Since sewer rehabilitation program requires long construction period and enormous capital investment, determination of rehabilitation priorities is important with systematic planning considering appropriate evaluation parameters. In this research, we applied PROMETHEE(Preference Ranking Organization METHod for Evaluations) known as very objective and scientific multi-criteria decision-making analysis, using the weights determined by AHP(Analytic Hierarchy Process) for the selected sewer evaluation items to calculate the rehabilitation priorities for each sewer sub-catchment in basin Gusan 1 of Seoul. Preference functions and preference thresholds were estimated for each criterion of ratio of lack of hydraulic capacity of sewers, defect ratio, ratio of sewers with velocity less than its minimum criteria, and density of sewers in the sub-catchment. As a result, it was found that region d had the first priority among four sub-catchments. For each and every sewer located in region d, we could also rank sewers to be rehabilitated urgently.

Sewer deterioration models are needed to forecast the remaining life expectancy of sewer networks by assessing their conditions. In this study, the serious defect (or condition state 3) occurrence probability, at which sewer rehabilitation program should be implemented, was evaluated using four probability distribution functions such as normal, lognormal, exponential, and Weibull distribution. A sample of 252 km of CCTV-inspected sewer pipe data in city Z was collected in the first place. Then the effective data (284 sewer sections of 8.15 km) with reliable information were extracted and classified into 3 groups considering the sub-catchment area, sewer material, and sewer pipe size. Anderson-Darling test was conducted to select the most fitted probability distribution of sewer defect occurrence as Weibull distribution. The shape parameters (β) and scale parameters (η ) of Weibull distribution were estimated from the data set of 3 classified groups, including standard errors, 95% confidence intervals, and log-likelihood values. The plot of probability density function and cumulative distribution function were obtained using the estimated parameter values, which could be used to indicate the quantitative level of risk on occurrence of CS3. It was estimated that sewer data group 1, group 2, and group 3 has CS3 occurrence probability exceeding 50% at 13th-year, 11th-year, and 16th-year after the installation, respectively. For every data groups, the time exceeding the CS3 occurrence probability of 90% was also predicted to be 27th- to 30th-year after the installation.

Even though sewers have been conventionally designed to prevent from sediment deposition using a specified minimum velocity or shear stress at a particular depth of flow or with a particular frequency of occurrence, it was appreciated that these methods do not consider the characteristics and concentration of the sediment and the specific hydraulic conditions of the sewer with sediment. In this study, a densimetric Froude number formula was suggested considering particle diameter and volumetric concentration of the sediment as well as flow depth and flowrate, based on several domestic field inspections, which was compared with other formulas proposed by previous investigators. When the sediment concentration was not considered, the calibration coefficient of 0.125-1.5 to the densimetric Froude numbers of this study was needed to obtain the similar ones with previous investigators’. For the densimetric Froude number formula obtained with consideration of sediment concentration, the exponent value of term Cv was almost the same as that of previous results and that of d50/Rh was similar for Fr < 2.2.

If sewage flows for an extended time at low velocities, solids may be deposited in the sewer. Sufficient velocity or tractive force should be developed regularly to flush out any solids that may have been deposited during low flow periods. This study aims to evaluate the periods (T) during which sewage flow greater than the minimum tractive force maintains on a spot in sewer pipe system with lower tractive force or lower velocity than expected in the design step, when a storage tank installed in a place upsteam pours water into the sewer. The effect to T of design factors of storage tank and sewer pipes was evaluated assuming the uniform flow in sewers. When the area of orifice in the storage tank is 0.062 ㎡(or 0.28 m diameter), the maximum T of 31sec was maintained using the usually used preset range of values of several design factors. As the horizontal cross section of storage tank and water depth of storage tank and roughness in sewers increase, T linearly increases. Also, T linearly decreases as the diameter of a sewer pipe increases. Although T gradually decreases as the sewer pipe slope decreases to around 0.005, T decreases sharply when the slope is less than 0.003.

It was confirmed that the extreme value distribution model applies to probability of exceeding more than once a day monthly the facility capacities using data of daily maximum inflow rate for 7 wastewater treatment plant. The result of applying the extreme value model, A, D, E wastewater treatment plant has a problem compared to B, C, F, G wastewater treatment plant. but all the wastewater treatment plant has a problem except C, F wastewater treatment plant based 80% of facility capacity. In conclusion, if you make a standard in statistical aspects probability exceeding more than once a day monthly can be ‘exceed day is less than a few times annually’ or ‘probability of exceeding more than once a day monthly is less than what percent’.

On account of the increase in water demand and climate change, droughts are in great concern for water resources planning and management. In this study, rainfall characteristics with stationary and non-stationary perspectives were analyzed using Weibull distribution model with 40-year records of annual minimum rainfall depth collected in major cities of Korea. As a result, the non-stationary minimum probable rainfall was expected to decrease, compared with the stationary probable rainfall. The reliability of ξ1, a variable reflecting the decrease of the minimum rainfall depth due to climate change, in Wonju, Daegu, and Busan was over 90%, indicating the probability that the minimal rainfall depths in those city decrease is high.

In this study, rainfall characteristics with stationary and non-stationary perspectives were analyzed using generalized extreme value (GEV) distribution and Gumbel distribution models with rainfall data collected in major cities of Korea to reevaluate the return period of sewer flooding in those cities. As a result, the probable rainfall for GEV and Gumbel distribution in non-stationary state both increased with time(t), compared to the stationary probable rainfall. Considering the reliability of ξ1, a variable reflecting the increase of storm events due to climate change, the reliability of the rainfall duration for Seoul, Daegu, and Gwangju in the GEV distribution was over 90%, indicating that the probability of rainfall increase was high. As for the Gumbel distribution, Wonju, Daegu, and Gwangju showed the higher reliability while Daejeon showed the lower reliability than the other cities. In addition, application of the maximum annual rainfall change rate (ξ1·t) to the location parameter made possible the prediction of return period by time, therefore leading to the evaluation of design recurrence interval.