Latin American and Caribbean Flood and Drought Monitor Colby Fisher, Nathaniel Chaney, Justin Sheffield, Eric F. Wood Princeton University … with support from UNESCO-IHP, ICIWaRM Management of Water Resources in Arid and Semiarid zones of Latin America (‘MWAR-LAC’) Meeting - ´Addressing Current Gaps and Needs´ 24h – 25th February 2016, Brussels, Belgium

US Federal Emergency Management Agency (FEMA) and other disaster management organizations estimate that for every $1 spent on reducing vulnerability to disaster $4 is saved. Impact Assessment Impact Assessment Response Recovery Reconstruction Mitigation Preparedness Prediction and Early Warning Prediction and Early Warning PROACTIVE REACTIVE Risk Management Crisis Management Protection Recovery Adapted from WMO How do we reduce the impacts of drought? Managing the risk of impacts relies on a variety of measures to reduce vulnerability that includes forewarning through early-warning systems. Disaster

The Challenge and Our Goals The challenge: How can early warning of physical flood and drought conditions be provided in regions with low data availability and/or low capacity? The goal: To develop a flexible framework for providing historic records, real-time monitoring and forecasts of relevant hydrological variables and indices for hazard risk management

Development of Flood and Drought Monitoring and Prediction Systems at Princeton University 4

System Overview Sheffield, J., et al., 2014; A drought monitoring and forecasting system for sub- Sahara African water resources and food security. Bull. Am. Met. Soc.

System Architecture and Usage 6 “Back End” Server Download of Data Bias Correction of Data Hydrological Model Calculation of Indices Processing of Forecasts Data served by Grads Data Server (GDS) Generally installed at operational center “Front End” Client Replicates final datasets Processes images Serves images and data to users through website Hosts website Provides data download Can be installed at operational center or locally User Interface Decision Support Direct access to database via scripts Research Applications Additional Modules (Agric, Water, Energy) Impact Assessment

User Interface: 7

User Interface Overview 8

7-day forecasting aimed at floods (also heatwaves, cold spells, …)

Example of Flood Forecasting – Recent floods in northern Chile, March 2015 Black line is observational estimate of streamflow Red line is the forecast initiated from 9 days before the event to 2 days after the event Ongoing work – evaluating flood forecasts systematically - globally for the Global Ensemble Forecast System (GEFS) - break down skill into ICs, precipitation, streamflow/inundation

Seasonal Forecasts 11 Downscaled and bias corrected NMME seasonal climate forecasts ESP and hydrological forecasts to be added

Current Work: Sub-Seasonal Climate and Hydrological Forecasts Discharge Groundwater Lead Time (days) Soil Moisture Upper Soil Moisture Lower Continental Precipitation Forecast Skill 10 weeks 6 weeks 4 weeks 2 weeks 0 weeks National (Ecuador) Precipitation and Temperature Skill Hydrological Forecast Skill Multi-Model Forecast Merging  Lead time Temperature Precipitation  Different forecast models 

Training Workshop in Santiago, Chile (2014) – also in Niger (2012, 2013), Kenya (2012), Namibia (2015) Training in the use of the system Transfer of technology/knowledge exchange Operational servers – regional clients Validation, feedback and collaboration

Summary and Potential Ways Forward Latin American and Caribbean Flood and Drought Monitor developed as a framework for disseminating hydrological data and drought/flood monitoring/forecasting … in support of research, assessment and decision making 14 Potential to improve estimates via data assimilation, calibration and knowledge exchange High resolution case studies and implementations (seamless sub- seasonal forecasts and 1km resolution) Extension to impact studies (e.g. crop production, power generation, water management, tourism, transport, …)