2.3. Linkage of SS sub-module and RPI equation in WASP model
To obtain the correlations between Kaoping River flow rate and SS
concentrations, water samples were collected from 12 sampling stations
for SS measurement. Flow rate were monitored at water monitoring
stations at each sampling event. Flow velocity and flow rate
were measured following the methods described in NIEA (2004).
To determine the correlation between the flow rate and SS concentrations,
water sample collection and flow rate measurement
were performed during the dry and wet seasons. The collected
water quality and hydrological data were analyzed to evaluate
the correlation between SS and flow rate (Cencic and Rechberger,
2008). The obtained correlation was used for the development of
SS sub-model and was then linked to the WASP model for direct
SS estimation. To obtain the immediate RPI value and determine
the river water quality status, RPI index was embedded into the
WASP model for direct RPI calculation. Fig. 3 presents the simulation
process using RPI and WASP. Fig. 4 presents the process of the
modeling procedure repeated for each segment until all segments
met the requirements. The developed decision-making process
could be used for the pollutant loading evaluation.
The source code of the SS equation and RPI index package were
embedded in the WASP coupling platform to improve the interactive
transfer of water quality information to the models. In the simulation
process, SS concentrations under different flow conditions
were simulated using the developed SS and flow rate equations,
and the results were stored in a data file in WASP model. This file
was then retrieved for RPI calculation and other application.
2.3. Linkage of SS sub-module and RPI equation in WASP modelTo obtain the correlations between Kaoping River flow rate and SSconcentrations, water samples were collected from 12 sampling stationsfor SS measurement. Flow rate were monitored at water monitoringstations at each sampling event. Flow velocity and flow ratewere measured following the methods described in NIEA (2004).To determine the correlation between the flow rate and SS concentrations,water sample collection and flow rate measurementwere performed during the dry and wet seasons. The collectedwater quality and hydrological data were analyzed to evaluatethe correlation between SS and flow rate (Cencic and Rechberger,2008). The obtained correlation was used for the development ofSS sub-model and was then linked to the WASP model for directSS estimation. To obtain the immediate RPI value and determinethe river water quality status, RPI index was embedded into theWASP model for direct RPI calculation. Fig. 3 presents the simulationprocess using RPI and WASP. Fig. 4 presents the process of themodeling procedure repeated for each segment until all segmentsmet the requirements. The developed decision-making processcould be used for the pollutant loading evaluation.The source code of the SS equation and RPI index package wereembedded in the WASP coupling platform to improve the interactivetransfer of water quality information to the models. In the simulationprocess, SS concentrations under different flow conditionswere simulated using the developed SS and flow rate equations,and the results were stored in a data file in WASP model. This filewas then retrieved for RPI calculation and other application.
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