Advancing In Information and Communication Technologies Solutions for Climate Smart Agricultural Practices using a Geographic Information System (GIS) Funded by the Presenter: CARICOM Japan Shivani Dawn Seepersad Friendship September,2019 Cooperation Fund
Use of f GIS-ICT f for Climate Smart Agricultural Practices • Collect space, time and agricultural data • Model potential effects of climate change on farms • Develop maps to inform decision making
Use of f GIS-ICT f for Climate Smart Agricultural Practices Use of GIS-ICT to: 1.Determine agricultural risk 2.Understand farm soil fertility 3.Plan water management interventions 4.Determine farm supply capabilities
What is is a Geographic In Information System (G (GIS)? Susceptibility to Name X Y drought John Smith -61.0148 13.7931 High Susceptibility of Farms to Drought
Following Hurricane Tomas: • Seven dead / missing as a result of landsliding • Major sections of primary road network impassable • Communities completely isolated • US$45M damage to road transport sector Arnold (2017) Use of GIS-ICT to d etermine agricultural risk to landslides
Satellite image from 2011 showing the large number of landslides triggered by the 2010 Hurricane Tomas
Debris flow in the Ti Rocher, Trois Pitons caused by Hurricane Tomas (2010): • Identified on the satellite image of 2011 • Difficult to identify in satellite image of 2012 • Important to acquire images soon after the event Access satellite images here: https://earthexplorer.usgs.gov/ RapidEye image The World Bank and CHARIM (2016)
Trigger: Rainfall Data used Environmental factors: to Id Identify fy Soil type Areas at Slope Ris isk due to Landslide Landslide inventory
St. Lucia’s National Landslide Susceptibility Map Susceptibility of farms to landslides Very high High Low Very low
Farms at high and very high susceptibility to landslide Very high High
Table 1: Farms with High and Moderate Susceptibility to Landslides (2019) Farmer’s ID Name X Y Susceptibility 2 Afania Smith/Trius Belas -61.0148 13.7931 High 3 Agatha Eudovique -60.942 14.0128 High 4 Alban Ford -60.95941 14.02009 Moderate 17 Brandel St. Brice -61.0518 13.8056 High 34 George Alcee -61.0022 13.9478 Moderate 37 Gideon Cazaubon -60.9852 13.9597 High 40 Hazel Moise -60.95533 13.94439 High 48 Jalan Edwin -60.9819 13.7658 Moderate 61 Linus Lovence -60.9631 13.8107 Moderate 68 Marva Placide -61.00306 13.77379 Moderate 69 Mary Louis -60.9255 13.8333 Moderate 0 Patrick Gilbert -60.9903 13.9571 High 86 Rosemand Aldonza -60.9631 13.8018 Moderate 88 Shamina Edwin -60.9814 13.7651 Moderate 89 Sheldon Wilson -60.9851 13.9597 High 101 Thomas Isidore -60.991 13.9574 High 107 Vince Dolcy -60.944 14.0069 Moderate 108 Vitalis Joseph -61.0161 13.7773 High 72 Montanus Smith -60.896 13.8408 Moderate 95 Simon Solomon -60.9526 13.8209 High 102 Titus Williams -60.95822 13.796185 High
Slope of Land on Farms across Saint Lucia Soil Type Farmi Crop Slope ng (deg) Syste Farm ID Name X Y m Agatha Canelles Exten Celery, mint, parsley Eudovi - 26 Clay sive 3 que 60.942 14.0128 Latille Clay Exten Cucumber, melon, Ines - Loam sive squash, cassava, banana Celesti 22 60.906 n 44 4 13.7984 Hardy Clay Exten Plantain, banana, - sive pumpkin, macabou, cane Ismael 60.950 14.0500 46 Clifford 42 6 31 Hardy Clay Exten Cucumber, cantaloupe, - sive okra, melon, tomato Lorna 60.917 14.0433 63 St.Ange 45 3 22 Micoud Exten Lettuce, cucumber, - Gritty Clay sive broccoli Marva 61.003 13.7737 68 Placide 06 9 24 Hardy Clay Exten Watermelon Shoann - sive 14.0422 Renee 60.912 91 Charles 08 1 22 Thoma Warwick Exten Yam, cush cush, sweet s - Clay sive cassava 101 Isidore 13.9574 21 60.991
Every year in rainy season, many farms experience damage to crops and livestock due to floods or excessive rainfall Use of GIS-ICT to d etermine agricultural risk to floods
Rainfall Data used Soil type to Id Identify fy Land use land cover: Areas at Natural vegetation Ris isk due to Built area Flash Flo lood Elevation of the land
National Flood Risk Map of Saint Lucia At risk of flood
Farm likely to experience flash floods Is your farm at risk due to floods?
Farm likely to experience flash floods How can losses due to flash floods be prevented?
Activity: You have been provided with ground-based data collected from the ground surveying CARDI team in Table 3. 1. How can this data be used to develop a flood risk management plan for the agriculture sector in St Lucia? 2. What parts of the country are most susceptible to floods due to heavy rainfall? Can you tell from Table 3? 3. When there is heavy rainfall, the excess water caused by the precipitation affects the agricultural area where the water drainage system is absent causing inundation. Flood due to overflow ultimately forms small tributaries and joins the river, creating a situation of flood in the vicinity of riverbanks and river plains. Using the map below, how can this be used in damage assessment caused by flood ? How can it improve the role of land use planning in managing flood risk?
Use of GIS-ICT to understand soil fertility
Use of GIS-ICT to understand Farm farm soil fertility SOIL TYPE Attributes of the soil at each farm
Activity: 1.How can a fertilizer supply company, for example, use this soil and land data to better anticipate how much fertilizer will be needed in specific regions of St Lucia? 2.How much agriculture is possible without land? 3.How much will agriculture be successful without knowing key land characteristics such as soil properties? 4.How will the land type on GIS maps help the farmer’s decision when looking to buy land?
To grow crops optimally, it is necessary to have water Use of ICT to plan water management interventions Shivani Seepersad Use of GIS-ICT p lan water management interventions
Info about selected farm: River Use of GIS-ICT to inform Farm without water management irrigation High susceptibility to interventions Water intake drought point Located along a river – has St. Lucia’s Drought Hazard Map water during dry season? Distance from water intake: 2 km Slope of land: 15 degrees Elevation: 196 m above mean sea level
Activity 1. As a stakeholder in the agricultural sector, how does this GIS map showing the farms without irrigation help you to visualize the susceptibility of St Lucia’s food supply capabilities to climate change? 2. Suppose you are the procurement manager of a major hotel chain in St Lucia, how would you feel about the capabilities of farmers to meet your supply requirement. 3. What would you recommend to the Planning Officers of the Ministry of Agriculture in terms of dealing with the “water for agriculture” issue? 4. Looking at the distribution of farms with irrigation, is this adequate to meet the country’s food demands in the dry season? 5. Do you think the country is susceptible?
Using weather data and market information, one can make more accurate and reliable crop estimates and help reduce uncertainty. Use of GIS-ICT to inform farm supply capabilities
Rainfall from Rainfall from Rainfall from January – January – January – April, 2014 April, 2013 April, 2010
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