Comprehensive Drought Assessment Using a Modified Composite Drought index: A Case Study in Hubei Province, China

Under the background of global climate change, accurate monitoring and comprehensive assessment of droughts are of great practical significance to sustain agricultural development. Considering multiple causes and the complexity of the occurrence of drought, this paper employs multiple input variables, i.e., precipitation, temperature, evaporation, and surface water content to construct a modified composite drought index (MCDI) using a series of mathematical calculation methods. The derived MCDI was calculated as a multivariate drought index to measure the drought conditions and verify its accuracy in Hubei Province in China. Compared with the existing multivariate drought index, i.e., meteorological drought composite index (CI), there was a high level of correlation in monitoring drought events in Hubei Province. Moreover, according to the drought historical record, the significant drought processes monitored by the MCDI were consistent with actual drought conditions. Furthermore, temporal and spatial analysis of drought in Hubei Province was performed based on the monitoring results of the MCDI. This paper generalizes the development of the MCDI as a new method for comprehensive assessments of regional drought.

A Hybrid Index for Characterizing Drought Based on a Nonparametric Kernel Estimator

This study develops a nonparametric multivariate drought index, namely, the nonparametric multivariate standardized drought index (NMSDI), by considering the variations of both precipitation and streamflow. Building upon previous efforts in constructing nonparametric multivariate drought index, the nonparametric kernel estimator is used to derive the joint distribution of precipitation and streamflow, thus providing additional insights into drought-index development. The proposed NMSDI is applied in the Wei River basin (WRB), on the basis of which the drought-evolution characteristics are investigated. Three main results were found: 1) In general, NMSDI captures drought onset in a way that is similar to that of the standardized precipitation index and captures drought termination and persistence in a way that is similar to that of the standardized streamflow index. The drought events identified by NMSDI match well with historical drought records in the WRB. Performance is also consistent with that of an existing multivariate standardized drought index at various time scales, confirming the validity of the newly constructed NMSDI in drought detections. 2) An increasing risk of drought has been detected for past decades and will persist to a certain extent in the future in most areas of the WRB. 3) The identified changepoints of annual NMSDI are mainly concentrated in the early 1970s and mid-1990s, coincident with extensive water use and soil conservation practices. In summary, this study highlights a nonparametric multivariable drought index that can efficiently and comprehensively be used for drought detections and predictions.

Characteristics of integrated droughts based on a nonparametric standardized drought index in the Yellow River Basin, China

Most current drought indices rely on a representative parametric distribution function to fit data, which results in different tail behaviors. Additionally, a drought index based on a single variable may not be sufficient for monitoring drought conditions timely and reliably. Therefore, a nonparametric multivariate drought index (NMSDI) combined with the information of precipitation and streamflow was introduced in this study, without assuming representative parametric distributions. It was applied to characterize drought in the Yellow River Basin (YRB) on seasonal and annual scales. Results indicate that: (1) the variations of developed NMSDI is well consistent with those of 1-month SPI (standardized precipitation index) and SSI (standardized streamflow index), indicating the reliability and effectiveness of the newly proposed nonparametric based drought index; (2) a decreasing NMSDI trend was found over the period of 1952–2012 at seasonal and annual time scales, which would reverse in the future as suggested by the Hurst index; (3) no significant change points were detected for the annual NMSDI series over the YRB except one (i.e. the year 1991) in the middle streamflow sub-basin Wei River Basin (WRB) which was primarily caused by the combined effects of climate change and human activities.

Drought assessment using a multivariate drought index in the Huaihe River basin of Eastern China

The Huaihe River Basin having China's highest population density (662 persons per km2) lies in a transition zone between the climates of North and South China, and is thus prone to drought. Therefore, the paper aims to develop an appropriate drought assessment approach for drought assessment in the Huaihe River basin, China. Based on the Principal Component Analysis of precipitation, evapotranspiration, soil moisture and runoff, the three latter variables of which were obtained by use of the Xin'anjiang model, a new multivariate drought index (MDI) was formulated, and its thresholds were determined by use of cumulative distribution function. The MDI, the Standardized Precipitation Index (SPI) and the self-calibrating Palmer Drought Severity Index (sc-PDSI) time series on a monthly scale were computed and compared during 1988, 1999/2000 and 2001 drought events. The results show that the MDI exhibited certain advantages over the sc-PDSI and the SPI in monitoring drought evolution. The MDI formulated by this paper could provide a scientific basis for drought mitigation and management, and references for drought assessment elsewhere in China.