Meteorological droughts can affect large areas and may have serious environmental, social and economic impacts. These impacts depend on the severity, duration, and spatial extent of the precipitation deficit and the socioeconomic vulnerability of the affected regions. This paper examines the spatiotemporal variation of meteorological droughts in the Haihe River basin. Meteorological droughts events were diagnosed using daily meteorological data from 44 stations by calculating a comprehensive drought index (CI) for the period 1961–2011. Based on the daily CI values of each station over the past 50 years, the drought processes at each station were confirmed, and the severity, duration and frequency of each meteorological drought event were computed and analyzed. The results suggest the following conclusions: (1) the use of the CI index can effectively trace the development of drought and can also identify the duration and severity of each drought event; (2) the average drought duration was 57–85 days in each region of the Haihe River basin, and the region with the highest average values of drought duration and drought severity was Bohai Bay; (3) drought occurred more than 48 times over the study period, which is more than 0.95 times per year over the 50 years studied. The average frequencies of non-drought days, severe drought days and extreme drought days over the study period were 51.2, 3.2 and 0.4 %, respectively. Severe drought events mainly occurred in the south branch of the Hai River, and extreme drought events mainly occurred in the Shandong Peninsula and Bohai Bay; (4) the annual precipitation and potential evapotranspiration of the Haihe River basin show decreasing trends over the past 50 years. The frequency of severe drought and extreme drought events has increased in the past 20 years than during the period 1961–1990. The results of this study may serve as a reference point for decision regarding basin water resources management, ecological recovery and drought hazard vulnerability analysis.
In 2013, Chang＇E-3 program will develop lunar mineral resources in-situ detection. A Visible and Near-infrared Imaging Spectrometer （VNIS） has been selected as one payload of CE-3 lunar rover to achieve this goal. It is critical and urgent to evaluate VNIS＇ spectrum data quality and validate quantification methods for mineral composition before its launch. Ground validation experiment of VNIS was carried out to complete the two goals, by simulating CE-3 lunar rover＇s detection environment on lunar surface in the laboratory. Based on the hyperspectral reflectance data derived, Correlation Analysis and Partial Least Square （CA-PLS） algorithm is applied to predict abundance of four lunar typical minerals （pyroxene, plagioclase, ilmenite and olivine） in their mixture. We firstly selected a set of VNIS＇ spectral parameters which highly correlated with minerals＇ abundance by correlation analysis （CA）, and then stepwise regression method was used to find out spectral parameters which make the largest contri- butions to the mineral contents. At last, functions were derived to link minerals＇ abundance and spectral parameters by partial least square （PLS） algorithm. Not considering the effect of maturity, agglutinate and Fe~, we found that there are wonderful correlations between these four minerals and VNIS＇ spectral parameters, e.g. the abundance of pyroxene correlates positively with the mixture＇s absorption depth, the value of absorption depth added as the in- creasing of pyroxene＇s abundance. But the abundance of plagioclase correlates negatively with the spectral parame- ters of band ratio, the value of band ratio would decrease when the abundance of plagioclase increased. Similar to plagioclase, the abundance of ilmenite and olivine has a negative correlation with the mixture＇s reflectance data, if the abundance of ilmenite or olivine increase, the reflectance values of the mixture will decrease. Through model validation, better estimates of pyroxene, plagioclase and ilmenite＇s abundances are given. It is concluded that VNIS has the capability to be applied on lunar minerals＇ identification, and CA-PLS algorithm has the potential to be used on lunar surface＇s in-situ detection for minerals＇ abundance prediction. 相似文献
