient-phytoplankton-zooplankton-detritus(NPZD) marine ecosystem dynamical model and the corresponding adjoint model areconstructed in the Bohai Sea and the Yellow Sea. The three-dimensional PrincetonOcean Model (POM) is used to calculate the ambient physical velocities, thetemperature, and the eddy diffusivities. Only the impact of background field onecological state variables is considered while the impact of ecological state variableon background field is neglected. The variational adjoint method is applied to estimatevalues of all the12parameters by utilizing real chlorophyll data from theSea-Viewing Wide Field-of-view Sensor (SeaWiFS). The seasonal variabilities ofthese parameters are reconstructed. It looks that that some parameters are highly correlated and the time variances of most parameters seem reasonable. The simulatedresults show that using time varing parameters values accord much better with theobservations than by using constant parameters.In the study of estimating spatially varying parameters, five parameters whichhave greatest impact on simulation results are selected by a conventional sensitivityanalysis. In order to guarantee the continuity of parameter values and make thecalculated results more reasonable, several grids are selected as independent grids,and only the parameter value of these independent grids need to be optimized whilethe other grids are calculated by interpolation method. Based on this method, weconfirmed the optimal influence radius by a twin experiment. In the followingexperiments, when the five parameters are inversed respectively, spatial variations ofthe two given types can be reproduced very well. But when all the five parameters areestimated simultaneously, the collocation of the changing trend of each parameterinfluences the estimation results remarkably. Only when this collocation coincideswith the ecological mechanisms which influence the growth of the phytoplankton inthe model, can the five parameters be estimated accurately. The result demonstratesthat it is reasonable to take the spatial variation of parameters into account in theecosystem dynamical model. This method can be applied to real experiments toestimate the distributions of ecological control variables such as chlorophyll.The Bohai Sea is the only inland sea of China，and its organic pollutants aretremendous. Unfortunately, water exchange of the Bohai Sea is very weak and itsphysical self-clean capacity is poor due to its special geographical position, so it ishard to recover if the Bohai Sea is polluted. Therefore, an accurate simulation of thetime varying pollutant (e.g. total Nitrate, total Phosphate, COD) distribution is neededif we want to achieve sustainable development of economy. The initial condition hasdramatic influence on the results when simulating the time varying pollutantdistribution. In this paper, the pollution is treated as conservative substance, and onlythe transporting diffusion process of pollution is considered. The adjoint assimilationmethod is firstly applied to estimate the pollutant initial field as far as I know, and some independent grids are also selected as before to guarantee the continuity ofpollutant distribution. No matter a parabolic or conical surface the initial distributionof pollutant concentration shows, and regardless the pollutant concentration is higherin the center or not, the initial distribution can be inversed successfully. Comparedwith the traditional interpolation methods, the adjoint assimilation method caneffectively reduce the errors between simulation results and observations, which provethe stability and reliability of this model. Therefore, this model could be applied inreal experiment to simulate the initial field and the distribution of pollution in anytime step by using the regular monitoring observations, and then the monthly meandistribution of pollution can be calculated by the statistical method. The results showthat this method has important practical significance because it can be used for themonitoring and evaluation of the marine environmental quality.