Climate Change and Land use Impacts on Flood in : Preliminary Results for Terengganu River Basin

Zulkifili Yusop1, Ahmad Zuhdi Ismail1 1 Centre for Environmental Sustainability and Water Security, Universiti Teknologi Malaysia

zulyusop@utm.

25 May 2016 Zulkifli Yusop

1 Outline

• Flood in Malaysia, major land use • Major Land use practices • Flood responses to land use • Climate change influence • Case Study: Terengganu River Basin

Source: Zulkifli Yusop (UTM) Introduction

3 Flood Prone Areas in Malaysia

• Affecting 10.1% of the total land mass and 5.67 million population • Average annual loss is about USD 250 mil.

Source: Zulkifli Yusop (UTM) Water Related Disaster in Malaysia

No Type of Disaster No of No of Remarks Death victim 1 Flood 1965 6 300,000 and Terengganu River Basins 2 Flood 1967 50 125,000 Kelantan, Terengganu and River Basins 3 Flood 1970 61 243,000 Kelantan, Terengganu, Perak , Muar and Kelang River Basins 4 Highland Towers landslide 1993 48 1000 Heavy storm that led to landslide , causing collapsed of one of the buildings at Highland tower apartment 5 Flood 1993 30 20,000 Kelantan, Terengganu, Perak, Kelang, Muar and River Basin 6 Debris flow at Genting Sempah 1995 20 5,000 Heavy storm series of debris flow. 10 vehicles were washed away 7 Storm Greg, Sabah, 1996 270 1,150 Tropical storm caused landslide and debris flow 8 Debris flow, Post Dipang 1996 44 500 Heavy storm caused landslide, riverbank erosion, burst of debris dam and debris flow 9 Landslide Kg Gelam, Sabah, 1999 17 300 Heavy storm cause landslide 10 Flood 2006 52 244,051 Kelantan, Terengganu, Perak, Kelang, , Muar and Batu Pahat River Basins 11 Landslide, Hulu Langat 2011 16 200 Heavy storm caused landslide 12 Flood Dec 2014 25 300,000 Kelantan, Terengganu, and Perak River basins, 1600 lost homes

Source: Zulkifli Yusop (UTM) Zulkifli Yusop (UTM) Malaysia’s Reported Losses Between 1990-2014. (CEDM&HA, 2015)

Source: Zulkifli Yusop (UTM) Major floods were reported since the early 20th century

10 days rainfall in Dec 1926, has caused large flood, known as “Bah Merah” or red flood by the local people in the state of Kelantan. The flood had caused losses of life and damages to houses and agricultural crops. About 40 years latter, in 1967, another big flood occurred which had taken 38 life and about 537,000 people British Officers during large flood in , Kelantan in 1926. were evacuated (84% of the population).

Zulkifli Yusop (UTM) Landuse

Forest - an Ultimate Protection

. Forest: multi- layered canopy, undergrowth, litter layer, thick hair root  high infiltration . Low erosion < 1 ton/ha/yr

NPS 2015: Zulkifli Yusop 9 Rainfall Forest Hydrological Evapotranspiration Cycle (1400mm/yr)

Transpiration Evaporation Interception -15-20%

Throughfall -80% Infiltration

Stemflo w 1% Tree uptake Overland flow <1%

Bedrock Water Table

Baseflow or Groundwater flow Urban

Vegetated/forested Forested/ Urban catchment – Catchment – more vegetated

Simple runoff processes complicated runoff Discharge processes

Time

Rainfall

Saturation Excess Sub surface SF Overlandflow Return Flow Horton Overland flow Channel Prec

Qg

Saturated Upstream Land use Stormflow Response

Tp Qp • Peakflow, Qp - increase • Stormflow volume, Qv - increase • Time to peak, tp - shorter Qv

Zulkifli Yusop (UTM) 13 Stormflow Response to Rainfall in Forested Catchment

Natural Forest Plantation Forest

35 mm 22 mm 52 mm 48 mm Peakflow Response to Storm Size

Peakflow

Is full reforestation Runoff/Rainfall =Q/P

adequate for flood control? Non Forested Non Forested

Peakflow Reduced storage capacity

Forested Runoff Coefficient (%) Coefficient Runoff Forested Different in initial loss

Rainfall Return Period (yr) Storm Size (mm) Zulkifli Yusop (UTM) Rainfall that caused Kelantan 2014 Flood

550 • Max Rainfall at Gunung Gagau 1765 mm (17 to 24 450 Dec)

350 • Other stations; Jenob 997 mm, Kusial 918 mm, Kuala 250 Kerai 704 mm, Dabong, 791

Rainfall (mm) Rainfall 150 mm, Tualang 783 mm, Kg Aring 655 mm 50 • Water level peak at on 25 Dec -50 • Annual Rainfall 2300mm Days Gunung Gagau Kg. Aring Gua Musang Kg Jeli Kg. Laloh Dabong Tualang Kuala Krai Jenob Kusial Jeti Kastam

Zulkifli Yusop (UTM) flood 2006/07

19.12.2006 12.1.2007 Total rainfall First wave = 486 mm Second wave = 356 mm

More prone to flood when the hydrologic storage has been filled up

Kota Tinggi High High Kota Tinggi

Medium Medium

Low Low 2014 Flood in Kelantan

Zulkifli Yusop (UTM) Flash Flood in

Source: Zulkifli Yusop (UTM) Framework for V&A Guidelines for Updated Intensity-Duration-Frequency FLOOD MITIGATION Curve (IDF) –Design Rainstorm

15Min Rainfall Freq. Analysis (AM Data) New Site 3117070@JPA Ampang Design Rainfall 90.00 AM Data:1970-2004 GEV:1970-2004 Upper confidence limit of EV1:1070-2004 Design Rainfall (for climate 80.00 UCL-GEV change LCL-GEV adjustment/adaptation) 73.4 UCL-EV1 LCL-EV1 70.00 HP1 66.9

60.4 65.7 60.00 58.3 61.4

51.6 56.8 55.2 50.00 51.0 Raindepth(mm) 44.6 50.1

46.0 44.4 40.00 42.0 34.1 38.0

34.9 30.00 32.0 Existing Design Rainfall

20.00 -2.000 -1.000 0.000 1.000 2.000 3.000 4.000 5.000 Reduced Variate, Y 20 1000.0 RAINFALL INTENSITY-DURATION-FREQUENCY CURVE 1437116-Stor JPS Johor Bharu

BASELINE 74.0T 0.1633 + CC I  100-Y d  0.12080.7928

100.0

100-Y 24Hr : 12.6mm/hr 0.1633 59.9723T 100-Y

Rainfall Intensity (mm/hr) Intensity Rainfall I  10.0 d  0.1208 0.7928 BASELINE

1.0 0.1 1 Duration (hrs) 10 100 Sea Level Rise

. Data on sea level rise collected over 20 years (1986-2006) at the southern tip of recorded an increase of 1.3 mm/year or 13 cm per decade. . Global mean 10 to 20 cm over the past century. In the future, the rise is expected to take place at a much faster rate . Salt water intrusion: already detected in some rivers, Sg Johor, Sg Muar . More intense coastal erosion 22 . Damage to agricultural crops Flood Mapping – Terengganu River Basin • Basin area =1,978 km2, total river length ~ 120km • A large man made reservoir (Kenyir Dam) in the upstream; catchment area 2,600 km2 and water body 370 km2. • Capacity 13.6 bil m3. • The reservoir has been effective in attenuating large floods • But during the 2014 Flood, the dam water level has reached maximum and the highest over the last 30 years • Strong need to simulate future flood affected by changing landuse and climate change

Landuse in 2010 and projected in 2020

Terengganu river basin Forest area +1.56% and its sub catchment Agricultural area - 8.72% Develped aea +98.4% Historical Observed, Flood Event 2014

Downstream (mm) (mm) 350 350 300 300 250 250 Menerong 200 200 STOR JPS KTRG Kg. Embong 150 150 RP P.MUSANG K. Berang 100 100 RP.P.BAHAGIA Dura 50 50 0 0 11 12 13 14 15 16 17 18 19 20 21 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 (Disember) (Disember) • Total rainfall in the upstream over 10 days was 1677 mm, 2.8 times higher then the average December rainfall Hydrological Modeling

. The model was calibrated and validated using streamflow data at Sg. Telemong at Kuala Ping (St no: 5129438) . Areal rainfall was estimated using data from 19 stations . Calibration data: 23 to 26 Nov. 2008, and for the validation from 23 to 27 Nov on 2010. . The events represent highflow but not causing flood. . Calibration using flood event data is not possible because of overbank flow that make rating the curve invalid.

General Methodology on Hydrological Analysis

Data

Data Correction Data Verification

Hydrologic Modelling Input parameter: Catchment Flow characteristic, CN and Hydrograph Tp parameters Model Calibration and Using Model Efficiency Validation (Nov 2008 and (ME) to calculated model Nov 2010) accuracy

Model applied to 2014 flood event to generate flow hydrograph Hydrological Modelling Process

• Hydrological transformation method - US SCS Unit Hydrograph to • Runoff was determined from rainfall for each sub-catchment • The time to peak (Tp) from the SCS Computed unit hydrograph

where D = time duration (hrs) of excess rainfall

tc = Time of concentration Hydrological Losses

• Hydrologic losses were determined based on the CN and soil group

Soil Group The Curve Number (CN) for these The curve number (CN) is based sub-catchments can be calculated on hydrological soils type by using a composite CN which is defined as an aerial weighted average of the CNs for the each sub catchments

Where CCN = is the composite CN,

CNi = curve number for sub catchment i Ai = the area for sub catchment i. Methodology – flood modelling

Generation of flood modeling Infoworks RS 15.0 Geometry Data: i. LiDAR/IFSAR Geometry data collection ii. Cross Section iii. Rivers Model Setup iv. Banks

Simulated 2014 flood

1D Hydraulic Modeling

Flood Validation Comparison with 2D Hydraulic Modeling flood mark 2D Flood modeling for various ARI Hydrological Model Calibration and Validation

Model Efficiency, ME

• Model calibration using rainfall-runoff data from 23 to 26 November 2008 • Model accuracy 93%

• Model validation using rainfall-runoff data from 23 to 27 November 2010 • Model accuracy 80% model accuracy 2D Model Setup in Infoworks RS 2014 Flood Map at TRB

• The 2D model is validated by comparing the simulated flood against the flood marks at 20 locations. • About 80% accuracy Simulated Flood Maps

Year 2014 Year 2020

14% difference in flood extent and 13% for flood depth. Simulated Flood in 2014 and 2020

The differences in flood 2014 extent and depth in 2014 Vs 2020 at the downstream of Terengganu River Basin.

2020 Conclusion

• Prolonged and heavy rainfall is always the main factor contributing to major floods • Forested land could attenuate normal floods but not for big floods. • Future flood is expected to be more severe due to more intense rainfall, more impervious land and sea level rise.

THANK YOU Model Setup - 2D Hydrodynamic

• The integration of 1D and 2D, give a new dimension on flood visualization • IFSAR data was used for DEM model input • The upstream boundary condition used present and future precipitation as the main input • The modeling of downstream boundary condition used the Highest Astronomical Tide (HAT) of 3.02m was adopted in flood as the boundary condition Climate Change Impact

39 Elsewhere – Forested Catchment

Stormflow vs Rainfall in oil palm 70 catchment 60

50

40

30 H.J. Andrews

20 Panola 4 mm Storm total (mm)flow Maimai Tatsunokuchi-yama 10

0 0 10 20 30 40 50 60 70 80 90 100 Storm total precipitation (mm)

Panola, Georgia, USA (Tromp-van Meerveld and McDonnell, Chapter 1) Maimai, New Zealand (Mosley, 1979) Tatsunokuchi-yama exp. forest, Honsyu Island, (Tani, 1997) H.J. Andrews exp. forest, Oregon, USA (McGuire, unpublished data) Soil Moisture Storage

• Deeper soil has bigger capacity to store water • Higher initial loss

Source: Zulkifli Yusop (UTM)