FORECAST EFFECTS OF DROUGHT ON AGRICULTURAL LAND USE BY GIS AND REMOTE SENSING IN BAC TRA MY DISTRICT, QUANG NAM PROVINCE

Keywords

Agricultural land use
drought
forecast
GIS
Remote sensing
Bac Tra My

Abstract

The phenomenon of prolonged drought as one of the consequences of climate change has significantly affected the agricultural production of rural communities in both mountainous and plain areas of Vietnam. This study, using standardized precipitation index (SPI) combining with the space technologies of Geographical Information Systems (GIS) and Remote Sensing (RS) to simulate and forecast the effects of drought on agricultural land use in Bac Tra My district, Quang Nam province. The data was set up for two scenarios of RCP 4.5 and RCP 8.5 in Bac Tra My district of Quang Nam province. Simultaneously, the research has also applied the focus group discussion, in-depth interview and field survey for data cross-checking to ensure highly reliable predictions. The research result has addressed four levels of drought, including normal, mild, moderate and severe drought appearing in the Summer-Autumn crop in the period 2016 – 2035 of the district. In which, severe drought will appear on large scale for both scenarios of RCP 4.5 and RCP 8.5 for 5 types of agricultural land use including paddy, annual crop, perennial, afforestation and aquacultural land. From these findings, the local authorities can consider and apply the adaptation and mitigation measures to climate change in agricultural land use planning.

https://doi.org/10.26459/hueunijard.v130i3C.6084

References

  1. Adamowski. J, Adamowski. K, Bougadis. J, (2010), Influence of trend on short duration design storms, Water Resour Manage, 24, 401–413.
  2. Adamowski. K, Prokoph. A, Adamowski. J, (2009), Development of a new method of wavelet aided trend detection and estimation, Hydrol Process, 23, 2686–2696.
  3. A. C. Cebrián and J. Abaurrea, (2006), Drought analysis based on a marked cluster Poisson model, Journal of Hydrometeorology, 7(4), 713–723.
  4. Adamowski. J, Chan. H, Prasher. S, Sharda. VN, (2012), Comparison of multivariate adaptive regression splines with coupled wavelet transform artificial neural networks for runoff forecasting in Himalayan micro-watersheds with limited data, Journal of Hydroinform, 3, 731–744.
  5. Bhuiyan. C, Singh. RP, Kogan. FN, (2006), Monitoring drought dynamics in the Aravalli region (India) using different indices based on ground and remote sensing data, Int J Appl Earth Obs Geoinf, 8, 289–302.
  6. Bayissa. YA, Moges. SA, Xuan. Y, Van Andel. SJ, Maskey. S, Solomatine. DP, Griensven. A, Van Tadesse. T, (2015), Spatio-temporal assessment of meteorological drought under the influence of varying record length: The case of Upper Blue Nile Basin, Ethiopia, Hydrol. Sci. J., 60, 1927–1942.
  7. Campisi. S, Adamowski. J, Oron. G, (2012), Forecasting urban water demand via wavelet- denoising and neural network models, Case study: City of Syracuse, Italy, Water Resour Manage, 26, 3539–3558.
  8. Capra. A, Scicolone. B, (2012), Spatio-temporal variability of drought on a short–medium time scale in the Calabria Region (Southern Italy), Theor. Appl. Climatol., 3, 471–488.
  9. Chuong. HV, Linh. NHK, Tung. PG, Phuong. TT, Non. D Q, Phung. LD, (2015), Studying drought situation in Summer-Autumn paddy rice land using Remote sensing technology and GIS in Dai Loc district, Quang Nam province, Hue University Journal of Science, 103(4), ISSN 1859-1388.
  10. DA. Wilhite, (2000), Drought: A Global Assessment, Natural Hazards and Disasters Series, Routledge, London, UK.
  11. Department of Natural Resources and Environment of Quang Nam province, (2020), Report on Land Inventory in 2019 of Bac Tra My district.
  12. Eric J. Gustafson and Brian R. Sturtevant, (2013), Modeling forest mortality caused by drought stress: implications for climate change, Ecosystems, 16(1), 60–74.
  13. Hydrometeorology Station in Central Central Vietnam, (2019), Statistical report on rainfall data by day in the period 1977 – 2019, City. Danang.
  14. Mishra. AK, Singh. VP, (2010), A review of drought concepts, J Hydrol, 391, 202–216.
  15. Monica. I, Patrick. S, Silvia. MC, (2016), Assessment of drought in Romania using the Standardized Precipitation Index, Journal of Natural Hazards, 81(3).
  16. Ministry of Natural Resources and Environment, (2016), The climate change and sea-level rise scenarios for Vietnam, Vietnam Map and Environmental Resources Publishing House.
  17. Mckee. TB, Doesken. NJ and Kleist. J, (1993), The relationship of drought frequency and duration to time scale, Preprints, Eighth Confrence on Applie Climatology, Anaheim, CA, American Meteorological Society, 179–184.
  18. Nalley. D, Adamowski. J, Khalil. B, (2012), Using discrete wavelet transforms to analyze trends in streamflow and precipitation in Quebec and Ontario (1954-2008), J Hydrol, 475, 204–228.
  19. Nagarajan. R, (2004), Drought Vulnerability Assessment Using Geoinformatics (Bombay, India: CSRE), Indian Institute of Technology.
  20. Ngu. NH, (2017), Assessment of drought situation using the Standardized Precipitation Index (SPI) in Thua Thien Hue province, Hue University Journal of Science, 123(7A), ISSN 1859-1388.
  21. Phuong. TT, Non. DQ, Chuong. HV, Linh. NHK, Tung. PG, An. LV, (2015), The impacts of drought on paddy rice productivity in Dai Loc district, Quang Nam province, Journal of Agriculture and Rural development, 6, 37–45.
  22. Phuong. T.T, Chuong H. V, (2018), Application of distance inverse interpolation (IDW) to simulate the effects of drought on paddy land in Hoa Vang district, Da Nang city, Journal of Agriculture & Rural Development ,2, 73–81.
  23. Tiwari. M, Adamowski. J, (2014), Urban water demand forecasting and uncertainty assessment using ensemble wavelet-bootstrap-neural network models, Water Resour Res, 49, 6486–6507.
  24. Tadesse. T, Tilhite. D.A., Harms. S.K, Hayes. M.J and Goddard. S, (2004), Drought monitoring using data mining techniques: a case study for Nebraska, USA, Natural Hazards, 33, 137–159.
  25. Nguyen Van Thang, Mai Van Khiem, Nguyen Dang Mau, (2014), Research to identify drought indicators for the Nam Trung Bo, Journal of Meteorology and Hydrology, 3, 49–55.
  26. Nguyen Van Thang, Mai Van Khiem, (2017), The assessment and projection of the dry condition for the Mekong river delta by using the SPI index, Journal of Meteorology and Hydrology, 6, 1–9.
  27. Vera Potop, Luboš Türkott, Věra Kožnarová and Martin Možný, (2010), Drought episodes in the Czech Republic and their potential effects in agriculture, Theoretical and applied climatology, 99(3–4), 373–388.
  28. World Meteorological Organization, (2012), Standardized Precipitation Index user guide, World Meteorological Organization, WMO-No.1090.
  29. Xihua Yang, Xiaojin Xie, De Li Liu, Fei. Ji and Lin Wang, (2015), Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Regio, Hindawi Publishing Corporation, Advances in Meteorology, Article ID 563629, 12 pages, http://dx.doi.org/10.1155/2015/56 3629.