[Show abstract][Hide abstract]ABSTRACT: An urban watershed in Xiamen was selected to perform the parameter uncertainty analysis for urban stormwater runoff modeling in terms of identification and sensitivity analysis based on storm water management model (SWMM) using Monte-Carlo sampling and regionalized sensitivity analysis (RSA) algorithm. Results show that Dstore-Imperv, Dstore-Perv and Curve Number (CN) are the identifiable parameters with larger K-S values in hydrological and hydraulic module, and the rank of K-S values in hydrological and hydraulic module is Dstore-Imperv > CN > Dstore-Perv > N-Perv > conductivity > Con-Mann > N-Imperv. With regards to water quality module, the parameters in exponent washoff model including Coefficient and Exponent and the Max. Buildup parameter of saturation buildup model in three land cover types are the identifiable parameters with the larger K-S values. In comparison, the K-S value of rate constant in three landuse/cover types is smaller than that of Max. Buildup, Coefficient and Exponent.
Full-text available · Article · Sep 2012 · Huan jing ke xue= Huanjing kexue / [bian ji, Zhongguo ke xue yuan huan jing ke xue wei yuan hui "Huan jing ke xue" bian ji wei yuan hui.]
[Show abstract][Hide abstract]ABSTRACT: Sensitivity analysis of urban-runoff simulation is a crucial procedure for parameter identification and uncertainty analysis. Local sensitivity analysis using Morris screening method was carried out for urban rainfall runoff modelling based on Storm Water Management Model (SWMM). The results showed that Area, % Imperv and Dstore-Imperv are the most sensitive parameters for both total runoff volume and peak flow. Concerning total runoff volume, the sensitive indices of Area, % Imperv and Dstore-Imperv were 0.46-1.0, 0.61-1.0, -0.050(-) - 5.9, respectively; while with respect to peak runoff, they were 0.48-0.89, 0.59-0.83, 0(-) -9.6, respectively. In comparison, the most sensitive indices (Morris) for all parameters with regard to total runoff volume and peak flow appeared in the rainfall event with least rainfall; and less sensitive indices happened in the rainfall events with heavier rainfall. Furthermore, there is considerable variability in sensitive indices for each rainfall event. % Zero-Imperv's coefficient variations have the largest values among all parameters for total runoff volume and peak flow, namely 221.24% and 228.10%. On the contrary, the coefficient variations of conductivity among all parameters for both total runoff volume and peak flow are the smallest, namely 0.
Article · Sep 2010 · Huan jing ke xue= Huanjing kexue / [bian ji, Zhongguo ke xue yuan huan jing ke xue wei yuan hui "Huan jing ke xue" bian ji wei yuan hui.]
[Show abstract][Hide abstract]ABSTRACT: A comparative study on characteristics of stormwater runoff from two urban lawn catchments in Macau (ELH) and Xiamen (PGH) with separated sewer system were conducted. The result obtained shows that COD, TP and NO3- -N are the major pollutants with mean EMC of 165.77-60.48 mg/L, 0.96-0.44 mg/L and 7.16-1.18 mg/L, respectively, and the mean values of pollutants loads of COD, TP and NO3- -N from study lawn catchments are 6.53-0.63 kg/hm2, 0.0375-0.0047 kg/hm2 and 0.0122-0.0128 kg/hm2, respectively. Peak values of major pollutant concentrations usually precede the flow peak. First flush effect of rainfall runoff from two study catchments is no obvious, which can be reflected by the low mean value of FF30 of TSS, COD, TP and NO3- -N, with 36.26%, 26.13%, 28.13% and 39.03%, respectively. Based on multivariate statistical analysis, first flush effect from urban lawn rainfall runoff is greatly influenced by total rainfall amount (Tr) and total runoff volume (V).
Article · Dec 2009 · Huan jing ke xue= Huanjing kexue / [bian ji, Zhongguo ke xue yuan huan jing ke xue wei yuan hui "Huan jing ke xue" bian ji wei yuan hui.]
[Show abstract][Hide abstract]ABSTRACT: The purpose of this paper is the application of storm water management model (SWMM) in simulating runoff hydrology and water quality. The study chose a roof as the typical impervious urban land surface, and monitored several rainfall-runoff events for parameter identification. We identified and validated hydrological and water quality parameters, using Monte Carlo sampling method and HSY algorithm, which are based on uncertainty analysis. Results show that impervious urban land surface runoff model includes 6 critical parameters, which are depression storage (S-imperv), Manning's n (N-imperv), maximum buildup possible (max buildup), buildup rate constant (rate constant), washoff coefficient (coefficient), and washoff exponent (exponent). Identification of S-imperv and N-imperv could use least square error as objectives, while others could use errors of event pollution load and peak concentration of pollutant as objectives. The identification results of the 6 parameters are N-imperv 0.012-0.025,S-imperv 0-0.7, max buildup 15-30,rate constant 0.2-0.8,coefficient 0.01-0.05, and exponent 1.0-1.2. Regional sensitivities of these parameters in non-ascending order are coefficient, S-imperv, N-imperv, max buildup, exponent, and rate constant. Identified parameters are able to be validated by SWMM model. However, current model structures still have some difficulties in simulating runoff pollutant concentration curves caused by some special rain patterns.
Article · Jul 2008 · Huan jing ke xue= Huanjing kexue / [bian ji, Zhongguo ke xue yuan huan jing ke xue wei yuan hui "Huan jing ke xue" bian ji wei yuan hui.]
[Show abstract][Hide abstract]ABSTRACT: The purpose of this study is identification and characterization of hydrological process of urban runoff, as well as concentration variation of pollutants in it. Samples were collected in 4 rainfall events in Beijing from Jun. 2006 to Aug. 2006. Hydrology and pollution of the rainfall-runoff process were analyzed on roof and road. Study results show that the shapes of hydrological curves of runoff, despite for a 5 - 20 min delay and a milder tendency, are similar to rainfall curves. Runoff coefficients of roof are 0.80 - 0.98, while 0.87 - 0.97 of road. Event mean concentrations (EMC) of pollutants are influenced by build-up and wash-off features, which leads to a higher concentration in road runoff than in roof runoff. Major pollutants that excess the water quality standards are COD, TN, and TP. Evident correlations (> 0.1) are found between pollutants. Correlation with particles are higher for COD and SO4(2-) (> 0.5), while lower for nutrients (<0.5). First flush effects (FFE) are found and affected by several factors, such as pollutant variety, types of land covers, and rainfall intensity. FFE are found more intense in SS, more frequently in road runoff, and more difficult to form for COD and nutrients with low rainfall intensity. Therefore, control of first period of runoff would be an effective approach for runoff management in Beijing.
Article · Mar 2008 · Huan jing ke xue= Huanjing kexue / [bian ji, Zhongguo ke xue yuan huan jing ke xue wei yuan hui "Huan jing ke xue" bian ji wei yuan hui.]
[Show abstract][Hide abstract]ABSTRACT: Characteristics of surface runoff from a 0.14-km2 urban catchment with separated sewer in Macau was investigated. Water quality measurements of surface runoff were carried out on five rainfall events during the period of August to November, 2005. Water quality parameters such as pH, turbidity, TSS, COD, TN, Zn, Pb, and Cu were analyzed. The results show that TN and COD are the major pollutants from surface runoff with mean concentration of 8.5 and 201.4 mg/L, both over 4-fold higher compared to the Class V surface water quality standard developed by China SEPA. Event mean concentration (EMC) for major pollutants showed considerable variations between rainfall events. The largest rainfall event with the longest length of antecedent dry weather period (ADWP) produced the highest EMC of TN, TSS and COD. From the pollutographs analysis, the peak concentration of TN precedes the peak runoff flow rate for all three rainfall events. The tendency of the concentration of TSS, turbidity and COD changing with runoff flow varies between rainfall events. The relationship between TSS and other parameters were analyzed to evaluate the efficiency of the physical treatment process to control the surface runoff in the urban catchment. Based on the correlation of parameters with TSS, high treatment efficiency of TSS, TN and COD was expected. The most significant event in term of first flush is the one with the strongest rainfall intensity and longest length of ADWP. TN always showed first flush phenomenon in all three rainfall events, which suggested that the surface runoff in the early stage of surface runoff should be dealt with for controlling TN losses during rainfall events.
Full-text available · Article · Feb 2007 · Journal of Environmental Sciences
[Show abstract][Hide abstract]ABSTRACT: Characteristics of pollutants from urban surface runoff were investigated. Two catchments with a seperated system in Macau were selected for sampling on rainfall events during the period of August to November, 2005. Water quality parameters such as pH, turbidity, TSS, COD, TOC, TN, TP, Zn, Pb, and Cu were analyzed. The results show that the commercial-residential urban catchment shows high level of COD, TN, TP, and the park urban catchment has high TN and TP concentration. From the pollutograph analysis, the peak of TSS, TN, TP concentration appears in the first and the third sample respectively in ELH and YLF catchments, and then the pollutants concentration tend to decrease. Regression analysis between TSS and TN & TP in two urban catchments resulted in a high value (R2 > 0.95) of the coefficient of determination R2 indicating a close relationship between soil losses and nitrogen & phosphorus discharged from surface runoff. The profile of TSS and COD discharged from surface runoff relates greatly to the surface flow change, whereas the surface flow change has little influence on the profile of TN and TP. The heavy metals such as Zn, Pb and Cu fluctuate with the continuous input of vehicles during rainfall events. Pollutants such as TSS, TN, COD discharged from surface runoff depend greatly on the dry periods and storms intensity in such two urban catchments.
Article · Sep 2006 · Huan jing ke xue= Huanjing kexue / [bian ji, Zhongguo ke xue yuan huan jing ke xue wei yuan hui "Huan jing ke xue" bian ji wei yuan hui.]
[Show abstract][Hide abstract]ABSTRACT: The modelling package Annualized Agricultural Nonpoint Source Model (AnnAGNPS) was used to predict pollutant loads, and simulate catchment processes and management practices in Jiulong River watershed, a medium-sized mountainous watershed in southeast of China. Four typical sub-watersheds were primarily chosen to calibrate AnnAGNPS model by data collected from storm events during the period of April to September, 2003. The model was further validated in the two biggest branches of Jiulong River watershed, i.e. West river and North river by the data regarding climate, and land using condition in 2002 - 2003. The simulation results show that annual total nitrogen load was 24.76kg/(hm2 x a) and 10.28kg/(hm2 x a) in the West river and North river, respectively, and annual total phosphorus load was 0.67 kg/(hm2 x a) and 0.40 kg/(hm2 x a) in the West river and North river, respectively. With the support of AnnAGNPS model, several management alternatives were separately simulated in the typical sub-watersheds, West river and North river. In the specific cell with cell-ID of 92 in Tianbao and Xiandu sub-watershed, after reforesting in sloping field, runoff surface, sediment yield, total nitrogen load and total phosphorus load cut down with 21.6%, 25.9%, 96% and 79.2%, respectively. In West river, with the cultivation plant changing from banana into rice, the total nitrogen, dissolved nitrogen, total phosphorus and dissolved phosphorus cut down with 23.83%, 25.44%, 9.08% and 19.84%, respectively. In North river, when removing all the hoggerys, nitrogen and dissolved nitrogen cut down with 63.54% and 76.92% , respectively.
Article · Aug 2005 · Huan jing ke xue= Huanjing kexue / [bian ji, Zhongguo ke xue yuan huan jing ke xue wei yuan hui "Huan jing ke xue" bian ji wei yuan hui.]