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.

Annual growth of Fagus orientalis is limited by spring drought conditions in Iran’s Golestan Province

Due to the lack of a uniform and accurate defi-nition of‘drought’,several indicators have been introduced based on different variables and methods,and the efficiency of each of these is determined according to their relationship with drought.The relationship between two drought indices,SPI(standardized precipitation index)and SPEI(standard-ized precipitation-evapotranspiration index)in different sea-sons was investigated using annual rings of 15 tree samples to determine the effect of drought on the growth of oriental beech(Fagus orientalis Lipsky)in the Hyrcanian forests of northern Iran.The different evapotranspiration calcula-tion methods were evaluated on SPEI efficiency based on Hargreaves-Samani,Thornthwaite,and Penman-Monteith methods using the step-by-step M5 decision tree regression method.The results show that SPEI based on the Penman-Monteith in a three-month time scale(spring)had similar temporal changes and a better relationship with annual tree rings(R^(2)=0.81)at a 0.05 significant level.Abrupt change and a decreasing trend in the time series of annual tree rings are similar to the variation in the SPEI based on the Penman-Monteith method.Factors affecting evapotranspiration,temperature,wind speed,and sunshine hours(used in the Penman-Monteith method),increased but precipitation decreased.Using non-linear modeling methods,SPEI based on Penman-Monteith best illustrated climate changes affecting tree growth.

Index System and Influence of Drought in Northwest China

In this paper, the index systems of the agricultura drought and decrease percentage of grain crop are established. Th trend and influence of drought in the region is analyzed based o the 50 years (1951-2000) statistical data of precipitation and 5 years (1951–2002) agricultural drought of the region, includin five provinces: Shaanxi, Gansu, Ningxia, Qinghai and Xinjiang The result shows that the drought disaster is increasing and th most serious were in the 1970s and 1990s, and main agricultura drought is a great disaster incident. The regression prediction equa tion of drought and flood grades and agricultural drought area grades are set up by the harmonic wave method, and forecastin the drought will lighten during the first ten years of the 21s century.

Selection of Cowpea [(Vigna unguiculata (L.) WALP] Genotypes for Drought Tolerance Using Selection Indices

Cowpea [(Vigna unguiculata (L.)] is one of the most important arid legumes cultivated for pulse and forage production. However, in cowpea, not much is known about the base index selection method in breeding for drought tolerance. Consequently, the present study has been conducted to: 1) evaluate the yield performance of cowpea genotypes under artificial drought and well-watered condition;2) develop a base index using multiple traits for ranking genotype performance. The experiment was a 25 × 2 factorial laid out in a Randomized Complete Block Design (RCBD) with three replications. The experiment was carried out in the screen house at the Department of Horticulture at KNUST. The result showed that KPR1-96-73, Simbo, CZ06-4-16, Wilibaly and Agyenkwa were high yielding in well-water condition while Ghana Shoba, Sangaraka, NKetewade, Ghana-Shoni and Korobalen were high yielding genotypes in water stress condition. The average yield reduction was 60.6% for grain respectively. The biplot displays revealed four groups among the genotypes tested which was based on their yielding capacity and drought tolerance. In cluster B high yielding and drought tolerant genotypes were identified, high yielding and drought susceptible have been identified in cluster A, low yielding and drought tolerant in cluster D, and lastly low yielding and drought susceptible in cluster C. Genotypes in cluster B, were the best due to the fact that it combines high yield and tolerance to drought. They were Ghana Shoni, Nketewade, Sangaraka and Ghana shoba. These genotypes might be suitably employed in further drought tolerance breeding program of cowpea.

变暖环境下华北地区农业气象灾害风险评估Ⅰ:基于综合指标体系法农业干旱风险评估及适应对策建议

随着全球气候变化,干旱发生频率及强度持续增加,农业干旱灾害风险评估是当前防灾减灾的重要方法之一。基于自然灾害风险形成机理,构建华北农业干旱风险评估指标体系模型,利用内部检验法对模型进行稳健性检验,根据华北34个市农业干旱风险形成特点聚类分类,并提出相应的风险防范建议。结果表明:调整风险评估模型中的指标和方法时,华北地区34个市农业干旱风险排名变化幅度多为1~2.5位,模型稳健性较好;除防灾减灾能力较高的北京、天津外,华北中部和北部农业干旱风险最高,与危险性和脆弱性指标较高有关,河南北部以及山东南部农业干旱风险较低,主要得益于该地区各市危险性较低;华北34个市可分为6个农业干旱风险集群,集群分布在空间上无分散、跨市分布,城市聚集性较好,其中北部山区集群4干旱风险最高,与其极高的环境脆弱性和低防灾减灾能力有关,应在农业种植结构上适当降低农业种植面积并加大农业投入;位于中部和南部的集群2、5和6具有较高的粮食种植面积且粮食因干旱减产率较高,可通过增加农业投入、提高灌溉保证率等进一步降低农业干旱风险。

Tree mortality and biomass loss in drought-aff ected forests of East Texas,USA

Changes in tree mortality due to severe drought can alter forest structure,composition,dynamics,ecosystem services,carbon fl uxes,and energy interactions between the atmosphere and land surfaces.We utilized long-term(2000‒2017,3 full inventory cycles)Forest Inventory and Analysis(FIA)data to examine tree mortality and biomass loss in drought-aff ected forests for East Texas,USA.Plots that experienced six or more years of droughts during those censuses were selected based on 12-month moderate drought severity[Standardized Precipitation Evaporation Index(SPEI)-1.0].Plots that experienced other disturbances and inconsistent records were excluded from the analysis.In total,222 plots were retained from nearly 4000 plots.Generalized nonlinear mixed models(GNMMs)were used to examine the changes in tree mortality and recruitment rates for selected plots.The results showed that tree mortality rates and biomass loss to mortality increased overall,and across tree sizes,dominant genera,height classes,and ecoregions.An average mortality rate of 5.89%year−1 during the study period could be incited by water stress created by the regional prolonged and episodic drought events.The overall plot and species-group level recruitment rates decreased during the study period.Forest mortality showed mixed results regarding basal area and forest density using all plots together and when analyzed the plots by stand origin and ecoregion.Higher mortality rates of smaller trees were detected and were likely compounded by densitydependent factors.Comparative analysis of drought-induced tree mortality using hydro-meteorological data along with drought severity and length gradient is suggested to better understand the eff ects of drought on tree mortality and biomass loss around and beyond East Texas in the southeastern United States.

Meteorological drought in semi-arid regions:A case study of Iran

Drought occurs in almost all climate zones and is characterized by prolonged water deficiency due to unbalanced demand and supply of water,persistent insufficient precipitation,lack of moisture,and high evapotranspiration.Drought caused by insufficient precipitation is a temporary and recurring meteorological event.Precipitation in semi-arid regions is different from that in other regions,ranging from 50 to 750 mm.In general,the semi-arid regions in the west and north of Iran received more precipitation than those in the east and south.The Terrestrial Climate(TerraClimate)data,including monthly precipitation,minimum temperature,maximum temperature,potential evapotranspiration,and the Palmer Drought Severity Index(PDSI)developed by the University of Idaho,were used in this study.The PDSI data was directly obtained from the Google Earth Engine platform.The Standardized Precipitation Index(SPI)and the Standardized Precipitation Evapotranspiration Index(SPEI)on two different scales were calculated in time series and also both SPI and SPEI were shown in spatial distribution maps.The result showed that normal conditions were a common occurrence in the semi-arid regions of Iran over the majority of years from 2000 to 2020,according to a spatiotemporal study of the SPI at 3-month and 12-month time scales as well as the SPEI at 3-month and 12-month time scales.Moreover,the PDSI detected extreme dry years during 2000-2003 and in 2007,2014,and 2018.In many semi-arid regions of Iran,the SPI at 3-month time scale is higher than the SPEI at 3-month time scale in 2000,2008,2014,2015,and 2018.In general,this study concluded that the semi-arid regions underwent normal weather conditions from 2000 to 2020.In a way,moderate,severe,and extreme dry occurred with a lesser percentage,gradually decreasing.According to the PDSI,during 2000-2003 and 2007-2014,extreme dry struck practically all hot semi-arid regions of Iran.Several parts of the cold semi-arid regions,on the other hand,only experienced moderate to severe dry from 2000 to 2003,except for the eastern areas and wetter regions.The significance of this study is the determination of the spatiotemporal distribution of meteorological drought in semi-arid regions of Iran using strongly validated data from TerraClimate.

Comprehensive drought monitoring in Yunnan Province, China using multisource remote sensing data

Development of drought monitoring techniques is important for understanding and mitigating droughts and for rational agricultural management. This study used data from multiple sources, including MOD13 A3, TRMM 3 B43, and SRTMDEM, for Yunnan Province, China from 2009 to 2018 to calculate the tropical rainfall condition index(TRCI), vegetation condition index(VCI), temperature condition index(TCI), and elevation factors. Principal component analysis(PCA) and analytic hierarchy process(AHP) were used to construct comprehensive drought monitoring models for Yunnan Province. The reliability of the models was verified, following which the drought situation in Yunnan Province for the past ten years was analysed. The results showed that:(1) The comprehensive drought index(CDI) had a high correlation with the standardized precipitation index, standardized precipitation evapotranspiration index, temperature vegetation dryness index, and CLDAS(China Meteorological Administration land data assimilation system), indicating that the CDI was a strong indicator of drought through meteorological, remote sensing and soil moisture monitoring.(2) The droughts from 2009 to 2018 showed generally consistent spatiotemporal changes. Droughts occurred in most parts of the province, with an average drought frequency of 29% and four droughtprone centres.(3) Monthly drought coverage during 2009 to 2014 exceeded that over 2015 to 2018. January had the largest average drought coverage over the study period(61.92%). Droughts at most stations during the remaining months except for October exhibited a weakening trend(slope > 0). The CDI provides a novel approach for drought monitoring in areas with complex terrain such as Yunnan Province.

Comparative evaluation of impacts of climate change and droughts on river flow vulnerability in Iran

Rivers in arid and semi-arid regions are threatened by droughts and climate change.This study focused on a comparative evaluation of the impacts of climate change and droughts on the vulnerability of river flows in three basins with diverse climates in Iran.The standardized precipitation-evapotranspiration index(SPEI)and precipitation effectiveness variables(PEVs)extracted from the conjunctive precipitation effectiveness index(CPEI)were used to analyze the drought severity.To investigate hydrological droughts in the basins,the normalized difference water index(NDWI)and the streamflow drought index(SDI)were calculated and compared.The effects of droughts were assessed under various representative concentration pathway(RCP)scenarios.Changes in the number of wet days and precipitation depth restricted hydrological droughts,whereas an increasing number of dry days amplified their severity.The projected increases in dry days and precipitation over short durations throughout a year under future climate scenarios would produce changes in drought and flood periods and ultimately impact the frequency and severity of hydrological droughts.Under RCP 4.5,an increase in the frequencies of moderate and severe meteorological/hydrological droughts would further affect the Central Desert Basin.Under RCPs 2.6 and 8.5,the frequencies of severe and extreme droughts would increase,but the drought area would be smaller than that under RCP 4.5,demonstrating less severe drought conditions.Due to the shallow depths of most rivers,SDI was found to be more feasible than NDWI in detecting hydrological droughts.©2020 Hohai University.Production and hosting by Elsevier B.V.This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Assessment of drought and its impact on winter wheat yield in the Chinese Loess Plateau

Drought has pronounced and immediate impacts on agricultural production,especially in semi-arid and arid rainfed agricultural regions.Quantification of drought and its impact on crop yield is essential to agricultural water resource management and food security.We investigated drought and its impact on winter wheat(Triticum aestivum L.)yield in the Chinese Loess Plateau from 2001 to 2015.Specifically,we performed a varimax rotated principal component analysis on drought severity index(DSI)separately for four winter wheat growth periods:pre-sowing growth period(PG),early growth period(EG),middle growth period(MG),and late growth period(LG),resulting in three major subregional DSI dynamics for each growth period.The county-level projections of these major dynamics were then used to evaluate the growth period-specific impacts of DSI on winter wheat yields by using multiple linear regression analysis.Our results showed that the growth period-specific subregions had different major DSI dynamics.During PG,the northwestern area exhibited a rapid wetting trend,while small areas in the south showed a slight drying trend.The remaining subregions fluctuated between dryness and wetness.During EG,the northeastern and western areas exhibited a mild wetting trend.The remaining subregions did not display clear wetting or drying trends.During MG,the eastern and southwestern areas showed slight drying and wetting trends,respectively.The subregions scattered in the north and south had a significant wetting trend.During LG,large areas in the east and west exhibited wetting trends,whereas small parts in south-central area had a slight drying trend.Most counties in the north showed significant and slight wetting trends during PG,EG,and LG,whereas a few southwestern counties exhibited significant drying trends during PG and MG.Our analysis identified close and positive relationships between yields and DSI during LG,and revealed that almost all of the counties were vulnerable to drought.Similar but less strong relationships existed for MG,in which northeastern and eastern counties were more drought-vulnerable than other counties.In contrast,a few drought-sensitive counties were mainly located in the southwestern and eastern areas during PG,and in the northeastern corner of the study region during EG.Overall,our study dissociated growth period-specific and spatial location-specific impacts of drought on winter wheat yield,and might contribute to a better understanding of monitoring and early warning of yield loss.

区域抗旱能力评价研究进展

干旱灾害是中国最主要的自然灾害之一,对中国经济社会高质量发展带来了重大威胁。开展区域抗旱能力评价,对抵御干旱灾害风险开展抗旱减灾工作具有重要的意义。在阐述抗旱能力概念与内涵的基础上,回顾了目前区域抗旱能力评价的两类方法:基于构成要素多指标的综合评价法和基于水量供需关系的定量评价法;总结了现有评价方法存在的3个不足:即理论体系与指标选取问题、评价结果的不确定性问题、评价结果的适用性问题。指出未来研究应注重评价指标体系基础数据的准确性与合理性,加强智能评价方法研究,运用多学科方法开展动态评价。研究成果可为区域抗旱减灾研究提供支撑。

我国杨树抗旱性研究进展

本文综述了我国多年来杨树抗旱性的研究进展。目前我国已建立起了杨树抗旱研究的指标体系,研究了在不同胁迫强度下、不同时间段各项抗旱指标的变化规律,以及与抗旱性的相关关系。用主成分分析等方法筛选出了与抗旱性相关的抗旱指标,用隶属度等方法对树种的抗旱性进行综合评价。多年来,我国已通过抗旱指标的综合评价及转基因技术筛选出多个杨树无性系,其抗旱性研究主要集中在苗期,今后有必要进行成年杨树的抗旱性研究以及与苗期抗旱性的相关关系研究,通过分子生物学技术提高自身抗旱能力是适应干旱环境的根本。

粒子群优化极限学习机模型在河南省干旱预测中的应用

干旱预测是提高防旱抗旱能力的重要非工程措施。在评价不同时间尺度标准化降水蒸散指数(SSPEI)对河南省干旱识别能力的基础上,以能有效表征河南省干旱状况的SSPEI为模型输出,以基于信息变化率和条件互信息的特征变量选择方法(ICR-CMIFS)筛选得到的河南省主要致旱气候系统指数为模型输入,构建了基于粒子群算法优化极限学习机(PSO-ELM)的干旱预测模型,通过对比该模型与标准极限学习机(ELM)、差分进化算法优化极限学习机(DE-ELM)模型的干旱预测结果,验证PSO-ELM模型在河南省干旱预测中的适用性。结果表明,SSPEI-3能有效识别河南省典型干旱事件,从时间和空间上可较准确地反映河南省干旱状况;ICR-CMIFS筛选出的河南省主要致旱气候系统指数为西太平洋副高面积指数和NINO指数;PSO-ELM模型能较准确地预测河南省干旱,且预测精度优于DE-ELM模型和标准ELM模型,在河南省干旱预测中具有较好的适用性。

西北干旱灾害影响趋势分析

根据1951—2000年中国西北五省区(陕西、甘肃、宁夏、青海、新疆)降水资料,1951—1994年主要农作物旱灾面积和粮食减产资料,建立了干旱等级指标、农业旱灾指标、因旱粮食减产指标体系,分析了西北干旱灾害的影响趋势。结果表明:西北干旱和农业旱灾呈增加趋势,以20世纪70、90年代最严重,农业旱灾以重大旱灾事件为主,其空间变化以西北东部干旱灾害严重。采用谐波和功率谱方法分析西北干旱周期,建立了拟合预测回归模型,并对西北干旱灾害进行影响预测,表明21世纪前十年西北干旱灾害有减缓趋势。

中国农业干旱脆弱性分区研究

根据各地水资源的特点、农业受旱成灾的情况及水利设施抗旱能力,确定农业干旱脆弱性分区的原则和指标,构造层次分析模型。应用MapInfo6.0软件绘制了中国农业干旱脆弱性分区图,结果表明:在全国340个农业干旱脆弱性分区中,极严重脆弱区47个,严重脆弱区104个,一般脆弱区175个,轻度脆弱区14个。

玉米自交系抗旱性评价指标体系的建立

【目的】筛选玉米不同时期抗旱鉴定指标,建立玉米抗旱性评价体系。【方法】室内运用PEG(6000)胁迫处理,研究了种子吸水速率等7个指标与玉米抗旱性的关系;大棚内通过水分胁迫,研究了叶片相对含水量等24个指标与玉米抗旱性的关系。【结果】通过简单相关分析筛选出15%PEG溶液处理GDRI、相对发芽势,20%PEG溶液处理GDRI、相对发芽势及胁迫后苗期叶片水势、抽雄吐丝期叶片保水力、行粒数、单轴重、百粒重和对照相对值9个与抗旱系数或抗旱指数相关显著的指标。通过逐步回归分析筛选出5个指标:20%PEG溶液处理相对发芽势和胁迫后苗期叶片水势、抽雄吐丝期叶片保水力、行粒数、百粒重和对照相对值。根据逐步回归筛选出的指标和偏相关系数,建立了不同时期的抗旱评价(D值)方程和评价体系。【结论】20%PEG溶液处理相对发芽势和胁迫后苗期叶片水势、抽雄吐丝期叶片保水力、行粒数和百粒重和对照相对值可作为玉米抗旱性鉴定指标,利用这些指标建立的评价(D值)方程可对玉米抗旱性进行较好的评价。

玉米不同时期抗旱性鉴定指标的灰色关联度与聚类分析

试验从玉米抗旱性的系统性和整体性出发,在玉米4个比较重要的生育时期,即:萌发期(播种-出苗)、苗期(出苗-拔节)、开花期(抽雄-吐丝)、灌浆期(授粉-收获)采用分阶段人工模拟干旱胁迫的方法,利用综合性状比较优良的超级玉米品种为试验材料,通过比较形态学、发育学、生理学等方面的抗旱性鉴定指标与玉米抗旱能力的关系,通过一些简便易测指标的分析筛选,建立一套可靠、迅速的指标体系。通过玉米抗旱性与各指标的相关分析、灰色关联度分析、聚类分析,明确了各指标与玉米抗旱性关系及抗旱性鉴定的指标体系,为综合评价不同玉米品种抗旱性奠定了基础。

基于土壤墒情模型的旱情评估预测模型研究

干旱灾害是对农业生产影响最为严重的自然灾害之一,严重制约了安徽省淮北地区经济社会可持续发展。首先简要介绍安徽省淮北地区干旱特点及原因,构建了区域干旱评价指标体系并划分不同季节旱情等级标准,然后建立了基于土壤墒情、降水量及地下水埋深的综合旱情评估预测模型。将干旱评价指标体系及评估预测模型分别应用到2008年冬旱评估、2009年3月份干旱预测评估,结果表明:该模型预测评估结果基本能够反映区域干旱的实际情况,能够为区域防旱抗旱提供技术服务。

安徽省淮北地区干旱评价指标体系研究

干旱灾害是安徽省淮北地区最主要的自然灾害之一,制约着区域社会经济和农业的快速发展。在对安徽省淮北地区干旱特征和干旱成因分析的基础上,选取了气象干旱指标(降水量距平百分率、降水排频和连续无雨日数)、农业干旱指标(土壤相对湿度)和水文干旱指标(地下水埋深)建立了干旱评价指标体系,通过分析确定了各指标对应春旱、夏旱、秋旱和冬旱不同干旱等级(轻度干旱、中度干旱、严重干旱和特大干旱)的划分标准。最后对安徽省淮北地区典型干旱年份的干旱状况进行评判和分析,结果表明:建立的干旱评价指标体系等级划分标准能够真实地反映区域干旱状况,弥补了单一干旱指标评价的不足。

江苏省苏北地区季节性干旱特征及动态风险评价研究

利用江苏省统计年鉴提供的气象资料,通过标准化降水指数(SPI)计算苏北地区近25 a(1989—2013年)的季节干旱指标,分析江苏省苏北地区五市的季节性干旱时空特征和发生规律,并对其进行动态干旱风险评价。基于危险性、脆弱性、暴露性和防灾减灾能力这四个影响因子构建相应干旱风险评价指标体系,选取适合苏北五市的气象、水文、地理、社会经济方面相关二级指标,组合运用熵权法和CRITIC法确定各指标综合权重,通过加权综合评价法对苏北五市进行动态旱灾风险评价。结果表明:苏北地区干旱时间特征存在明显的季节性差异,发生干旱多为轻旱和中旱,且多发生于春夏秋三季,盐城市冬季发生中旱和重旱相对较频繁;干旱强度变化趋势和干旱频率趋势大体一致,五市发生春旱的频数和强度总体都呈增加趋势,而秋季情况略有好转。近年来,苏北地区五市的旱灾风险具有一定的稳定性,风险排名依次为:淮安>连云港>宿迁>徐州>盐城,其中,防灾减灾能力对于干旱风险的动态变化体现出较强相关性。