# Flood-Prone Area Assessment Using GIS-Based Multi-Criteria Analysis: A Case Study in Davao Oriental, Philippines

^{1}

^{2}

^{*}

## Abstract

**:**

^{2}) of Davao Oriental is under low and moderate flood risk. The high and very high flood risk area covers approximately 3.39% (192.52 km

^{2}) of the province, primarily in the coastal areas. Thirty-one out of the one hundred eighty-three (31/183) barangays (towns) are at a high to very high risk of flooding at current climate, calling for the immediate attention of decision-makers to develop mitigation strategies for the future occurrence of flooding in Davao Oriental.

## 1. Introduction

## 2. Flood Risk Assessment Methodology in Literature

## 3. Study Region and Dataset

#### 3.1. Case Study Area

^{2}. The population is approximately 558,958 with a population density of 98 km

^{2}.

#### 3.2. Dataset

#### 3.2.1. Rainfall

#### 3.2.2. Digital Elevation Model

#### 3.2.3. Administration Boundary

#### 3.2.4. Population and Socio-Economic Data

#### 3.2.5. Soil Type

## 4. Methodology

#### 4.1. Indicators and Criteria

#### 4.2. Analytic Hierarchy Process

_{ij}is the value of an indicator in the pairwise comparison matrix, X

_{ij}is the normalized score and PV

_{ij}is the priority vector. The PVs give the relative importance of the indicators being compared and represent the weights of the indicators. Table 3 depicts the normalized comparison matrix and the PVs.

_{max}was 6.121 obtained from Table S8 and then the CI was 0.024 with n = 6. Therefore, by dividing the CI by RI (1.24 for n = 6 from Saaty), the CR was obtained as 0.02. Saaty suggests the value of CR should be less than 1 to have an acceptable consistency. Since the CR was 0.02 in this case, it can be assumed that the comparison matrix was reasonably consistent so that we could continue the decision-making process using AHP.

#### 4.3. Weights by Rank

_{i}is the normalized weight for ith indicator, n is the total number of indicators under consideration (j = 1, 2, …, n) and r

_{j}is the rank position of jth indicator. Each indicator is weighted (n − r

_{i}+ 1) and then normalized by the sum of all weights ∑(n − r

_{j}+ 1). Therefore, the ranking method estimated weight should be considered as an approximation [60]. The results are given in Table 4. The average rank (AR) values are the average results from the four experts in the study area. Then, the resulting weight (W) in Table 4 was used to calculate the HI as shown in Equation (7).

#### 4.4. Ratio Weighting

_{i}is the geometric mean for ith indicator, n is the total number of indicators and W

_{i}is the normalized weight for ith indicator. The HI is computed by using the average weight (AW) in Table 4 as in Equation (10).

#### 4.5. Validation

## 5. Results

#### 5.1. Vulnerability Map

#### 5.2. Hazard Map

#### 5.3. Risk Map

## 6. Effects of Varying Consistency Ration (CR) on Flood Hazard Map

## 7. Conclusions

## Supplementary Materials

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Study area of Davao Oriental, Philippines, and its DEM dataset. (

**A**) Map of the Philippines, (

**B**) map of Mindanao where Davao Oriental is located, (

**C**) Davao Oriental map with National Climatic Data Center (NCDC) precipitation data points and (

**D**) Davao Oriental Map with its DEM and two weather stations (DOST-RXI and Hinatuan), and 70 field survey points at the historical flooded areas due to Typhoon Haiyan in 2013. The elevations of 70 field survey points flooded due to the typhoon are all between 10 m and 20 m, and thus the area below 20 m above mean sea level are considered as flood-prone (1: red zones) and the other area as non-flood-prone (0: grey zone) in Figure 1C.

**Figure 2.**Comparisons of the observed annual rainfalls at the (

**A**) Hinatuan and (

**B**) DOST-RXI Stations with the NCDC and Global Precipitation Climatology Centre (GPCC) rainfall data at DO63 and DO20 points, respectively. Annual maximums of 5-day continuous rainfall at DO63 and DO20 are also presented in green. The locations of DO20 and DO63 are 7.083° N, 125.95° E, and 8.00° N, 126.33° E, respectively.

**Figure 3.**Flowchart of multi-criteria data analysis for flood risk assessment. I1-I6 mean the six indicators and C1–C2 are the two criteria considered in the analysis.

**Figure 4.**Multi-source datasets for Davao Oriental: (

**A**) 25-yr averaged (1990–2015) 5-day continuous rainfall distribution, (

**B**) slope, (

**C**) elevation, (

**D**) soil type, (

**E**) drainage density and distance to the main channel and (

**F**) Population density. (

**G**) The resulting flood hazard map by analytic hierarchy process (AHP) method, and (

**H**) flood risk map are also shown.

**Figure 5.**Results of accuracy assessment: (

**A**) Comparison of the accuracy assessment for the three methods using accuracy (ACC), true negative rate (TNR) and true positive rate (TPR). (

**B**) Model evaluation using TPR and false positive rate (FPR). Redline show the line of discrimination or random guess. The upper part of redline indicates the model is accurate, otherwise not accurate.

**Figure 7.**AHP-based flood hazard maps with different CR scenarios, (

**A**) CR was 2.7%, (

**B**) CR was 5.8% and (

**C**) CR was 8.6%.

**Table 1.**Census of population and housing by municipality/city [48].

Municipality | District | Population | Area (km^{2}) | Density (/km^{2}) | No. of Barangay. | |||
---|---|---|---|---|---|---|---|---|

Ratio in Total (%) | 2010 | 2015 | Annual Growth Rate (%) | |||||

Baganga | 1st | 10.1 | 53,426 | 56,241 | 0.98 | 945.50 | 59 | 18 |

Banaybanay | 2nd | 7.4 | 39,121 | 41,117 | 0.95 | 408.52 | 100 | 14 |

Boston | 1st | 2.4 | 12,670 | 13,535 | 1.27 | 357.03 | 38 | 8 |

Caraga | 1st | 7.2 | 36,912 | 40,379 | 1.72 | 642.70 | 63 | 17 |

Cateel | 1st | 7.3 | 38,579 | 40,704 | 1.03 | 545.56 | 75 | 16 |

Gov. Gen. | 2nd | 9.9 | 50,372 | 55,109 | 1.73 | 365.75 | 150 | 20 |

Lupon | 2nd | 11.8 | 61,723 | 65,785 | 1.22 | 886.39 | 74 | 21 |

Manay | 1st | 7.6 | 40,577 | 42,690 | 0.97 | 418.36 | 100 | 17 |

Mati City | 2nd | 25.3 | 126,143 | 141,141 | 2.16 | 588.63 | 240 | 26 |

San Isidro | 2nd | 6.4 | 32,424 | 36,032 | 2.03 | 220.44 | 160 | 16 |

Tarragona | 1st | 4.7 | 25,671 | 26,225 | 0.41 | 300.76 | 87 | 10 |

Total | 517,618 | 558,958 | 1.47 | 5679.64 | 98 | 183 |

Indicators | R | Sl | E | Dc | Dd | St |
---|---|---|---|---|---|---|

Rainfall (R) | 1.00 | 2.00 | 4.00 | 5.00 | 6.00 | 7.00 |

Slope (Sl) | 0.50 | 1.00 | 2.00 | 3.00 | 4.00 | 5.00 |

Elevation (E) | 0.25 | 0.50 | 1.00 | 2.00 | 3.00 | 4.00 |

Distance to main channel (Dc) | 0.20 | 0.33 | 0.50 | 1.00 | 2.00 | 3.00 |

Drainage (Dd) | 0.17 | 0.25 | 0.33 | 0.50 | 1.00 | 2.00 |

Soil type (St) | 0.14 | 0.20 | 0.25 | 0.33 | 0.50 | 1.00 |

Sum | 2.26 | 4.28 | 8.08 | 11.83 | 16.50 | 22.00 |

**Table 3.**Normalized comparison matrix with priority vectors (weights). Note that the values in the tables are rounded off at 3 digits from decimal points.

Indicators | R | Sl | E | Dc | Dd | St | Sum of Rows | PV |
---|---|---|---|---|---|---|---|---|

Rainfall (R) | 0.44 | 0.47 | 0.49 | 0.42 | 0.36 | 0.32 | 2.51 | 0.418 |

Slope (Sl) | 0.22 | 0.23 | 0.25 | 0.25 | 0.24 | 0.23 | 1.43 | 0.238 |

Elevation (E) | 0.11 | 0.12 | 0.12 | 0.17 | 0.18 | 0.18 | 0.88 | 0.147 |

Distance to main channel (Dc) | 0.09 | 0.08 | 0.06 | 0.08 | 0.12 | 0.14 | 0.57 | 0.095 |

Drainage (Dd) | 0.07 | 0.06 | 0.04 | 0.04 | 0.06 | 0.09 | 0.37 | 0.061 |

Soil type (St) | 0.06 | 0.05 | 0.03 | 0.03 | 0.03 | 0.05 | 0.24 | 0.041 |

Sum | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | - | 1.000 |

**Table 4.**The results of the weights by rank (WR) and ratio weighting (RW) derived from the ranking of the indicators from the same local experts considered in the AHP method. The W and AW are the resulting weights of each indicator used in the calculations of hazard index in Equations (7) and (10) (refer to Tables S9 and S10 in the Supplementary Material for derivation procedure).

Indicators | Weights by Rank (WR) | Ratio Weighting (RW) | |||
---|---|---|---|---|---|

AR | W | GM | W | AW | |

Rainfall (R) | 1.5 | 0.26 | [2.99,1.98,1.98,2.99] | [0.38,0.27,0.25,0.41] | 0.33 |

Slope (Sl) | 1.75 | 0.25 | [1.98,2.99,2.99,1.47] | [0.25,0.40,0.38,0.20] | 0.31 |

Elevation (E) | 2.75 | 0.20 | [1.26,1.26,1.26,1.26] | [0.16,0.17,0.16,0.17] | 0.17 |

Distance to main channel (Dc) | 4.75 | 0.11 | [0.79,0.44,0.79,0.79] | [0.10,0.06,0.10,0.11] | 0.09 |

Drainage (Dd) | 4.75 | 0.11 | [0.51,0.40,0.51,0.51] | [0.06,0.05,0.04,0.05] | 0.06 |

Soil type (St) | 5.5 | 0.07 | [0.33,0.33,0.33,0.33] | [0.04,0.05,0.04,0.05] | 0.04 |

Sum | - | 1.00 | [7.87,7.40,7.87,7.35] | [1,1,1,1] | 1.00 |

**Table 5.**Confusion matrix to calculate the accuracy (ACC), true positive rate (TPR), true negative rate (TNR) and false positive rate (FPR) for performance evaluation of three methods, AHP, WR and RW.

Observed | Predicted | ||
---|---|---|---|

Flood | Non-flood | Sum | |

Flood | true positive (TP) | false negative (FN) | P |

Non-flood | false positive (FP) | true negative (TN) | N |

AHP | |||

Flood | 228,388 | 298,332 | 526,720 |

Non-flood | 358,439 | 701,247 | 1,059,686 |

RW | |||

Flood | 197,607 | 329,113 | 526,720 |

Non-flood | 719,362 | 340,324 | 1,059,686 |

WR | |||

Flood | 209,746 | 316,974 | 526,720 |

Non-flood | 592,507 | 467,179 | 1059,686 |

**Table 6.**Flood risk assessment (affected population and the number of affected barangay) in each municipality by the AHP method.

Municipality | Population Affected | No. of Barangay. | Municipality | Population Affected | No. of Barangay |
---|---|---|---|---|---|

Boston | 13,538 | 8 | Tarragona | 8308 | 5 |

Cateel | 40,704 | 16 | Mati | 20,276 | 5 |

Baganga | 51,837 | 16 | Lupon | 8660 | 3 |

Caraga | 4704 | 4 | Banaybanay | 6252 | 3 |

Manay | 13,755 | 4 | - | - | - |

Total | 124,538 | 48 | Total | 43,496 | 16 |

CR (%) | Rainfall | Slope | Elevation | Distance | Drainage | Soil Type |
---|---|---|---|---|---|---|

8.60 | 39.32 | 23.77 | 17.27 | 10.44 | 5.83 | 3.36 |

5.80 | 45.73 | 25.54 | 13.45 | 8.03 | 4.32 | 2.94 |

2.00 | 42.17 | 22.46 | 14.92 | 10.21 | 6.15 | 4.09 |

Classifications | CR 2.0 | CR 5.8 | CR 8.6 | Average Change (%) | |||
---|---|---|---|---|---|---|---|

% | Rank | % | Rank | % | Rank | ||

Very Low | 0.68 | 4 | 0.98 | 4 | 1.4 | 4 | −0.36 |

Low | 22.23 | 2 | 23.27 | 2 | 22.23 | 2 | 0 |

Moderate | 54.93 | 1 | 55.92 | 1 | 52.52 | 1 | 1.21 |

High | 22.15 | 3 | 19.84 | 3 | 23.68 | 3 | −0.77 |

Total | 100 | - | 100 | - | 100 | - | average: 0.02 |

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Cabrera, J.S.; Lee, H.S.
Flood-Prone Area Assessment Using GIS-Based Multi-Criteria Analysis: A Case Study in Davao Oriental, Philippines. *Water* **2019**, *11*, 2203.
https://doi.org/10.3390/w11112203

**AMA Style**

Cabrera JS, Lee HS.
Flood-Prone Area Assessment Using GIS-Based Multi-Criteria Analysis: A Case Study in Davao Oriental, Philippines. *Water*. 2019; 11(11):2203.
https://doi.org/10.3390/w11112203

**Chicago/Turabian Style**

Cabrera, Jonathan Salar, and Han Soo Lee.
2019. "Flood-Prone Area Assessment Using GIS-Based Multi-Criteria Analysis: A Case Study in Davao Oriental, Philippines" *Water* 11, no. 11: 2203.
https://doi.org/10.3390/w11112203