scott curtis, phd15 october associate professor, east carolina universityvirtual seminar

Scott Curtis, PhD 15 OctoberAssociate Professor, East Carolina University Virtual SeminarAssistant Director, Center for Natural Hazards Research CDRE, Millersville University

Center for Natural Hazards Research

Established in 2004, with the impetus being the 1999 Hurricane Floyd flood

CNHR’s mission is to promote research and analysis that ultimately reduces the harm caused by forces of nature to life, communities, and the environment

Dr. Jamie Kruse (director, temporarily at NOAA), Dr. Craig Landry (interim director), Dr. Scott Curtis (assistant director)

Hurricane Floyd Symposium www.ecu.edu/hazards


Floods and landslides represent the most extreme hazards, especially in terms of loss of life

Overpopulation and socio-economic pressures have forced some of the most vulnerable populations into areas of high risk (flood plains and hillsides)

Further, land degradation and climate change have exacerbated the problem


Pakistan, July-August, 2010

China, August, 2010


Lack of in situ data Transboundary

complications Modeling

complexities


(Wolf et al. 1999; Hossain et al. 2007)

Percentage within IRBs

Number of Countries

90-100 39

80-90 11

70-80 14

60-70 11

50-60 17

40-50 10

30-40 10

20-30 13

10-20 9

0-10 11

Hossain et al. (2007)


The majority of floods and landslides are ultimately caused by extreme rainfall

The Tropical Rainfall Measuring Mission was launched in 1997 and is still flying today

Through passive and active sensors onboard as well as complementary satellites, we have learned more about tropical rainfall than ever before

TRMM Multi-Satellite Precipitation Analysis (TMPA)


To obtain and study multi-year science data sets of tropical and subtropical rainfall measurements.

To understand how interactions between the ocean, air, and land masses produce changes in global rainfall and climate. To improve modeling of tropical rainfall processes and their influence on global circulation in order to predict rainfall and its variability at various space and time scales.

To test, evaluate, and improve satellite rainfall measurement techniques.


ENSO Variability

(Curtis et al. 2007)


(Curtis, Crawford, Lecce 2007)


Basin Volumetric rainfall x109 m3

(bias % w/ gauge)Discharge x109 m3

TRMM RADAR GAUGE USGS

Tar - Greenville 2.12 (+6%) 1.91 (-5%) 2.00 0.92

Neuse - Ft. Barnwell 2.88 (+10%) 2.57 (-2%) 2.61 0.92

Cape Fear - Kelley 2.83 (+49%) 1.73 (-9%) 1.90 0.47

Curve numbers are based on empirical rainfall-runoff relationships

Q = (P - 0.2S)2 / (P + 0.8S) and CN = 1000 / (S + 10); where Q = discharge, P = precipitation, S = maximum retention, and assuming initial abstraction is 20% of S.

CN 55, which fits the gauge and radar data reasonably well represents woodlands in good hydrologic condition. TMPA curve numbers are lower. Thus, if we had global CN numbers, they could be adjusted to account for the difference


TAR

NEUSE

CAPE FEAR

gauge

TRMM

radar



Hong et al. (2007a) extended this work by deriving global CN numbers from remotely sensed data sets of soil and land use.


Hong et al. (2007b)

Hong , Adler, Huffman (2007)

Hong et al. (2007b)


4% of the globe is in the “High” susceptibility category, concentrated in the tropics and subtropics

“In the future, the increasing availability of improved yet low-cost remote sensing products that can support geographic information system (GIS)–based landslide models will likely be useful for disaster prevention for landslide-prone regions”

Hong, Adler, and Huffman (2007)


Hong et al. (2007b)

http://trmm.gsfc.nasa.gov/publications_dir/potential_flood_hydro.html


To improve ongoing efforts to predict climate by providing near-global measurement of precipitation, its distribution, and physical processes

To improve the accuracy of weather and precipitation forecasts through more accurate measurement of rain rates and latent heating

To provide more frequent and complete sampling of Earth’s precipitation

Scheduled to launch 2013

Curtis, S., T.W. Crawford, and S.A. Lecce. 2007. A comparison of TRMM to other basin-scale rainfall during the 1999 Hurricane Floyd flood. Natural Hazards, 43:187-198.

Curtis, S., A. Salahuddin, R.F. Adler, G.J. Huffman, G. Gu, and Y. Hong. 2007. Precipitation extremes estimated by GPCP and TRMM: ENSO relationships. Journal of Hydrometeorology, 8:678-689.

Hong, Y., R.F. Adler, F. Hossain, S. Curtis, and G.J. Huffman. 2007a. Estimate gridded and time-variant runoff curve numbers using satellite remote sensing and geospatial data. Water Resources Research, 43:W08502.

Hong, Y., R.F. Adler, A. Negri, G.J. Huffman. 2007b. Flood and landslide applications of near real-time satellite rainfall products. Natural Hazards, 43:285-294.

Hong, Y., R.F. Adler, and G.J. Huffman. 2007. Satellite remote sensing for global landslide monitoring. EOS, 88:357-358.

Hossain, F., N. Katiyar, Y. Hong, and A. Wolf. 2007. The emerging role of satellite rainfall data in improving the hydro-political situation of flood monitoring in the under-developed regions of the world. Natural Hazards, 43:199-210.

Wolf, A., J. Nathrius, J. Danielson, B. Ward, and J. Pender. 1999. International river basins of the world. International Journal of Water Resource Development, 15:387-427.


scott curtis, phd15 october associate professor, east carolina universityvirtual seminar

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