Advertisement

Journal of Arid Land

, Volume 6, Issue 1, pp 3–15 | Cite as

Index-based assessment of agricultural drought in a semi-arid region of Inner Mongolia, China

  • Rui Li
  • Atsushi Tsunekawa
  • Mitsuru Tsubo
Article

Abstract

Agricultural drought is a type of natural disaster that seriously impacts food security. Because the relationships among short-term rainfall, soil moisture, and crop growth are complex, accurate identification of a drought situation is difficult. In this study, using a conceptual model based on the relationship between water deficit and crop yield reduction, we evaluated the drought process in a typical rainfed agricultural region, Hailar county in Inner Mongolia autonomous region, China. To quantify drought, we used the precipitation-based Standardized Precipitation Index (SPI), the soil moisture-based Crop Moisture Index (CMI), as well as the Normalized Difference Vegetation Index (NDVI). Correlation analysis was conducted to examine the relationships between dekad-scale drought indices during the growing season (May-September) and final yield, according to data collection from 2000 to 2010. The results show that crop yield has positive relationships with CMI from mid-June to mid-July and with the NDVI anomaly throughout July, but no correlation with SPI. Further analysis of the relationship between the two drought indices shows that the NDVI anomaly responds to CMI with a lag of 1 dekad, particularly in July. To examine the feasibility of employing these indices for monitoring the drought process at a dekad time scale, a detailed drought assessment was carried out for selected drought years. The results confirm that the soil moisture-based vegetation indices in the late vegetative to early reproductive growth stages can be used to detect agricultural drought in the study area. Therefore, the framework of the conceptual model developed for drought monitoring can be employed to support drought mitigation in the rainfed agricultural region of Northern China.

Keywords

drought assessment drought index dekad time scale rainfed agriculture 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Allen R G, Pereira L S, Raes D, et al. 1998. Crop evapotranspiration: guidelines for computing crop water requirements. Rome, Italy: FAO Irrigation and Drainage Paper, 56: 23–28, 106.Google Scholar
  2. Bayarjargal Y, Karnieli A, Bayasgalan M, et al. 2006. A comparative study of NOAA-AVHRR derived drought indices using change vector analysis. Remote Sensing Environment, 105(1): 9–22.CrossRefGoogle Scholar
  3. Brown, J F, Wardlow B D, Tadesse T, et al. 2008. The Vegetation Drought Response Index (VegDRI): a new integrated approach for monitoring drought stress in vegetation. GIScience and Remote Sensing, 45(1): 16–46.CrossRefGoogle Scholar
  4. Cai J, Liu Y, Lei T, et al. 2007. Estimating reference evapotranspiration with the FAO Penman-Monteith equation using daily weather forecast messages. Agricultural and Forest Meteorology, 145: 22–35.CrossRefGoogle Scholar
  5. Deng K M, Sun J L, Chen P F, et al. 2011. Estimation of spring wheat yield by remote sensing information from China’s environmental disaster mitigation satellite-taking Chen Barag Banner of Inner Mongolia as an example. Journal of Natural Resources, 26(11): 1942–1952.Google Scholar
  6. Dominic S, Derric R. 2002. Schaum’s Outline of Theory and Problems of Statistics and Econometrics. New York: McGraw-Hill Companies, Inc.Google Scholar
  7. Donald A W. 1994. Preparing for Drought: A Guidebook for Developing Countries. Pennsylvania: Diane Books Publishing Company, 7–8.Google Scholar
  8. Duan H, Yan C, Tsunekwawa A, et al. 2011. Assessing vegetation dynamics in the Three-North Shelter Forest region of China using AVHRR NDVI data. Environmental Earth Sciences, 64(4): 1011–1020.CrossRefGoogle Scholar
  9. Gu Y X, Hunt E, Wardlow B, et al. 2008. Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data. Geophysical Research Letters, 35: L22401.CrossRefGoogle Scholar
  10. Heim R R. 2002. A review of twentieth century drought indices used in the United States. Bulletin of the American Meteorological Society, 83(8): 1149–1165.Google Scholar
  11. Heinrich H W, Petersen D, Roos N. 1980. Industrial Accident Prevention: A Safety Management Approach. New York: McGraw-Hill, 468.Google Scholar
  12. Hirota O, Oka M, Takeda T. 1990. Sink activity estimation by sink size and dry matter increase during the ripening stage of barley (Hordeum vulgare) and rice (Oryza sativa). Annals of Botany, 65: 349–354.Google Scholar
  13. Holben B N. 1986. Characteristics of maximum-value composite images for temporal AVHRR data. International Journal of Remote Sensing, 7: 1435–1445.CrossRefGoogle Scholar
  14. Huete A, Justice C, van Leeuwen W. 1999. MODIS Vegetation Index (MOD13) Algorithm Theoretical Basis Document. Tucson: University of Arizona.Google Scholar
  15. Huete A, Didan K, Miura T, et al. 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83(1–2): 195–213.CrossRefGoogle Scholar
  16. Ji L, Peters A. 2003. Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sensing of Environment, 87(1): 85–89.CrossRefGoogle Scholar
  17. Jin H J, Li S X, Cheng G D, et al. 2000. Permafrost and climatic change in China. Global and Planetary Change, 26: 387–404.CrossRefGoogle Scholar
  18. Jordan C F, 1969. Deviation of leaf area index from quality of light on the forest floor. Ecology, 50: 663–666.CrossRefGoogle Scholar
  19. Karl T R. 1986. The sensitivity of the Palmer Drought Severity Index and Palmer’s Z-Index to their calibration coefficients including potential evapotranspiration. Journal of Applied Meteorology, 25: 77–86.CrossRefGoogle Scholar
  20. Kogan F, Sullivan J. 1993. Development of global drought-water system using NOAA/AVHRR data. Advances in Space Research, 13(5): 219–222.CrossRefGoogle Scholar
  21. Kogan F. 1994. NOAA plays leadership role in developing satellite technology for drought watch. Earth Observation Magazine: 18–21.Google Scholar
  22. Kogan F. 1997. Global drought watch from space. Bulletin of the American Meteorological Society, 78: 621–636.CrossRefGoogle Scholar
  23. Li F X, Wang L X, Liu J, et al. 2003. Study on water requirement and the moisture index of spring wheat in irrigated areas of Ningxia. Chinese Journal of Eco-agriculture, 11(4): 108–110.Google Scholar
  24. Li P J, Mi D S. 1983. Distribution of snow cover in China. Journal of Glaciology and Cryopendology, 5(4): 9–17.Google Scholar
  25. Liu M L, Tang X M, Liu J Y, et al. 2001. Research on scaling effect based on 1 km grid cell data. Journal of Remote Sensing, 5(3): 183–190.Google Scholar
  26. Ma Z G, Fu C B. 2006. Some evidence of drying trend over northern China from 1951 to 2004. Chinese Science Bulletin, 51(23): 2913–2925.CrossRefGoogle Scholar
  27. McKee T B, Doesken N J, Kleist J. 1993. The relation of drought frequency and duration to time scales. In: Proceedings of the Eighth Conference on Applied Climatology. Boston: American Meteorological Society, 179–184.Google Scholar
  28. McKee T B, Doesken N J, Kleist J. 1995. Drought monitoring with multiple time scales. In: Proceedings of the Ninth Conference on Applied Climatology. Boston: American Meteorological Society, 233–236.Google Scholar
  29. Miller T D. 1999. Growth stages of wheat: identification and understanding improve crop management. Texas Agricultural Extension Service, the Texas A&M University system, SCS-1999-16. http://varietytesting.tamu.edu/wheat/docs/mime-5.pdf.Google Scholar
  30. Mkhabela M S, Bullock P, Raj S, et al. 2011. Crop yield forecasting on the Canadian prairies using MODIS NDVI data. Agricultural and Forest Meteorology, 151(3): 385–393.CrossRefGoogle Scholar
  31. Nicholson S E, Farrar T J. 1994. The influence of soil type on the relationships between NDVI, rainfall, and soil moisture in semi-arid Botswana. I. NDVI response to rainfall. Remote Sensing of Environment, 50(2): 107–120.CrossRefGoogle Scholar
  32. Palmer W C. 1965. Meteorological Drought. US Weather Bureau Research Paper No. 28.Google Scholar
  33. Palmer W C. 1968. Keeping track of crop moisture conditions, nationwide: the new crop moisture index. Weatherwise, 21: 156–161.CrossRefGoogle Scholar
  34. Quiring S M. 2009. Developing objective operational definitions for monitoring drought. Journal of Applied Meteorology and Climatology, 48(6): 1217–1229.CrossRefGoogle Scholar
  35. Quiring S M, Ganesh S. 2010. Evaluating the utility of the Vegetation Condition Index (VCI) for monitoring meteorological drought in Texas. Agricultural and Forest Meteorology, 150(3): 330–339.CrossRefGoogle Scholar
  36. Rouse J W, Hass R H, Schell J A, et al. 1974. Monitoring vegetation systems in the Great Plains with ERTS. In: The Third Earth Resources Technology Satellite-1 Symposium, Greenbelt, MD, 309–317.Google Scholar
  37. Shen J G. 2008. Chinese Meterological Disasters Dictionary: Inner Mongolia volume. Beijing: China Meteorological Press, 8Google Scholar
  38. Shu B R, Liu Y Z, Lu X P, et al. 2008. Application of the theory of energy analysis to the sustainability assessment of cultivated lands: a case study of Nanjing. Journal of Natural Resources, 23(5): 876–885.Google Scholar
  39. Svoboda M. 2000. An introduction to the drought monitor. Drought Network News, 12: 15–20.Google Scholar
  40. Tannehill I R. 1947. Drought: Its Causes and Effects. Princeton: Princeton University Press, 264.Google Scholar
  41. ai]Thornthwaite C W. 1948. An approach toward a rational classification of climate. Geographical Review, 38(1): 55–94.CrossRefGoogle Scholar
  42. United Nations Convention to Combat Desertification (UNCCD). 1994. Intergovernmental Negotiating Committee for the Elaboration of an International Convention to Combat Desertification in Those Countries Experiencing Serious Drought and/or Desertification, Particularly in Africa. General Assembly: 5. http://www.unccd.int/en/about-the-convention/Pages/About-the-Convention.aspx.Google Scholar
  43. Wang J, Price K P, Rich P M. 2001. Spatial patterns of NDVI in response to precipitation and temperature in the central Great Plains. International Journal of Remote Sensing, 22: 3827–3844.CrossRefGoogle Scholar
  44. Wang X P, Zhao H Y. 2006. The Climate Resource and Zoning of Forestry, Animal Husbandry and Fishery in Hulunbeier Municipality of Inner Mongolia. Beijing: China Meteorological Press, 111–112, 145–148.Google Scholar
  45. World Meteorological Organization (WMO). 1975. Drought and Agriculture. WMO Note 138, Publ. WMO-392, Geneva, Switzerland, 127.Google Scholar
  46. Zarafshani K, Sharafi L, Azadi H, et al. 2012. Drought vulnerability assessment: the case of wheat farmers in western Iran. Global and Planetary Change, 98–99: 122–130.CrossRefGoogle Scholar
  47. Zhang C F, Wang D H, Qiu B J. 1987. Agricultural Phenology Atlas in China. Beijing: Science Press, 26–31, 50–53, 88–90.Google Scholar
  48. Zhang J Q. 2004. Risk assessment of drought disaster in the maize-growing region of Songliao Plain, China. Agriculture, Ecosystems and Environment, 102(2): 133–153.CrossRefGoogle Scholar
  49. Zhou H J, Rompaey A V, Wang J A. 2009. Detecting the impact of the ‘Grain for Green’ program on the mean annual vegetation cover in the Shaanxi province, China using SPOT-VGT NDVI data. Land Use Policy, 26(4): 954–960.CrossRefGoogle Scholar
  50. Zipporah M. 2011. Temporal relationships between remotely sensed soil moisture and NDVI over Africa: potential for drought early warning? MSc Thesis. Enschede: University of Twente, 30.Google Scholar

Copyright information

© Science Press, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.United Graduate School of Agricultural SciencesTottori UniversityTottoriJapan
  2. 2.Arid Land Research CenterTottori UniversityTottoriJapan

Personalised recommendations