TWO ALERT FLOOD EARLY WARNING SYSTEM METHOD BASED ON RAINFALL RUNOFF MODEL

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1 International Journal of Civil Engineering and Technology (IJCIET) Volume 8, Issue 12, December 2017, pp , Article ID: IJCIET_08_12_112 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed TWO ALERT FLOOD EARLY WARNING SYSTEM METHOD BASED ON RAINFALL RUNOFF MODEL Ariani Budi Safarina Civil Engineering Department, Universitas Jenderal Achmad Yani, Cimahi , West Java, Indonesia Ramli Civil Engineering Department, Universitas Jenderal Achmad Yani, Cimahi 40532, West Java, Indonesia Muhammad Shiddiq Sayyid Hashuro School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung , West Java, Indonesia ABSTRACT Some residential areas and the main road of Cimahi city that connect Cimahi with other city are often flooded. Based on rainfall runoff model, this research have prepared two alert flood early warning system method with the threshold of river water level and total rainfall. These two alerts indicate that the system is supported by complete flood process and meanwhile rainfall alert still works even though the water level sensor in trouble by sedimentation. Cimahi river cross section in the upstream, midstream and downstream have maximum discharge and water level respectively m 3 / s and 2.28 m, 95.2 m 3 / s and 1.8 m, 59.4 m 3 / s and 2.53 m. Cimahi River unit hydrograph generated threshold of total rainfall and time to peak in the upstream, midstream and downstream respectively, 915 mm and 2 hours, 80 mm and 3 hours, 50 mm and 3 hours with 0.57 runoff coefficient. Based on this calculation, the threshold used is the smallest threshold that is in the downstream area and applied as a benchmarking parameter in the upstream. The water level threshold in the upstream is 1.48 m and total rainfall threshold is 50 mm with the time for warning preparation is 3 hours. Bed river elevation is a part of threshold for sedimentation control, that repectively in the upstream, midstream and downstream are m msl, m msl and m msl. The two alert flood early warning system method as the result of the research is completed with The Information Map of Total Rainfall Threshold and Unit Hydrograph for Cimahi Flood Early Warning System and publish in the public area editor@iaeme.com

2 Ariani Budi Safarina, Ramli and Muhammad Shiddiq Sayyid Hashuro Keywords: Alert, Flood Early Warning System, Maximum Water Level, Runoff Coefficient, Total Rainfall Cite this Article: Ariani Budi Safarina, Ramli and Muhammad Shiddiq Sayyid Hashuro, Two Alert Flood Early Warning System Method Based on Rainfall Runoff Model, International Journal of Civil Engineering and Technology, 8(12), 2017, pp INTRODUCTION Flood early warning system with many sensor and information technology device is a system used for nonstructural flood control. Fakhruddin et al., (2015), make an early warning as a key element of disaster risk reduction [1]. Castro et al., (2013), Patra et al., (2015) and Hoedjes et al., (2014) used water level as the input parameters in the flood early warning system [2, 3, 4]. Philippines decision supporting system develop a Flash Flood Warning System using SMS with advanced warning information of increasing water level and water speed because these two factors considered as a triggers of flashflood [2]. Priya et al., (2017), placed pressure sensors at the bottom of the river or surroundings, which requires high maintenance cost since they can be easily destroyed or buried by floods and sedimentation [5]. Aliakbar et al., (2009) integrated hydrologic and hydraulic model in the flood eary warning system. Fluctuations in river water levels can be measured hydrologically based on several parameters namely rainfall, topography, and hydraulic [6]. Alfieri et al., (2013) simulated hydrological model for forecasting streamflow in Nanjing China. The first input of river water change is rainfall, therefore the change of river water level can be known from rainfall information through hydrological model calculation. An accurate simulation of initial model conditions and an improved parameterization of the hydrological model are key components to reproduce accurately the streamflow variability in the many different runoff regimes of the earth [7]. In some studies, rainfall becomes the parameter in flood prediction. Rodriguez et al., (2015) used extreme rainfall alert to predicting surface water flooding in England. The research relating to three case study area and the existing extreme rainfall thresholds do not relate directly to surface water flooding in all areas [8]. Patel et al., (2015) used fuzzy logic for analized rainfall runoff model. Rainfall is an input of rainfall runoff model which produces surcafe runoff that increased river water level [9]. The model represents the whole parameter of flood process. The flood of urban areas is a unity in the flood watershed. Urban flooding can come from overflowing rivers or overflowing drainage before entering the river. Identifying urban flood areas particularly vulnerable to the effects of heavy rains can be achieved by adapting hydrological models, but they require an appropriate adjustment and highly accurate input data such as land cover, soil type, humidity, wind speed, growing season, roughness and porosity of the cover, soil moisture, land-use and environmental planning strategies for disaster resilience [10, 11]. Taimeng et al., (2015) designed decision supportiny system for urban flood. Design and implementation of an urban flood defense decision support system is required big data. The system connects real-time sensor to collect streaming data, and uses a data-driven method that considers temporal and spatial factors to forecast water level in the next 6 hours. Thus, it can provide enough time for the authorities to take pertinent flood protection measures such as evacuation [12]. Kaoje (2016) used technical of GIS for urban flood risk assessment. GIS as a modern technology has several techniques and tools that can be used for effective urban flood modelling and mapping. The development of GIS functionalities for hydraulic and hydrological models made it possible to identify areas that editor@iaeme.com

3 Two Alert Flood Early Warning System Method Based on Rainfall Runoff Model are at risk of flooding in a particular earth s surface area. The purpose of flood risk mapping is to steer strategies towards protection, prevention and preparedness, in attempts to minimize future costs from flooding [13]. The purpose of this study is to create a new basic hydrology model of flood early warning system in Cimahi city that complete the system with total rainfall input beside the water level input. In the model, total rainfall threshold is converted into effective rainfall based on the runoff coefficient calculated from the land use map and the maximum discharge based on the existing cross section. Change of landuse and river cross section causing the model to be invalid, so these two parameters control the model. The model also complete with a GIS information map that contains Cimahi river cross section in the upstream, midstream and downstream, completed by its maximum discharge, unit hydrograph, total rainfall threshold, and time to peak that the printed map publish in public area. In the GIS layer is also added with ten puddle location in Cimahi city which can be used for research development by adding a threshold of the drainage system load parameter. 2. DATA AND METHOD Flow of methodology in the research consist of three steps. First step is survey and generate Cimahi River unit hydrogaph, the second is river cross section and maximum discharge threshold, and the last is landuse threshold, effective rainfall threshold and total rainfall threshold. The area of this study is located in Cimahi river watershed, with the area of 72.2 km2, including three regency cities namely Cimahi city, Bandung regency and west Bandung regency. Cimahi river is the largest river in cimahi city with the main river is 30.6 km length. Cimahi city consists of three subdistricts of North Cimahi, Central Cimahi, and South Cimahi with an total area of km2. Intersection map of Cimahi watershed and Cimahi city is shown in Figure 1. Cimahi River Upstream Cimahi City Cimahi River Downstream Figure 1 Intersection Map of Cimahi Watershed and Cimahi City Puddle points in Cimahi spread in North Cimahi, Middle Cimahi and South Cimahi with total area of puddle is 5.31 km2 and widest puddle is in Melong village, South Cimahi. The editor@iaeme.com

4 Ariani Budi Safarina, Ramli and Muhammad Shiddiq Sayyid Hashuro average puddle occurred for 2 hours with an average puddle height of 0.8 m, so that the total inundation volume that cannot be accommodated by the drainage channel is 4.3 million cubic meters. Map of subdistrict Cimahi and many puddle points is shown in Figure 2. Figure 2 Subdistrict of Cimahi and Puddle Location 2.1 Derivation of Cimahi River Unit Hydrograph Upper Cimahi River in Curug Layung area of West Bandung regency at coordinates 06o 46 '19.9" south latitude and 107o 34' 41.9" east longitude lies at an altitude of 1412 m mean sea level. The unit hydrograph at this location is derived using the Nakayasu synthetic method that has been calibrated based on the characteristics of the watershed in previous research [14, 15, 16]. The peak discharge in the upstream is 1.4 m3/s as is shown in Figure 3. Discharge(m3/s.mm) Nakayasu Unit Hydrograph Cimahi river-curug Layung Time(hour) Nakayasu Figure 3 Cimahi River Upstream Unit Hydrograph Central Cimahi river located in the territory of Cimahi city government office at the coordinates 06o52'16.4'' south latitude and 107o33'08.8" east longitude, lies at an altitude of 804 m mean sea level. The unit hydrograph at this location is derived using the Nakayasu synthetic method that has been calibrated based on the characteristics of the watershed as same as unit hydrograph in the upstream, with the peak discharge is 2.1 m3/s as is shown in Figure editor@iaeme.com

5 Two Alert Flood Early Warning System Method Based on Rainfall Runoff Model Nakayasu Unit Hydrograph Cimahi River- Government Office 2.50 Discharge(m3/s.mm) Time(hour) Nakayasu Figure 4 Cimahi River Midstream Unit Hydrograph Downstream Cimahi river in Margaasih district Bandung Regency, is located at the coordinates 06o57 36,5 south latitude and 107o east longitude, lies at an altitude of 693 m mean sea level. The unit hydrograph at this location is derived using the Nakayasu synthetic method that has been calibrated based on the characteristics of the watershed as same as unit hydrograph in the upstream and midstream. Downstream peak discharge is 3.5 m3/s as is shown in Figure 5. Nakayasu Unit Hydrograph Cimahi river-margaasih Discharge(m3/s.mm) Time(Hour) Nakayasu Figure 5 Cimahi River Midstream Unit Hydrograph 2.2 Determination of Maximum Discharge The maximum discharge of Cimahi River in the upstream, midstream and downstream is determined based on river cross section measurement. This hydraulic method is more effective at determining maximum discharge than using quantitative calculations [17, 18, 19, 20, 21]. Based on the measurements, the cross section of the Cimahi river upstream, is shown in Figure 6. Figure 6 Cross Section of Cimahi River Upstream editor@iaeme.com

6 Ariani Budi Safarina, Ramli and Muhammad Shiddiq Sayyid Hashuro Cross-sectional measurements using Real Time Kinematic Geodetic GPS that facilitates measurements in spite of rainfall. In this survey, the flow velocity is also measured at fifteen cross-sectional using a current meter. The cross section of the Cimahi river midstream, is shown in Figure 7. Figure 7 Cross Section of Cimahi River Midstream The river cross section at Margaasih is the end of the Cimahi river that flows into its main river, the Citarum river. The cross section of the Cimahi river downstream, is shown in Figure 8. Figure 8 Cross Section of Cimahi River Upstream 2.3 Determination of Total Rainfall Threshold Total rainfall means all the rainfall indicate in rainfall gauge. Not all the total rainfall flow into the river because there are abstracted and also evaporated. The rainfall that causes the increase of river water level is call effective rainfall. Estimation of effective rainfall are extremely usefull for operation planning [22, 23]. To calculate the rainfall that causes overflowing river water, effective rainfall is required while to diseminate to the public and stakeholders needed is the total rainfall that can be seen in rainfall station displays. This causes the threshold rainfall in early warning system is required the total rainfall. Effective rainfall computations with soil-water balance depend mainly on vegetative cover interception, editor@iaeme.com

7 Two Alert Flood Early Warning System Method Based on Rainfall Runoff Model surface runoff, available soil water storage capacity and evapotranspiration [24, 25]. The effective rainfall can also be estimated with a Curve Number (CN) of Soil Conservation Service (SCS) procedure. The CN parameter can be computed directly from recorded rainfall depths and direct runoff volumes in case of existing data [26][27]. Effective rainfall is also associated with runoff depth. Runoff is one of most important hydrological variables that are used in many civil works. The runoff curve number (CN) is a key factor in determining runoff in the SCS (Soil Conservation Service) based hydrologic modeling method that needs the necessary parameters such as land use map, hydrologic soil groups, rainfall data, DEM, physiographic characteristic of the basin [28]. The most common abstraction index is the φ- index, defined as the infiltration rate to be subtracted from the rainfall rate resulting in effective rainfall. The φ-index is normally estimated from concurrent rainfall and runoff records, however when only rainfall events and the runoff coefficient are available then it is possible to calculate the value of φ. ( ) (1) where r d is depth of runoff, R m is observation rainfall and t is time interval. The equation for the runoff coefficient is shown in equation 2. = (2) In this study the effective rainfall was calculated using land use on the GIS map which then produced the runoff coefficient for the Cimahi river basin. The coefficient has been calculated in the previous study and the runoff coefficient of Cimahi river basin is Direct runoff discharge is obtained by following convolution calculation, = Where Q is matrix of direct runoff discharge, P is matrix of effective rainfall and U is matrix of unit hydrograph and the index on the equation shows the size of the matrix. Direct runoff discharge is maximum discharge without baseflow. Baseflow is available from the river survey. Based on equation (3) if maximum direct runoff discharge and peak discharge from unit hydrograph are known then effective rainfall can be calculated. The threshold of total rainfall is obtained from effective rainfall and runoff coefficient. 3. RESULTS AND DISCUSSION At the upstream, flow velocity measurements show varying and inconsistent results. This is due to the declining river bed such as a ladder so that at a small depth if the river velocity is measured in the flat section then the speed becomes low and if measured near the steep one then the speed becomes high. 3.1 Maximum Discharge in the Upstream, Midstream and Downstream To predict the maximum discharge it is calculated using the maximum cross section geometry so that the slope of the water surface is equal to the bed slope of 0.17 and it can be assumed as a uniform flow. At the cross section, the result of field measurement in the dry season with the depth of 0.85 m, the average velocity is 0.4 m/s while the velocity at the wet season with the depth of 1.3 m is 2.9 m/s. At this cross section with the depth of 2.3 m the maximum discharge is m 3 /s. (3) editor@iaeme.com

8 Ariani Budi Safarina, Ramli and Muhammad Shiddiq Sayyid Hashuro The river cross section at Cimahi office Government, is not as steep as in the upstream. Field measurement in the dry season with the depth of 0.4 m, the average velocity is 0.3 m / s while the velocity at the wet season with the depth of 1.03 m is 2.9 m/s. At this cross section predicted maximum discharge at the depth of 1.8 m is 95.2 m 3 /s. The discharge is calculated using the maximum cross section geometry so that the slope of the water surface is equal to the bed slope of and it can be assumed as a uniform flow. The river cross section at Margaasih has a bed slope of Field measurement in the dry season with the depth of 0.52 m, the average velocity is 1.1 m/s. Velocity at the wet season with the depth of 1.3 m is 2.9 m/s. At this cross section with the maximum depth of 2.53 m the maximum discharge is 59.4 m 3 /s. The discharge is calculated using the maximum cross section geometry so that the slope of the water surface is equal to the bed slope and it can be assumed as a uniform flow. Visualition of the three cross sections can be seen in the Figure.9 Figure 9 Maximum Discharge of Cimahi River at The Upstream, Midstream and Downstream 3.2 Threshold of Total Rainfall Based on the convolution equations and baseflow discharge, the effective rainfall at the maximum discharge in the upstream, midstream and downstream sections is 522 mm, 46 mm and 29 mm. Baseflow discharge at upstream, midstream and downstream is respectively 0.41 m3/s, 0.56 m3/s and 0.58 m3/s. Effective rainfall is converted into total rainfall using the approach of runoff coefficient so the total rainfall threshold at the upstream, midstream and downstream sections respectively are 915 mm, 80 mm and 50 mm. Effective rainfall and threshold of total rainfall is shown in Figure 10. Figure 10 Effective Rainfall and Threshold of Total Rainfall editor@iaeme.com

9 Two Alert Flood Early Warning System Method Based on Rainfall Runoff Model Threshold of total rainfall in the midstream and downstream is smaller than the threshold in the upstream cross section due to high peak discharge in unit hydrograph and also narrowing of rivers and houses in riverbanks, the location is near Melong Village, one of the flood area in Cimahi city. This threshold rainfall is the total rainfall, not the effective rainfall so it can be inputted from the automatic rainfall station as an input in the Cimahi flood early warning system besides river water level. If the rainfall reaches the threshold then the alarm will sound. The alarm will also sound if the threshold of the maximum water level is reached. In flood conditions, meaning the water level reaches the maximum level, coming from the threshold rainfall. This condition is accurate for land use condition with 0.57 drainage coefficient and cross section of river in the above condition. If there is any change in both parameters then the threshold rainfall becomes invalid. This means that the input of rainfall threshold can control the changes of land use and cross section of the river. 3.3 Rainfall Runoff Model for Two Alert Flood Early Warning System Method of flood early warning system in the research is analized with rainfall runoff model that serves as early warning and flood prevention. The method uses the overall flood process parameters in the model. Parameters that can provide flood prevention function are the runoff coefficient that controls land use change and river cross section which controls the change of maximum river capacity due to river basin agradation due to sediment motion. The peak time of the unit hydrograph of each cross section is used to determine the evacuation time in the flood early warning. This time it is used by stakeholders to make policies in flood conditions such as the diversion of traffic flows and appeals to citizens to save valuable items that may be flooded. This time is also used by the community to be alert to the policies of stakeholders. The smallest peak time of the three unit hydrographs is the peak time at the upstream of 2 hours. If this time is calculated since half the duration of effective rainfall then the time available for evacuation is 1.5 hours, meaning if the alarm sounds then the stake holder can immediately take a policy such as closing the area or divert traffic flow. Cimahi watershed map, Cimahi city map, puddle area and all the parameters that analized in the research are included in an information GIS map for flood early warning system namely The Information Map of Total Rainfall Threshold and Unit Hydrograph for Cimahi Flood Early Warning System as a part of new model as is shown in Figure 11. This map is printed and diseminated in the public area and rainfall station. The threshold used is the smallest threshold that is in the downstream area and applied as a benchmarking parameter in the upstream. The final water level threshold in the early warning system is referring in the upstream equal to 1.48 m and with rainfall threshold is 50 mm and the time for warning preparation is 3 hours. Bed river elevation is a part of threshold for sedimentation control, that repectively in the upstream, midstream and downstream are m msl, m msl and m msl. The scheme of the two alert flood early warning system can be seen in figure editor@iaeme.com

10 Ariani Budi Safarina, Ramli and Muhammad Shiddiq Sayyid Hashuro Figure 11 The Information Map of Total Rainfall Threshold and Unit Hydrograph for Cimahi Flood Early Warning System Upstream Water Level Station Midstream Water Level Station Downstream Water Level Station Remote Sensing Data Logger Alarm Master Station Rainfall Station SMS Gateway Reporting Rainfall Station Stake Holder Public RunoffCoefficient (Landuse) River Cross Section (Bed Elevation, Top Width) Figure 12 Two Alert Flood Early Warning System Method Scheme

11 Two Alert Flood Early Warning System Method Based on Rainfall Runoff Model 4. CONCLUSION Two alert flood early warning system have been developed in order to provide a system that is resistant to sedimentation and has a preventive function against flood by adding threshold parameters ie threshold rainfall. Threshold rainfall is controlled by land use conditions through runoff coefficient and cross section of river through maximum discharge. Contribution of these parameters would improve the system to be more accurate because the rainfall is initial process in rising river water level so the system is controlled by the whole flood process in a rainfall runoff model. ACKNOWLEDGEMENTS This research is fully supported by Ristekdikti Competitive Research, SP DIPA /2017 and UNJANI Competitive Research SKEP/133/UNJANI/VII/2017. The authors fully acknowledged Ministry of Research Technology Higher Education (Ristekdikti) and Jenderal Achmad Yani University for the approved fund which makes this important research viable and effective. REFERENCES [1] S.H.M. Fakhruddin Akiyuki Kawasaki and Mukand S.Babel Community Responsisto Flood Early Warning System: Case Study in Kaijuri Union, Bangladesh, International Journal of Risk Reduction. 14(4): 1-9. [2] Joel T de Castro, Gabriel M Salistre, Jr.Young-Cheol Byun and Bobby D Gerardo Flash Flood Prediction Model Based on Multiple Regression Analysis for Decision Support Sstem. Word Congress on Engineering and Computer Science Proceedings Vol II San Fransisco, USA March [3] Jagadish Prasad Patra, Rakesh Kumar, Pankaj Mani. 2015, Combined Flufial and Plufial Flood Inundation Modelling for a Project Site. International Conference ICETEST India December [4] Joost C.B Hoedjes, AndreKooiman, Ben H.P.Maathuis, Mohammed.Y.Said,, Robert Becht, Agnes Limo, Mark Mumo, Joseph Nduhiu-Mathenge, Ayub Shaka and Bob Su. 2014: A Conceptual Flash Flood Early Warning System for Africa, Based on Terrestrial Microwave Links and Flash Flood Guidance. International Journal of Geo-Information 3(2): [5] Priya Menon K, Kala L A Review of Flood Monitoring: Design, Implementation and Computational Modules. International Jornal of Innovative Research in Computer and Communication Engineering. 5(2): [6] Aliakbar Matkan, Alireza Shakiba, Hossain Pourali and Hamid Azari Food Early Warning With Integration of Hydrologic and Hydraulic Models, RS and GIS (Case study: Madarsoo basin, Iran). World Applied Sciences Journal. 6(12) : [7] L.Alfieri, P.Burek, E.DutraB.Krzeminski, D.MuraroJ.Thielen and F.Pappenberger. 2013, GIoFAS-Global Ensemble Streamflow Forecasting and Flood Early Warning. Journal Hydrology and Earth System Sciences. 17: [8] S.Ochoa-Rodriguez, LP Wang, L Thraves, A. Johson and C.Onof Surface Water Flood Warnings in England: overview, assessment and recommendations based on Survey Responses and Workshps. Jornal of Flood Risk Management. 1:1-11. [9] N.H Patel, T.M.V Suryanarayana An Use of Fuzzy Logic for Development and Analysis of Rainfall-Runoff Model International Journal of Modern Engineering Research,. 4 (2): editor@iaeme.com

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