Abstract
Early warning on crop injuries aroused by waterlogging is the guarantee of crop yield in the middle and lower reaches of the Yangtze River. The waterlogging warning measures based on precipitation index were often inaccurate. In this literature, a new method based on DHSVM (Distributed Hydrology Soil Vegetation Model) was used for practice in summer crops at county-level, real-time and high-precision forecasting, which simulates soil groundwater depth and soil volumetric moisture content in grid unit on time step of 1 day. According to the agricultural standard of waterlogging level, the meteorology characteristic data were calculated, and then spatial distribution of the waterlogging eigenvalues was mapped. Waterlogging distribution from Jianli County was clustered into five types of regions with a 90-m spatial resolution via the unsupervised classification method (k-means) algorithm. Based on the partition statistics of waterlogging eigenvalues, the character values of each kind were extracted. Using these eigenvalues as criteria, we predicted the waterlogging in the years from 1970 to 2015. The experimental results show that the average value of kappa coefficient is between 0.87 and 0.93, which illustrates that our method is effective for warning waterlogging level.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abliz A, Tiyip T, Ghulam A, Halik Ü, Ding J, Sawut M, Zhang F, Nurmemet I, Abliz A (2016) Effects of shallow groundwater table and salinity on soil salt dynamics in the Keriya oasis, Northwestern China. Environ Earth Sci 75(3):260–275
Ren B, Dong S, Liu P, Zhao B, Zhang J (2016) Ridge tillage improves plant growth and grain yield of waterlogged summer maize. Agric Water Manag 177:392–399
Yu M, Chen G (2013) Conditional QTL mapping for waterlogging tolerance in two RILs populations of wheat. SpringerPlus 2(1):245–252
Cai SM, Wang XL, Huang JL (1996) The four-regional development of Jianghan plain and agriculture sustainable development. Science Press Publishers, Beijing, pp 28–64
Wu HY, Gao P, Liu M (2013) The spring wet stained harm prediction model of winter wheat based on the Pacific SST. Geogr Res 32(8):1421–1429
Sheng SX, Lei S, Zhang YL (2009) Research on winter wheat waterlogging indexes and risk assessment model in Jianghuai region. Chin Agric Sci Bull 25(19):263–268
Jin SQ, Shi CL (2006) Wheat waterlogging warning system (WWWS) in Jianghuai plain. Acta Agron Sin 32(10):1458–1465
Shi CL, Jin ZQ (2003) Wheat waterlogging model based on WCSODS and its application in disaster warning. J Appl Meteorol Sci 14(4):462–468
Liu H, Jin ZQ (2005) Rape waterlogging forecast model in Jianghuai plains. Jiangsu J Agric Sci 21(2):86–91
Xiong QX (2015) Risk evaluation of sub-surface waterlogging of summer crops based on DHSVM model on county scale. Trans Chin Soc Agric Eng (Trans CSAE) 31(21):177–183
Singh A, Panda S (2012) Integrated salt and water balance modeling for the management of waterlogging and salinization. I: validation of SAHYSMOD. J Irrig Drain Eng 138(11):955–963
Singh A, Panda S (2012) Integrated salt and water balance modeling for the management of waterlogging and salinization. II: application of SAHYSMOD. J Irrig Drain Eng 138(11):964–971
Wigmosta MS, Vail LW, Lettenamaier DP (1994) A distributed hydrological-vegetation model for complex terrain. Water Resour Res 30(6):1665–1679
Wigmosta MS, Nijssen B, Storck P (2002) The distributed hydrological soil vegetation model. Mathematical models of small watershed hydrological and applications. Water Resource Publications, Department of Civil and Environment Engineering Louisiana State University, Baton Rouge
Tesfa KT (2010) Distributed hydrological modeling using soil depth estimated from landscape variables derived ith enhanced terrain analysis. Dissertations & Theses-Gradworks.
Yu GM (1993) Research on ecological characteristics of Jianghan plain Waterlogging land. Acta Ecol Sin 13(3):252–260
Chen JY (1989) Quantitative analysis on waterlogging middle-and-low-yielding fields’ discriminant standard. China Rural Water Hydropower 4:13–15
Wen RX, Hu XM, Ling BJ (1997) Study of the effect of waterlogging on wheat and the critical index of the stains. China Rural Water Hydropower 4:9–11
Cao HX, Yang TM, Jiang YL (2015) Simulation growing and yields of winter rapeseed under flower season waterlogging stress. J Agric Sci Technol 1:137–145
Yang W, Zhu JQ, Wu QX (2013) Research on the rape yield affected by stains and the relevant drainage index. J Irrig Drain 32(6):31–34
Acknowledgements
The authors acknowledge the financial grants from Open Fund of Ministry of Agriculture Key Laboratory of Agricultural Information Technology in 2012 (Grant: 2012001), Scientific Special Project on Public Welfare Industry (agriculture) in 2012 (Grant: 201203032), Open fund of Hubei Collaborative Innovation Center for Grain Industry, Yangtze University, China (Grant: H2015009).
Author information
Authors and Affiliations
Corresponding authors
Rights and permissions
About this article
Cite this article
Ma, Y., Xiong, Q., Zhu, J. et al. Early warning indexes determination of the crop injuries caused by waterlogging based on DHSVM model. J Supercomput 76, 2435–2448 (2020). https://doi.org/10.1007/s11227-018-2556-6
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11227-018-2556-6