Reconstructing and analyzing China's fifty-nine year (1951–2009) drought history using hydrological model simulation

Abstract

Abstract. The recent fifty-nine year (1951–2009) drought history of China is reconstructed using daily soil moisture values generated by the Variable Infiltration Capacity (VIC) land surface macroscale hydrology model. VIC is applied over a grid of 10 458 points with a spatial resolution of 30 km × 30 km, and is driven by observed daily maximum and minimum air temperature and precipitation from 624 long-term meteorological stations. The VIC soil moisture is used to calculate the Soil Moisture Anomaly Percentage Index (SMAPI), which can be used as a measure of the severity of agricultural drought on a global basis. We develop a SMAPI-based drought identification procedure for practical uses in the identification of both grid point and regional drought events. As the result, a total of 325 regional drought events varying in time and strength are identified from China's nine drought study regions. These drought events can thus be assessed quantitatively at different spatial and temporal scales. The result shows that the severe drought events of 1978, 2000 and 2006 are well reconstructed, indicating SMAPI is capable of indentifying the onset of a drought event, its progressing, as well as its ending. Spatial and temporal variations of droughts on China's nine drought study regions are studied. Our result shows that on average, up to 30% of the total area of China is prone to drought. Regionally, an upward trend in drought-affected areas has been detected in three regions Inner Mongolia, Northeast and North during the recent fifty-nine years. However, the decadal variability of droughts has been week in the rest five regions South, Southwest, East, Northwest, and Tibet. Xinjiang has even been wetting steadily since the 1950s. Two regional dry centers are discovered in China as the result of a combined analysis on the occurrence of drought events from both grid points and drought study regions. The first center is located in the area partially covered by two drought study regions North and Northwest, which extends to the southeastern portion of Inner Mongolia and the southwest part of Northeast. The second one is found in the central to southern portion of the drought study region South. Our study demonstrates the applicability and the value of using modeled soil moisture for reconstructing drought histories, and SMAPI is useful to analyzing drought at different spatial and temporal scales.

Exploring spatiotemporal relationships among meteorological, agricultural, and hydrological droughts in Southwest China

“…The simulation system was verified by the measured discharge data at 43 river basins nationwide as well as the measured soil moisture content data at 28 stations, and runoff and soil moisture data showed a relatively high degree of accuracy (Wu et al 2007). These data have been applied to studies of the nationwide soil moisture distribution , drought characteristics (Wu et al 2011b, and drought monitoring and predictions (Wu et al 2011a). …”

“…The classification in this paper employed the standards as defined in the literature (Zhao 2011), which are a modification of previous studies (Wu et al 2011b). …”

“…The SMAPI (Wu et al 2011b) represents the percentage calculated from the difference between the actual soil moisture and the multiyear average value during the same period divided by the multiyear average value during the same period. The averaged soil moisture from multiple years in a particular region at a particular time instant is used as the climatological soil moisture at that particular time instant in that region.…”

“…Specifically, the standardized precipitation evapotranspiration index (SPEI) [Vicente-Serrano et al 2010] that reflects meteorological droughts, soil moisture anomaly percentile index (SMAPI) [Wu et al 2011b] that reflects agricultural droughts, and standardized runoff index (SRI) [Shukla and Wood 2008] that reflects hydrological droughts were selected to analyze the spatiotemporal relationships between the different types of drought indices and the resulting data were used to gain insight into drought processes. These three indices were constructed using precipitation, evaporation, soil moisture content, and runoff data, which are indicative of the physical mechanisms underlying all drought indices.…”

A New Physically Based Self-Calibrating Palmer Drought Severity Index and its Performance Evaluation

“…These two indices mainly range from −2.0 to 2.0. Furthermore, the soil moisture anomaly percentage index (SMAPI, Bergman et al 1988) is employed to monitor soil moisture conditions in view of its good applicability in China (Wu et al 2011). To fit the time scale of PDSI indices, SMAPI is computed at a monthly scale, and is defined as:…”