A Study on setting appropriate revenue water rate target reflecting the operating characteristics of each city
|dc.description||Thesis(Master) --KDI School:Master of Public Management,2021.||-|
|dc.description.abstract||In 2015, the Ministry of Environment in Korea has ben pushing for the 2nd operation eficiency improvement project of tap water management for 103 local governments whose RWR(Revenue Water Rate) is stil les than 70% among total 161 local governments. The main contents of this project are to establish a DMA system and replace old water suply networks. Through this project, the Ministry of Environment in Korea subsidizes 70% of total facilty investment to local governments. However, the conditons of grant suport must be achieved and maintained at least 85% of the RWR(Revenue Water Rate) for five years after the DMA system is established. The target of RWR for 1st operation eficiency improvement project was 80% 15 years ago in 200, but now it is questionable why the RWR target for the 2nd project has ben changed to 85%. Furthermore, it is also questionable whether it is the right policy to target al local governments at the same 85%, even though the RWR varies greatly depending on the size of the city, the density of the city, and the financial status of the city. For example, should the two local governments achieve the same 85% target if the curent RWR is 45% of local governments A and that of local governments B is 69%. Rather, it can be more reasonable for both local governments to improve 20% to set targets at 65% for local governments A and 89% for local governments B. Therefore, the research questions to be reviewed in this study are as folows. First, what is the most suitable RWR target in Korea, and 80% of the 2010s is a reasonable target? Or is 85% of the 2020s the right target? Second, is the Ministry of Environment''s corect policy to present the same RWR target to al local governments? Or should diferent RWR targets be presented acording to the unique characteristics of local governments? Third, if local governments have to set diferent RWR targets acording to their unique characteristics, what are the variables that afect the RWR target, and what is the predictive model for an apropriate RWR target? Lastly, if the RWR target is low due to the characteristics of local governments with low density like in rural areas, if leakage continues, what other alternatives are there to solve this problem? Therefore, in this study, the RWR and the regresion analysis on various variables are performed to review the RWR target suitable for each local government. In order to determine which variables afect RWR, I first performed a corelation analysis of RWR with 15 independent variables. As a result, RWR has the greatest corelation with urban density factors. In other words, the higher the city''s density, the higher the RWR, and the lower the city''s density, the lower the RWR. In aditon, the financial status of each local government and the technical variables such as GIS, DMA systems were also analyzed to have some corelation with RWR. For the prediction of suitable RWR targets for each local government, I conduct multiple regresion analyses by combining these 15 variables through stepwise regresion. As a result of the verification of the RWR prediction model for 161 local governments in Korea, the coeficient of adjustment determination was analyzed to 0.7238, creating a highly reliable prediction model. In other words, the target of RWR for each local government can be explained by the prediction model by aproximately 72%. Therefore, it is not reasonable for the Ministry of Environment to aply the same RWR target to al local governments at 85% for 2nd operation eficiency improvement project for tap water management. The Ministry of Environment should set diferent RWR targets suitable for each local government by comprehensively considering their urban density, financial status and level of technology of WDS (Water Distribution Network) management. As previously mentioned, it is not the right government policy to set the same RWR target for al local governments, as RWR depends on the unique characteristics of each city, such as density. Therefore, I would like to propose an improvement policy for a suitable RWR target seting that reflects the unique characteristics of each city. First, it is required to introduce the global standard, Infrastructure Leakage Index (ILI), in Korea. Because ILI presents an objectified target caled Unavoidable Anual Real Los (UARL), depending on the density and presure of various cites, it is posible to set the corect leak index target reflecting the unique characteristics of each city. Second, in case of smal cites where UARL is highly generated due to low density, the latest SWM(Smart Water Management) technologies such as Sub-DMA and smart metering should be introduced more actively. By instaling many of these smart water flow rate, presure, and quality measurement sensors in the WDS (Water Distribution System), it is easier to find and repair leaks of vast pipelines even in smal cites with low density. Ultimately, these smart technologies can reduce leakage by dramaticaly reducing the ALR(Aware–Location–Repair) time for leakage. It is clear that leakages in pipes wil improve when SWM technology is introduced to smal cites with low density. However, there are some limitations and chalenge to the introduction of SWM technology by government policy. First, there is stil a lack of cases in Korea that have overcome the problem of leakage in cites with low density by aplying SWM technology. Therefore, more studies on SWM aplication cases are required. Second, the development of a big data system (S/W) for analyzing vast smart sensors acording to the introduction of SWM technology is required first. No mater how many sensors and budgets are invested, if there is no big data analysis S/W, we may fail to achieve the leak reduction goal because it takes a lot of time to analyze and proces vast amounts of data by human resources. Finaly, a Benefit-Cost (B/C) analysis study of SWM infrastructure deployment is also required first, even though SWM technology dramaticaly reduces leaks.||en_US|
|dc.description.tableOfContents||1. Introduction & Research Question 2. Literature Review 3. Methods 4. Policy Recommendation 5. Limitation and Future Research||en_US|
|dc.title||A Study on setting appropriate revenue water rate target reflecting the operating characteristics of each city||en_US|
|dc.contributor.department||KDI School, Master of Public Policy||-|
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