Flash Flood Risk Mitigation Plan: Zarqa Ma'in Basin, Along the Dead

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INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 03, MARCH 2020 ISSN 2277-8616 Flash Flood Risk Mitigation Plan: Zarqa Ma‘in Basin, Along The Dead Sea In Jordan

Hüseyin Gökçekuş, Youssef kassem, Nour Alijl and Mohammad Tawalbeh

Abstract— Flash flooding risk impacts can be reduced through the implementation of mitigation strategies plan (MSP) on flood management. Flood risks and natural hazards, which have been increased due to changing physic characteristics of the hydrological system caused by climate change in the Middle East In this decade and all over the world. The presented paper proposes a flash flood risk mitigation plan(FFRSMP) to be implemented by municipalities, provincial administrators and authorities to reduce impact of flash flood based on identified strategies, risk matrix and generated flood inundation map using 2D HEC-RAS software based on unsteady flow analyses for rainfall with limitation of measured data, applied on wadi Zarqa Ma‘in (hot springs ) in dead sea area, a fill sink digital elevation model (DEM) was extracted to analysis catchment area, flow accumulation, channel networks, basins, slopes, flow path using SAGA and QGIS.

Index Terms— flash flood, risk matrix, DEM, QGIS, HEC-RAS, mitigation, strategies plan. ——————————  ——————————

1 INTRODUCTION Flash floods are natural hazard frequently occurred over the world and a harmful risk for human beings, and flood impact is 2. The study proposed a scheme integration of hydrological about a 30% of the economic losses mete out to natural models based on runoff simulation and rainfall data hazards [25]. Over 175,000 people were killed in a total 1816 mutually with FIM to assess the flash flood risk impact for flood worldwide in 1975–2001[11] Moreover, around 2.3 billion Wadi Fatimah in an arid region in Saudi Arabia (SA) Using people from the third of the world's population has been GIS techniques. This concludes the integrated scheme is affected by floods in last 20 years due to climate changes a useful tool to evaluate the impact of flood risk and which have been estimated by the United Nations [24]. hazard, in addition, the dam construction with limited Conducting and planning for the flood risk which is identified as ‗hazard‘[2] can be translated into maps developed by measured hydrological data [7]. computer modeling showing the boundary of the terrain at risk 3. The study is conducted the United States, including Iowa - as well as flow depth, water surface elevations(WSE) and Cedar River watershed and Alabama - Black Warrior River velocities to inform the public, planners, decision-maker about to compare two new generated hydrodynamic model for prone areas inflicted by flood. Previous studies over the world flow inundation maps using 2D HEC-RAS, and low- have used the same criteria as summarized below. complexity tools HAND( AutoRoute and Height Above the Nearest Drainage ), which result as fast predictions tool in 1. a hydrological model considering the wetness index large-scale hyper-resolution operational frameworks [5]. using QGIS and SAGA software by using the Digital 4. The study proposed a risk flood matrix technique applied Elevation Model (DEM) of the study area. In addition to in Taibah and Islamic universities catchment in Saudi analyzing the hydraulic model using HEC-RAS under a Arabia (SA). developed matrix based on the probability of wide range of return period-flood events to generate flood flood occurrence and inundation flood map generated by inundation maps. That results in taking safety measures HEC-RAS software. A quantitative analysis was against flood impact on human beings and economic conducted to assess flood economic losses impact [8]. losses in urban areas particularly [1]. 5. The study proposed an integrated model using KINEROS2 and HEC-RAS software to forecast flash flood occurrence in Northern Vietnam which is a heavy flash ——————————————— * Correspondence Author flooding prone area. using different precipitation datasets  Hüseyin Gökçekuş, Department of Civil Engineering, Civil and which conclude a relation between flow velocity, water Environmental Engineering Faculty, Near East University, 99138 level and streamflow power to predict flood occurrence on Nicosia (via Mersin 10, Turkey), Cyprus. Email: [email protected] the gauged data [14].  Youssef Kassem, Department of Mechanical Engineering, Engineering Faculty/ Department of Civil Engineering, Civil and Environmental Engineering Faculty, Near East University, 99138 Nicosia (via Mersin 10, Turkey), Cyprus. Email: 2 STUDY OBJECTIVE [email protected] The study proposes a flash flood risk mitigation plan to be  Nour Alijl, Department of Civil Engineering, Civil and Environmental Engineering Faculty, Near East University, 99138 Nicosia (via Mersin implemented by municipalities, provincial administrators, 10, Turkey), Cyprus. Email: [email protected] authorities to reduce impact of flash flood using flood  Mohammad Tawalbeh, Department of Civil Engineering, Civil and inundation map generated by SAGA,QGIS and 2D HEC RAS Environmental Engineering Faculty, Near East University, 99138 Nicosia (via Mersin 10, Turkey), Cyprus. Email: software‘s in addition of flood risk matrix to identify local [email protected] communities and structural strategies to be used in a

3 STUDY-AREA BACKGROUND The catchment area of Wadi Zarqa Ma‘in (hot springs) is located between 35° and 36° longitude and 31° 40‘ and 31° 60‘ latitude within dead sea area which considered is the lowest point on the world as shown in Fig. 1 below. Which received a flash flood on the 25th of October 2018 that caused death for 22 people mainly school students and teachers also destroyed a bridge on the Dead Sea Cliffs. The temperatures of Wadi Zarqa Ma‘in (hot springs) area are ranged from 30 to 63℃, receiving their water from the Lower Cretaceous and older sandstones with groundwater for Wadi aquifers is the main . supply for Madaba water demand [23] Agricultural activities Fig. 2. : schematic description for proposed methodology have been developed in the study area which is supported by rainfall with major corps of wheat, tobacco, olive, barley, and The proposed method requires the main set of input data as summarized below. grapes.

 Extracted a Digital Elevation Model (DEM) in Geo-Tiff format.  Extracted hydrologic model by wetness indices.  Rainfall data.

4.1. EXTRACTED DIGITAL ELEVATION MODEL (DEM) Extracted digital elevation model (DEM) using USGS earth explorer after fill sink area by using saga plug 2.3.2 based on wang Liu method, updated DEM was used to extract network channel, flow accumulation based on top-down method, basin, slopes, flow path cross-sections and profile using Quantum Fig. 1. : Wadi zarqa ma‘in catchment area location– QGIS-street map geographic information system (QGIS10.3) software as shown in Fig. 3 below.

4 METHODOLOGY The proposed methodology is shown in Fig. 2 consists of the analysis of catchment area and flow delineation using QGIS Fig. 3. : catchment area with fill sink -DEM using SAGA and QGIS,Map and SAGA plug, gathering available precipitation data from the scale 1:250000 nearest CC02 station in the study area. The collected and analyzed runoff and precipitation to be used as input into the 4.2. EXTRACTED HYDROLOGIC MODEL BY WETNESS INDICES 2D HEC-RAS model used by US federal emergency management agency (18) to determine the flood depths, a risk A hydrologic model by wetness indices has been extracted flood matrix is generated to estimate probability and impact of using Saga 2.3.2 based on sink DEM and using basic analysis flood hazards. Quantitative risk analysis to be conducted in terrain tool as shown in Fig‘s 4 & 5 to extract Topographic future works; define strategies for local communities and Wetness Index (푇�푊�퐼�) which is widely used in hydrological structure analysis [13, 19, 23] and defined by Beven and Kirkby [4] as

푇푊퐼 ( )��( ) 푇 Where, � is the upslope area of flow accumulation (6) and �

4090 IJSTR©2020 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 03, MARCH 2020 ISSN 2277-8616 is the slope angle, assuming the soil is homogeneous and smallest catchment within the dead sea area (16) and isotropic for study area as constrain. heterogeneous area as a result of the pervious study (15) and Madaba water demands were supplied by wadi aquifers. The extracted flow path with a total length 50,126m profile shows a high difference in elevations range between 771 to - 293 and non-uniform slopes which result in increasing water velocity to reach 10 m/s and non-uniform cross sections of wadi as illustrated in Fig. 7 below.

Fig. 4. : basic terrain analysis by SAGA 2.3.2

Fig. 7. : flow path plan as per HEC-RAS model.

In summarized table 1 and Fig. 8 below slopes variances along flow path in station 0+000 to 20+420 is a gentle slope Fig. 5. : Hydrologic model by wetness indices using SAGA ,Map scale will not increase flow velocity , following stations from 20+420 1:250000 to 44+230 the slope is moderate but the velocity is increased but still within accepted velocity limit which is around 5 m/s , for stations 44+346 to 50+126 slope is steep which result to 4.3. RAINFALL DATA increase it to 10 m/s which require structural mitigations such Precipitation data is available in the nearest stations CC01 as wadi bed lining , adding sand bags , chutes , Baffles or and CC02 in the surrounding of the study area as shown in wadi diversion. Fig. 6, also there is no ungauged station to measure flow.

Fig. 8. : flow path profile.

TABLE1.: CALCULATED SLOPES FOR FLOW PATH.

Stations Elevations (m) Distance Slope From To Top Bottom (m)

17+00 771.7 0.375 0+000 17,000.0 707.96 0 1 % 0 20+42 707.9 0.741 17+000 682.61 0 3,420.00 6 % 22+22 682.6 1.114 20+420 662.51 5 1,805.00 1 % Fig. 6. : Rainfall stations within the study area and average rainfall over 22+22 23+98 662 1.467 1,763.00 636.65 Jordan Intensity-Duration-Frequency Relationship Manual IDF 5 8 .51 % Curves,2011. 23+98 30+80 636 2.399 6,821.00 473.01 8 9 .65 % 5 DISCUSSIONS AND RECOMMENDATIONS 30+80 41+12 473 2.123 ATCHMENT REA AND FLOW DELINEATION 10,317.00 254.03 5.1. C A 9 6 .01 % The catchment area is 266 km 2 which is considered the 41+12 44+23 3,104.00 254 154.68 3.201 4091 IJSTR©2020 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 03, MARCH 2020 ISSN 2277-8616

6 0 .03 % 44+34 44+62 82. 6.061 277.00 65.61 6 3 4 % 44+62 47+22 82. - 8.727 2,605.00 3 8 4 144.94 % - 47+22 50+12 - 4.420 2,898.00 144 8 6 273.02 % .94

Cross sections shown in Fig. 9 along flow path is not regular and require retention shaping to reduce flood wave.

Fig. 9. : flow path cross sections.

Accumulated flow as QGIS analysis equal 1409 cu.m/s which

compared to reported flow (1000 -1500 cu.m/s) when the flash

flood happened last year.

5.2. RAINFALL DATA As per a pervious study conducted the flow of the main wadi was decreased from 37.5 cu.m/s in 1981 to .23 in 2010 cu.m/s during 31 years measurement (17), the reported data in the Fig. 10 below was used as input to estimate flood depth using unsteady flow analysis.

Fig. 10. : annual flow dated from 1980 to 2011. Collected data for daily precipitation dated from 22nd October2018 to 31st December2018 which received from the municipality of water and irrigation was used as input for flood map inundation as shown in the Fig. 11 below the maximum daily precipitation recorded in October is 50 mm and 46.7 mm respectively. November and December the maximum daily precipitation recorded is 12.3 mm and 12.1 mm. 4092 IJSTR©2020 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 03, MARCH 2020 ISSN 2277-8616

nd Fig. 14. : flow map inundation depth based on daily precipitation dated Fig. 11. :daily precipitation dated from 22 October 2018 to from 22nd October2018 to 31st December 2018. (maximum depth =7.00 st 31 December2018. m).

In the event of dead sea flash flood, the intensity of rainfall, which reached 50 mm in a period of time not exceeding 20 minutes, the frequency as per IDF is 25 years which has been checked from below IDF diagram shown in Fig. 12 for the collected rain fall depth from 1980 to 2005.

Fig. 15. : flow map inundation depth based on annual flow dated from 1980 to 2011(maximum depth =10.00 m).

5.4. GENERATE A RISK FLOOD MATRIX

Fig. 12. : IDF curve Proposed risk matrix shown in the Fig. 16 below based on the impact of flow depth in horizontal row with classified consequences namely: low, minor, major, sever and 5.3. GENERATE INUNDATION FLOOD MAP catastrophic and probability of occurrence of return period in Using HEC-RAS software to generate a 2D hydraulic model vertical row classified to almost certain(every time), likely(1-5 based on unsteady flow analysis to estimate the water surface years), possible(25 years), unlikely(25-50 years), rare(100-200 years), which used to define degree of risk by multiply impact elevations, depth and velocity using precipitation, flow by probability and the results classified into low, medium and hydrograph and normal depth data as shown in Fig‘s 13,14 & high, represented green, yellow and red respectively. 15. Quantitative and cost analysis for the risk to be conducted in future works.

Fig. 16. : Risk Matrix

Fig. 13. : unsteady flow data and analysis tool -HEC-RAS 5.5. DEFINE STRATEGIES OF THE VULNERABLE LOCAL COMMUNITIES Due to the lack of warning system the response of emergency was weak as reported and discussed in the

previous studies [21, 9]. The strategies summarized in table most of Jordan and human alterations of the landscape to I below are essential to eliminate risk. further increase flash flood risk, being aware of the experiences and lessons learned during flash flood in dead TABLE 2.: STRATEGIES OF THE VULNERABLE LOCAL COMMUNITIES sea area. 1. Generate flooding risk maps to assess planners and Strategies Indications for evaluation decision makers for potential impact of floods to avoid. . Flood warnings to be increased to 2. A developed web platform data and information to be reach the most flooded areas. shared among NMHSs (National Meteorological and Warning system & . Warning responses to be identified Hydrological Services), Authorities, civil defense response . provide evacuation paths. educational institutions on flash floods awareness. . Implement flash flood warning system based on the France experience using 3. A global meteorological data and flash flood guideline to AIGA (method in 2017 (10). be provided, monitored based on NWP (Numerical Weather Prediction) and now casting procedures. 4. Local authorities such as ministry of water and irrigation . Flood insurance, Response after the . Provide flood assistance plan to undertake spatial planning considering flash floods flood hazards. . warning systems and responses to be 5. Proposed flood risk mitigation plan as per Fig.17 below. learned in schools and companies awareness raising . Internet pages, through learning . Accessibility of information for risk map locations.

Mental models analysis. Improving flash flood risk communication and public decision making (12).

Spatial Planning . Flood damage limitation, . Natural retention protection for catchment area. . Negative environmental fallout limitation from second flood hazard. Fig. 17. : Flood Risk Mitigation Plan

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