Study on the North China Rural Water Supply Project O&M Cost Standard Rating

Transcription

1 rd International Conference on Engineering Technology and Application (ICETA 2016) ISBN: Study on the North China Rural Water Supply Project O&M Cost Standard Rating Lei Zhao China Institute of Water Resources and Hydropower Research, Beijing, China Jing Yang Datang Environment Industry Co., Ltd., Beijing, China ABSTRACT: For the purpose of further regulating the set-up standard of rural water supply project operation and maintenance cost, O&M cost accounting method should be identified; with North China plain area as the study target, water supply projects at 722 places are selected randomly for study. On the basis of survey data, multiple regression analysis means is employed to analyze relations between O&M cost and operation cost, annual actual output of water supply, personnel cost, electric tariff and water supply facility O&M frequency, and three O&M calculating models are established. O&M cost check computation has high reliability through personnel cost and electric tariff, operation cost and personnel cost, personnel cost and pump, purification equipment, electromechanical equipment, instrument and meter, valve and transmission and distribution pipe network maintenance frequency to some extent. Meanwhile, three O&M calculating models should be selected flexibly in combination with project conditions in actual application. Keywords: rural water supply project; survey; multiple regression analysis; O&M cost; calculating models 1 INTRODUCTION As a rural water supply project involves many operation and maintenance (O&M) items and costs are hard to be quantified, there are no unified provisions for O&M cost at present. As far as municipal water supply is concerned, with mature water supply system, 2.5% of the project fixed assets are withdrawn as the water supply project O&M cost [1]. For the operation management aspect of the rural water supply project, some areas set up rural water supply project maintenance fund based on their own conditions. Take Henan province as an example, the maintenance fund amount is RMB100, ,000 each county, RMB 0.1~0.2/t water is drawn from water charge of the water supply project as project O&M fund, which basically addresses the routine O&M cost of the rural water supply project [2]. For the rural water supply project O&M cost issue, in line with Chinese actual *Corresponding author: zhaolei_cdte@163.com conditions of rural water supply project, we learnt current drawing methods of O&M cost are mainly fixed limit drawing method, fixed-asset fixed proportion drawing method, and water charge fixed quota drawing method [3]. As some rural water supply projects are limited by natural geographic conditions, topographical and geological conditions and water charge collection difficulty in some areas, rural water supply projects feature high water supply cost and non-implementation of water price [4]. Such being the case, O&M cost has too high or too low problems, whether drawn as per fixed proportion of the project operation cost or as per water charge fixed quota. For the purpose of further identifying accounting method of rural water supply project O&M cost, with North China plain area as the study target, water supply projects at 722 places are selected randomly for study, examples are employed to analyze relations between water supply O&M cost and operation cost and other operation conditions, set forth O&M cost calculating method and establish corresponding calculating models [5]. 1046

2 2 SURVEY ITEMS Survey items of rural water supply projects at 722 places mainly include two aspects of project general and O&M [6]. Detailed survey items have project operation time (time the project is commissioned), water source type (groundwater, surface water), design water supply size (Qd), operation cost (Ecost), water resource charge (Ew), electric tariff (Ee), chemical cost (Ec), personnel cost (Ep), O&M cost (Em), chemical quality test fee (Et), tax fee (Etax), actually collected fee (Ecollect) as well as specially for rural water supply projects - pump maintenance frequency (Fp), purification equipment maintenance frequency (Fpw), electromechanical equipment maintenance frequency (Fem), meter maintenance frequency (Fmeter), valve maintenance frequency (Fvalve), transmission and distribution pipe network patrol frequency (Fpipe), etc [7]. According to design water supply size classification method in the Rural water supply project design specification (SL ) [8], V type water supply projects (design water supply size less than 200m³/d) at 172 places, IVtype water supply projects (design water supply size is 200m³/d~1000m³/d) at 333 places, III type water supply projects (design water supply size is 1000m³/d~5000m³/d) at 206 places, II type water supply projects (design water supply size is 5000m³/d~10000m³/d) at 9 places and Itype water supply projects (design water supply size more than 10000m³/d) at 2 places are selected randomly out of 722 places. On the basis of survey data, O&M cost calculating methods are described and O&M calculating models are established by analyzing relations between O&M cost and operation cost, personnel cost, electric tariff and water supply facility O&M frequency [9]. 3 O&M CALCULATING MODELS As current fixed limit drawing method, operation cost fixed proportion drawing method, and water charge fixed quota drawing method cannot completely describe survey data and cannot cover most water supply projects, O&M cost calculating methods are prepared and corresponding calculating models are established by comprehensively analyzing relations between O&M cost and design water supply scale, actual water supply output, operation cost, electric tariff, personnel cost, and water supply facility maintenance frequency and other parameters [10]. Through overall data analysis and processing of water supply projects at 722 places, we found there are good multiple linear relations between O&M cost and personnel cost and electric tariff, between logarithm-processed O&M cost and operation cost and personnel cost, and between O&M cost and personnel cost and facilities maintenance frequency. Based on that, this essay builds O&M cost calculating model based on personnel cost and electric tariff, O&M cost calculating model based on operation cost and personnel cost and O&M cost calculating model based on personnel cost and facilities maintenance frequency [11]. Detailed analysis is as follows: 3.1 O&M cost calculating model based on personnel cost and electric tariff Through multiple linear regression analysis between O&M cost and personnel cost and electric tariff, it correlation coefficient R2 is 0.636, showing 63.6% of O&M cost data can be explained by changes in personnel cost and electric tariff, and analysis conclusions are in good multiple linear relations; through regression model F test, F=628.17,P=0.000,complies with α<0.05, so this regression equation fitting degree is good and has statistical significance. Multiple linear regression analysis coefficients are shown in Table 1, corresponding standardized residue histogram and normality P-P diagram are shown in Figure 1. As apparent from Table 1, according to test result t of electric charge and personnel fee regression coefficient, its t value is (P=0.009<0.01), (P=0.000<0.01), showing linear fitting result is fairly good. Absolute value of standard coefficient is a parameter reflecting independent variable impact on dependent variable, the larger absolute value, the larger impact of independent variable on dependent variable. Through standard coefficient values of electric charge and personnel fee, standard coefficients are 0.06 and respectively, which shows in relation to electric charge, and personnel fee plays a decisive role. Further, regression coefficients of electric charge and personnel fee are and respectively, and both are positive values, which show project O&M cost increases with increase of electric charge and personnel fee. Table 1. O&M cost calculating model coefficient table based on personnel cost and electricity tariff. Non-standard coefficient Standard coefficient t Sig. Constant Electric charge Personnel fee For standardized residue histogram and normality P-P diagram, if regression standardized residue histogram matches the normality distribution conditions or standardized residue normality P-P diagram points are in a straight line, the established O&M cost calculating model well describes original data. Through Figure 1, regression standardized residue histogram cannot completely matches normality distribution and normality P-P diagram points are not on a straight line, showing O&M cost calculating model based on per- 1047

3 sonnel cost and electric tariff has certain statistical significance, but it can only describe part of original data. (a) Histogram is good and has statistical significance. Multiple linear regression analysis coefficients are shown in Table 2, corresponding standardized residue histogram and normality P-P diagram are shown in Figure 2. As apparent from Table 2, t test result of operation cost and personnel fee regression coefficient show that linear fitting result is fairly good, and project O&M cost increases with increase of operation cost and personnel fee; Through standard coefficient values of operation cost and personnel fee, standard coefficients are 0.25 and 0.34 respectively, which shows both operation cost and personnel fee play a decisive role. Table 2. O&M cost calculating model based on operation cost and personnel cost Non-standard coefficient Standard coefficient t Sig. Constant Operation cost Personnel fee (b) Normality P-P diagram Figure 1. Regression standard residue histogram and Regression equation of O&M cost is Formula (1): (a)histogram Em=0.211Ep+0.031Ee (1) Where, Em, Ee and Ep are maintenance cost, electric charge and personnel fee, and the unit is all RMB/year. As apparent from Formula (1), for the surveyed water supply projects, each water supply project has to draw 21.1% from personnel fee and 3.1% from electric charge, and given fixed annual maintenance fund is RMB as annual O&M cost of that water supply project. 3.2 O&M cost calculating model based on operation cost and personnel cost Through logarithm analysis for overall data of water supply projects at 722 places, we found O&M cost and personnel fee and operation cost have good multiple linear relations, its correlation coefficient R2 is 0.296, showing about 29.6% of can be explained by changes in personnel cost and operation cost; through regression model F test, F=67.997,P=0.000,complies with α<0.05, so this regression equation fitting degree (b)normality P-P diagram Figure 2. Regression standard residue histogram and As apparent from Figure 2, standardized residue histogram basically matches the normality distribution, standardized residue normality P-P diagram points are in a straight line, showing the established O&M cost calculating model has statistical significance, and it is reasonable and feasible, the established O&M cost calculating model based on operation cost and per- 1048

4 sonnel cost well describes original data, with high simulation result reliability. Regression equation of O&M cost is Formula (2): lnem=0.254lnecost+0.340lnep (2) Where, Em, Ecost, and Ep are maintenance cost, operation cost and personnel cost, and the unit is all RMB/year. As apparent from Formula (2), for the surveyed water supply projects, logarithm of water supply project O&M cost at each place is composed of 25.4% of operation cost logarithm, 34% of personnel cost logarithm and fixed constant O&M cost calculating model based on personnel cost and facilities maintenance frequency O&M cost of rural water supply projects is decided by pump maintenance frequency (Fpump), purification equipment maintenance frequency (Fpw), electromechanical equipment maintenance frequency (Fem), valve maintenance frequency (Fv) and transmission and distribution water pipe network patrol frequency (Fp). Before multivariate statistical analysis, descriptive statistics is performed for facility maintenance frequency in the survey and difference of maintenance frequency of all water supply facilities for various rural water supply projects (See Table 3). Table 3 reflects big differences of maintenance frequency of all water supply facilities for various rural water supply projects; for instrument and meter transmission and distribution pipe network maintenance, some water works conduct monthly maintenance as required, but water works only conduct annual maintenance; for water purification equipment, some water works do not conduct water purification facility maintenance; O&M of other facilities also have big differences, showing O&M of rural water supply projects needs further enhancement. Difference in water supply facility maintenance frequency is one of important reasons for differences of O&M cost for rural water supply projects. Through comprehensive analysis for multiple linear regression of O&M cost and pump, purification equipment, electromechanical equipment, instrument and meter, valve and transmission and distribution water pipe network maintenance frequency and other indicators, O&M cost calculating models for dependent variables such as personnel cost and pump, purification equipment, electromechanical equipment, instrument and meter, valve and transmission and distribution water pipe network maintenance frequency are established. For the established O&M cost calculating models, correlation coefficient R2 is 0.712, showing 71.2% of data can be explained by changes in personnel cost and pump, purification equipment, electromechanical equipment, instrument and meter, valve and transmission and distribution water pipe network maintenance frequency; through regression model F test, F= , P=0.000, complies with α<0.05, so this regression equation fitting degree is good. Coefficients of O&M cost calculating model based on personnel cost and facilities maintenance frequency are shown in Table 4, corresponding standardized residue histogram and normality P-P diagram are shown in Figure 3. Table 4 shows t test results of purification equipment maintenance frequency Fpw, electromechanical equipment maintenance frequency Fem, instrument and meter maintenance frequency Fmeter, valve maintenance frequency Fv, and personnel cost Ep, t values are (P=0.001), (P=0.001), (P=0.000), (P=0.000) and (P=0.000) respectively, complies with α<0.05, linear fitting results are fairly good, meanwhile, pump maintenance frequency Fpump regression coefficient t test results show its linear relations are slightly not significant. Table 3. Description of O&M frequency of facilities. Item Min.(time/year) Max.( time/year) Average (time/year) Standard difference SD Coefficient of variation CV Fpump Fpw Fem Fmeter Fv Fpn Table 4. Coefficients of O&M cost calculating model based on personnel cost and facilities maintenance frequency. Non-standardcoefficient Standard coefficient t Sig. Constant Fpump Fpw Fem Fmeter Fv Fpn Ep

5 Through regression standard coefficient, project O&M cost increases with increase in Fpump, Fem, Fv, Fpn and Ep, but decreases with increase in Fpw and Fmeter. Through analysis and comparison of absolute values of standard coefficients, personnel cost Ep plays a decisive role in O&M cost, sequence of other indicators in terms of impact on O&M cost is Fv, Fmeter, Fpw, Fem, Fpn and Ep. corresponding O&M cost accounting formula is shown in Formula (3). Em= Fp Fpw Fem Fmeter Fv Fpn Ep (3) Where, Em and Ep, are maintenance cost, operation cost and personnel cost, and the unit is RMB/year; Fp, Fpw, Fem, Fmeter, Fv and Fpn are maintenance frequency, and the unit is time/year. through regression model F test, F=42.556, P=0.000, complies with α<0.05, so the regression equation fitting degree is fairly good, has statistical significance. Its multiple linear regression analysis coefficient is shown in Table 5, and the corresponding regression standard residue histogram and P-P diagram are shown in Figure 4. Table 5. Coefficients of O&M cost calculating model (improved) based on personnel cost and facilities maintenance frequency. Non-standard coefficient Standard coefficient t Sig. Constant Fpump Fpw Fem Fmeter Fv Fpn Ep (a)histogram (a)histogram (b)normality P-P diagram Figure 3. Regression standard residue histogram and Figure 3 shows that although correlation coefficient R2 is 0.712, histogram of regression standard residue cannot well match normality distribution, and P-P diagram points are not in a straight line, which cannot fully describe original data. To further establish O&M cost calculating models which fully describe original data, logarithmic treatment is made to O&M cost and personnel cost, then multiple linear regression step is repeated, for improved O&M cost and personnel cost, (b)normality P-P diagram Figure 4. Regression standard residue histogram and Table 5 shows that t test results of purification equipment maintenance frequency Fpump, electromechanical equipment maintenance frequency Fem, instrument and meter maintenance frequency Fmeter, valve maintenance frequency Fv, and personnel cost 1050

6 Table 6. O&M cost accounting method summary table. Project type V Type O&M cost calculating model based on personnel cost and electric tariff(cost unit RMB/year) O&M cost calculating model based on operation cost and personnel cost(cost unit RMB/year) O&M cost calculating model based on personnel cost and facilities maintenance frequency(cost unit RMB/year) IV type III type II type I type Em=0.211Ep+0.031Eem lnem=0.254lnecost+0.340lnep lnem=0.173fpump-0.046fpw Fem-0.041Fmeter-0.038Fv Fpn+0.516lnEp Ep, P value is less than 0.01, showing linear fitting result is fairly good; t test results of Fp, Fmeter, and Fv, regression coefficients show linear fitting result is fairly poor. From values of standard coefficient, Ep standard coefficient is 0.527, with the largest effect on O&M cost Em, takes the absolute dominating position, showing personnel cost plays a decisive role in O&M cost, sequence of other indicators in terms of impact on O&M cost is Ep, Epn, Fem, Fpw, Fmeter and Fv. from Figure 4, regression standard residue complies with normality distribution, P-P diagram points of regression standard residue are basically distributed on a straight lie, showing improved O&M cost calculating models fairly well describe original data, with high reliability. Regression equation of O&M cost is Formula (4): lnem=0.173fpump 0.046Fpw 0.117Fem (4) 0.041Fmeter 0.038Fv+0.136Fpn+0.516lnEp Where, Em, Ep, Fpump, Fpw, Fem, Fmeter, Fv, and Fpn are the same as in Formula (3). 4 CONCLUSIONS For water supply projects at 722 places in survey, on the basis of survey data, relations between O&M cost and operation cost, annual actual output of water supply, personnel cost, electric tariff and water supply facility O&M frequency are analyzed, O&M cost accounting methods are described, and corresponding O&M cost calculating models are established. Accounting methods for the above O&M cost are summarized as shown in Table 6. Multiple regression analysis means is employed to establish three calculating models, all with statistical significance, O&M cost check computation has high reliability through personnel cost and electric tariff, operation cost and personnel cost, personnel cost and pump, purification equipment, electromechanical equipment, instrument and meter, valve and transmission and distribution pipe network maintenance frequency to some extent. What is worth mentioning is established O&M cost calculating methods and models for the above analysis have respective advantages and disadvantages and have corresponding scope of application, detailed methods shall be selected flexibly in line with actual project conditions. REFERENCES [1] Shanghai Municipal Engineering Design Study Water Supply and Drainage Design Manual (10) Techno-Economy (Edition 2). Beijing: China Building Industry Press. [2] State Development and Reform Commission, Ministry of Water Conservancy, Ministry of Health, etc. National Rural Drinking Water Safety Project 12th Five-Year Plan [R]. June [3] Beuth Verlag Economic benefits of standards: Summary of results. DIN German Institute for Stand, pp: [4] DTI The empirical economics of standards. DTI Economics Paper. [5] Dracupja, Leeks, Paulsoneg On the statistical characteristics of drought events. Water Resources Research, 16(2): [6] Tian Shougang, Fan Mingyuan Research on coordinated evaluation of district water resources allocation. Proceedings of 2011 International Symposium on Water Resource and Environmental Protection (ISWREP 2011) VOL.01. [7] Wenkun Liu, Yuansheng Pei, Yong Zhao, Weihua Xiao The research of the regional meteorological drought assessment model. Applied Mechanics and Materials, pp: [8] Rural water supply project technical specification (SL ) [S]. China Water Conservancy and Hydropower Press, 2005 [9] ISO Standardization of Economic Benefits - International Case Studies. Beijing: China Standard Press. [10] He Shoukui, Wang Yuanyuan, Huang Mingzhong, The management mode of water users association from the perspective of autonomy, China Rural Water and Hydropower, pp: [11] Zhou Guangan, Zhang Luyang, Sun Jingke Exploration and practice of new pattern for secondary water supply management, China Water & Wastewater, (18):