MODELLING DOMINANT PROCESSES AFFECTING THE TRANSPORT AND FATE OF DOMESTIC POLLUTION IN HIGHLY CONTAMINATED URBAN RIVERS. THE CASE OF THE CILIWUNG IN JAKARTA. DIOGO COSTA (1, 2), PAOLO BURLANDO (3), SHIE-YUI LIONG (2), CINDY PRIADI (4), SENTHIL GURUSAMY (1) (1): FCL, Singapore-ETH Centre (SEC), Singapore (2): Department of Civil Engineering, National University of Singapore, Singapore (3): Institute of Environmental Engineering, ETH Zurich, Switzerland (4): Department of Civil Engineering, University of Indonesia, Indonesia pinho.da.costa@arch.ethz.ch ABSTRACT The Ciliwung River in Jakarta is a case of extreme environmental degradation. Without adequate basic sanitary infrastructures available, the river is used as an open sewer by the city’s most vulnerable and deprived commu- nities. This case is particularly challenging due to the high urban density and proliferation of poor communities along the river banks. Understanding the system as a whole and quantifying the magnitude of the anthropogenic influence is therefore crucial to plan remediation actions. Due to the limited available data, a preliminary and exploratory modelling analysis is presented to estimate pollution loads, to identify the dominant natural process- es and to investigate the river potential for environmental degradation of pollution. This is expected to drive a future and comprehensive monitoring and modelling effort towards remediation. INTRODUCTION The nature of pollution sources in environments like the “kampungs” (i.e. hamlets often turned into slums) can be very much seen like that of a diffuse source. The number and location of effective point sources is undocu- mented, thus making their individual modelling practically impossible. To investigate the river response to pol- lution and the self-healing potential, a coupled 1D hydrodynamic and water quality model was calibrated to es- timate not only reaction rates but also pollution loads. The parameterization of the model consisted in fitting the modelled data to observations between stations located in the upstream regions where pollution sources are known to be smaller. This allowed minimising the influence of large pollution inputs that would have made dif- ficult, given the available data, modelling natural processes. Pollution loads were in turn estimated through in- verse modelling by fitting simulations to observations. To this purpose, data from stations located in the down- stream regions of the metropolitan area of Jakarta were used, which are known to receive more pollution. DATA DESCRIPTION AND ANALYSIS The flow and water quality datasets used in this study were collected by the Department of Water Resources Management of the West Java Province Government. The water level and quality gauging stations are located in Katulampa, Kampung Kelapa, Ratu Jaya and Sugumatu. Two additional water quality monitoring stations exist at Jembatan Sempur and Kendung Halang. Flow was estimated on the basis of rating curves derived for each of the sections.. The data was collected at monthly intervals between 2005 and 2006 and includes a range of chem- ical and biological parameters, from which dissolved oxygen (DO), biological oxygen demand (BOD), ammonia (NH 3 ), nitrate (NO 3 ) and total suspended solids (TSS) were used in this study. Table 1 provides a brief summary of the flow and quality data used for the both dry (July-Oct.) and wet (Nov.-June) seasons. Table 1- Water quality indicators and flows at different stations in the wet and dry seasons (wet-dry values) Station Katulampa J. Sempur K.Halang Kelapa Ratu Jaya Sugutamu DO (mg/l) 6.0 – 5.8 7.1 – 5.0 7.1 – 5.8 6.4 – 6.5 6.9 – 5.7 6.6 – 5.5 BOD 5 (mg/l) 10.9 – 3.0 11.7 – 3.6 8.0 – 5.3 17.4 – 5.1 19.2 – 5.3 20.6 – 10.3 NH3 (mg/l) 0.04 – 0.05 0.18 – 0.04 0.09 – 0.07 0.09 – 0.06 0.10 – 0.07 0.10 – 0.08 NO3 (mg/l) 2.17 – 2.20 2.67 – 2.86 4.20 – 2.99 2.51 – 2.84 2.41 – 2.94 2.50 – 2.29 TSS (mg/l) 45.0 – 69.6 71.3 – 107.9 60.6 – 118.1 140.5 – 105.8 87.3 – 100.0 380 – 342.5 Temperature ( o C) 27.8 – 26.8 28.5 – 26.1 28.4 – 27.3 29.4 – 29.9 29.8 – 30.5 29.5 – 29.6 Flow rate (m 3 /s) 12.8 – 1.8 n/a n/a 28.4 – 8.8 18.2 – 6.3 54.1 – 34.0 The dissolved oxygen clearly drops during the dry season throughout the river length. During this period and contrary to what one would expect, the concentration of BOD 5 also decreases significantly, thus suggesting that