Kao-Ping river, so-called the largest river in Taiwan, is also known as Low Dan-Swe river. It is originated from Chi-San to the Lin-Yuan industrial section, and flow into the ocean. It is also divided the Southern Taiwan Pin-Dong province from the Kaoshiang Province. The Kao-Ping river is about 171 km long, the river surface area is about 3625 square meter. Its river roots supply more than 24 states and towns. It is said to be the largest river in Taiwan, not only because of its surface area, but also its nourish ability. In industrial use, in farming agriculture, or in water resource, the Kao-Ping river devotes itself as a river of life to many culture. In the raining season, the Kao-ping river has enough water supply, but sometimes in the hot season, the river¡¦s supply ability is limited. In this study, the drainage area's background, geographic environment, climate, hydrology goes pasturage aquatic products output and population add with analysis, and in water resource takes advantage of present situation, water quality's quality and develop in plan, with future plan adds with expound in layout. It high screen stream drainage area each plan it face problem with bottleneck, will bring up and add with analysis analyse in this article.

The Kaoping River basin is the largest and the most intensively used river basin in Taiwan. It is 171-km long, drains a catchment of more than 3,250 km2. Based on the current water quality analysis, the Kaoping River is heavily polluted. Concern about the deteriorating condition of the river led the Government of Taiwan to amend the relevance legislations and strengthen the enforcement of the discharge regulations to effectively manage the river and control the pollution. Investigation results demonstrate that both point and non-point source pollutants are now the causes of biochemical oxygen demand (BOD), nutrients, and pathogens in the river. The main water pollution sources are livestock wastewater from hog farms, municipal wastewater, industrial wastewater, non-point source (NPS) pollutants from agricultural areas, and leachate from riverbank landfills. The current daily BOD, NH3-N, and TP loadings to Kaoping River are 74,700, 39,400, and 5,100 kg, respectively. However, the calculated BOD, NH3-N, and TP carrying capacities are 27,700, 4,200, and 600 kg per day. To protect public health and improve the river water quality, the comprehensive management and construction strategy is proposed. The proposed strategy includes the following measures to meet the calculated river carrying capacity: (1) hog ban in the entire Kaoping River basin, (2) sewer system construction to achieve 30% of connection in the basin within 10 years, (3) removal of 10 riverbank landfills, and (4) enforcement of the industrial wastewater discharge standards. After the implementation of the proposed measures, the water quality should be significantly improved and the BOD and nutrient loadings can be reduced to below the calculated carrying capacities.

Kao-ping submarine canyon is straightly connected with Kao-ping River. Thus, it is influenced by the river¡¦s discharge. In order to investigate this seasonal difference in the canyon, we conducted several researches, which were based on temporal and spacial observations of the hydrological and dynamical characteristic of the canyon. We also studied the transport of suspended sediment particles in the canyon according to the distribution of SSC (suspended sediment concentration). In our research, we made along-canyon profile observations. We collected data by using CTD, ADCP and Transmissometer on R/V Ocean Researches Vessel ¢». The data include flood season cruises (CR536, CR248, CR552, CR634 and CR639), and dry season cruises (CR572, CR598, CR608). Based on the temporal and spacial observations, in June and July 1999 we found a cold pool at the location where canyon topography changed sharply. We also found the density disturbance and high concentration at the same location. When the tidal current was landward in the deep canyon, we can observes upwelling in the head region of the canyon. Conversely, we can observe downwelling while the tidal current was seaward. Moreover, we observed a strong vertical flow in the dry season, which can make resuspended easily. Besides, we deployed an instrument covey, including sediment traps, Recording Current Meter (RCM), wave gauge (S700) and Laser In-Suit Scattering and Transmissiometry (LISST-100), at the location where we previously observed SSC localizes high for one month (from June to July 2000) to investigate the temporal relations among temperature, salinity, flow, and suspended particles. From this time series observation we found a coincidence between cold temperature signal and the northward flow. It showed that the cold water from deep sea was transported to the head region of the canyon by a ¡¥Pump¡¦ process. We also observed the suspended particles at the top (195m), middle (245m), and the bottom (285m) of the ocean. According to their different sizes, we found that the upper depth has more sands which were from the continental shelf, and the middle and lower depth have more silt and clay. Subsequently, we used Empirical Orthogonal Function (EOF) analysis to explain the relationship among hydrological and flow factors of the canyon. We concluded that two major modes to explain the observed relationship: Submarine canyon seasonal effect, and dynamic stability.

Studies of phase speciation of trace metals were conducted in Kao-ping river estuary in September 2001 and May 2002. Influence of seasonal variation, salinity and organic carbon content on the trace metal¡¦s phase speciation were of special interest. Water samples collected from four different sampling stations were analyzed for their contents which include salinity, pH value, dissolved oxygen, turbidity, total organic carbon and trace metals. Subsamples observed by cross-flow filtration treatment were further analyzed for the contents of total organic carbon and trace metals. The results showed that manganese has the highest concentration( 8.23 ~ 291.24 £gg/L ), followed by zinc( 2.83 ~ 5.89 £gg/L), nickel( 1.69 ~ 5.82 £gg/L ), copper( 1.75 ~ 4.71 £gg/L ), lead( 0.27 ~ 0.89 £gg/L ) and cadmium( 0.01 ~ 0.27 £gg/L ). Cadmium existed in particulate phase predominately. Copper existed in truly dissolved phase predominately. Particle and truly dissolved phase were the major species of zinc, nickel, manganese and lead. Percentage of all metals in colloidal fraction of the filter-passing pool were low( 9 ~ 16 % for Cu, 5 ~ 21 % for Zn, 4 ~ 30 % for Ni, 2 ~ 38 % for Mn, 5 ~ 30 % for Pb and 8 ~ 34 % for Cd ), they were found predominately in truly dissolved fraction. Effect of seasonal variation was not significant on the distribution of trace metals. Percentage of all truly dissolved metals increased with increasing salinity, however, percentage of particulate metals decreased with increasing salinity ( except for Zn ). Values of partition coefficients between colloids and true solution( Kc ) were considerably higher than those between particles and true solution( Kp ) for all trace metals indicate a high complexation capacity and binding intensity of colloidal organic matter.

In this study, time series analysis and factor analysis of multivariate analysis were applied to surface water quality monitoring data sets. In order to gain a better understanding on water pollution situations and sources of different river basin, we have done some statistical analysis according to the water quality monitoring data from the database of Environmental Protection Administration Executive Yuan in the years from 2004 to 2008. The statistical analysis is based on the aforementioned contents to find the common latent factors of the water pollution and try to explain the main sources of water pollution of river basins. Specifically the water quality monitoring data of the Tamsui River and the Kao-Ping River basin are analyzed. In seriously polluted areas, from the time series results they reveal that the water quality monitoring data has significant serial correlations. Therefore we firstly use vector autoregression (VAR) model to eliminate the dynamic dependencies of data, and later perform the factor analysis for the residuals. With this analysis procedure, the resulting models and factor variables from the factor analysis, sufficiently explained water quality variables with the potential relationship between environmental pollution in the region.

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