500 5th St NW - KWS 502
Washington, DC 20001
Tel: (202) 334-2800
Fax: (202) 334-2139
Phase 4 (2009 Deadline)
Capacity Building in Disaster Risk Assessment and Management Through Training and
Research in Geoinformatics and Hydrometeorological Hazard Risk Reduction Strategies
Yang Hong, University of Oklahoma
The University of Oklahoma team at the American Geophysical Union (AGU) 2010 Fall Meeting: Drs. Yang Hong, Sadiq Khan and Jonathan Gourley (left to right).
Umar Khattak, National University of Sciences and Technology
Pakistani Funding (HEC): $147,513
US Funding (Department of State): $230,000
Project Dates: November 15, 2010 - November 14, 2013 (Extended through June 30, 2014)
Pakistan is a country prone to hydrometeorological disasters, including landslides, droughts, and flooding, as shown in the catastrophic floods that occurred in the summer of 2010. These events underscore the need for a disaster management information system that can present a wide range of relevant data to first responders and policymakers in the right format to aid in decision-making. The ultimate goal of this project is to build Pakistan’s national capacity in natural disaster risk mitigation through training and research in geographical information science, which should help to improve prediction of natural hazards and reduce hydrometeorological disaster fatalities in Pakistan. This effort will be the first of its kind to promote exchanges of technical information between the two countries on disaster impact assessment and management research. The two partner institutions will conduct collaborative research in natural disaster and vulnerability assessment methodologies, and the US partners will conduct training in new interdisciplinary programs in geoinformatics and disaster risk reduction techniques. The project should help to prepare a cadre of professionals for disaster risk assessment and management in Pakistan. Ultimately, losses of life and economic damage due to floods, landslides, and other disasters should be minimized through more effective pre- and post-disaster management.
Economic and societal impact of floods can be reduced by flood monitoring and early warning systems. In most of the developing world, flood warnings are issued couple of days in advance, if at all. This warning time is not enough for evacuation of general masses with their precious belongings and livelihoods. The need for a rapid flood monitoring and warning system in Pakistan became apparent following the 2010 floods. Therefore, this project was implemented and following intended targets are achieved. The main results include:
- Developed capacity of project partners on flood mapping, risk assessment and early warning through numerous face-to-face weekly meetings, discussions and seminars. Trained one Pakistani scholar at OU and 4 Pakistanis students at NUST.
- Established direct linkages and rapport among key stakeholders on flood monitoring research in Pakistan.
- Produced 5 research manuscript related to floods in Pakistan.
- Conducted research on flood evolution throughout Indus River basin during the intense Monsoon Season (July-August) in Pakistan.
- Implemented a flood detection framework that utilizes unconventional satellite remote sensing data and numerical model on a web based flood monitoring syste.
- Adopted a Memorandum of Understanding that guides partnership with key stakeholders for future research and collaboration between in U.S and Pakistan research institutions.
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2011 Show summary || Hide summary || Download full report
Postdoctoral researcher Dr. Sadiq Khan of the University of Oklahoma began an extended visit to Pakistan on May 31, 2011, to provide training to the counterparts at NUST and participate in crucial meetings with representatives of Pakistani government agencies being asked to collaborate on the project. Dr. Khan and Pakistani project director Dr. Umar Khattak met with senior officials from the Pakistan Meteorological Department (PMD) and National Disaster Management Authority (NDMA), with their discussions focusing on how to establish a more effective flood monitoring system in Pakistan. The feasibility of initiating flood modeling efforts was also addressed. It was decided that a rainfall runoff model would be set up covering the Indus and Jhelum catchments. The PMD director general, Dr. Arif Mahmood, has agreed to cooperate with this joint research team by providing daily precipitation data from selected locations. Meanwhile, meetings at the NDMA focused on how to build linkages between the product team and relevant Pakistani government agencies to disseminate and apply the expected research outputs and promote improved flood monitoring and warning efforts in the country. Dr. Khan remained in Pakistan through early August working with his NUST counterparts on flood model setup and evaluation using data provided by PMD and other stakeholders. Once the model is fully evaluated it will be transferred to the stakeholders, and training seminars and workshops will be conducted at NUST. Unfortunately, the International Conference on Advances in Space Technologies (ICAST) that was to be held in Islamabad July 6-8, 2011 had to be postponed due to security concerns, but it will be rescheduled at a later date. Meanwhile, Dr. Khan and Dr. Hong delivered a presentation on “Multispectral and Microwave Satellite Remote Sensing for Flood Prediction in Data Scarce Environments” at the International Symposium on Earth-Science Challenges held at the University of Oklahoma September 14-16, 2011.
2012 Show summary || Hide summary || Download full report
During the last quarter of 2011 and first quarter of 2012, the researchers on this project focused on processing and analyzing data collected from the Pakistan Meterological Department (PMD) and satellite-based U.S. sources, including the National Aeronautics and Space Administration and the National Oceanic and Atmospheric Administration. A quality controlled digital database of all intercomparison data from January 2005 to December 2010 has been prepared, and the team has also been evaluating daily satellite-based precipitation data as compared with actual observations from a network of 24 rain gauge stations around Pakistan. In addition, they have compiled and digitized stream flow data obtained from the National University of Science and Technology (NUST) and the Pakistani Federal Flood Commission that were previously unavailable in digital form. The research team is also focusing on creating and evaluating a flood model for the Indus Basin using data from relevant stakeholders, especially PMD. They expect to prepare and publish an article on their modeling and precipitation comparison work in 2012.
During the 2nd quarter, the research team at the University of Oklahoma (OU) has been evaluating unconventional data for hydrologic modeling. Specifically, they have worked to correlate remote sensing data collected by satellites with actual observed measurements of streamflow for several stations in the Indus River basin. They have also set up the Coupled Routing and Excess Storage (CREST) hydrological model for five stations in this basin, which they will continue to calibrate and validate over the coming months using remote sensing data as well as archival data in the public domain. A research article resulting from the project, entitled “Evaluation of Three High-Resolution Satellite Precipitation Products over Pakistan: the Potential for Hydrologic Prediction System for Monsoon Floods,” was recently submitted to the Journal of Hydrometeorology.
On the Pakistani side, the team had a series of meetings with collaborators and stakeholders including Pakistani government agencies and international organizations. The team archived river flow and rainfall data, identified data gaps, and worked to obtain the missing information from relevant agencies. The CREST model was installed on the Linux-based super-computer at NUST; however, trial runs have so far been unsuccessful. During this quarter, three research assistants were recruited to the project, and they have conducted three seminars at the Institute of GIS for students and faculty members from NUST and representatives from the Pakistan Meteorological Department and the Space and Upper Atmosphere Research Commission. Planning is currently underway for Dr. Umar Khattak’s post-doc research training at OU, starting from September 2012 (tentatively). In the meantime, the researchers on both sides will continue gathering and archiving river flow and rainfall data and honing and evaluating their hydrological models.
By the end of 2012, studies at OU were conducted on two important predictors of flood monitoring and forecasting especially in regions with sparse data and in mountainous terrains found in Pakistan. Dr. Umar Khattak, the Pakistani counterpart arrived to the OU laboratory in September 2012 to work on research and training on flood modeling including training sessions on the CREST model, data input preparation, and how to setup the model over the Indus River Basin. While at OU, Dr. Khattak worked on evaluating recent satellite rainfall data throughout Pakistan and comparing it with rain gauge data to quantify errors in rainfall estimates. The second study looked at monsoon diurnal change which showed that during 2010, both pre-monsoon (April–June) and the monsoon (June–August) showed unusually high amount of rainfall, that lead to the catastrophic floods in 2010. The highest number of events and the most intense rainfall occurs in the early morning and afternoon hours. This kind of information will provide scientists more insight into the error sources in satellite based rainfall estimates and focus on the exact situations that can cause flood hazards. This visit also provided opportunity for both researchers to submit a new proposal on landslide monitoring and prediction in Pakistan to the Pakistan-U.S. S&T Cooperation Program Phase 5 call for proposals. Upon completion of the OU visit, Dr. Khattak will take the flood model and related data back to Pakistan to further refine the model. At least three graduate students (one is female) will be trained on flood monitoring, data acquisition, and processing at NUST.
2013 Show summary || Hide summary || Download full report
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