Monitoring Meteorological Drought in Southern China Using Remote Sensing Data

Abstract

Severe meteorological drought is generally considered to lead to crop damage and loss. In this study, we created a new standard value by averaging the values distributed in the middle 30–70% instead of the traditional mean value, and we proposed a new index calculation method named Normalized Indices (NI) for meteorological drought monitoring after normalized processing. The TRMM-derived precipitation data, GLDAS-derived soil moisture data, and MODIS-derived vegetation condition data from 2003 to 2019 were used, and we compared the NI with commonly used Condition Indices (CI) and Anomalies Percentage (AP). Taking the mid-to-lower reaches of the Yangtze River (MLRYR) as an example, the drought monitoring results for paddy rice and winter wheat showed that (1) NI can monitor well the relative changes in real precipitation/soil moisture/vegetation conditions in both arid and humid regions, while meteorological drought was overestimated with CI and AP, and (2) due to the monitoring results of NI, the well-known drought event that occurred in the MLRYR from August to October 2019 had a much less severe impact on vegetation than expected. In contrast, precipitation deficiency induced an increase in sunshine and adequate heat resources, which improved crop growth in 78.8% of the area. This study discusses some restrictions of CI and AP and suggests that the new NI index calculation provides better meteorological drought monitoring in the MLRYR, thus offering a new approach for future drought monitoring studies.

Quantitative Study on Morphological Change Characteristics of Tonle Sap Lake Based on DEM

“…A Digital Elevation Model (DEM) is a data set of plane coordinates (X, Y) and their elevation (Z) of regular grid points within a certain range. It is formed Open Journal of Modern Hydrology through data interpolation of contour lines or elevation points, etc., and can be used to achieve digital simulation of terrain with limited terrain elevation data [14].…”

“…Based on the existing research results [3] [5] [6] [7] [14], the evaluation indexes of lake morphology selected in this paper are divided into two aspects. First, the basic geometric morphological indexes include lake area (S), lake perimeter (P), perimeter/area ratio (K), longest axis length (L) and maximum width (W).…”