Water-related Disaster Risk Management

TeamGiriraj Amarnath

Karthikeyan MatheswaranShuhei Yoshimoto

Niranga AlahacoonPeejush Pani

k.matheswaran@cigar.org

• Assessment of flood risk and the evaluation of measures

to reduce flood risks;

• Calculating the averaged annual costs of damages or

losses, and economic assessment of flood risk;

• Allows flood risk managers, stakeholders and politicians

to propose new strategies;

Flood

Mixed (Crop)

Water bodies

Inter-annual variation (2000 – 2011)

Normal River

2010

2010

Flood Risk Assessment for SA using RS

REGIONAL FLOOD MAPPING: SOUTH EAST ASIA

Flood over land use

Flood over population

Flood Frequency

Regional View; e.g. 13th Oct 2011

Integrated flood risk management that reduces flood risk

while increasing its positive impact is needed

– Socio-economic aspects

• Building multi-objective reservoir that reduces flood impact

during wet season and used stored water for irrigation

purpose during dry season

• Proper Dam operation and application of basin scale

forecasting system

– Ecosystem Management aspect

• Re-establishing wetlands in the downstream of the basin area

• Re-forestation in the upstream areas

Flood Protection measures

Operational Flood Management Information – Eastern Sudan

Mobile app based flood early warning - Nigeria

• WetIn will be limited to the android operating system devices, for the time being.

• To provide an alternative to traditional monitoring using radar altimetry and improve model-predicted discharge in the downstream

• This mobile app aims to give added support to authorities and citizens during this rainy season in Nigeria

“WetIn allows users to monitor rivers and streams in the Niger-Benue river system in Nigeria using satellite altimetry”

INDEX-BASED FLOOD INSURANCE IN INDIA TO ENHANCE AGRICULTURE RESILIENCE AND FLOOD PROOFING LIVELIHOODS

Setting up pilot-scale trials to demonstrate that positive verifiable impacts emerge from IBFI in terms of agriculture resilience and improving productivity, and household incomes, locally and at the broader scale

Developing tools and strategies that support IBFI development and upscaling, integrated with existing and future flood control measures.

Partners: International Food Policy Research Institute (IFPRI), Indian Institute of Technology (IIT)-Gandhinagar, Indian Council of Agricultural Research, Agriculture Insurance Corporation of India, MoA; Bajaj Allianz, Insurer, Swiss Reinsurance

Project Period: 2015 - 2018Pilot Districts : Muzaffarpur – India

Sirajganj - Bangladesh

IBFI Concept

http://ibfi.iwmi.org/

SOUTH ASIA DROUGHT MONITOR SYSTEM (SA-DMS)

• First of its kind to establish for entire South Asia using multisource remote sensing observations;

• Historical drought risk mapping and assessment covering SA countries (2000 – Current);

• IDSI allows better understanding on drought frequency, duration over the 15years;

• Products are useful tools in drought mitigation studies and in decision-making process;

2015 field observations in Jalna, Maharashtra

Drought Monitoring and Prediction System for India

Short-term precipitation forecast for drought prediction

Development of robust drought index using precipitation, soil moisture and NDVI

Multi-Hazard mappingFor planner / manager: What type and level of protection is

appropriate?

Funding Donor: CCAFSPhotos: IWMI

For planner / manager: What type and level of protection is appropriate?

High to Extreme Risk Districts: East and West Nimar, Dhar, Barwani, Ratlam, Mandsaur, Shajapur, Bhopal, Hoshangabad

Farmer Adaptation: Pond Farming using Satellite Data in Maharashtra (India)

Source: IWMIFunding Donor: CCAFS

• Total of 1100 ponds were mapped for the 4 taluks of which 86% of the ponds are without polythene covered

• Highest number of farm ponds (84) were noticed only in Nashik and followed by Wada (40)

Sl Crop Before

FP

Yield

After

FP

Yield

%

change

1 Maize 31.45 39.37 25.17

2 Paddy 28.00 20.65 -26.12

3 Sorghum 15.07 23.00 52.66

4 Soybean 20.16 24.29 20.49

5 Onion 149.70 175.05 16.93

6 Pigeon Pea 12.44 13.25 6.51

Crop yield variation by introducing farm ponds in Nashik district

Farmer Adaptation: Pond Farming using Satellite Data in Maharashtra (India)

Thank You