Abstract
Agricultural drought can have long-lasting and harmful impacts on both the ecosystem and economy. Therefore, it is important to monitor and predict agricultural drought accurately. Soil moisture is the key variable to define the agricultural drought index. However, in situ soil moisture observations are inaccessible in many areas of the world. Remote sensing techniques enrich the surface soil moisture observations at different tempo-spatial resolutions. In this study, the Level 2 L-band radiometer soil moisture dataset was used to estimate the Soil Water Deficit Index (SWDI). The Soil Moisture Active Passive (SMAP) dataset was evaluated with the soil moisture dataset obtained from the China Land Soil Moisture Data Assimilation System (CLSMDAS). The SMAP-derived SWDI (SMAP_SWDI) was compared with the atmospheric water deficit (AWD) calculated with precipitation and evapotranspiration from meteorological stations. Drought monitoring and comparison were accomplished at a weekly scale for the growing season (April to November) from 2015 to 2017. The results were as follows: (1) in terms of Pearson correlation coefficients (R-value) between SMAP and CLSMDAS, around 70% performed well and only 10% performed poorly at the grid scale, and the R-value was 0.62 for the whole basin; (2) severe droughts mainly occurred from mid-June to the end of September from 2015 to 2017; (3) severe droughts were detected in the southern and northeastern Xiang River Basin in mid-May of 2015, and in the northern basin in early August of 2016 and end of November 2017; (4) the values of percentage of drought weeks gradually decreased from 2015 to 2017, and increased from the northeast to the southwest of the basin in 2015 and 2016; and (5) the average value of R and probability of detection between SMAP_SWDI and AWD were 0.6 and 0.79, respectively. These results show SMAP has acceptable accuracy and good performance for drought monitoring in the Xiang River Basin.
Highlights
Drought is a natural disaster that occurs with high frequency and which has long-lasting impacts on agriculture production, the ecological environment, and the economy [1]
Soil moisture on each grid obtained from Soil Moisture Active Passive (SMAP) and China Land Soil Moisture Data Assimilation System (CLSMDAS) between 1 April to 30 November 2017 were used for calculation of R-value
Higher consistency between CLSMDAS and SMAP soil moisture was mostly observed in the southwest part of the Xiang River Basin, which is located in a region with relatively low altitude compared to surrounding regions
Summary
Drought is a natural disaster that occurs with high frequency and which has long-lasting impacts on agriculture production, the ecological environment, and the economy [1]. Agricultural drought can occur in many parts of the world but usually develops slowly and causes widespread devastation and economic loss [2]. During the growing seasons from 1988 to 2001, Canada suffered more than 5 billion dollars in economic losses per year due to agricultural drought [3]. USA, experienced drought at the same time, at a different magnitude, duration, and extent, and the agricultural economic sector was the primary sector affected [4]. Some regions of China, such as the Xiang River Basin, have suffered agricultural drought due to climate change in recent years [1,6,7]. Agricultural drought disasters may be further aggravated around the world due to climate change [8]. It is urgent and necessary to predict and monitor agricultural drought accurately, for it is of importance to risk management
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