International Conference on Computer Science and Information Technology (ICCSIT'2011) Pattaya Dec. 2011

Mathematical Modeling for Flood Forecasting in the : AmphurMuang, , Case

Kantima Meeyaem1, Pattarawit Polpinit2,*

damaging cause is becoming more serious. A reliable system Abstract— This paper develops a mathematical model in order that can predict a water level in the Chi River that can be used toanalyze the maximum water level of the area in the Chi River as a basis for forecasting the floodscan be helpfulfor basin. The analysis is based on Gumbel distribution function that has authorities to set up planand toprevent and mitigate damage been shown to be generally effective with the areas in Thailand [1], from flood that occurs at areasnear Khon Kaen on both sides [2]. The study area is PhraLup district that is separated from the Khon Kaen City only by a bypass road. A heavy flood on that area of the Chi River. will directly affect the city. The data of monthly water levels from the Flood forecasting has been studied for a long time using hydrological station (E.16A) of the year 2005-2010 are used.The various different methods in many different fields. There are results show that the recurrence period of the maximum water level is software programs to flood forecasting allows the user to approximately2 years.The water level at the recurrence period is conveniently forecast flood. For exampleMIKE11 model and approximately 152 m.(MSL.). This resultsshow0.46-2.61% error INFOWORKS RS model that is software programs for flood when tested with real data. This information is a basic data for forecasting[7],flow routing algorithm and the probability floodforecasting and flood warning system. distribution functionsare algorithm for flood forecasting [8]. Keywords—Maximum water level, Gumbel Distribution This paper chooses the probability distribution functions to Functions,Period of recurrence, Flood forecasting. develop the mathematical modeling for flood forecasting. This paper studies a mathematical model used to analyze I. INTRODUCTION the likelihood of flood.Gumbel Distribution Functions are ATURAL disaster is one of the most serious problems that used in order to analyze the water level ofthe Chi River.The Nare affecting countries worldwide. Flood is one of the results show the predicted recurrence of the maximum water main natural disasters that can cause a large damaging area level,the minimum of the maximum water level and the water and has a long-term effect after. In the year 2010 and recently level at each the period of recurrence.This information can be in 2011, flood has been causing a large damage in many essential to prepare for futureflood problem and help find the for example NakhonRatchasima in the best way to cope with current flood.The study area in this northeast[3],Phitsanulok, Sukhothai, Lampang and Chiang paper is the Chi River at the hydrological stations E.16A in Mai in the north[4],Songkhla in the south [3], Ayutthaya, Lop AmphurMuang, Khon Kaen. Buri, NakhonSawan, Phichit, and Ang Thong in the central, and even in . II. THE STUDY AREA Flood is a problem that is difficult to predict because there A. Detail of the Study Area are many natural and unnatural factors that can cause flood. The study area isBan Phue that is a village located at the Monitoring these factors can help predicting the likelihood of PhraLup district next to the Chi River,thatis in flood. Whenthe potential of flood occurrence is high the AmphurMuang, Khon Kaen. The area is at third section of the appropriate preparation can be set upfor the minimal impact Chi River in between the hydrological stations E.16A and E.1, and damage.Flood real time monitoring system and flood as shown in Fig.1. forecasting model is difficult to develop, due to a large amount of data required are difficult to obtain. Khon Kaen province is located in the northeast of Thailand with the population of 187,242 [5] in the capital of the province. The province has flood almost every year especially in the areas along both sides of the ChiRiver [6]and the

Kantima Meeyaemis a graduate student at the Department of Computer Engineering, Faculty of Engineering, , Khon Kaen, 40002 Thailand (corresponding author to provide phone: +66880545052; fax: 043918140; e-mail: [email protected]). Pattarawit Polpinit is alecturer also at the Department of Computer Engineering, Khon Kaen University, Khon Kaen, 40002 Thailand (e-mail: [email protected]). Fig. 1 Maps of the Study area [9],[10]

42 International Conference on Computer Science and Information Technology (ICCSIT'2011) Pattaya Dec. 2011

The study area has the hydrological stations E.16A on the road. If the study area gets flood, a bypass road can be a wall, upstream of the Chi River close to the study area. protecting water getting into the city. However,if the flood According to the flood news of Department of Royal problem becomes more serious, the road may not be sufficient, Irrigation [11] PhraLup districtnear the Chi River is one of and this situation has been nearly happen in the past.Therefore flood problem region. The reason is because normally water flood problem in the study area directly affects Khon Kaen from Ban Phue canal flow to the Chi River. If there are a lot of City. heavy rains, thewater level of the Chi River that getswater from upstream will rise steadily. Therefore the water cannot III. GUMBEL DISTRIBUTION FUNCTIONS easily flow to the Chi River affecting nearby area to be Gumbel Distribution Functionsare one type of the flooded. probability distribution functions that is effective to be applied

to flood flows with respect to the criteria required [12]. In the paper titled “Regional Flood Frequency Analysis of Thailand Research” [1], Md. AbdusSabur conducted a flood frequency analysis of the divided flood regions in order to determinethe best probability distributions of annual flood peaks in Thailand. Sabur recommended that the best probability distribution function for fitting the empirical frequency distribution of annual flood peaks series in Thailand is Gumbel Distribution Functions. Natural Environmental Research Council of the United Kingdom [2] also recommended that the first choice among distributions of the annual flood peaks, when only a small sample is available and the distribution to be fittedif an estimate based on the sample data along is required, is Gumbel distribution. A. Gumbel Distribution Gumbel Distribution Functions arethe method for estimating two parameters function. Gumbel E.J. [13] proposed a common term, a continuous random variable is said to follow a Gumbel distribution if its distribution function is given as: 𝑋𝑋 ( ) = [ { }] (1) Fig. 2 Flood in Ban Phue, PhraLup District

The temporary solution for the problem is to use water when 𝐹𝐹 =𝑥𝑥 𝑒𝑒𝑒𝑒𝑒𝑒 − 𝑒𝑒𝑒𝑒 𝑒𝑒 −𝑦𝑦 (2) pumps to drain from the flood area to the Chi River. There has 𝑋𝑋−𝛽𝛽𝑂𝑂 and , are parameters of Gumbel Distribution. been no system for flood forecasting or flood warning to 𝑦𝑦 𝛼𝛼𝑂𝑂 It can be shown that the mean and standard deviation are as prevent flood within the district. 𝑂𝑂 follows 𝛼𝛼respectively,𝑂𝑂 𝛽𝛽 B. The Importance of Geography of theStudy area = + 0.45 (3)

PhraLup district,AmphurMuang, Khon Kaen has a = (4) 𝜇𝜇 𝛽𝛽 6 𝜎𝜎 geographical importance to be studied.Thedistrict is close to a 𝜋𝜋 bypass road thatis in the southeast of Khon Kaen City, as B. Estimation𝛼𝛼√ of parameter: Moment method shown in Fig.3. 𝜎𝜎 Moment method [14]:By using Eqs.(3) and (4) and by using the sample mean, , and the sample standard deviation, , as the population mean, , and population standard deviation, , respectively, the moment𝑋𝑋� estimates, , and can be obtained𝑆𝑆 by solving the following𝜇𝜇 Eqs. 𝜎𝜎 𝛼𝛼 𝛽𝛽 = (5) 6 𝜋𝜋 𝑂𝑂= 0.45 (6) 𝛼𝛼 𝑆𝑆√ Where𝑂𝑂 and are defined as 𝛽𝛽 1𝑋𝑋� − 𝑆𝑆 = (7) 𝑋𝑋� 𝑆𝑆 =1

𝑛𝑛 Fig. 3Geography of the Study Area [9] 1𝑖𝑖 𝑖𝑖 2 𝑥𝑥̅ = 𝑛𝑛 ∑ 𝑥𝑥 ( ) (8) Khon Kaen City is surrounded by a bypass road. The study 1 =1 𝑛𝑛 area is close to Khon Kaen City and in between is a bypass where𝑠𝑠 being�𝑛𝑛− the ∑number𝑖𝑖 𝑥𝑥 of𝑖𝑖 − observations 𝑋𝑋� (or sample size). 𝑛𝑛 43 International Conference on Computer Science and Information Technology (ICCSIT'2011) Pattaya Dec. 2011

C. Period recurrence TABLE I THE WATER LEVEL DATA FROM THE HYDROLOGICAL STATION E.16A [16] Find the period of recurrencefrom ( ) [15] by defining Year ( ) = ( ) = 1 ( ) (9) 2006 2007 2008 2009 2010 𝐹𝐹 𝑥𝑥 month and (m.(MSL.)) (m.(MSL.)) (m.(MSL.)) (m.(MSL.)) (m.(MSL.)) 𝐹𝐹 𝑥𝑥 𝑃𝑃 𝑋𝑋1 ≤𝑥𝑥 − 𝑃𝑃 𝑋𝑋 ≥𝑥𝑥 ( ) = 1 (10) January 146.790 146.970 146.690 14 6 . 9 3 0 14 6 . 9 3 0 February 14 6 . 9 3 0 146.970 14 7 . 6 10 147.200 146.790 The period𝐹𝐹 recurrence𝑥𝑥 − 𝑇𝑇𝑟𝑟 can be found as March 14 6 . 8 0 0 146.700 14 7 . 0 9 0 147.230 146.780 ( ) 1 = 1 𝑟𝑟 (11) April 146.860 147.000 146.750 146.480 146.620 −𝑦𝑦 𝑇𝑇 We take logarithm− 𝑒𝑒 on both sides of (11), we have May 146.880 14 7 . 13 0 146.950 146.730 148.770 𝑇𝑇𝑟𝑟 𝑒𝑒 − 1 June 147.890 148.990 152.900 14 7 . 9 0 0 15 0 . 7 10 (12) = { 1 } July 152.090 15 1. 9 4 0 152.520 15 1. 4 2 0 153.290 August 15 1. 6 5 0 15 1. 8 8 0 15 1. 6 0 0 15 0 . 9 10 153.380 𝑦𝑦 −𝑙𝑙𝑙𝑙⁡−𝑙𝑙𝑙𝑙 � − 𝑇𝑇𝑟𝑟 � IV. MODEL CONCEPT September 146.980 146.860 150.800 146.980 147.350 The model studied in this paper uses Gumbel Distribution October 147.020 146.760 146.860 146.880 14 6 . 8 0 0 Functions to analyze and predict the water level in the Chi November 147.000 146.760 14 6 . 8 3 0 14 6 . 9 10 153.397 River. By use the monthly water level data of the Chi River of December 146.990 14 6 . 7 10 146.850 14 6 . 9 3 0 146.988 the previous yearswe predict theperiod of recurrencein the A. The analysis of annual water level future. The results of the analysis are basic information for flood forecasting and flood warning. The input/output are as From Table I,the average of the annual maximum water follows: level and standard deviation at the hydrological stations E.16A input: the average amount of water/the maximum water are 152.0875 and 0.6130, respectively. These results are based level data of the hydrological stations E.16A on the annual water level of the continually four years. Then output:the period of recurrence andthe water level at the calculation of the two parameters of Gumbel Distribution each period of recurrence Functions; are 0.4780 and are 151.8116.

The Gumbel Distribution Functions model concept is I) From 𝛼𝛼the𝑂𝑂 relative value 𝛽𝛽of𝑂𝑂 the water level ( ) and the shown in Fig.4. period of recurrence ( ), the water level ( ) can be obtained 𝑇𝑇𝑟𝑟 from the period of recurrence ( ),by solving the𝑄𝑄 following 𝑟𝑟 𝑇𝑇𝑟𝑟 Eqs. 𝑇𝑇 𝑄𝑄 The average amount of water / the maximum water level 𝑟𝑟 𝑇𝑇 1 data of the hydrological stations E.16A = 1 (13)

when 𝑟𝑟 is the maximum water level at each the 𝑄𝑄𝑇𝑇 𝛽𝛽𝑂𝑂 − 𝛼𝛼𝑂𝑂 𝑙𝑙 𝑙𝑙 �− 𝑙𝑙𝑙𝑙 � − 𝑇𝑇𝑟𝑟 �� period ofrecurrenceof the hydrological Gumbel Distribution Functions model 𝑇𝑇𝑟𝑟 𝑄𝑄 stations E.16A and is the period of recurrence The maximum water level of the hydrological stations The water level at each the period of 𝑟𝑟 recurrence E.16A ( 𝑇𝑇) at each the period of recurrence for 10 years, by at period recurrence ( ) of 2 years to 11 years, can be shown 𝑇𝑇𝑟𝑟 in Table𝑄𝑄 II. The period of recurrence of the maximum water level 𝑟𝑟 The period of recurrence of the minimum of maximum 𝑇𝑇 TABLE II water level THE MAXIMUM WATER LEVEL DATA FROM THE HYDROLOGICAL STATION E.16A AT THE PERIOD OF RECURRENCE OF 2 YEARS TO 11 YEARS

Fig. 4Gumbel Distribution Functions model concept Tr Q Tr Tr Q Tr V. IMPLEMENTATION (years) (m.(MSL.)) (years) (m.(MSL.)) The data of monthly water level from the hydrological 2 15 1. 9 8 6 8 7 152.7054 station E.16A from2005 to 2010 is used in the analysis. The 3 152.2431 8 152.7740 data of water level data from the hydrological station E.16A of theyear 2010 is used as calibration accuracy. 4 152.4072 9 152.8340 The water level data from the hydrological stations 5 152.5286 10 152.8873 E.16Aused in the study of this paper is shown in Table I. 6 152.6252 11 152.9352 The analysis of the Gumbel Distribution Functions can be

divided into two parts, namely the analysis of annual water Then the values of the maximum water level of annual are level and the analysis of monthly water level. plotted on a graph,as shown in Fig.5.

44 International Conference on Computer Science and Information Technology (ICCSIT'2011) Pattaya Dec. 2011

TABLE III THE MAXIMUM WATER LEVEL DATA FROM THE HYDROLOGICAL STATION E.16A AT THE PERIOD OF RECURRENCE OF 2 MONTHS TO 61 MONTHS

Tr Q Tr Tr Q Tr Tr Q Tr Tr Q Tr Tr Q Tr (months) (m.(MSL.)) (months) (m.(MSL.)) (months) (m.(MSL.)) (months) (m.(MSL.)) (months) (m.(MSL.)) 2 147.6806 14 15 1. 18 13 26 152.1776 38 15 2 . 7 8 16 50 15 3 . 2 16 4 3 148.5202 15 15 1. 2 9 3 3 27 152.2379 39 152.8228 51 153.2477 4 149.0575 16 15 1. 3 9 7 8 28 152.2959 40 152.8630 52 153.2784 5 149.4553 17 151.4957 29 15 2 . 3 5 18 41 152.9021 53 153.3085 6 14 9 . 7 7 17 18 15 1. 5 8 7 9 30 152.4058 42 152.9403 54 153.3380 7 150.0345 19 15 1. 6 7 5 0 31 152.4580 43 152.9776 55 153.3670 8 150.2593 20 15 1. 7 5 7 4 32 152.5086 44 15 3 . 0 14 0 56 153.3955 9 150.4558 21 15 1. 8 3 5 8 33 152.5575 45 153.0496 57 153.4235 Fig. 5The Graph of the annual predict maximum water level ( ) at 10 150.6303 22 15 1. 9 10 4 34 152.6050 46 153.0844 58 153.4509 the period of recurrence ( ) of 2 years to 11 years 11 150.7873 23 15 1. 9 8 16 35 15 2 . 6 5 10 47 15 3 . 118 5 59 153.4779 Tr 𝑇𝑇𝑟𝑟 𝑄𝑄 12 150.9299 24 152.0497 36 152.6958 48 15 3 . 15 18 60 153.5045 From the previous calculation and data, the maximum water 13 15 1. 0 6 0 7 25 15 2 . 115 0 37 152.7393 49 15 3 . 18 4 4 61 153.5306 level at period recurrence of 2 years to 11 years at the hydrological stations E.16A tends to increase steadily every Then the values of the maximum water level of monthly are year. plotted on a graph, as shown in Fig.6.

II)The period of recurrence ( ) can be obtained from the water level ( ) by solving the following Eqs. 𝑟𝑟 Forthe maximum water level case;𝑇𝑇 𝑇𝑇𝑟𝑟 𝑄𝑄 1 ( ) = ( ) = 1 (14) For the minimum of maximum water level case; 𝑇𝑇𝑟𝑟 𝐹𝐹 𝑋𝑋 𝑃𝑃 𝑋𝑋 ≤𝑥𝑥 − 1 ( ) = 1 ( ) = 1 (15) From the past data, the water level that would cause flood in 𝐹𝐹 𝑋𝑋 − 𝑃𝑃 𝑋𝑋 ≤𝑥𝑥 − 𝑇𝑇𝑟𝑟 the study area is 152 m.(MSL.) [11]. Therefore, in Eqs. (2) is set to 152. From Eqs.(2), = 0.3941. FromEqs. (14)and(15)we have:𝑋𝑋 At the maximum water level equal to 152 m.(MSL.), the value ( ) = 0.𝑦𝑦5095 and the period of recurrence is 2.04 Fig. 6The Graph of the monthly predict maximum water level ( )at the period of recurrence ( )of 2 months to 61 months years or about 2 years. Tr 𝑇𝑇𝑟𝑟 𝑄𝑄 At the𝐹𝐹 𝑋𝑋 minimum of maximum water level equal to 152 From the previous calculation and data, the maximum water m.(MSL.), the value ( ) = 0.4905 and the period of level at period recurrence of 2 months to 61 months at the recurrence is 1.9627 years or about 2 years too. hydrological stations E.16A tends to increase steadily every 𝐹𝐹 𝑋𝑋 month similar the analysis of annual water level.

B. The analysis of monthly water level The water level in the Chi River can be increased in the II)The period of recurrence ( ) can be obtained from the water level ( ) by solving the following rainy season, and when monsoons hit the study area or 𝑟𝑟 Eqs.(14)and(15).From the past data,𝑇𝑇 the water level that would upstream river. Monsoons can happen several times a year. 𝑇𝑇𝑟𝑟 Therefore is necessary to analyze the monthly water level cause flood in the study𝑄𝑄 area is 152 m.(MSL.)[11]. Therefore, From Table I, the average of the monthly maximum water in Eqs. (2) is set to 152. level and standard deviation at the hydrological stations E.16A From Eqs.(2), = 3.1251. From Eqs. (14)and(15) we are 148.0104 and 2.0082, respectively. These results are based have: 𝑋𝑋 on the monthly water level of the continually 48 months. Then At the maximum𝑦𝑦 water level equal to 152 m.(MSL.), the the calculation of the two parameters of Gumbel Distribution value ( ) = 0.9570 and the period of recurrence is Functions; are 1.5658 and are 147.1067. 23.267months or about 2 years. The result is similar to the analysis𝐹𝐹 of𝑋𝑋 annual water level. I) From the𝑂𝑂 relative value of𝑂𝑂 the water level ( ) and the 𝛼𝛼 𝛽𝛽 At the minimum of maximum water level equal to 152 period of recurrence ( ), the water level ( ) can be obtained 𝑇𝑇𝑟𝑟 m.(MSL.), the value ( ) = 0.0430 and the period of from the period of recurrence ( ), by solving the𝑄𝑄 following 𝑟𝑟 𝑇𝑇𝑟𝑟 recurrence is 1.0449 months or about every1 month.The result Eqs.(13). The maximum𝑇𝑇 water level of𝑄𝑄 the hydrological 𝐹𝐹 𝑋𝑋 𝑟𝑟 differentthe analysis of annual water level. stations E.16A ( ) at each the𝑇𝑇 period of recurrence for 60 months, by at period recurrence ( ) of 2 months to 61months, VI. EVALUATION 𝑄𝑄𝑇𝑇𝑟𝑟 can be shown in Table III. This paper uses the water level data from a hydrological 𝑇𝑇𝑟𝑟 station E.16A of the year 2005 to 2009in the analysis, and uses the water level data from a hydrological station E.16A in year

45 International Conference on Computer Science and Information Technology (ICCSIT'2011) Pattaya Dec. 2011

2010 as a calibration accuracy. ACKNOWLEDGMENT In the analysis, the valuesusing the annual water level data The authors would like to thank Department of Royal obtained from the calculation when compare tothe water level Irrigation, Khon Kaenprovince, for the data of monthly water of the actual measurement is very similarbecause the average levels from the hydrological station in the Chi River of the water level of the Chi Riverfrom the actual measurement, tend year 2005-2010tousein this research. to increase steadily every year.And in the analysisof the monthly water level,that found the values obtained from the REFERENCES calculation, at equal to 2 to equal to 6 when compare the [1] Sabur, M.A., “Regional Flood Frequency Analysis of Thailand,” Asian water level of the actual measurement is very similar, and tend Institute of Technology Thesis No. Wa-82-19, Bangkok, Thailand, 1982. 𝑟𝑟 𝑟𝑟 to increase. However𝑇𝑇 when 𝑇𝑇equal to 7, the values obtained [2] Natural Environment Research Council, “Flood Studies Report,” Vol. 1, from the calculation when compare to the water level of the Chapter 1 and 2, THE UNITED KINGDOM, 1975. 𝑇𝑇𝑟𝑟 [3] Flood news in Thailand, “Flood Problem of Provinces in Thailand, actual measurement starts to be differentiate at about 2% - 3%, 2011,” [ Online]. Available: http://www.thaiflood.com/. [Accessed: can be shown in Table IV, due to it is the rainy season and September 29, 2011]. monsoon, with the flood routing season from upstream. That [4] Department of Disaster Prevention and Mitigation, “Public hazard in Thailand,”[Online]. Available: http://www.disaster.go.th/dpm/. cause the water level is to increase. When conditions return to [Accessed: September 28, 2011]. normal, the water level will be lowered. [5] Department of Provincial Administration, “Population in Provinces,”[Online]. Available: http://www.dopa.go.th/. [Accessed: TABLE IV December 30, 2010]. THE VALUES OBTAINED FROM THE CALCULATION OF THE ANALYSIS OF [6] Sri-AmpornW. andKhantiyawichai K., “A Flooding Simulation of Chi MONTHLY WATER LEVEL WHEN COMPARE TO THE WATER LEVEL OF THE Basin,”KKU Engineering Journal Vol. 32, No. 6, pp. 803-812, ACTUAL MEASUREMENT November-December, 2005. From the calculation From the actual measurement [7] School of Engineering and Technology (SET), Asian Institute of Differentiate (%) Technology,“Flood Modeling and Management,” [Online]. Available: Tr (mont hs) Q Tr (m.(MSL.)) Tr (mont hs) QTr (m.(MSL.)) http://203.159.12.3/interimcodes/coursecatalog/CourseDetailInfo.cfm?R 2 147.681 2 146.790 0.60 everse=off&CCode=CE74.61. [Accessed: September 29, 2011]. 3 148.520 3 146.780 1. 17 [8] Viessman W. Jr., Lewis G.L. and Knapp J.W., “Introduction to 4 149.058 4 146.620 1. 6 4 Hydrology,” Harper & Row Publisher, USA, 1996. 5 149.455 5 148.770 0.46 [9] Map, “Map of PhraLup district, AmphurMuang, Khon Kaen,” [Online]. Available: http://maps.google.co.th/. [Accessed: September 29, 2011]. 6 149.772 6 15 0 . 7 10 0.63 [10] KhantiyawichaiK.,“An Application of INFOWORKS RS Model for 7 150.034 7 153.290 2 . 17 Flood Routing in Chi Basin,” Master of Engineering Thesis in Civil 8 150.259 8 153.380 2.08 Engineering, Graduate School, Khon Kaen University, [ISBN 974-435- 9 150.456 9 147.350 2.06 846-7], 2004. [11] Department of Royal Irrigation, “The confidential flooding report of 10 150.630 10 146.800 2.54 PhraLup district, AmphurMuang, Khon Kaen,”[Online]. Available: 11 150.787 11 153.397 1. 7 0 http://www.irrkhonkaen.com/2553/index.php?option=com_content&vie 12 150.930 12 146.988 2.61 w=article&id=78:2010-09-21-08-04-09&catid=37:2010-04-22-08-22- 18&Itemid=56, September 2010. [Accessed: September 21, 2010]. [12] Ward R.C. and Robinson M., “Principle of Hydrology,” McGraw-Hill VII. CONCLUSION AND FUTURE WORK Publishing, USA, 1999. By usingGumbel Distribution Functions to analyze the [13] GumbelE.J.,“Statistical Control Curves for Flood Discharges,” Transactions, AGU, Paper, Hydrology-1942, Vol. 23, pp. 489-500, water level in the Chi River at the hydrological station E.16A 1942. both annual analysis and monthly analysis, we found that the [14] Wangwongwiroj N., “Hydrology,”Department of Civil Engineering, peak of the water level tend to increase steadily.Due to Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok, Thailand, October, 2008. changes in climate in the present, raining season tends to get [15] Budhakooncharoen S., “Engineer Hydrology,” Mahanakorn University longer. If there are heavy and continuous rainsthe water level of Technology, Bangkok, Thailand, November, 2008. can increase very much.The analysis the maximum water level [16] Department of Royal Irrigation, “GAGE HEIGHT IN METER in the Chi River at the hydrological station E.16A shows that (m.(MSL.)), Water Level in Chi River,”[Online]. Available:http://ridceo.rid.go.th/khonkhan/html/kkperson.html. several months have higher level of water level at the [Accessed: October 30, 2010]. riverbank.This tends to happen every two years.This will cause the flood riverbank and flood into the city. Therefore it is necessary to have a flood warning for the people who live in the study area. However, there are many factors that will cause the water level in the Chi Riverto increase. And there are many factors that cause floodin the study area.The authors are still developing and improving flood forecasting and flood warning.The algorithm of drainage densityand flow routing in the Chi River will also be added,to provide more efficiently and accuracy flood forecasting.We also aim to develop the flood warning system provide a real time in the form of a web service.

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