基于GRACE重力卫星数据的珠江流域干旱监测

为探究重力恢复和气候试验任务（Gravity Recovery and Climate Experiment mission，GRACE）卫星数据在干旱研究中的应用潜力，该研究采用基于GRACE重力卫星数据的无量纲的标准化水储量赤字干旱指数（Water Storage Deficit Index，WSDI）对珠江流域2002-2017年进行干旱监测，通过将其和常用干旱指数与实际干旱质心轨迹进行对比，评估其在珠江流域的干旱监测效用。研究结果表明：1）2002-2017年期间，WSDI监测到的旱情与实际发生的旱情基本一致，GRACE重力卫星数据能捕捉到干旱事件的发生、发展和消亡以及其干旱特征；2）WSDI的时间变化及其对气候异常的响应与常用干旱指数吻合良好，具有有着较强的相关性，且能反映研究区长期的综合水分变化。除了SPI-3与SPEI-3外，其他常用干旱指数与WSDI的相关系数都在0.665以上，其中scPDSI相关指数最高，为0.803；3）WSDI与常用干旱指数在空间上描述的干旱事件的干旱质心轨迹基本一致，都能大致反映出了大范围干旱事件的干旱质心从东往西移动的现象。WSDI能从时间和空间上刻画出研究区水文干旱的演变规律，适用于大尺度水文干旱的监测与评估，具有明显的优势和应用潜力。

Drought monitoring based on GRACE data in the Pearl River Basin, China

Abstract: Intensity and frequency of extreme climate events are ever-increasing, as the global climate is changing all the time. Drought has caused the tremendous impact and destruction on water resources, natural ecological environment, agricultural production, as well as the social and economic development. Therefore, the drought monitoring and evaluation are necessary to make emergency measures, thereby to reduce the loss triggered by the drought. However, the drought behaves an obviously temporal and spatial characteristics, one of which the terrestrial water storage has been lower than the historical average. Note that the terrestrial water storage is the sum of surface water, biowater, soil moisture, groundwater, and snow/ice. Fortunately, the Gravity Recovery and Climate Experiment mission (GRACE) satellite can provide a long-term and effective method to in-situ monitor the changes in terrestrial water storage. A continuous, rapid, and repetitive observation can be conducted in the GRACE gravity satellite, without being restricted by ground conditions. The global data with uniform distribution and observation scale can be obtained, to effectively solve the problems related to the depth of ground observation, insufficient data acquisition, uneven distribution of spatial and hydrological models. In this study, a dimensionless standardized Water Storage Deficit Index (WSDI) based on GRACE data was proposed to monitor drought in the Pearl River Basin from April 2002 to June 2017. A systematic evaluation was made to explore the capability of WSDI for the spatiotemporal variation of drought, and thereby to identify the drought events, compared with the common drought indexes, including the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Runoff Index (SRI), and Self-Calibrating Palmer Drought Severity Index (scPDSI). The WSDI was calculated by the GSM data from the GRACE Level-2 RL06 published by CSR (Center for Space Research) and JPL (Jet Propulsion Laboratory). The SPEI and SPI were calculated by the meteorological data collected from 183 meteorological stations in the Pearl River Basin, and then interpolated with the Kriging method. The SRI and scPDSI were calculated by the output data from the Variable Infiltration Capacity (VIC) land surface hydrological model. The drought events were analyzed during 2002 to 2015 which monitored by the WSDI and common drought indexes, compared with the drought centroid trajectories of drought events. The results showed that: 1) In the 7 drought events monitored by the WSDI during 2002 to 2017, the drought events from 2003 to 2006 were the worst with the longest drought duration, the highest drought intensity, and the greatest drought severity. Evaluation of drought in the Pearl River Basin showed that the drought situation monitored by the WSDI was basically consistent with the actual drought situation recorded by the Pearl River Water Resource Commission of the Ministry of Water Resources. It verified that the GRACE data can be used to capture the occurrence, development, and disappearance of drought events, together with the drought characteristics; 2) The time variation of WSDI and its response to climate anomalies were in good agreement with the SPI-6, SPI-12, SPEI-6, SPEI-12, SRI-3, SRI-6, SRI-12, and scPDSI, indicating the similar peaks and troughs. It infers that there was a strong correlation with the WSDI. Specifically, the WSDI had the highest Pearson correlation coefficient with the scPDSI (0.803, P<0.05), which can comprehensively describe drought, whereas, a low Pearson correlation coefficients with the SPI-3 and SPEI-3, which have obviously seasonal characteristics to reflect the condition of short- and medium-term moisture. The WSDI can better reveal comprehensive water changes in the mid-and-long term for the study area, and thereby it can be used to monitor drought events caused by the water deficit in all layers of land; 3) The centroid trajectories of drought events recorded by the WSDI was basically consistent with those recorded by the SPI-12, SPEI-12, SRI-12, scPDSI, where the drought centroid of large-scale drought events appeared a movement from eastern to western regions. This result demonstrated that the WSDI can be used to reasonably represent the spatiotemporal changes of drought. Therefore, the WSDI has obvious advantages and application potentials suitable for monitoring and evaluation of large-scale hydrological drought. The finding can provide valuable information and a new data source in the large-scale monitoring and assessment for hydrological drought.