基于多源数据的农业干旱监测模型构建

在全球气候变暖的大背景下,干旱事件发生越来越频繁,严重危害我国的粮食生产安全。构建准确的干旱监测模型不仅能够及时地反映出干旱事件的发生,同时可以为地方政府制定减灾保产措施提供科学支撑和保障。传统的气象干旱监测方法因为缺乏对植被本身需水状态和土壤供水信息的考虑旱情判定结果往往比实际情况偏重,而遥感监测指标大多只考虑了植被或土壤等单方面因素具有局限性,目前已有的综合干旱监测模型大多以气象指标为因变量,一方面需要数据资料较多参数复杂,另一方面模型准确度依赖于气象指标对当地农业干旱的响应能力,而同一气象指标在不同区域适应性存在差异,因此同样存在局限性。本文以河南省的冬小麦为研究对象,利用2001-2011年的EOS-MODIS数据产品以及气象站点监测数据,计算了标准化降水蒸散指数SPEI、植被状态指数VCI、温度状态指数TCI、温度植被状态指数TVDI,同时结合河南省农业气象灾害旬报对冬小麦受灾的记录,构建了基于决策树的定性农业干旱监测模型。测试集结果表明,模型综合了大气异常信息、植被状态信息以及土壤水分信息,优于单个指标的监测结果。另外,基于此模型监测了河南省2009年4-5月的干旱事件,结果与实情相符,能够较好地反映农业旱情的发生和空间演变情况。     

Hydrological Processes in the Huaihe River Basin,China: Seasonal Variations,Causes and Implications

Understanding streamflow changes in terms of trends and periodicities and relevant causes is the first step into scientific management of water resources in a changing environment. In this study, monthly streamflow variations were analyzed using Modified Mann-Kendall(MM-K) trend test and Continuous Wavelet Transform(CWT) methods at 9 hydrological stations in the Huaihe River Basin. It was found that: 1) streamflow mainly occurs during May to September, accounting for 70.4% of the annual total streamflowamount with Cv values between 0.16–0.85 and extremum ratio values between 1.70–23.90; 2) decreased streamflow can be observed in the Huaihe River Basin and significant decreased streamflow can be detected during April and May, which should be the results of precipitation change and increased irrigation demand; 3) significant periods of 2–4 yr were detected during the 1960 s, the 1980 s and the 2000 s. Different periods were found at stations concentrated within certain regions implying periods of streamflow were caused by different influencing factors for specific regions; 4) Pacific Decadal Oscillation(PDO) has the most significant impacts on monthly streamflow mainly during June. Besides, Southern Oscillation Index(SOI), North Atlantic Oscillation(NAO) and the Ni?o3.4 Sea Surface Temperature(Ni?o3.4) have impacts on monthly streamflow with three months lags, and was less significant in time lag of six months. Identification of critical climatic factors having impacts on streamflow changes can help to predict monthly streamflow changes using climatic factors as explanatory variables. These findings were well corroborated by results concerning impacts of El Nino-Southern Oscillation(ENSO) regimes on precipitation events across the Huaihe River Basin. The results of this study can provide theoretical background for basin-scale management of water resources and agricultural irrigation.     

基于植被状态指数的云南省农业干旱状况时空分析

本文首先计算了云南省2004-2013年农业干旱指数VCI,然后使用Pearson相关系数评价降水与VCI的相关性,基于VCI识别云南省2004-2013年农业干旱事件,最后,与SPEI气象干旱识别结果进行对比分析,在VCI农业干旱识别的基础上,使用干旱频率和干旱面积占比指标分析了云南省2004-2013年农业干旱时空特征。结果表明：降水只是影响VCI指数的关键因素之一;VCI和SPEI指数均能够较好对干旱进行监测并识别典型干旱,但两者的识别结果存在差异;云南省农业干旱频率在春冬两季较高,夏季较低,秋季介于夏季和春冬季之间;春夏冬三季农业干旱频率空间分布较为均匀,秋季农业干旱频率呈南低北高的分布态势,整体上北部干旱频率高于南部;2004-2013年云南省整体干旱面积占比呈现先减小后增加再波动的趋势,春冬两季整体干旱面积占比最高,分别为46.63%和47.18%,呈现下降趋势,夏季整体干旱面积占比最低,为43.81%,呈现上升趋势,秋季整体干旱面积占比介于冬春季和夏季之间,为45.74%,呈现下降趋势。总之,云南省农业干旱春冬易发性最高,影响范围最大,夏季易发性最低,影响范围最小。     

Daily SPEI Reveals Long-term Change in Drought Characteristics in Southwest China

Drought is the most widespread and insidious natural hazard, presenting serious challenges to ecosystems and human society. The daily Standardized Precipitation Evapotranspiration Index (SPEI) has been developed to identify the regional spatiotemporal characteristics of drought conditions from 1960 to 2016, revealing the variability in drought characteristics across Southwest China. Daily data from142 meteorological stations across the region were used to calculate the daily SPEI at the annual and seasonal time scale. The Mann-Kendall test and the trend statistics were then applied to quantify the significance of drought trends, with the following results. 1) The regionally averaged intensity and duration of all-drought and severe drought showed increasing trends, while the intensity and duration of extreme drought exhibited decreasing trends. 2) Mixed (increasing/decreasing) trends were detected, in terms of intensity and duration, in the three types of drought events. In general, no evidence of significant trends (P < 0.05) was detected in the drought intensity and duration over the last 55 years at the annual timescale. Seasonally, spring was characterized by a severe drought trend for all drought and severe drought conditions, while extreme drought events in spring and summer were very severe. All drought intensities and durations showed an increasing trend across most regions, except in the northwestern parts of Sichuan Province. However, the areal extent of regions suffering increasing trends in severe and extreme drought became relatively smaller. 3) We identified the following drought hotspots: Guangxi Zhuang Autonomous Region from the 1960s to the 1990s, respectively. Guangxi Zhuang Autonomous Region and Guizhou Province in the 1970s and 1980s, and Yunnan Province in the 2000s. Finally, this paper can benefit operational drought characterization with a day-to-day drought monitoring index, enabling a more risk-based drought management strategy in the context of global warming.     

基于随机森林的遥感干旱监测模型的构建

利用遥感数据进行大面积旱情监测是现有干旱监测的重要方法之一,然而传统的遥感干旱监测方法主要侧重于对土壤湿度或植被状况等单一干旱响应因子进行监测,对综合多因子的干旱监测研究较为有限。随机森林是一种机器学习方法,具有学习过程快速、运算速度快、稳定性好、预测精度高的优点,近年来被应用于生态环境等多个领域。本文利用2001-2010年4-9月的MODIS数据提取的植被状态指数（VCI）、温度状态指数（TCI）和土地覆盖类型（LC）,TRMM降水资料计算的TRMM-Z指数及SRTM-DEM、土壤有效含水量（AWC）等多个遥感及土壤资料提取的干旱因子为自变量,以气象站点的综合气象干旱指数（CI）为因变量,利用随机森林模型构建遥感干旱监测模型,并以河南省为研究区进行了评价和分析。该模型在2009-2010年的监测值和实测CI值的具有显著的相关性,并且二者干旱等级的一致率为81%。在2001-2010年4-9月间,模型监测值与气象站点的标准降水蒸散发指数（SPEI）总体干旱等级一致率为74.9%,较为一致,其中9月的模型结果与SPEI的干旱等级一致率最高,达到82.4%,空评估率和漏评估率最低;与10 cm土壤相对湿度的相关系数在0.475-0.639之间,达到极显著水平。河南省2011年4-6月干旱事件同样验证了本文构建的模型旱情监测结果,说明本模型能较好地就应用于监测区域旱情监测。     

随机森林算法在全球干旱评估中的应用

干旱是发生频率最高,造成社会、经济损失和生态破坏最严重、最广泛的自然灾害之一,因此对干旱进行可靠、有效的评估十分重要。本文以月平均降水、月平均温度、月最高温度、月最低温度、土壤湿度、蒸散发、NDVI、叶绿素荧光等作为解释变量,以基于SPI的干旱等级作为目标变量,采用随机森林算法,以2007—2012年的数据作为训练数据,以2013—2014年的数据作为预测数据,对全球11个气候区分别建立干旱等级评估模型。研究结论如下：SPI的时间尺度影响模型精度,在基于SPI1、SPI3、SPI6和SPI12划分的干旱等级的评估模型中,以基于SPI1的干旱等级为目标变量的模型的预测精度（60%~75%）较高,且模型能够捕捉到EM-DAT旱灾记录次数的90.91%、月份的78.47%,表明该模型对实际干旱事件具有良好的评估性能;干旱等级划分标准对模型的预测性能影响较小,可根据需求选择标准I（干旱/非干旱）或标准Ⅱ（重旱/非重旱）进行干旱评估;解释变量的相对重要性与SPI的时间尺度和气候差异等因素有关。降水对基于SPI1的干旱等级的重要性最大,随着SPI时间尺度的增加,降水的重要性逐渐减小,温度、土壤湿度、NDVI和ET的重要性逐渐增大。降水以外的其他变量在不同气候区的重要性不同。在热带气候区、亚寒带气候区和苔原气候区,温度或蒸散发的影响较大;在干燥气候区,土壤湿度的影响较大;在温带气候区,仍以降水的相对重要性最大;在湿润大陆性气候区,植被对干旱的影响较大。     

长江流域陆地水储量异常的卫星重力监测与干旱指数对比分析北大核心CSCD

利用GRACE/GRACE-FO数据对长江流域2003~2021年期间发生的干旱事件进行定量分析,以探究卫星重力监测区域性干旱的可行性。采用3个机构发布的5种GRACE/GRACE-FO数据产品(CSR_SH、JPL_SH、GFZ_SH、CSR_M、JPL_M)反演长江流域陆地水储量异常(TWSA),计算陆地水储量亏损(WSD)和水储量亏损指数(WSDI),结合气象干旱数据(SPI、SPEI、scPDSI)对5种数据产品的结果进行比较,并对2003~2021年长江流域干旱事件进行分析。结果表明,不同机构发布的GRACE/GRACE-FO数据产品对长江流域干旱事件严重等级的划分具有一定差异;WSDI与6个月时间尺度的SPEI相关性最高,相关系数为0.66,与scPDSI相关系数最低为0.54,降水是影响长江流域陆地水储量变化的重要因素;长江流域最严重的干旱事件发生在2019年夏秋季,干旱强度为2.31,持续10个月,水储量累计亏损达到415 Gt,此次干旱事件的WSDI空间分布图显示2019-09干旱最为严重,出现极端干旱区域。WSDI可反映长江流域干旱分布的时空变化,可在监测全球和大尺度区域干旱方面发挥重要作用。     

遥感及再分析降水产品在缺资料干旱内陆盆地的适用性评估

山区降水较集中,但降水测站多位于山谷或人口密集区,代表性差。遥感和再分析降水产品能提供时空分布连续的数据,不受地形条件限制。柴达木盆地中心属干旱荒漠区,水是制约该区开发的首要条件,其四周属高寒山区,降水相对较多,但降水监测十分薄弱。为获取该区相对精确的降水时空分布信息,本文评估了4套高分辨率降水产品（CMADS、TRMM、GPM和MSWEP）的适用性。首先基于地面站点数据评估它们在不同时空尺度上的精度,并分析它们在柴达木盆地的空间分布和年内分配特征。然后,以盆地东南隅的无测站山区香日德河流域为研究区,利用降水产品驱动SWAT模型来评估它们的分布式水文模拟适用性。结果表明：① MSWEP在年、月尺度上与站点降水的吻合程度最高（R ≥ 0.79,PBIAS = 0.5%）,其次是GPM和TRMM,CMADS精度最低（R ≥ 0.64,PBIAS = 5.8%）;② 从降水精度与站点高程的关系来看,降水产品在相对低海拔区容易高估站点降水,而在相对高海拔区常低估实际降水;③ 在香日德河流域,MSWEP（NSE = 0.64）在基准期（2009—2012年）的径流模拟表现明显好于其它降水产品（NSE = 0.36~0.59）,变化期（2013—2016年）表现最好的是CMADS（NSE = 0.75,其余产品NSE = 0.53~0.68）。本研究可为缺资料干旱山区获取精确的降水时空信息和后续水资源的科学管理与规划提供重要支撑。     

Tree-ring reconstruction of streamflow for Palgong Mountain forested watershed in southeastern South Korea

Tree-ring chronologies from pine, oak and black locust tree species were used to reconstruct annual streamflow and examine hydrological drought years for Palgong Mountain forested watershed in southeastern South Korea for the period from 1954-2015. The backward elimination multiple regression analysis provided the statistically significant predictor chronologies of streamflow. The final calibration and verification test models accounted for 84.8% and 81.6%, respectively, of the variability in streamflow observed in the gage data. Further verification of the validity of the reconstructed model was undertaken with the Pearson Correlation Coefficient, the Reduction of Error Test, and the Durbin-Watson Statistics and indicated fidelity of the model for reconstructing the annual streamflow. Analyses of the reconstructed annual streamflow indicate that the most persistent years of high flows above the median annual discharge occurred from 1986-2008. This period included 7 single or multiple years of highest flow above the 90th percentile discharge and multiple years of high flows with a time interval of 2-6 years, although with intervening multiple years of low flows below the 10th and 50th percentile. In comparison, the most persistent years of low flows below the median annual discharge occurred from 1954-1985 and 2009-2015. This period included 8 single or multiple years of lowest flow below the 10th percentile discharge and multiple years of low flows with a time interval of 2-9 years, although also with intervening multiple years of high flows above the 50th percentile. No single years of extreme hydrological droughts below the 10th percentile were identified from 1986-2015 whereas a greater proportion of high flows above the 90th percentile occurred during this period. The persistent single or multiple years of lowest flows between 1954 and 1985 were the recent most critical hydrological drought years identified in the Palgong Mountain forested watershed providing supportive evidence of the severity of past hydrological droughts during that period, applicable to the southeastern South Korea where the study watershed is located. This interpretation agrees with the hydrological drought event years identified from 1951 to the early 1980s in a related national study that used precipitation proxy data to reconstruct past occurrences of droughts in Korea.     

北方农牧交错区干旱特征变化及其对植被总初级生产力的影响

北方农牧交错区地处半湿润/半干旱生态脆弱过渡带,干旱是影响该区植被生产力的关键因素之一。探究干旱对植被总初级生产力的影响,对深刻理解气候变化下生态系统生产力变化响应特征及优化区域碳水循环具有重要意义。为了更好地了解水分限制区不同干旱特征对GPP影响,本研究以北方农牧交错区为例,基于长时间序列的标准化降水蒸散发指数(SPEI3,1900—2020年)和植被总初级生产力(GPP,1982—2018年)等数据,首先采用小波分析明确SPEI3与GPP强相关周期,在此基础上利用游程理论识别干旱特征,进而分析了北方农牧交错区干旱特征与GPP的变化趋势,最后厘定了不同干旱特征对GPP的影响。结果表明:(1) 1982—2018年北方农牧交错区SPEI3与GPP在半年周期和年周期存在显著相关关系,滞后效应随时间变化而变化;年际分析能够减弱滞后效应对SPEI3与GPP相关性的影响;(2) 1900—2020年北方农牧交错区干旱历时、干旱烈度和烈度峰值均呈现显著增加趋势,干旱烈度随着干旱历时和烈度峰值的增加而加剧,干旱特征高值区往往具有更强的增加趋势;(3) 1982—2018年北方农牧交错区GPP总体呈...     

2011年洪湖和梁子湖受旱程度差异和成因分析

湿地是水陆交错的生态系统,往往受旱灾影响大,故此,对不同湖泊湿地受旱程度差异及其原因分析,可为减灾和湿地保护提供科学依据。本文利用2010年5月和2011年5月2个时相的HJ-1卫星CCD影像,提取洪湖和梁子湖2个时相的湿地水面积,结合统计资料和问卷调查数据,从湿地水面积及空间分布变化、湿地生态系统功能退化、湿地生态系统,对人类福祉影响3方面,分析了两湖湿地受旱程度的差异。并综合气象数据、统计资料和问卷调查数据,从气象因子、区域自然地理环境、湿地类型及特点、区域水文条件和湿地受保护程度5方面探讨两湖受旱程度差异的原因。结果表明：（1）2011年春旱期间,洪湖比梁子湖受旱程度更严重。旱灾时,洪湖水面积减少83.93 km2,减小比例为26%,梁子湖水面积减少13.02 km2,减小比例为4%;两湖的涵养水源、保护生物多样性、物质生产和水质净化功能均受到损害,洪湖较梁子湖更严重;受旱灾影响,洪湖湿地对人类福祉的消极影响大于梁子湖。（2）降雨量、气温和风速等气象因素、湖泊湿地成因类型、区域自然地理环境和水文条件是影响两湖受旱程度差异的主要因素,另外,湿地保护措施的差异及效果也会造成两湖受旱程度不同。     

Effects of drought on net primary productivity: Roles of temperature,drought intensity,and duration

Northeast China has experienced frequent droughts over the past fifteen years. However, the effects of droughts on net primary productivity (NPP) in Northeast China remain unclear. In this paper, the droughts that occurred in Northeast China between 1999 and 2013 were identified using the Standardized Precipitation Evapotranspiration Index (SPEI). The NPP standardized anomaly index (NPP-SAI) was used to evaluate NPP anomalies. The years of 1999, 2000, 2001, and 2007 were further investigated in order to explore the influence of droughts on NPP at different time scales (3, 6, and 12 months). Based on the NPP-SAI of normal areas, we found droughts overall decreased NPP by 112.06 Tg C between 1999 and 2013. Lower temperatures at the beginning of the growing season could cause declines in NPP by shortening the length of the growing season. Mild drought or short-term drought with higher temperatures might increase NPP, and weak intensity droughts intensified the lag effects of droughts on NPP.     

利用GRACE时变重力场数据监测长江流域干旱

利用2003-01~2014-12 CSR和JPL的RL06 Mascon解、RL06球谐系数（SH）解及level-3等6种GRACE时变重力场模型数据和GPM数据产品,分别计算长江流域的水储量和降雨变化,并利用广义三角帽方法分析GRACE数据的不确定性,同时计算水储量亏损指数（WSDI）,以监测和分析长江流域干旱的时空特征,并与改进的帕默尔指数（scPDSI）进行对比。结果表明：目前在反演水储量变化方面,Mascon方法的不确定性小于球谐系数法,JPL_M、CSR_M、CSR_L3、JPL_L3、CSR_SH和JPL_SH的具体不确定性分别为3.51 mm、3.78 mm、5.45 mm、9.87 mm、9.12 mm及10.71 mm;降雨是影响长江流域水储量变化的重要因素,两者的相关系数达0.67,同时两者都具有明显的季节性变化;水储量亏损指数探测到2003-01~2014-12长江流域共历经6次干旱事件,最长时间的干旱始于2003-02,持续24个月;最严重的干旱发生于2006年春季和2011年夏季,强度分别为2.15和1.97;平均水储量亏损指数的空间分布表明,2006-07~2007-06几乎整个长江流域都处于干旱状态,而2011-03~11干旱主要集中于长江流域下游、中游和上游东南地区。     

Drought Impacts on Vegetation Indices and Productivity of Terrestrial Ecosystems in Southwestern China During 2001–2012

Drought, as a recurring extreme climate event, affects the structure, function, and process of terrestrial ecosystems. Despite the increasing occurrence and intensity of the drought in the past decade in Southwestern China, the impacts of continuous drought events on vegetation in this region remain unclear. During 2001–2012, Southwestern China experienced the severe drought events from 2009 to 2011. Our aim is to characterize drought conditions in the Southwestern China and explore the impacts on the vegetation condition and terrestrial ecosystem productivity. The Standardized Precipitation Index(SPI) was used to characterize drought area and intensity and a light-use efficiency model was used to explore the effect of drought on the terrestrial ecosystem productivity with Moderate Resolution Imaging Spectrometer(MODIS) data. The SPI captured the major drought events in Southwestern China during the study period, indicated that the 12-year period of this study included both ‘normal' precipitation years and two severe drought events in 2009–2010 and 2011. Results showed that vegetation greenness(Normalized Difference Vegetation Index, NDVI and Enhanced Vegetation Index, EVI) both declined in 2009/2010 drought, but the 2011 drought resulted in less declines of vegetation greenness and productivity due to shorten drought duration and rising temperature. Meanwhile, it was about 5 months lapse between drought events and maximum declines in vegetation greenness for 2009/2010 drought events. In addition, forest, grassland and cropland revealed significant different ecosystem responses to drought. It indicated that grassland showed an early sensitivity to drought, while cropland was the most sensitive to water deficit and forest was more resilient to drought. This study suggests that it is necessary to detect the difference responses of ecosystem to drought in a regional area with satellite data and ecosystem model.     

MIKE BASIN支持下的流域水文建模与水资源管理分析——以西藏达孜县为例

基于ArcView GIS平台,利用流域水资源规划管理软件工具MIKE BASIN,以西藏达孜县为试验区,采用50×50m格网DEM数据,开展拉萨河流域内的地表水的产汇计算,并进行流域水资源合理配置研究。本文建立了流域供需水的空间分析网络,对各汇流区进行流域模拟分析,研究结果以直观的专题图表显示,为本区的流域水资源管理提供了可视化的研究框架。     

干旱遥感监测方法及其应用发展（可下载全文）

 干旱是世界上影响范围最广和造成社会经济损失最严重的一种自然灾害。本文从干旱遥感监测的不同角度出发,总结了目前干旱遥感监测的主要方法、应用状况及优缺点。主要包括针对裸土地表类型的热惯量法、微波法,针对植被覆盖地表类型的可见光、近红外、短波红外等波段反射率数据的归一化植被指数法、距平指数法、条件植被指数法、归一化差值水分指数、归一化干旱指数、植被供水指数等,以及热红外遥感数据的温度植被干旱指数、温度条件指数、作物缺水指数、水分亏缺指数等。最后,提出了加强干旱遥感监测技术研究的建议,同时指出将可见光和微波相结合的指数模型的研究是干旱遥感监测可能的发展方向。     

Drought and Spatiotemporal Variability of Forest Fires Across Mexico

Understanding the spatiotemporal links between drought and forest fire occurrence is crucial for improving decision-making in fire management under current and future climatic conditions. We quantified forest fire activity in Mexico using georeferenced fire records for the period of 2005–2015 and examined its spatial and temporal relationships with a multiscalar drought index, the Standardized Precipitation-Evapotranspiration Index(SPEI). A total of 47975 fire counts were recorded in the 11-year long study period, with the peak in fire frequency occurring in 2011. We identified four fire clusters, i.e., regions where there is a high density of fire records in Mexico using the Getis-Ord G spatial statistic. Then, we examined fire frequency data in the clustered regions and assessed how fire activity related to the SPEI for the entire study period and also for the year 2011. Associations between the SPEI and fire frequency varied across Mexico and fire-SPEI relationships also varied across the months of major fire occurrence and related SPEI temporal scales. In particular, in the two fire clusters located in northern Mexico(Chihuahua, northern Baja California), drier conditions over the previous 5 months triggered fire occurrence. In contrast, we did not observe a significant relationship between drought severity and fire frequency in the central Mexico cluster, which exhibited the highest fire frequency. We also found moderate fire-drought associations in the cluster situated in the tropical southern Chiapas where agriculture activities are the main causes of forest fire occurrence. These results are useful for improving our understanding of the spatiotemporal patterns of fire occurrence as related to drought severity in megadiverse countries hosting many forest types as Mexico.     

基于深度神经网络的蒙古国色楞格河流域水体信息提取

蒙古高原地处干旱半干旱地区,河流水系对该区域的资源环境格局及其生态环境影响重大。发源于蒙古国的色楞格河是蒙古高原最主要的水资源来源,准确掌握该流域的水体信息对东北亚地区生态环境问题及资源保护具有重要意义。本文以蒙古高原色楞格河流域为研究对象,基于谷歌地球引擎（Google Earth Engine,GEE）云平台,使用 Sentinel-2 多光谱卫星遥感影像,利用深度神经网络（Deep Neural Network, DNN）方法对色楞格河流域的水体信息进行提取,并与支持向量机方法进行对比;利用全球30 m SRTM数据生成水系分布矢量图,通过空间分析形成河流提取目标区,结合深度神经网络分类结果,绘制蒙古国色楞格河流域2019年河流分布图。研究结果表明：① 该方法能够准确地完成大流域范围内的水体制图,提取结果能够体现色楞格河流域河流的空间分布,且能够减少河流断流、空洞现象;② 深度神经网络模型中批量大小设置为8时,在处理数据速度与精度中达到最优,而神经网络结构中隐含层数达到4层时,在精度评价指标测试数据集上达到0.9666,保证了模型特征挖掘能力;③ 经样本点的验证,结果总体精度达到97.65%,可以满足实际应用需求。本研究预期可以为蒙古高原的水体提取提供方法支持和相关数据支持。     

基于GRACE重力卫星数据监测分析贵州干旱特征

基于GRACE重力卫星数据,采用改进的组合高斯滤波法和尺度因子法提高数据精度,利用陆地水储量变化原理反演贵州2003-08~2013-07的水储量变化量,并将计算的相对水储量指数作为干旱指标,提出运用游程理论基于相对水储量指数识别干旱历时和干旱烈度,监测分析贵州干旱特征。结果表明,基于GRACE卫星数据获得的相对水储量指数与SPI3变化趋势基本一致;GRACE卫星监测到2003-08~2013-07贵州每年都有干旱事件发生,历时最短为1个月,其中历时≥3个月的干旱事件共9次;干旱强度较大的事件发生在2003~2006年和2009~2011年,其中2006年和2011年水储量亏损较严重,与贵州实际的干旱情况相吻合。     

利用GRACE/GRACE-FO重力卫星探测黄河流域水储量能力及极端气候发生的可能性

基于2004~2021年GRACE/GRACE-FO重力卫星数据反演黄河流域陆地水储量时空变化,并构建干旱指数模型和洪水因子模型,对黄河流域的极端气候现象进行分析研究。结果表明,2004~2021年黄河流域的陆地水储量以0.56 cm/a的速度减少,具有明显的季节周期性特征,在夏季和秋季呈盈余状态,春季和冬季呈亏损状态;干旱指数模型监测到期间黄河流域发生极度干旱事件22次、重度干旱事件37次,干旱事件范围涵盖整个黄河流域;洪水因子模型探测到黄河流域共发生洪水事件118次,多出现在夏季和秋季雨水较为丰沛的时候,期间黄河流域陆地水储量能力较弱,降雨量增大。利用GRACE/GRACE-FO重力卫星数据构建的干旱指数模型和洪水因子模型探测的气象结果与实际观测结果较为符合,能真实反映黄河流域发生的极端气候,可为极端气候研究提供有利工具。