GIS-BASED CROP SUITABILITY AND CLIMATE CHANGE

VULNERABILITY OF FARMING SYSTEMS

IN CAGAYAN VALLEY

Januel P. Floresca1 1Isabela State University, Echague, Isabela, 3309, Philippines

Email: januelpf@yahoo.com.ph

KEY WORDS: GIS-based crop suitability analysis, climate change vulnerability, farming systems

ABSTRACT: Geographic information system (GIS) is a tool capable of facilitating assessment of vulnerability to the

impacts of climate change of farming systems and analyzing crop suitability of crops for agroforestry establishment to

enhance the resiliency of existing farming systems. The study was aimed to assess the vulnerability of existing rice

and corn farming systems to the impacts of climate variability and extremes and to assess the suitability of tropical

fruits to be introduced for the establishment of agroforestry farming systems using GIS. The weighted rating model

(equal weights) was used in overlaying thematic maps following the IPCC framework that vulnerability is a function

of exposure, sensitivity and adaptive capacity. Results indicated Echague, Isabela had the highest land area with high

vulnerability of 99,726.53 ha, followed by Penablanca with 22,872.85 ha, then by Maddela with 7,737.87 ha and

Bagabag as the lowest with only 378.85 ha. For the four study sites, most of the land area had low vulnerability with

298,862.93 ha, followed by moderately vulnerable with 176,250.34 ha while the lowest was highly vulnerable with

130,716.10 ha. Babaran, Echague, Isabela had the highest climate change vulnerability index considering that the

main crop is only corn exposed to more frequent typhoons and drought. Results also indicated that all the tropical

fruits (rambutan, Mango, lanzones, pummelo) and bamboo were suitable to be planted in all the municipal study sites

and selected model farms based on the ecological requirements of each. Tropical fruits and bamboo are suitable in

climate change-vulnerable areas in Cagayan Valley. The GIS climate change vulnerability maps should be

disseminated to LGUs and vulnerable communities to enhance their awareness and utilize the information for

planning and decision-making on climate change-resilient farming system development.

1. INTRODUCTION The Cagayan Valley Region (where the Cagayan River, the longest river in the country of approximately 490 km long

is located) is geographically positioned adjacent the Pacific Ocean that made it exposed to the wide area climate

variability and extremes such as intensified and more frequent tropical cyclones, monsoon rains as well as the El

Niño-La Niña Southern Oscillation (ENSO) oceanic phenomenon that cause floods, flashfloods and landslides/soil

erosion, and droughts. Cagayan Valley is considered as one of the most vulnerable regions to climate variability and

extremes particularly typhoons and floods in the Philippines based on the collaborative action research titled

“Enhancing the climate change adaptive capacities of LGUs and Scientists in the Philippines” conducted by

CPAF-UPLB with ISU as their research partner. Results confirmed high degree of adverse impacts of typhoons and

monsoon rains on flooding affecting smallholder rice and corn farmers.

The identification of the areas most vulnerable to climate change risks in the Country is among the most urgent of

policy needs based on the National Framework Strategy on Climate Change (NFSCC) formulated by the Climate

Change Commission (CCC) in accordance to Section 13 of the Philippine Climate Change Act of 2009 or RA 9729

which is to assess risks and impacts of climate change and identify the most vulnerable communities, areas and

ecosystems. Moreover, Section 6(d) of the Philippine Disaster Risk Reduction and Management (PDRRM) Act of

2010 or RA 10121 ensures a multi-stakeholder participation in developing, updating and sharing DRRM information

through GIS-based risk mapping policy, planning and decision-making tools for science-based analysis and

information on geographically targeted interventions on climate change adaptation, mitigation and disaster

preparedness.

Agroforestry theoretically depicts a climate change-resilient farming system in terms of its ability to sustain

productivity in the face of recurring climate variability and extremes. The ecosystem services of agroforestry being

more diverse coupled with existence of water harvesting/impoundments offer opportunities to reduce the adverse

effects of extreme climate events. Tropical fruits and bamboo/forest trees serve as windbreaks and soil erosion/runoff

control during typhoons and monsoon rains. Backyard crops such as root crops provide alternative food and income

during calamities to take the place of field crops (rice and corn) that have higher risks of damage. Water

impoundments/groundwater provide available irrigation and potable water during periods of drought. Thus,

vulnerability of farming systems to the impacts of climate change are reduced and become climate change resilient.

From overlaying various spatially-referenced biophysical and socioeconomic factors (e.g. topography, soil, climate,

land use, demographic profile, farming practices, problems and constraints), GIS is capable of analyzing crop

suitability for any agroforestry crop (tropical fruits and bamboo) in a given geographic region using sets of criteria

based on ecological requirements.

The study aimed to assess the climate change vulnerability of existing farming systems using geographic information

system (GIS) and crop suitability of agroforestry crops (tropical fruits and bamboo) as intervention for enhancing the

climate change resiliency of existing farming systems in the study sites.

2. METHODOLOGY

2.1 Selection of Study Sites

Using the set criteria on high risk municipalities for floods, landslides and typhoons in Cagayan River basin identified

by DENR-MGB and accessibility being near the national road, four LGUs were selected namely: Penablanca,

Cagayan, Echague, Isabela, Maddela, Quirino and Bagabag, Nueva Vizcaya (Figure 1).

Figure 1. Selected study sites.

2.2 Climate Change Vulnerability Mapping

The climate change vulnerability mapping procedure of Yusuf and Francisco downscaled at Cagayan Valley was

adopted following the IPCC framework that vulnerability is a function of exposure, sensitivity and adaptive capacity

as follows:

1) Assessment of exposure using information from historical records of climate-related hazards as past exposure to

climate risks are considered as the best available proxy for future climate risks. Climate hazard maps for the

climate-related risks include tropical cyclones, floods, landslides, and droughts;

2) Use of population density as a proxy for human sensitivity to climate-hazard exposure. The assumption here is that

regions that are relatively less inhabited will be less vulnerable compared to regions with high population densities,

given the same degree of exposure to climate hazards;

3) In addition to the human aspect of vulnerability, ecological sensitivity of the region using biodiversity information

is included as a proxy variable. A biodiversity-rich region, measured by the percentage of protected areas, is thus

considered here as more vulnerable than other areas to climate hazards, other things being equal; and

4) Adaptive capacity is defined as the degree to which adjustments in practices, processes, or structures can moderate

or offset potential damage or take advantage of opportunities (from climate change). It is a function of

socio-economic factors, technology and infrastructure.

Cartographic Model – Exposure Map

TYPHOON HITS

1=L; 2=M; 3=H

TEMPERATURE

INCREASE

1=L; 2=M; 3=H

RAINFALL

INCREASE

1=L; 2=M; 3=H

RAINFALL

DECREASE

DUE TO EL NINO

1=L; 2=M; 3=H

FLOOD-PRONE

AREAS

1=L; 2=M; 3=H

EROSION-PRONE

AREAS

1=L; 2=M; 3=H

CLIMATE RISKS

MAP1=L; 2=M; 3=H

MULTI-HAZARD

MAP1=L; 2=M; 3=H

EXPOSURE

MAP

1=L; 2=M; 3=H

Intersect

Intersect

Merge

0.4

0.6

0.4

0.3

0.2

0.1

0.6

0.4

Reclass

Reclass

Reclass

Cartographic Model – Sensitivity Map

POPULATION/

AREA

(No. of indiv./ha)

BUILT-UP

AREAS

1=L; 2=M; 3=H

PRIME AGRIC’L

LANDS

1=L; 2=M; 3=H

FORESTS/

PROTECTED

AREAS

1=L; 2=M; 3=H

POPULATION

DENSITY1=L; 2=M; 3=H

LAND USE

SENSITIVITY

1=L; 2=M; 3=H

SENSITIVITY

MAP

1=L; 2=M; 3=H

0.3

0.4

0.2

Reclass

Calculate

Reclass

Reclass

Merge

0.6

Intersect

0.4

OTHER LAND

USES

1=L; 2=M; 3=H

0.1

The cartographic models (Figures 2-5) indicate the map layer inputs, the geoprocessing used (reclassification,

intersect) and the resulting output composite maps such as exposure, sensitivity, adaptive capacity and overall climate

change vulnerability.

Figure 2. Cartographic model for exposure map.

Figure 3. Cartographic model for sensitivity map.

Figure 4. Cartographic model for adaptive capacity map.

Cartographic Model – Adaptive Capacity Map

HDI

1=L; 2=M; 3=H

POVERTY

INCIDENCE

1=H; 2=M; 3=L

INCOME GAP

1=H; 2=M; 3=L

TECHNO-GABAY

(FITS+MS) CENTERS

1=L; 2=M; 3=H

SOCIO-

ECONOMICS

MAP

1=H; 2=M; 3=L

INFRA-

STRUCTUREMAP

1=H; 2=M; 3=L

ADAPTIVE

CAPACITY

MAP

1/3=H; 1/2=M; 1/1=L

TECHNOLOGYMAP

1=H; 2=M; 3=L

TELECOMS (GSM &

G3 COVERAGE)

ELECTRICITY

eq

ual w

eig

hts

0.6

Reclass

Merge0.2

0.2

0.6

Reclass

Reclass

Reclass

Merge

Merge

HEALTH CENTERS/

HOSPITALS

ROAD DENSITY

HOUSE & LOT

IRRIGATION

SAFE WATER

SOURCE

STRONG HOUSES

0.4

0.2

0.4

Figure 5. Cartographic model for overall climate change vulnerability map.

3.3 Multi-criteria Crop Suitability Analysis

Mapping of the biophysical conditions of selected farming systems using GPS and available geo-referenced digital

maps and digital elevation model (DEM) and linking attributes on ecological requirements of tropical fruits such as

climate (temp, rainfall), elevations and slope, and soil types (Table 1) as follows:

Table 1. Basic ecological requirements of selected tropical fruits.

Tropical

Fruit/ Bamboo

Topography (Elevation & Slope) Requirements

Soil Requirements Climate Requirement

Mango Flat to slightly rolling terrain

Should not be higher than 600 meters above sea level as it delays fruit maturity at higher elevations.

400 meters ideal for growing mango

Sandy loam,relatively rich in organic matter

Good drainage (very important)

pH 6.0-7.0

Distinct wet and dry season (4 to 5 months dry priod)

Temperature of 21 to 30 degree celsius

No strong winds

Sweet Tamarind

The tree tolerates a great diversity of soil types, from deep alluvial soil to rocky land and porous, oolitic limestone.

It withstands salt spray and can be planted fairly close to the seashore.

Distinct wet and dry season.

Dry weather is important during the period of fruit development.

Pummelo 400 meters ideal for growing pummelo.

The best orchards are situated on the banks of current and former river courses.

It can tolerate a wide range of soils from coarse sand to heavy clay.

Optimum pH from 5.5 to 6.5

Optimum temperature of 25-30o C

Annual rainfall requirement 1500-1800 mm

Lanzones Should not be higher than

650-750 meters above sea

level.

It prefers soil with good

drainage and water retention;

Rich in organic matter and

slightly acidic.

It cannot tolerate sandy

coastal soils and alkaline

soils.

It thrives best in humid

condition, plenty of

moisture.

Some shade is beneficial

especially during the early

years.

Rambutan Plants can grow at 10-500 m

above mean sea level

It prefers clay loam soil, but

can be grown in a wide range

of soil types.

pH 5 to 6.5.

Not water-logged.

Best grown in the

temperature range between

22C to 35C.

Well distributed rainfall.

Figure 8. Cartographic Model of Biophysical Suitability Analysis

SOIL PH6.5 = H; 5 –6.4 = M;

Below 5 = L

SLOPE0-18%=H;

18-50%=M; Above 50%=L

ELEVATION0-600 masl=H;

600-1,000 masl = MAbove 1,000 =L

LAND USE/COVERIdle/Grasslands=H;

Croplands/plantations=M;

Forests/prime rice/

builtup areas=Not

suitable

TOPO

SUITABILITY1=L; 2=M; 3=H

0.5

0.5

Intersect

TYPHOONFreq > 10 = M; Freq 10

& below + typh tack = M; Freq above 10 = L

0.5

Reclass

IntersectSOIL x

LAND USE

SUITABILITY1=L; 2=M; 3=H

Reclass

0.5

SOIL

SUITABILITY1=L; 2=M; 3=H

BIOPHYSICAL

SUITABILITY

1=L; 2=M; 3=H

Reclass

Reclass

0.5

TEMPERATURE22-28 = H;

Above 28 = M;

Below 22 = L;

0.5

CLIMATE

SUITABILITY1=L; 2=M; 3=H

Intersect

Intersect

Intersect

Reclass

0.5

0.5

0.5

0.5

SOIL TEXTUREClay = H;

Loam = M; Sand = L

RAINFALL200-220 mm = H;

101-199 mm = M;Below 100 mm = L;

TEMP x

RAIN

SUITABILITY1=L; 2=M; 3=H

Reclass

0.5

0.5

Intersect

LAND

SUITABILITY1=L; 2=M; 3=H

0.5

Intersect

Reclass

0.5

Figure 6 presents the cartographic model used in the crop suitability analysis using GIS. Meantime, the crop

suitability was only limited to biophysical (topography, soil and climate) criteria to come up with a composite

biophysical suitability map.

Figure 6. Cartorgraphic model of crop suitability analysis.

3. RESULTS AND DISCUSSION

3.1 Geographic Locations and Areas of

Existing Farming Systems

in Cagayan Valley

The study sites were dominated with rice and corn farming systems (Figure 7).

Figure 7. Dominant farming systems in Cagayan Valley and the Study Sites.

3.2 Climate Change Vulnerability of

Rice and Corn Farming Systems

Figures 8 - 10 are the layers used in generating exposure, sensitivity and adaptive capacity maps in Penablanca,

Cagayan for example.

Figure 8. Layers used in generating exposure map.

Figure 9. Layers overlaid to generate the sensitivity map.

Figure 10. Layers overlaid to generate the adaptive capacity map.

Sensitivity Index of the Study Sites

Study SitesDominant

Farming System

Ave. Area

Planted

No. of

Farmers

Sensitivity

IndexRank

Penablanca Upland Corn 2.0 84 2 1

Echague Upland Corn 1.9 87 2 1

Maddela Upland Corn 1.9 81 1 2

Bagabag Irrigated Rice 1.5 87 1 2

Overlaying the exposure, sensitivity and adaptive capacity maps, the overall climate change vulnerability map in

Cagayan Valley with the rice and corn farming systems resulted to the following: Echague, Isabela had the highest

land area with high vulnerability of 99,726.53 ha, followed by Penablanca with 22,872.85 ha, then by Maddela with

7,737.87 ha and Bagabag as the lowest with only 378.85 ha (Figure 11). For the four study sites, most of the land

area had low vulnerability with 298,862.93 ha, followed by moderately vulnerable with 176,250.34 ha while the

lowest was highly vulnerable with 130,716.10 ha.

Figure 11. Overall climate change vulnerability map

Farming systems in the study sites.

Based on the attributes of the layers, the exposure, sensitivity, adaptive capacity and overall climate change

vulnerability indices (Tables 2 - 5) of the rice and corn farming systems in the study sites were tabulated and ranked

as follows:

Table 2. Exposure index of rice and corn farming systems in the study sites.

Table 3. Sensitivity index of rice and corn farming systems in the study sites.

Table 4. Adaptive capacity index of rice and corn farming systems in the study sites.

Table 5. Overall climate change vulnerability of rice and corn farming systems in the study sites.

3.3 GIS-based Crop Suitability of Climate

Change-Resilient Tropical Fruits

3.3.1 Topographic Suitability: For topographic suitability combining elevation and slope as overlay factors, all the

tropical fruits (mango, pummelo, lanzones, rambutan and jackfruit) were within highly suitable topography (within

600 masl elevation and within 0-50% slope category). The eastern parts of Penablanca and Maddela which were the

mountain ranges of Sierra Madre are moderately suitable. Also the mountain ranges of Caraballo made some parts of

Bagabag and Maddela moderately suitable for the tropical fruits (Figure 12).

Figure 12. Topographic suitability of the study sites.

3.3.2 Soil Suitability: Overlaying the soil texture, soil pH and Land Use maps produced the soil suitability map

(Figure 13). Forests, built-up areas, aquatic areas and rivers were not suitable. Highly suitable areas were those that

have loam to clay loam soil and croplands mixed with brushlands and grasslands.

Figure 13. Soil and land use suitability of tropical fruits in the study sites.

3.3.3 Climate Suitability: Monthly temperature and rainfall were both suitable for tropical fruits considering

temperature and rainfall ranges of 24.3–27.2 oC and 465.7–657 mm, respectively. However, frequent occurrence and

tracks of typhoons in Cagayan Valley reduced suitability of tropical fruits (Figure 14).

Figure 14. Climate suitability of tropical fruits.

3.3.4 Overall Biophysical Suitability: Overlaying topographic, soil and climate suitability produced the following

overall biophysical suitability map (Figure 15).

Figure 15. Overall biophysical suitability of tropical fruits in the study sites.

4. CONCLUSION AND RECOMMENDATIONS

The monocrop corn farming systems in Penablanca, Cagayan and Echague, Isabela had the highest climate change

vulnerability index considering that the crop had higher exposure to multi-hazards, more areas with more farmers

affected, lower income, knowledge, perception and less access to land/water resources.

All the tropical fruits (rambutan, Guimaras Mango, lanzones, pummelo) and bamboo were suitable to be planted in all

the barangay study sites based on their basic ecological requirements: Elevation < 700 masl; Slope = 18-30%; Soil

texture= sandy clay-loam; Soil ph > 5; Gen. climate = pronounced; Rainfall > 1,000 mm/yr; and Temperature < 30oC.

The climate change vulnerability of major farming systems should be disseminated to farmers, communities and

LGUs and develop and formulate appropriate climate change adaptation plans for farming systems.

Hands-on training on GIS for LGUs should be conducted in order to utilize the geodatabase on crop suitability and

climate change vulnerability maps for climate change resilient-farming system planning and development.

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