Skip to main content
Log in

Analysis of the Relationship among Flood Severity, Precipitation, and Deforestation in the Tonle Sap Lake Area, Cambodia Using Multi-Sensor Approach

  • Surveying and Geo-Spatial Engineering
  • Published:
KSCE Journal of Civil Engineering Aims and scope

Abstract

Cambodia is the 9th country in the world to be vulnerable to natural disasters in 2011, especially due to the storm and flood. Also, it is worrisome that there is a rapid deforestation in Cambodia, which can be abundant and accelerate the increase in damage. Nevertheless, only few research has been studied to establish the relationship between deforestation and flood damage in Cambodia. In this study, several remote sensing techniques were applied to reveal the relationship among the water level change, changing patterns of precipitation, and deforestation in Cambodia. In addition, the trends of precipitation and deforestation were identified and the impact of them on future flood risk was analyzed using Monte Carlo simulations. We could find a high correlation between water level change and precipitation and predict how high the flood risk in Cambodia would increase if rainfall continued. However, a significant relationship between deforestation and increased flood risk was not identified.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Alsdorf, D., Han, S. C., Bates, P., and Melack, J. (2010). “Seasonal water storage on the Amazon floodplain measured from satellites.” Remote Sensing of Environment, vol. 114, no. 11, pp. 2448–2456. DOI: 10.1016/j.rse.2010.05.020.

    Article  Google Scholar 

  • Avtar, R., Sawada, H., Takeuchi, W., and Singh, G. (2012). “Characterization of forests and deforestation in Cambodia using ALOS/PALSAR observation.” Geocarto International, vol. 27, no. 2, pp. 119–137. DOI: 10.1080/10106049.2011.626081.

    Article  Google Scholar 

  • Balogh, P., Golea, P., and Inceu, V. (2013). “Profit forecast model using Monte Carlo Simulation in Excel.” Romanian Statistical Review, vol. 61, no. 12, pp. 33–40.

    Google Scholar 

  • Belward, A. S. (1996). The IGBP-DIS global 1 km land cover data set “DISCover”: Proposal and implementation plans, Report of the Land Cover Working Group of IGBP-DIS, IGBP-DIS Office, Toulouse, France.

    Google Scholar 

  • Berry, P. A. M., Garlick, J. D., Freeman, J. A., and Mathers, E. L. (2005). “Global inland water monitoring from multi-mission altimetry.” Geophysical Research Letters, vol. 32, no. 16, pp. 1–4. DOI: 10.1029/2005GL022814.

    Article  Google Scholar 

  • Birkett, C. M. (1998). “Contribution of the TOPEX NASA Radar Altimeter to the global monitoring of large rivers and wetlands.” Water Resources Research, vol. 34, no. 5, pp. 1223–1239. DOI: 10.1029/98WR00124.

    Article  Google Scholar 

  • Bradshaw, C. J. A., Sodhi, N. S., Peh, K. S.-H., and Brook, B. W. (2007). “Global evidence that deforestation amplifies flood risk and severity in the developing world.” Global Change Biology, vol. 13, no. 11, pp. 2379–2395. DOI: 10.1111/j.1365-2486.2007.01446.x.

    Article  Google Scholar 

  • Cauhopé, M., Gennero, M. C., DoMinh, K., Cretaux, J. F., Berge-Nguyen, M., Cazenave, A., and Seyler, F. (2006). “Worldwide validation of satellite altimetry-based water level time series.” EGU General Assembly 2006. 02-0. April 2006. Wien, Austria.

    Google Scholar 

  • Didan, K., Munoz, A. B., Solano, R., and Huete, A. (2015). MODIS vegetation index user’s guide (MOD13 series), The University of Arizona, Tucson, AZ, USA.

    Google Scholar 

  • Duana, Z. and Bastiaanssena, W. G. M. (2013). “Estimating water volume variations in lakes and reservoirs from four operational satellite altimetry databases and satellite imagery data.” Remote Sensing of Environment, vol. 134, pp. 403–416. DOI: 10.1016/j.rse.2013.03.010.

    Article  Google Scholar 

  • EM-DAT (2016). “Disaster database.” http://www.emdat.be/.

    Google Scholar 

  • FAO (2007). Brief on National Forest Inventory NFI, Food and Agriculture Organization of the United Nations.

    Google Scholar 

  • Frappart, F., Calmant, S., Cauhopé, M., Seyler, F., and Cazenave, A. (2006a). “Preliminary results of ENVISAT RA-2-derived water levels validation over the Amazon basin.” Remote Sensing of Environment, vol. 100, no. 2, pp. 252–264. DOI: 10.1016/j.rse.2005.10.027.

    Article  Google Scholar 

  • Frappart, F., Do Minh, K., L’Hermitte, J., Cazenave, A., Ramillien, G., Le Toan, T., and Mognard-Campbell, N. (2006b). “Water volume change in the lower Mekong from satellite altimetry and imagery data.” Geophysical Journal International, vol. 167, no. 2, pp. 570–584. DOI: 10.1111/j.1365-246X.2006.03184.x.

    Article  Google Scholar 

  • Hence, D. A. and Houze, R. A. (2011). “Vertical structure of hurricane eyewalls as seen by the TRMM Precipitation Radar.” Journal of Atmospheric Science, vol. 68, no. 8, pp. 1637–1652. DOI: 10.1175/2011JAS3578.1.

    Article  Google Scholar 

  • Huete, A., Didan, K., Miura, T., Rodriguez, E.P., Gao, X., and Ferreira, L. G. (2002). “Overview of the radiometric and biophysical performance of the MODIS vegetation indices.” Remote Sensing of Environment, vol. 83, Nos. 1–2, pp. 195–213. DOI: 10.1016/S0034-4257(02)00096-2.

    Article  Google Scholar 

  • Huete, A., Justice, C., and Liu, H. (1994). “Development of vegetation and soil indices for MODIS-EOS.” Remote Sensing of Environment, vol. 49, no. 3, pp. 224–234. DOI: 10.1016/0034-4257(94)90018-3.

    Article  Google Scholar 

  • Huffman, G. J., Adler, R. F., Morrissey, M., Bolvin, D. T., Curtis, S., Joyce, R., McGavock, B., and Susskind, J. (2001). Global precipitation at one-degree daily resolution from multi-satellite observations. Journal of Hydrometeorology, vol. 2, no. 1, pp. 36–50.

    Google Scholar 

  • IFRC (2012). World disaster report 2012, International Federation of Red Cross.

    Google Scholar 

  • Jiang, H., Liu, C., and Zipser, E. J. (2011). “A TRMM-based tropical cyclone cloud and precipitation feature database.” Journal of Applied Meteorology and Climatology, vol. 50, no. 6, pp. 1255–1274. DOI: 10.1175/2011JAMC2662.1.

    Article  Google Scholar 

  • Karl, T. R., Meehl, G. A., Miller, C. D., Hassol, S. J., Waple, A. M., and Murray, W. L. (2008). Weather and cliamte extremes in a changing climate; Regions of focus: North America, Hawaii, Caribbean, and US Pacific Islands, US Climate Change Science Program and the Subcommittee on Global Change Research, Washington, DC, USA.

    Google Scholar 

  • Kelley, O. A. (2014). “Where the least rainfall occurs in the Sahara Desert, the TRMM radar reveals a different pattern of rainfall each season.” Journal of Climate, Vol 27, no. 18, pp. 6919–6939. DOI: 10.1175/JCLI-D-14-00145.1.

    Article  Google Scholar 

  • Lee, H., Beighley, R. E., Alsdorf, D., Jung, H. C., Shum, C. K., Duan, J., Guo, J., Yamazaki, D., and Andreadis, K. (2011). “Characterization of terrestrial water dynamics in the Congo Basin using GRACE and satellite radar altimetry.” Remote Sensing of Environment, vol. 115, no. 12, pp. 3530–3538. DOI: 10.1016/j.rse.2011.08.015.

    Article  Google Scholar 

  • Lee, H., Durand, M., Jung, H. C., Alsdorf, D., Shum, C. K., and Sheng, Y., (2010). “Characterization of surface water storage change in Arctic lakes using simulated SWOT measurements.” International Journal of Remote Sensing, vol. 31, no. 14, pp. 3931–3953. DOI: 10.1080/01431161.2010.483494.

    Article  Google Scholar 

  • Lee, H., Jung, H. C., Yuan, T., Beighley, R. E., and Duan, J. (2014). “Controls of terrestrial water storage changes over the central Congo Basin determined by integrating PALSAR ScanSAR, Envisat altmetry, and GRACE data.” Remote Sensing of the Terrestrial Water Cycle, V. Lakshmi, Ed., Vol. 206, American Geophysical Union and John Wiley & Son, Inc., Canada, pp. 117–129. DOI: 10.1002/9781118872086.ch7.

    Google Scholar 

  • Liu, H. Q. and Huete, A. (1995). “A feedback based modification of the NDVI to minimize canopy background and atmospheric noise.” IEEE Transactions on Geoscience and Remote Sensing, vol. 33, no. 2, pp. 457–465. DOI: 10.1109/36.377946.

    Article  Google Scholar 

  • Lonfat, M., Marks Jr., F. D., and Chen, S. S. (2004). “Precipitation distribution in tropical cyclones using the Tropical Rainfall Measuring Mission (TRMM) microwave imager: A global perspective.” Monthly Weather Review, vol. 132, no. 7, pp. 1645–1660.

    Article  Google Scholar 

  • Long, S., Fatoyinbo, T., and Policelli, F. (2014). “Flood extent mapping for Namibia using change detection and thresholding with SAR.” Environmental Research Letters, vol. 9, no. 3, pp. 1–8. DOI: 10.1088/1748-9326/9/3/035002.

    Article  Google Scholar 

  • Maani, K. (2017). Multi-stakeholder decision making for complex problems: A systems thinking approach with cases, World Scientific Publishing Company.

    Book  Google Scholar 

  • Maillard, P, Bercher, N., and Calmant, S. (2015). “New processing approaches on the retrieval of water levels in Envisat and SARAL radar altimetry over rivers: A case study of the São Francisco River, Brazil.” Remote Sensing of Environment, vol. 156, pp. 226–241. DOI: 10.1016/j.rse.2014.09.027.

    Article  Google Scholar 

  • Mason, D. C., Davenport, I. J., Neal, J. C., Schumann, G. J. P., and Bates, P. D. (2012). “Near real-time flood detection in urban and rural areas using high-resolution synthetic aperture radar images.” IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 8, pp. 3041–3052. DOI: 10.1109/TGRS.2011.2178030.

    Article  Google Scholar 

  • McCulloch, J. S. G. and Robinson, M. (1993). “History of forest hydrology.” Journal of Hydrology, vol. 150, Nos. 2–4, pp. 189–216. DOI: 10.1016/0022-1694(93)90111-L.

    Article  Google Scholar 

  • Morton, D. C., DeFries, R. S., Shimabukuro, Y. E., Anderson, L. O., Bon Espírito-Santo, F. D., Hansen, M., and Carroll, M. (2005). “Rapid assessment of annual deforestation in the Brazilian amazon using MODIS data.” Earth Interactions, vol. 9, no. 8, pp. 1–22. DOI: 10.1175/EI139.1.

    Article  Google Scholar 

  • NCDM (2003). Mapping vulnerability to natural disaster in Cambodia, National Committee on Disaster Management, Phnom Penh, Cambodia.

    Google Scholar 

  • Okeowo, M. A., Lee, H., Hossain, F., and Getirana, A. (2017). Automated generation of lakes and reservoirs water elevation changes from satellite radar altimetry. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 8, pp. 3465–3481. DOI: 10.1109/jstars.2017.2684081, DOI: 10.1109/jstars.2017.2684081.

    Google Scholar 

  • Phoeurn, C. and Ly, S. (2018). “Assessment of satellite rainfall estimates as a pre-analysis for water environment analytical tools: A case study for Tonle Sap lake in Cambodia.” Engineering Journal, vol. 22, no. 1, pp. 229–241. DOI: 10.4186/ej.2018.22.1.229.

    Article  Google Scholar 

  • Pryde, J. K., Osorio, J., Wolfe, M. L., Heatwole, C., Benham, B., and Cardenas, A. (2007). Comparison of watershed boundaries derived from SRTM and ASTER digital elevation datasets and from a digitized topographic map, American Society of Agricultural and Biological Engineers Paper 072093. St. Joseph, Michigan, USA.

    Google Scholar 

  • Reuters, T. (2003). Logging threatens Cambodian tragedy, United Nations.

    Google Scholar 

  • Sakamoto, T., Nguyen, N. V., Kotera, A., Ohno, H., Ishitsuka, N., and Yokozawa, M. (2007). “Detecting temporal changes in the extent of annual flooding within the Cambodia and the Vietnamese Mekong Delta from MODIS time-series imagery.” Remote Sensing of Environment, vol. 109, no. 3, pp. 295–313. DOI: 10.1016/j.rse.2007.01.011.

    Article  Google Scholar 

  • Simpson, J., Adler, R. F., and North, G. R. (1988). “A proposed Tropical Rainfall Measuring Mission (TRMM) satellite.” Bull Am Meteorol Soc., vol. 69, no. 3, pp. 278–295, https://doi.org/10.1175/1520-0477(1988)069<0278:APTRMM>2.0.CO;2.

    Article  Google Scholar 

  • Sulistioadi, Y. B., Tseng, K.-H., Shum, C. K., Hidayat, H., Sumaryono, M., Suhardiman, A., Setiawan, F., and Sunarso, S. (2015). “Satellite radar altimetry for monitoring small rivers and lakes in Indonesia.” Hydrology and Earth System Sciences, vol. 19, no. 1, pp. 341–359, https://doi.org/10.1175/1520-0477(1988)069<0278:APTRMM> 2.0.CO;2.

    Article  Google Scholar 

  • UNDP (2011). Building resilience: The future for rural livelihoods in the face of climate change, Cambodia Human Development Report 2011, United Nation Development Programme.

    Google Scholar 

  • UNU-EHS (2011). World risk report 2011, Alliance Development Works.

    Google Scholar 

  • USGS (2002). Design of a real-time ground-water level monitoring network and portrayal of hydrologic data in southern Florida, Water-Resource Investigations Report 01-4275. US Geological Survey, Tallahassee, FL, USA.

    Google Scholar 

  • Wingham, D. J., Rapley, C. G., and Griffiths, H. (1986). “New techniques in satellite altimeter tracking systems.” Proceedings of IGARSS’86 Symposium, Zurich, pp. 1339–1344.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hong-Gyoo Sohn.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, S., Sohn, HG., Kim, MK. et al. Analysis of the Relationship among Flood Severity, Precipitation, and Deforestation in the Tonle Sap Lake Area, Cambodia Using Multi-Sensor Approach. KSCE J Civ Eng 23, 1330–1340 (2019). https://doi.org/10.1007/s12205-019-1061-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12205-019-1061-7

Keywords

Navigation