This study demonstrates the feasibility of coastal water quality mapping using satellite remote sensing images. Water quality sampling campaigns were conducted over a coastal area in northern Taiwan for measurements of three water quality variables including Secchi disk depth, turbidity, and total suspended solids. SPOT satellite images nearly concurrent with the water quality sampling campaigns were also acquired. A spectral reflectance estimation scheme proposed in this study was applied to SPOT multispectral images for estimation of the sea surface reflectance. Two models, univariate and multivariate, for water quality estimation using the sea surface reflectance derived from SPOT images were established. The multivariate model takes into consideration the wavelength-dependent combined effect of individual seawater constituents on the sea surface reflectance and is superior over the univariate model. Finally, quantitative coastal water quality mapping was accomplished by substituting the pixel-specific spectral reflectance into the multivariate water quality estimation model.

Rainfall amount drawn by typhoon events accounts for a significant portion of annual rainfall in Taiwan. Changes in typhoon rainfall due to climate change may have severe consequences for water resources management. A stochastic simulation approach is proposed for evaluation of changes in typhoon rainfall under certain climate change scenarios. The number of typhoon events and total rainfall of individual typhoon events are, respectively, considered as random variables of the Poisson and Gamma distributions. Climate change scenarios were set by varying various degrees of changes in average number of typhoon events annually and the mean of eventtotal rainfall. Using stochastic simulation, basin-wide annual typhoon rainfalls were simulated for the Shihmen Reservoir watershed in northern Taiwan. It is found that 10% increases in average annual number of typhoon events and mean event-total rainfall will result in 18% increase in the annual typhoon rainfall of 5-year return period, whereas the annual typhoon rainfall of 10-year return period will increase by 15% under the same climate change scenario. Such increases may cause significant increase in reservoir sediment and pose challenges to reservoir management.

A frequency-factor based approach for stochastic simulation of bivariate gamma distribution is proposed. The approach involves generation of bivariate normal samples with a correlation coefficient consistent with the correlation coefficient of the corresponding bivariate gamma samples. Then the bivariate normal samples are transformed to bivariate gamma samples using the well-known general equation of hydrological frequency analysis. We demonstrate that the proposed bivariate gamma simulation approach is capable of generating random sample pairs which not only have the desired marginal densities of component random variables but also their correlation coefficient. Scatter plots of simulated bivariate sample pairs also exhibit appropriate linear patterns (dependence structure) that are commonly observed in environmental and hydrological applications. Caution should also be exercised when specifying combinations of coefficients of skewness and the correlation coefficient for bivariate gamma simulation.

The effects of climate change on synoptic scale storms like typhoons can have profound impacts on practices of water resources management. A stochastic multisite simulation approach is proposed for assessing the impact of climate changes on basin-average annual typhoon rainfalls (BATRs) under certain synthesized climate change scenarios. Number of typhoon events and event-total rainfalls are considered as random variables characterized by the Poisson and gamma distributions, respectively. The correlation structure of event-total rainfalls at different rainfall stations is found to be significant (higher than 0.80) and plays a crucial role in the proposed stochastic simulation approach. Basin-average annual typhoon rainfalls were simulated for the Shihmen Reservoir watershed in northern Taiwan by considering changes in the mean values of annual number of typhoon events and event-total rainfalls, while assuming the correlation structure of multisite typhoon rainfalls to remain unchanged. The simulation results indicate that changes in expected values of BATR can be easily projected with simpler models; however, changes in extreme properties of BATR are more complicated. Comparing to changes in expected values of BATRs, lesser changes in more extreme events can be observed. This is due to the reduction in coefficient of skewness of gamma distribution BATR under different climate change scenarios. With consideration of the multisite correlation structure, changes in BATRs become more significant. Thus, in assessing the impacts of climate change on many hydrological and environmental variables which exhibit significant spatial correlation pattern, the multisite correlation structure needs to be taken into consideration.