Volume 14 Issue 3
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Article Navigation >  Water Science and Engineering  > 2021  >  14(3): 171-183
Zheng-guang Xu, Zhi-yong Wu, Hai He, Xiao Guo, Yu-liang Zhang. 2021: Comparison of soil moisture at different depths for drought monitoring based on improved soil moisture anomaly percentage index. Water Science and Engineering, 14(3): 171-183. doi: 10.1016/j.wse.2021.08.008
Citation: Zheng-guang Xu, Zhi-yong Wu, Hai He, Xiao Guo, Yu-liang Zhang. 2021: Comparison of soil moisture at different depths for drought monitoring based on improved soil moisture anomaly percentage index. Water Science and Engineering, 14(3): 171-183. doi: 10.1016/j.wse.2021.08.008
shu

Comparison of soil moisture at different depths for drought monitoring based on improved soil moisture anomaly percentage index

doi: 10.1016/j.wse.2021.08.008

  • a Institute of Water Problems, Hohai University, Nanjing 210098, China;

  • b College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China

Funds:

This work was supported by the National Key Research and Development Program of China (Grant No. 2017YFC1502403), the National Natural Science Foundation of China (Grant No. 51779071), and the Fundamental Research Funds for the Central Universities (Grant No. 2019B10214).

  • Received Date: 2020-12-04
  • Accepted Date: 2021-01-28
    • Available Online: 2021-10-11
    Abstract
  • To better understand the characteristics and mechanisms of droughts at different drought stages, this study selected the Xiangjiang River Basin in China as the study area, and evaluated soil moisture (SM) at different depths for drought monitoring, through SM data simulated with the variable infiltration capacity (VIC) model. To solve the problem of unreasonable drought/wetness classifications based on the soil moisture anomaly percentage index (SMAPI), an improved soil moisture anomaly percentage index (ISMAPI) was developed by introducing the Box-Cox transformation. The drought/wetness frequency generated by ISMAPI demonstrated preferable spatial comparability in comparison with those from SMAPI. The lag time of ISMAPI relative to the standardized precipitation evapotranspiration index was closely related to soil depth, and was characterized by a fast response in shallow soil layers and a relatively slow response in deep soil layers. SM in shallow soil layers provided a measure for monitoring short-term droughts, whereas SM in deep soil layers provided a better measure for long-term persistent drought events. Furthermore, the occurrence and mitigation time of drought events identified by SM in deep soil layers usually lagged behind that identified by SM in shallow soil layers. Compared with deep SM, SM in shallow soil layers responded faster to meteorological anomalies, thereby resulting in shorter periods of SM persistence in shallow soil layers than in deep soil layers. This can explain the differences of SM at different depths in drought monitoring.

     

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  • Box, G.E.P., Cox, D.R., 1964. An analysis of transformations. J. Roy. Stat. Soc. B 26(2), 211-243. https://doi.org/10.1111/j.2517-6161.1964.tb00553.x.
    China Meteorological Administration, 2012. Yearbook of Meteorological Disasters in China, 2012. China Meteorological Press, Beijing (in Chinese).
    China Meteorological Administration, 2015. Yearbook of Meteorological Disasters in China, 2014. China Meteorological Press, Beijing (in Chinese).
    Hansen, M.C., Defries, R.S., Townshend, J.R.G., Sohlberg, R., 2000. Global land cover classification at 1km spatial resolution using a classification tree approach. Int. J. Rem. Sens. 21(6-7), 1331-1364. https://doi.org/10.1080/014311600210209.
    Huang, S.Z., Li, P., Huang, Q., Leng, G.Y., Hou, B.B., Ma, L., 2017. The propagation from meteorological to hydrological drought and its potential influence factors. J. Hydrol. 547, 184-195. https://doi.org/10.1016/j.jhydrol.2017.01.041.
    Li, R.H., Chen, N.C., Zhang, X., Zeng, L.L., Wang, X.P., Tang, S.J., Li, D.R., Niyogi, D., 2020. Quantitative analysis of agricultural drought propagation process in the Yangtze River Basin by using cross wavelet analysis and spatial autocorrelation. Agric. For. Meteorol. 280, 107809. https://doi.org/10.1016/j.agrformet.2019.107809.
    Liang, X., Wood, E.F., Lettenmaier, D.P., 1996. Surface soil moisture parameterization of the VIC-2L model: Evaluation and modification. Global Planet. Change 13(1-4), 195-206. https://doi.org/10.1016/0921-8181(95)00046-1.
    Liu, Y., Yang, X.L., Ren, L.L., Yuan, F., Jiang, S.H., Ma, M.W., 2015. A new physically based self-calibrating Palmer drought severity index and its performance evaluation. Water Resour. Manag. 29(13), 4833-4847. https://doi.org/10.1007/s11269-015-1093-9.
    Liu, Y.W., Liu, Y.B., Wang, W., 2019. Inter-comparison of satellite-retrieved and Global Land Data Assimilation System-simulated soil moisture datasets for global drought analysis. Remote Sens. Environ. 220, 1-18. https://doi.org/10.1016/j.rse.2018.10.026.
    Lu, G.H., Liu, J.J., Wu, Z.Y., He, H., Xu, H.T., Lin, Q.X., 2015. Development of a large-scale routing model with scale independent by considering the damping effect of sub-basins. Water Resour. Manag. 29(14), 5237-5253. https://doi.org/10.1007/s11269-015-1115-7.
    Ma, M.W., Ren, L.L., Singh, V.P., Yang, X.L., Yuan, F., Jiang, S.H., 2014. New variants of the Palmer drought scheme capable of integrated utility. J. Hydrol. 519, 1108-1119. https://doi.org/10.1016/j.jhydrol.2014.08.041.
    Ma, M.W., Wang, W.C., Yuan, F., Ren, L.L., Tu, X.J., Zang, H.F., 2018. Application of a hybrid multiscalar indicator in drought identification in Beijing and Guangzhou, China. Water Sci. Eng. 11(3), 177-186. https://doi.org/10.1016/j.wse.2018.10.003.
    Mao, Y., Wu, Z.Y., He, H., Lu, G.H., Xu, H.T., Lin, Q.X., 2017. Spatiotemporal analysis of drought in a typical plain region based on the soil moisture anomaly percentage index. Sci. Total Environ. 576, 752-765. https://doi.org/10.1016/j.scitotenv.2016.10.116.
    Mckee, T.B., Doesken, N.J., Kleist, J., 1993. The relationship of drought frequency and duration to time scales. In: Paper Presented at 8th Conference on Applied Climatology. American Meteorological Society, Anaheim, pp. 179-183.
    Mishra, V., Shah, R., Azhar, S., Shah, H., Modi, P., Kumar, R., 2018. Reconstruction of droughts in India using multiple land-surface models(1951-2015). Hydrol. Earth Syst. Sci. 22(4), 2269-2284. https://doi.org/10.5194/hess-22-2269-2018.
    Modanesi, S., Massari, C., Camici, S., Brocca, L., Amarnath, G., 2020. Do satellite surface soil moisture observations better retain information about crop-yield variability in drought conditions? Water Resour. Res. 56(2), e2019WR025855. https://doi.org/10.1029/2019wr025855.
    Otkin, J.A., Zhong, Y.F., Hunt, E.D., Basara, J., Svoboda, M., Anderson, M.C., Hain, C., 2019. Assessing the evolution of soil moisture and vegetation conditions during a flash drought-flash recovery sequence over the southcentral United States. J. Hydrometeorol. 20(3), 549-562. https://doi.org/10.1175/jhm-d-18-0171.1.
    Park, S., Im, J., Park, S., Rhee, J., 2017. Drought monitoring using high resolution soil moisture through multi-sensor satellite data fusion over the Korean peninsula. Agric. For. Meteorol. 237-238, 257-269. https://doi.org/10.1016/j.agrformet.2017.02.022.
    Reynolds, C.A., Jackson, T.J., Rawls, W.J., 2000. Estimating soil waterholding capacities by linking the Food and Agriculture Organization soil map of the world with global pedon databases and continuous pedotransfer functions. Water Resour. Res. 36(12), 3653-3662. https://doi.org/10.1029/2000wr900130.
    Rosenbrock, H.H., 1960. An automatic method for finding the greatest or least value of a function. Comput. J. 3(3), 175-184.
    Sadri, S., Wood, E.F., Pan, M., 2018. Developing a drought-monitoring index for the contiguous US using SMAP. Hydrol. Earth Syst. Sci. 22(12), 6611-6626. https://doi.org/10.5194/hess-22-6611-2018.
    Samaniego, L., Thober, S., Kumar, R., Wanders, N., Rakovec, O., Pan, M., Zink, M., Sheffield, J., Wood, E.F., Marx, A., 2018. Anthropogenic warming exacerbates European soil moisture droughts. Nat. Clim. Change 8(5), 421-426. https://doi.org/10.1038/s41558-018-0138-5.
    Shao, Q.X., Li, M., 2013. An improved statistical analogue downscaling procedure for seasonal precipitation forecast. Stoch. Environ. Res. Risk Assess. 27(4), 819-830. https://doi.org/10.1007/s00477-012-0610-0.
    Vicente-Serrano, S.M., Beguería, S., López-Moreno, J.I., 2010. A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index. J. Clim. 23(7), 1696-1718. https://doi.org/10.1175/2009jcli2909.1.
    Wang, A.H., Shi, X.L., 2019. A multilayer soil moisture dataset based on the gravimetric method in China and its characteristics. J. Hydrometeorol. 20(8), 1721-1736. https://doi.org/10.1175/jhm-d-19-0035.1.
    Wu, Z.Y., Lu, G.H., Wen, L., Lin, C.A., 2011. Reconstructing and analyzing China’s fifty-nine year (1951-2009) drought history using hydrological model simulation. Hydrol. Earth Syst. Sci. 15(9), 2881-2894. https://doi.org/10.5194/hess-15-2881-2011.
    Wu, Z.Y., Mao, Y., Li, X.Y., Lu, G.H., Lin, Q.X., Xu, H.T., 2016. Exploring spatiotemporal relationships among meteorological, agricultural, and hydrological droughts in Southwest China. Stoch. Environ. Res. Risk Assess. 30(3), 1033-1044. https://doi.org/10.1007/s00477-015-1080-y.
    Wu, Z.Y., Zhou, J.H., He, H., Lin, Q.X., Wu, X.T., Xu, Z.G., 2018a. An advanced error correction methodology for merging in-situ observed and model-based soil moisture. J. Hydrol. 566, 150-163. https://doi.org/10.1016/j.jhydrol.2018.09.018.
    Wu, Z.Y., Xu, Z.G., Wang, F., He, H., Zhou, J.H., Wu, X.T., Liu, Z.C., 2018b. Hydrologic evaluation of multi-source satellite precipitation products for the upper Huaihe River Basin, China. Rem. Sens. 10(6), 840-860. https://doi.org/10.3390/rs10060840.
    Xu, Z.G., Wu, Z.Y., He, H., Wu, X.T., Zhou, J.H., Zhang, Y.L., Guo, X., 2019. Evaluating the accuracy of MSWEP V2.1 and its performance for drought monitoring over mainland China. Atmos. Res. 226, 17-31. https://doi.org/10.1016/j.atmosres.2019.04.008.
    Yan, G.X., Liu, Y., Chen, X., 2018. Evaluating satellite-based precipitation products in monitoring drought events in southwest China. Int. J. Rem. Sens. 39(10), 3186-3214. https://doi.org/10.1080/01431161.2018.1433892.
    Yin, J.F., Zhan, X.W., Hain, C.R., Liu, J.C., Anderson, M.C., 2018. A method for objectively integrating soil moisture satellite observations and model simulations toward a blended drought index. Water Resour. Res. 54(9), 6772-6791. https://doi.org/10.1029/2017wr021959.
    Yuan, X., Ma, Z.G., Pan, M., Shi, C.X., 2015. Microwave remote sensing of short-term droughts during crop growing seasons. Geophys. Res. Lett. 42(11), 4394-4401. https://doi.org/10.1002/2015gl064125.
    Zhou, J.H., Wu, Z.Y., He, H., Wang, F., Xu, Z.G., Wu, X.T., 2019. Regional assimilation of in situ observed soil moisture into the VIC model considering spatial variability. Hydrol. Sci. J. 64(16), 1982-1996. https://doi.org/10.1080/02626667.2019.1662024.
    Zhu, Q., Luo, Y.L., Xu, Y.-P., Tian, Y., Yang, T.T., 2019. Satellite soil moisture for agricultural drought monitoring: Assessment of SMAP-derived soil water deficit index in Xiang River Basin, China. Rem. Sens. 11(3), 362. https://doi.org/10.3390/rs11030362.
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