Evaluation of Drought Monitoring Effect of Winter Wheat in Henan Province of China Based on Multi-Source Data
Open Access
- 1 April 2020
- journal article
- research article
- Published by MDPI AG in Sustainability
- Vol. 12 (7), 2801
- https://doi.org/10.3390/su12072801
Abstract
Monitoring agricultural drought is important to food security and the sustainable development of human society. In order to improve the accuracy of soil moisture and winter wheat yield estimation, drought monitoring effects of optical drought index data, meteorological drought data, and passive microwave soil moisture data were explored during individual and whole growth periods of winter wheat in 2003–2011, taking Henan Province of China as the research area. The model of drought indices and relative meteorological yield of winter wheat in individual and whole growth periods was constructed based on multiple linear regression. Results showed a higher correlation between Moderate-Resolution Imaging Spectroradiometer (MODIS) drought indices and 10 cm relative soil moisture (RSM10) than 20 cm (RSM20) and 50 cm (RSM50). In the whole growth period, the correlation coefficient (R) between vegetation supply water index (VSWI) and RSM10 had the highest correlation (R = −0.206), while in individual growth periods, the vegetation temperature condition index (VTCI) was superior to the vegetation health index (VHI) and VSWI. Among the meteorological drought indices, the 10-day, 20-day, and 30-day standard precipitation evapotranspiration indices (SPEI1, SPEI2, and SPEI3) were all most relevant to RSM10 during individual and whole growth periods. RSM50 and SPEI3 had a higher correlation, indicating that deep soil moisture was more related to drought on a long time scale. The relationship between Advanced Microwave Scanning Radiometer for EOS soil moisture (AMSR-E SM) and VTCI was stable and significantly positive in individual and whole growth periods, which was better compared to VHI and VSWI. Compared with the drought indices and the relative meteorological yield in the city, VHI had the best monitoring effect during individual and whole growth periods. Results also showed that drought occurring at the jointing–heading stage can reduce winter wheat yield, while a certain degree of drought occurring at the heading–milk ripening stage can increase the yield. In the whole growth period, the combination of SPEI1, SPEI2, and VHI had the best performance, with a coefficient of determination (R2) of 0.282 with the combination of drought indices as the independent variables and relative meteorological yield as the dependent variable. In the individual growth period, the model in the later growth period of winter wheat performed well, especially in the returning green–jointing stage (R2 = 0.212). Results show that the combination of multiple linear drought indices in the whole growth period and the model in the returning green–jointing period could improve the accuracy of winter wheat yield estimation. This study is helpful for effective agricultural drought monitoring of winter wheat in Henan Province.Funding Information
- National Natural Science Foundation of China (41701507)
This publication has 32 references indexed in Scilit:
- Spatio-temporal variation of drought in China during 1961–2012: A climatic perspectiveJournal of Hydrology, 2015
- Combination of multi-sensor remote sensing data for drought monitoring over Southwest ChinaInternational Journal of Applied Earth Observation and Geoinformation, 2015
- Evaluation of AMSR‐E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan PlateauJournal of Geophysical Research: Atmospheres, 2013
- Increasing drought under global warming in observations and modelsNature Climate Change, 2012
- Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing dataRemote Sensing of Environment, 2010
- A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration IndexJournal of Climate, 2010
- Use of NDVI and Land Surface Temperature for Drought Assessment: Merits and LimitationsJournal of Climate, 2010
- Satellite-Observed Sensitivity of World Land Ecosystems to El Niño/La NiñaRemote Sensing of Environment, 2000
- Application of vegetation index and brightness temperature for drought detectionAdvances in Space Research, 1995
- A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation coverRemote Sensing Reviews, 1994