Material and Methods Optimization of the Acid Catalyst Concentration for Synthesis of Anti‐Cancer Agent Gamavuton‐0 by Using Mathematical and Statistical Software

73 Figure 2. Elevation Data in the Sungai Mariam Mahakam Estuary The averaged monthly river discharge data of the Mahakam river – 8 obtained from the Research and Development rrigation Ministry Public Work, Republic of ndonesia are shown in Fig. Figure 3. The average monthly river discharge data of the Mahakam river 2.2. Hydrodynamics Model Estuary and Coastal Ocean Model with Sediment Transport ECOMSED is a three‐ dimensional hydrodynamic and sediment transport model. The hydrodynamic module solves the conservation of mass and momentum equations with a . ‐level turbulent closure scheme on a curvilinear orthogonal grid in horizontal plane and ‐coordinate in the vertical direction. Water circulation, salinity, and temperature are obtained from the hydrodynamic module. The sediment transport module computes the sediment settling and resuspension processes for both cohesive and noncohesive sediments under the impact of waves and currents. The governing equations of the hydrodynamic component in ECOMSED are the continuity equation, Reynold’s equations, heat and salinity transport equations. The basic equations for the three-dim ensional m ode are: The continuity equations:          z W y V x U , 74 where U,V,W are the eastward z , northward y , and upward z components of the current. A dynamic boundary condition evaluated at the sea surface z =  will indicate the relation between sea surface elevation  and vertical velocity at the sea surface W  as,       W V y U x t          , The vertical velocity at the sea surface W  can be obtained by integrating from the bottom z = ‐H to the sea surface z = . The m om en tum equation s usin g the Boussin esq approxim ation s an d the assum ption of vertical hydrostatic equilibrium in Cartesian coordin ates are given below. , 2 1                                                           x V y U A y x U A x z U A z x P fV z U W y U V x U U t U M M V  3 , 2 1                                                           y V A y x V y U A x z V A z y P fU z V W y V V x V U t V M M V  4     z dz B g P    , g B      , an d, the equation s of tem perature an d salin ity, ,                                             y T H A y x T H A x z T V K z z T W y T V x T U t T ,                                            y S A y x S A x z S K z z S W y S V x S U t S H H V 8 where T denotes the temperature, S the salinity, f the Coriolis parameter =  sin ;  = . x ‐ s ‐ and  is the latitude , ρ the density, ρ the reference density = . 8 kg m ‐ , g the acceleration of gravity = .8 m s ‐ , P the pressure, B the buoyancy, A V and K V the vertical eddy viscosity and vertical diffusion coefficient, A M the horizontal eddy viscosity, A H the horizontal diffusion coefficient. The horizontal eddy viscosity and diffusivity coefficient is given on the basis of Smagorinsky formula where they increase proportionally to the grid spacing and the velocity shear.   , 2 2 1 2 2 2                                  y V y U y V x U y x A A H M  where α is a constant = . and x and y are horizontal mesh size x = y = m . The vertical eddy diffusivity coefficients of momentum, temperature, salinity, and suspended sediment concentration are obtained through the . level turbulence closure scheme developed by Mellor and Yamada 8 . 7 The development of three‐dimensional ‐D hydrodynamic models started in the late s. Three‐dimensional hydrodynamic models are numerical code solving generally the Boussinesq equations. The availability of equations based on physical laws of classic mechanics, know from 8th century, is one of the main differences between hydrodynamic and biogeochemistry models, because equations for biogeochemical phenomena are generally not universally accepted and in most cases empirical or semi‐ empirical. 2.3. Ecosystem Model The biological model cycles concentrations of organic carbon and nitrogen through microplankton and detrital compartments with associated changes in dissolved concentrations of nitrate, ammonium and oxygen. The concentrations are updated in time by solving a transport equation for each state variable where by the biological interactions are included as source and sink terms and which takes account of vertical sinking and the physical transport by advection and diffusion. As an exception, chlorophyll is derived algebraically from microplankton carbon and nitrogen concentrations. The sediment model determines the time evolution and transport of inorganic particulate material. Exchanges between the water column and the seabed are modelled through a fluff” layer in the microplankton and detritus compartments and in the sediment model. The nutrient N N and N P N N ; Dissolved norganic Nitrogen and N P ; Phosphate , phytoplankton P, zooplankton Z and detritus D are included in this numerical ecosystem model Yanagi, ; Anukul et al., 8 . The concentration of dissolved oxygen O is calculate at the same time. The state variables obey the following equations which include advection, diffusion and biochemical processes : , 3 2 1 Z A P A P A z P V K z x P H K x z P p S z P W y P V x P U t P                                        , 6 5 4 3 Z A Z A Z A Z A z P V K z x P H K x z Z W y Z V x Z U t Z                                      , 7 6 1 Z A Z A Z A z P V K z x P H K x z N N W y N N V x N N U t N N                                     , 7 6 1 D A P A P A z P N V K z x P N H K x z P N W x P N U t P N                                      , 7 5 4 2 D A D A P A P A z D V K z x D H K x z D D S z D W x D U t D                                      7 . 4 3 2 1 2 2 2 2 2 P B P B P B P B z O V K z x O H K x z O W x O U t O                                       The origin of the Cartesian coordinate system is set at the sea surface of the estuary head with the x ‐ axis directed toward the estuary mouth and the z‐axis upward. U and W denote the velocity in the x and z directions, respectively. Sp denotes the sinking speed of phytoplankton and SD that of detritus. K H and K V denote the horizontal and vertical diffusivities, which depend on the tidal current Amplitude and the Richardson number. The computational domain, grid spacing and time steps were the same as those of ECOMSED the same as those of temperature and salinity with fixed values at all grid locations along the boundary plane throughout model operation. The loads of major rivers were taken into consideration, while non‐point source nutrients along coastlines were ignored due to a lack of reliable data. nitial values of ecosystem parameters, derived from the overall average of measured data, were set to be identical in all experiments – . mg m– , . µM‐N l – and . µM‐P l– for chl‐a, DN and DP, respectively. Zooplankton and detritus were assigned as 8. of chl‐a and equal to chl‐a concentrations, respectively, similar to the lateral boundary setting. The model operation was tested and a steady state of all simulated parameters was attained after days of computation. Calculated results were collected and averaged from days to in the same way as those of circulation model. Simulated chl‐a distributions in the same months of observational cruises are presented and discussed.

3. Results and Discussion

Simulations of the spatial and temporal variations in chlorophyll‐u, nitrate, phosphate and suspended particulate matter distributions in winter, spring and summer show how the development of the spring bloom and subsequent maintenance of primary production is controlled by the physicochemical environment of the plume zone. Results are also shown for two stations, one characterized by the high nutrient and suspended matter concentrations of the plume and the other by the relatively low nutrient and sediment concentrations of the offshore waters. The modelled net primary production at the plume site was g C m‐ a‐’ and g C m‐ a‐’ offshore. Primary production was controlled by light limitation between October and March and by the availability of nutrients during the rest of the year. The phytoplankton nutrient demand is met by in‐situ recycling processes during the summer. The likely effect of increasing and decreasing anthropogenic riverine inputs of nitrate and phosphate upon ecosystem function was also investigated. Modelling experiments indicate that increasing the nitrogen to silicate ratio in freshwater inputs increased the production of non‐siliceous phytoplankton in the plume. The results of this model have been used to calculate the annual and quarterly mass balances describing the usage of inorganic nitrogen, phosphate and silicate within the plume zone. The modelled Mahakam Estuary retains . of the freshwater dissolved inorganic nitrogen, . of the freshwater phosphate and . of the freshwater silicate input over the simulated seasonal cycle. The remainder is transported into the Makassar Strait in either dissolved or particulate form. The reliability of these results is discussed. 77 Figure 4. Verification model between simulation and observation data for nitrate and phosphate a b c Figure 5. Distribution pattern a DP, b DN, and c Chl‐a in the Mahakam Estuary. Acknowledgement The author would like to thank The Ministry of Research, Technology, and igher Education Republic of ndonesia and for financial support. References Buranaprathprat. B, Yanagi. T, Niemann. K, Matsumura. K, and Sojisporn. P. 8 . Surface chlorophyll‐a dynamics in the upper Gulf of Thailand revealed by a coupled hydrodynamic‐ecosystem model. Journal of Oceanography,Vol. , pp. ‐ . Allen, G.P., and Chambers, J.L.C. 8 . Sedimentation in the Modern and Miocene Mahakam delta, Jakarta, ndonesia Petroleum Association, Field Trip Guidebook. Andreas. M, and Gunther. R . Reviewe of three‐dimensional ecological modelling related to the North Sea shelf system: Part : models and their results. Progress in Oceanography, Vol. , pp ‐ . Blumberg, A.F., and G. L. Mellor. 8 A description of a three‐dimensional coastal ocean model”, n: Coastal and Estuarine Sciences , Three‐Dimensional Coastal Ocean Models”, Amer Geophys. Union, Washington D.C., – . 0.000 0.005 0.010 0.015 0.020 0.025 0.030 0.035 0.040 0.045 0.050 0.055 0.060 0.065 0.070 Nitrate Simulation results Month mm ol l Observation data 0.000 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 Phosphate Simulation results Month mm ol l Observation data