Assessing the Performance of CMIP6 Models in Simulating Droughts across Global Drylands

Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.

Monitoring vegetation drought in the nine major river basins of China based on a new developed Vegetation Drought Condition Index

The effect of global climate change on vegetation growth is variable.Timely and effective monitoring of vegetation drought is crucial for understanding its dynamics and mitigation,and even regional protection of ecological environments.In this study,we constructed a new drought index(i.e.,Vegetation Drought Condition Index(VDCI))based on precipitation,potential evapotranspiration,soil moisture and Normalized Difference Vegetation Index(NDVI)data,to monitor vegetation drought in the nine major river basins(including the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin,Yangtze River Basin,Southeast River Basin,Pearl River Basin,Southwest River Basin and Continental River Basin)in China at 1-month–12-month(T1–T12)time scales.We used the Pearson's correlation coefficients to assess the relationships between the drought indices(the developed VDCI and traditional drought indices including the Standardized Precipitation Evapotranspiration Index(SPEI),Standardized Soil Moisture Index(SSMI)and Self-calibrating Palmer Drought Severity Index(scPDSI))and the NDVI at T1–T12 time scales,and to estimate and compare the lag times of vegetation response to drought among different drought indices.The results showed that precipitation and potential evapotranspiration have positive and major influences on vegetation in the nine major river basins at T1–T6 time scales.Soil moisture shows a lower degree of negative influence on vegetation in different river basins at multiple time scales.Potential evapotranspiration shows a higher degree of positive influence on vegetation,and it acts as the primary influencing factor with higher area proportion at multiple time scales in different river basins.The VDCI has a stronger relationship with the NDVI in the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin and Yangtze River Basin at T1–T4 time scales.In general,the VDCI is more sensitive(with shorter lag time of vegetation response to drought)than the traditional drought indices(SPEI,scPDSI and SSMI)in monitoring vegetation drought,and thus it could be applied to monitor short-term vegetation drought.The VDCI developed in the study can reveal the law of unclear mechanisms between vegetation and climate,and can be applied in other fields of vegetation drought monitoring with complex mechanisms.

Formation of Assimilating Surface Areas and Photosynthetic Potential of Various Assimilating Parts of Wheat Species under Drought Conditions

Some of environmental factors (weather sharp fluctuations) may accrue stress within a few minutes, while others may not be long for this period of stress in this situation. It has formed stress in organisms, to eliminate the stress, there starts over various biochemical and physiological mechanisms for protection. Therefore, a large variety of plants to examine ways of increasing the resistance against stress factors have a scientific and practical importance. Thus, the primary processes of photosynthesis, based on the results of the study and its corresponding morphophysiological higher photochemical activity, has been found in a range of genotypes. Their leaves and plants assimilate the biological productivity of the intensity of the symptoms associated with the use of photosynthetic learned of the opportunity to create a new perspective varieties. This allows the research to prove the expansion of the electronic delivery of high-yielding genotypes and phosphorised chloroplast high speed, as well as the pH of thylacoid membranes are characterized by a great price, also photosynthetic electron transport, CO2 assimilation and it was approved to be the link between productivity.

Propagation characteristics from meteorological drought to agricultural drought over the Heihe River Basin, Northwest China

In the context of global warming,drought events occur frequently.In order to better understanding the process and mechanism of drought occurrence and evolution,scholars have dedicated much attention on drought propagation,mainly focusing on drought propagation time and propagation probability.However,there are relatively few studies on the sensitivities of drought propagation to seasons and drought levels.Therefore,we took the Heihe River Basin(HRB)of Northwest China as the case study area to quantify the propagation time and propagation probability from meteorological drought to agricultural drought during the period of 1981–2020,and subsequently explore their sensitivities to seasons(irrigation and non-irrigation seasons)and drought levels.The correlation coefficient method and Copula-based interval conditional probability model were employed to determine the drought propagation time and propagation probability.The results determined the average drought propagation time as 8 months in the whole basin,which was reduced by 2 months(i.e.,6 months)on average during the irrigation season and prolonged by 2 months(i.e.,10 months)during the non-irrigation season.Propagation probability was sensitive to both seasons and drought levels,and the sensitivities had noticeable spatial differences in the whole basin.The propagation probability of agricultural drought at different levels generally increased with the meteorological drought levels for the upstream,midstream,and southern downstream regions of the HRB.Lesser agricultural droughts were more likely to be triggered during the irrigation season,while severer agricultural droughts were occurred mostly during the non-irrigation season.The research results are helpful to understand the characteristics of drought propagation and provide a scientific basis for the prevention and control of droughts.This study is of great significance for the rational planning of local water resources and maintaining good ecological environment in the HRB.

基于产量相关性状的大麦种质干旱适应性分析

于2019—2021年,通过测定62份大麦(Hordeum vulgare L.)种质在不同灌水条件下的产量相关性状数据,分析了大麦7个产量相关性状与灌水的相关性。结果表明,z1450066w的生育期较短,正常灌水条件下为82.67 d,干旱胁迫下为65.33 d;TRADI70w的穗长较长,正常灌水条件下为7.82 cm,干旱胁迫下为8.11 cm;ZDM5458的产量较高,正常灌水条件下为397.93 g·m^(-2),干旱胁迫下为309.52 g·m^(-2),且3个试验年份均呈增产趋势。依据62份种质在干旱胁迫下产量相关性状适应能力的不同,将其分为5类,I类的有效分蘖、千粒重性状表现较好,II类和III类分别在穗长和株高性状上表现较好,IV类穗粒数、产量性状表现较好,V类的生育期性状表现较好。与正常灌水相比,干旱胁迫下大麦生育期、株高、穗长、有效分蘖、穗粒数和产量分别降低14.25%、11.37%、1.64%、5.68%、7.61%和27.98%。正常灌水下,穗长与株高、千粒重均呈极显著正相关关系,有效分蘖与穗长、生育期和穗粒数分别呈极显著负相关、极显著正相关和显著负相关关系,千粒重、株高与产量均呈极显著正相关关系;干旱胁迫下,穗长与穗粒数、千粒重和产量分别呈显著负相关、极显著负相关和极显著正相关关系,有效分蘖与株高、千粒重分别呈极显著负相关和极显著正相关关系,生育期与千粒重呈极显著正相关关系。同时,筛选出4份抗旱的大麦种质(ZDM5458,GERTROV,ZDM5430,G0401018K-1),其中干旱胁迫下ZDM5458产量较高,GERTROV和ZDM5430穗粒数较多,G0401018K-1有效分蘖较多。

基于植被状态指数的中国干旱演变特征及遥相关驱动研究

干旱会引发植被绿度下降、农作物减产、生物栖息地破坏等诸多问题,对人类和自然环境均具有显著影响。以植被状态指数作为干旱指标,利用极点对称模态分解EPSMD方法对1999~2019年全国植被状态指数序列进行周期与趋势识别,采用网格化趋势检验法揭示网格化的干旱趋势特征,运用多变量小波相干方法探讨干旱与多种遥相关因素的内在关系。结果表明,1999~2019年基于植被状态指数的全国干旱大体呈减轻趋势,植被状态指数的线性倾向率为0.044/10a;不同分区的干旱变化特征各不相同,其中黄土高原区的干旱减轻趋势最为明显,植被状态指数线性倾向率为0.215/10a;网格尺度的植被状态指数趋势特征Z均值在春季、夏季、秋季、冬季分别为0.41、0.79、0.50、0.11,各季度旱情均呈减轻态势;遥相关因素组合PNA-ENSO对全国干旱的影响最为明显。未来可将PNA、ENSO作为干旱预警输入因子提高干旱预报精度。

2003–2022年黄河流域TCI、VCI、VHI、TVDI逐年1 km分辨率数据集

黄河流域大部分属于干旱、半干旱气候,先天水资源条件不足,是中国各大流域中受干旱影响最为严重的流域。随着全球环境和气候变化,黄河流域的干旱愈加频繁,对黄河流域的干旱监测研究已经成为当下的热点。本数据集基于MODIS植被和地表温度产品,通过对逐年数据进行去云、重构等质量控制,分别生产了2003–2022年黄河流域逐年的温度条件指数(Temperature Condition Index,TCI)、植被状态指数(Vegetation Condition Index,VCI)、植被健康指数(Vegetation Health Index,VHI)、温度植被干旱指数(Temperature Vegetation Dryness Index,TVDI)数据集。本数据集空间范围为32°10′N–41°50′N,95°53′E–119°05′E,数据格式为Geo Tiff,空间分辨率为1 km。同其他干旱指数数据集相比,本产品可以在逐年时间尺度上表现黄河流域的干旱格局,在时间序列上反映黄河流域干旱变化趋势,为黄河流域干旱灾害监测提供基础数据支撑。

Coping with drought?Effects of extended drought conditions on soil invertebrate prey and diet selection by a fossorial amphisbaenian reptile

Arid climates are characterized by a summer drought period to which animals seem adapted.However,in some years,the drought can extend for unusually longer periods.Examining the effects of these current extreme weather events on biodiversity can help to understand the effects of climate change,as models predict an increase in drought severity.Here,we examined the effects of“unusual”extended drought on soil invertebrate prey availability and on diet composition(based on fecal contents)and diet selection of a fossorial amphisbaenian,the checkerboard worm lizard Trogonophis wiegmanni.Weather data show interannual variations in summer drought duration.The abundance and diversity of soil invertebrates in spring were high,and similar to those found in a“normal”early autumn,after some rain had ended with the summer drought.In contrast,in years with“unusual”extended drought,abundance,and diversity of soil invertebrates in early autumn were very low.Also,there were seasonal changes in amphisbaenians’diet;in autumn with drought,prey diversity,and niche breadth decreased with respect to spring and autumns after some rain had fallen.Amphisbaenians did not eat prey at random in any season,but made some changes in prey selection that may result from drought-related restrictions in prey availability.Finally,in spite that amphisbaenians showed some feeding flexibility,their body condition was lower in autumn than in spring,and much lower in autumn with drought.If extended drought became the norm in the future,amphisbaenians might suffer important negative effects for their health state.

Detecting Agro-Droughts in Southwest of China Using MODIS Satellite Data

The normalized difference vegetation index （NDVI） has proven to be typically employed to assess terrestrial vegetation conditions. However, one limitation of NDVI for drought monitoring is the apparent time lag between rainfall deficit and NDVI response. To better understand this relationship, time series NDVI （2000-2010） during the growing season in Sichuan Province and Chongqing City were analyzed. The vegetation condition index （VCI） was used to construct a new drought index, time-integrated vegetation condition index （TIVCI）, and was then compared with meteorological drought indices-standardized precipitation index （SPI）, a multiple-time scale meteorological-drought index based on precipitation, to examine the sensitivity on droughts. Our research findings indicate the followings： （1） farmland NDVI sensitivity to precipitation in study area has a time lag of 16-24 d, and it maximally responds to the temperature with a lag of about 16 d. （2） We applied the approach to Sichuan Province and Chongqing City for extreme drought monitoring in 2006 and 2003, and the results show that the monitoring results from TIVCI are closer to the published China agricultural statistical data than VCI. Compared to VCI, the best results from TIVCI3 were found with the relative errors of -4.5 and 6.36% in 2006 for drought affected area and drought disaster area respectively, and 5.11 and -5.95% in 2003. （3） Compared to VCI, TIVCI has better correlation with the SPI, which indicates the lag and cumulative effects of precipitation on vegetation. Our finding proved that TIVCI is an effective indicator of drought detection when the time lag effects between NDVI and climate factors are taken into consideration.

Analysis of the forest fires in the Antalya region of Turkey using the Keetch–Byram drought index

We investigated the correlation of large fires（[300 ha） from 1992 to 2013 within the borders of the Antalya Regional Directorate of Forestry using the Keetch–Byram drought index（KBDI）. Daily KBDI values were calculated for each year, and values for the period before the year 2000 differed significantly from those after2000. After 2000（large fires occurred in 2004, 2006, 2007,2008, 2010, and 2013）, when KBDI values increased, the KBDI, but not the number of fires, was inversely correlated with the natural log of the burned area（NLBA）. While there were both high and low KBDI values when the NLBA was small, only high KBDI values were associated with high NLBA values. Particularly for logarithmic values of 4 and higher, KBDI values increased in parallel with increases in NLBA values. On the basis of a Mann–Whitney U test done in addition to a Pearson correlation test, we found that when the burned areas were grouped according to small and large areas, the KBDI could be used to distinguish the two groups. Using a conditional probability analysis, we found that 4th, 5th and 6th class KBDI values may lead to large fires at the 60 % possibility.Similarly, the possibility of large fires greater than the median burned area in any given 6 years was found to be48 %. In addition, while the mean value of KBDI is 390.51 for the period from May to September for these 6 years, it is 359.93 for the other years. Consequently, the area burned also increased as the KBDI classes（Class 0： 0–99, Class 1：100–199, Class 2： 200–299, Class 3： 300–399, Class 4：400–499, Class 5： 500–599, Class 6： 600–699, and Class 7：700–800） increase.

APPLICATION OF VEGETATION INDEX OF METEOROLOGICAL SATELLITE IN DROUGHT ANALYSIS OF NINGXIA

There are five channels in NOAA-N series meteorological satellites. The channel No.1 is exactly located in the absorbtion band of vegetation, the channel No. 2 in the strong re-flection one. Therefore the two channels are suitable for monitoring and analysing vegeta-tion. To make certain mathematical value combination of two channels and specify its val-

Analysis of Drought in Poyang Lake

[Objective] The drought situation and causes in Poyang Lake were analyzed.[Method] In response to the drought in Poyang Lake in ten years ago and in recent 10 years,the causes of drought in Poyang Lake were discussed.[Result] Drought occurred frequently in Poyang Lake and the consecutive serious drought occurred now and then.The water level in Poyang Lake since 21st century was lower.The drought in Poyang Lake was due to reduction of precipitation,low water level in Yangtze River and 'five lakes',hydraulic project,industrial and agricultural water increase and other aspects.[Conclusion] The study provided theoretical basis for the formulation of drought prevention measures by relevant departments.

Modeling Spatio-temporal Drought Events Based on Multi-temporal,Multi-source Remote Sensing Data Calibrated by Soil Humidity

Inspired by recent significant agricultural yield losses in the eastern China and a missing operational monitoring system,we developed a comprehensive drought monitoring model to better understand the impact of individual key factors contributing to this issue.The resulting model,the‘Humidity calibrated Drought Condition Index’(HcDCI)was applied for the years 2001 to 2019 in form of a case study to Weihai County,Shandong Province in East China.Design and development are based on a linear combination of the Vegetation Condition Index(VCI),the Temperature Condition Index(TCI),and the Rainfall Condition Index(RCI)using multi-source satellite data to create a basic Drought Condition Index(DCI).VCI and TCI were derived from MODIS(Moderate Resolution Imaging Spectroradiometer)data,while precipitation is taken from CHIRPS(Climate Hazards Group InfraRed Precipitation with Station data)data.For reasons of accuracy,the decisive coefficients were determined by the relative humidity of soils at depth of 10-20 cm of particular areas collected by an agrometeorological ground station.The correlation between DCI and soil humidity was optimized with the factors of 0.53,0.33,and 0.14 for VCI,TCI,and RCI,respectively.The model revealed,light agricultural droughts from 2003 to 2013 and in 2018,while more severe droughts occurred in 2001 and 2002,2014-2017,and 2019.The droughts were most severe in January,March,and December,and our findings coincide with historical records.The average temperature during 2012-2019 is 1℃ higher than that during the period 2001-2011 and the average precipitation during 2014-2019 is 192.77 mm less than that during 2008-2013.The spatio-temporal accuracy of the HcDCI model was positively validated by correlation with agricultural crop yield quantities.The model thus,demonstrates its capability to reveal drought periods in detail,its transferability to other regions and its usefulness to take future measures.

关于构建“四预”措施和“四个链条”相结合的干旱灾害防御矩阵的思考

在充分借鉴洪水灾害防御“四个链条”基础上,考虑干旱及其灾害孕育、发生及发展规律和特点等,明晰干旱灾害“四个链条”,构建“四预”措施和“四个链条”相结合的干旱灾害防御矩阵迫在眉睫。提出要遵循“气象干旱—水文干旱—社会经济干旱”链式传导规律,加强雨情、水情、墒情、旱情的“四情”监测,精准“范围—对象—调度”,贯通“技术—料物—队伍—组织”的旱灾防御“四个链条”,实现滚动更新旱情预报、及时发布旱情预警信息、动态预演干旱灾害影响以及迭代更新抗旱预案。

2023年夏季气象条件对农业生产的影响

2023年夏季(6-8月),全国平均气温为22.1℃,较常年同期偏高0.8℃,为1981年以来历史同期第2高。全国平均降水量为311.3mm,较常年同期偏少3.3%,但空间分布差异大。全国平均日照时数为661.6h,较常年同期偏少1.7%。全国夏收夏种期间多晴好天气,夏收夏种进展总体顺利,仅河南、陕西出现持续阴雨天气,夏收受阻。夏季大部农区光温适宜、降水充沛,利于秋收作物形成丰产群体;但京津冀和东北等地强降水导致部分农田出现渍涝灾害,华北黄淮和新疆等地高温极端性强,北方和西南部分农区出现阶段性夏旱,导致部分秋收作物长势偏弱,产量下降。

基于VCI的内蒙古生长季干旱变化及对气候响应

为有效开展内蒙古干旱监测及抗旱减灾工作,基于2000—2021年5—9月逐月MODIS植被长势产品,计算植被状态指数(vegetation condition index,VCI),结合内蒙古118个气象站的生长季气温、降水数据,利用Sen趋势分析法、偏相关系数法等分析内蒙古生长季干旱时空变化及其与气象要素的关系.分析结果表明,研究期内内蒙古生长季的VCI整体呈上升趋势,主要上升区位于内蒙古的东南部农牧交错带和西部草原与荒漠过渡区,在人类的正向干扰下这些地区的植被抗旱能力明显提升.变异系数分析可知,春末夏初内蒙古东部地区的干旱风险相对较高,随着夏季到来,干旱高风险区向西移动至内蒙古中部地区,秋季干旱风险范围增大但强度相对减小.降水偏少是内蒙古干旱发生的决定性气象因素,而高温主要与草原干旱的发生密切相关.基于VCI的干旱分析可有效反映区域抗旱能力的提升,为干旱的精细化管理提供科学参考.

基于条件分布模型的干旱传递概率分析

气象干旱发展到一定程度可以传递为水文干旱。以潘家口水库流域1961—2010年逐月平均降水数据和潘家口水库的入库径流序列为基础数据,分别计算了1、3、6、12个月时间尺度的标准化降水指数(SPI)和标准化径流指数(SRI),以表征研究区域的气象干旱和水文干旱。基于条件分布模型,分析了不同时间尺度的气象干旱传递到未来的不同等级和不同的预测期(或滞后期)的水文干旱的概率。结果表明,当SPI时间尺度较短或预测期(滞后期)较短时,其对应的SRI水文干旱等级越倾向于维持与SPI相同的干旱等级;随着SPI时间尺度的增长或预测期(滞后期)延长,其对应的SRI水文干旱等级略低于气象干旱或恢复到正常状态。

基于水分利用效率的生态干旱敏感性评估

【目的】准确量化生态系统的干旱敏感性程度,为生态干旱早期预警和减少生态损失提供参考。【方法】以中国西北地区为例,基于生态缺水量构建标准化生态干旱指数(standardized ecological water deficit index,SEWDI),结合植被水分利用效率(water use efficiency,WUE)定义生态干旱敏感性;采用Copula方法探讨生态干旱加剧条件下WUE升高的概率,以此分析生态干旱的敏感性。【结果】塔里木盆地、昆仑山脉、吐鲁番盆地以及柴达木盆地、河西走廊等地植被生态缺水量较高,逐月均值最高达75 mm。在研究区大部分区域SEWDI与WUE相关性较强,其中显著正相关区域占全区的24.2%,主要分布于新疆大部、青海西部、陕西南部等地;显著负相关区域占全区的36.8%,主要分布于黄土高原等地;随着生态干旱的加剧,WUE对生态干旱的敏感性在不同地区并非单调增加。植被生长期内生态干旱的敏感性随着干旱胁迫程度加剧而升高,且草地的生态干旱敏感性高于林地和耕地。5-6月WUE升高概率上升的速率最快,轻旱-中旱、中旱-重旱、重旱-特旱3个干旱变化情况下,WUE升高概率的月平均速率分别为0.09,0.07和0.06。【结论】水分利用效率(WUE)可以很好地反映植被在生长期遭受干旱胁迫时的生态干旱敏感性,可用作表征生态干旱敏感性的因子。

2003-2021年黄河流域逐月1 km分辨率VCI和TCI干旱指数数据集

黄河流域地跨干旱、半干旱和半湿润气候带,其多年平均水资源总量为719.4亿立方米,占全国水资源总量的2.5%,是中国各大流域中受干旱影响最为严重的流域。随着全球气候变化,黄河流域的干旱变化成为研究的热点。本文基于MODIS植被指数产品(MYD13A2,V6)和地表温度辐射产品(MYD11A2,V6),采用Kogan在1995年提出的VCI和TCI指数计算方法,分别生产了黄河流域2003–2021年逐月1 km分辨率VCI和TCI干旱指数数据集。数据经过去云处理、填补缺值和滤除背景噪声等数据质量控制操作,以确保数据集能够满足研究人员使用。通过数据共享,期望为全球变化背景下黄河流域的干旱监测及研究提供重要数据支撑。

干旱条件下长江上游梯级水库群蓄水形势初探

2022年整个长江流域汛期遭遇了不同程度的持续高温旱情,给长江上游梯级水库群调蓄带来了严峻挑战。针对干旱条件下水库群蓄水问题,设计了期末水位、蓄满度及拦蓄水率等指标,选取三峡以上14级防洪控制性水库群为对象,分析了近10 a同期蓄水过程及蓄满度指标情况。在此基础上,提取历史典型干旱年份流域来水情势及地区组成,分析不同量级干旱典型年来水条件下水库群蓄水期蓄水态势及蓄水任务完成情况,重点分析了不同频率来水过程及组成下水库群蓄水任务破坏程度。当来水>80%频率来水条件时,本次分析的14个梯级水库群能完成9、10月份蓄水任务;但对于来水<90%频率来水条件时,梯级累积欠蓄水量达165.5亿m^(3)。研究揭示了类似2022年来水水平下三峡以上梯级水库群蓄水态势,为流域水资源高效利用提供水情风险分析技术支撑。