Winter Wheat Drought Monitoring and Comprehensive Risk Assessment： Case Study of Xingtai Administrative District in North China

Drought monitoring is the base for drought coping and adaptation. Xingtai is located in North China＇s key winter wheat production areas where drought is severe and frequent. The rainfall during winter wheat growing season is just about 1/3 of total demand. Xingtai has typical mountainous, hilly and plain agricultural zones, compound rain-fed and irrigated farming patterns. The winter wheat irrigation has heavily depended on overdraw of groundwater in recent decades. In the study, the MODIS （Moderate-Resolution Imaging Spectroradiometer） images taken at the key winter wheat growing season （Mar. to May） in normal rainfall year （2006） were selected, extracted NDVI （Normalized Difference Vegetation Index） and LST （Land Surface Temperature） data, calculated TVDI （Temperature and Vegetation Drought Index）, classified and mapped winter wheat drought intensity. Further, based on TVDI, a CDRA （Comprehensive Drought Risk Assessment） model for winter wheat drought disaster risk assessment was constructed and zoning was made. Verified by winter wheat yield, the risk zoning by CDRA is consistent with actual crop failure space. This method can be used in drought risk management.

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.

Canopy Temperature Depression as a Potential Selection Criterion for Drought Resistance in Wheat

Field studies were conducted at Bushland, Texas, USA, in 2004 to examine usefulness of canopy temperature depression （CTD）, the difference of air-canopy temperature, in screening wheat （Triticum aestivum L.） genotypes for yield under dryland and irrigated. Forty winter wheat genotypes were grown under irrigation and dryland. CTDs were recorded after heading between 1 330 and 1 530 h on 6 clear days for dryland and 9 days for irrigation. Drought susceptible index （DSI） for each genotype was calculated using mean yield under dryland and irrigated conditions. Genotypes exhibited great differences in CTD under each environment. The dryland CTDs averaged 1.33℃ ranging from -0.67 to 2.57℃, and the average irrigation CTD were 4.59℃ ranging from 3.21 to 5.62℃. A low yield reduction was observed under dryland conditions relative to irrigated conditions for high-CTD genotypes. CTD values were highly negatively correlated with DSI under dryland, and genotypes of CTDs = 1.3℃ in dryland condition were identified as drought resistant. For 21 genotypes classified as drought resistant by DSI, their CTDs were 1.68℃ for dryland and 4.35℃ for irrigation on average; for 19 genotypes classified as drought susceptible by DSI, average CTD was 0.94℃ in dryland and 4.85℃ in irrigation. The high-yield genotypes consistently had high CTD values, and the low-yield ones had low CTD values for all measurements in dryland. After heading, genotypes maintained consistent ranking for CTD. Regression results for CTD and yield suggested that the best time for taking CTD measurement was 3-4 weeks after heading in irrigation but any time before senescence in dryland. Crop water stress index （CWSI） calculated from CTD data was highly correlated with CWSI calculated from yield, which suggesting traditional costly CWSI measurement may be improved by using portable infrared thermometers. Most importantly, grain yield was highly correlated with CTD under dryland （R^2 = 0.79-0.86） and irrigation （R^2 = 0.46-0.58） conditions. These results clearly indicated grain yield and water stress can be predicted by taking CTD values in field, which can be used by breeding programs as a potential selection criterion for grain yield and drought resistance in wheat, but a second study year is needed to confirm further.

陇东旱地冬小麦品种抗旱性鉴定

为研究陇东特殊干旱气候条件下抗旱育种的进展与现状,选取近20 a陇东旱地选育的14个冬小麦新品种(系)为材料,以籽粒产量抗旱指数等为全生育期抗旱性鉴定指标,在旱棚进行全生育期干旱胁迫试验。结果表明,陇育4号和宁麦5号抗旱指数在1.100~1.299范围内,抗旱级别为2级;陇育7号和陇鉴387抗旱指数在0.700~0.899范围内,抗旱级别为4级;其余10个材料抗旱指数在0.900~1.099范围内,抗旱级别为3级。抗旱性级别在2~3级的材料占85.7%。产量性状主因子分析发现,抗旱级别为2级的陇育4号和宁麦5号,在干旱胁迫下有效穗数、穗粒数和千粒重无明显变化;抗旱级别为4级的陇育7号和陇鉴387,在干旱胁迫下有效穗数、穗粒数和千粒重均减幅较大;抗旱级别为3级的其余10个材料在干旱条件下,其产量性状三要素有效穗数、穗粒数、千粒重中只有一项发生变化,没有两项叠加变化。

基于多源遥感数据与模型对比的冬小麦土壤含水量区域监测研究

实时、精准的土壤水分含量监测是农业用水管理的基础,探究冬小麦土壤水分反演的最优模型对于提高农业用水效率和可持续发展均具有重要的意义。本研究以河南省鹤壁市浚县冬小麦种植区域的土壤水分含量为研究对象,采用无人机遥感数据、卫星遥感数据、田间采样数据,分别运用温度植被干旱指数模型、水云模型和改进的水云模型3种方法,进行土壤含水量反演对比分析与最优模型选择。结果表明,3种方法中10 cm深度的反演精度均高于20 cm,且R^(2)均大于0.4。其中采用改进的水云模型方法在10 cm深度的R^(2)为0.7055、RMSE为0.0209,20 cm深度的R^(2)为0.5069、RMSE为0.0271,优于水云模型和温度植被干旱指数的反演效果。因此,改进的水云模型是一种适合用于麦田土壤水分反演的方法,它能够提供较高的反演精度。

淮北平原冬小麦农业干旱时空变化规律

【目的】探究淮北平原冬小麦农业干旱的时空变化规律。【方法】以作物水分亏缺指数(CWDI)作为干旱指标,分析淮北平原1957—2018年各地区冬小麦各生育阶段CWDI年际变化趋势、空间分布、波动范围、干旱站次比和空间频率分布,探讨淮北平原冬小麦农业干旱的时空变化规律。【结果】淮北平原冬小麦整个生育期内旬需水量和旬供水量均呈先降低后上升的变化趋势,旬有效降水量变幅不大,均在10mm以内,而潜水蒸发强度在3月中旬—5月下旬显著增加,增幅达260%。阜阳、蚌埠和蒙城地区的冬小麦生长期水分供需相对平衡,而砀山、亳州和宿州地区水分供需不平衡;宿州CWDI波动性最大,蚌埠CWDI波动性最小。1957—2018年,冬小麦生育期干旱站次比呈显著上升趋势;2010年干旱范围最广、干旱程度最大。各生育阶段农业干旱程度的空间分布不均,呈由南到北递增的趋势,黄潮土区干旱等级普遍高于砂姜黑土区;轻旱发生频率高值中心由淮北平原南部向北部迁移,中旱高值区主要集中在亳州和宿州;重旱呈北高南低的特征;特旱在全生育期内较为罕见,发生频率不足5%。【结论】淮北平原1957—2018年冬小麦干旱程度呈上升趋势,水分供需不平衡,砀山和宿州地区需增加灌溉量。

基于Landsat-8影像的农田土壤含水量反演研究

快速实时地获取大范围土壤含水量可以为科学有效地应对干旱提供强有力的数据支撑。研究选择河北省定兴县和易县的冬小麦种植区作为研究区域,基于多光谱遥感数据Landsat-8和野外实测土壤含水量数据,构建了垂直干旱指数(PDI)、改进型垂直干旱指数(MPDI)、温度植被旱情指数(TVDI)3种干旱指数模型来反演研究区土壤含水量,并分析反演结果的精度和适用性。研究结果表明:3种干旱指数计算结果显示研究区整体偏干,不同干旱指数的空间分布存在差异,其中PDI和另外2种干旱指数的差异最大;3种干旱指数均与土壤含水量实测值呈负相关,其中MPDI、TVDI和土壤含水量之间存在较为明显的线性相关关系,从拟合精度来看MPDI表现最优,因此被用于反演研究区的土壤含水量。反演结果显示研究区的含水量整体偏少,主要介于12%~15%,含水量的空间分布特征和地表覆盖特征一致。研究结果证明了MPDI指数在冬小麦冬季干旱监测方面具有较大的应用潜力。

冬小麦综合干旱评估指标建立及应用--以半干旱黄土高原地区为例

为提高冬小麦干旱监测和定量灾损评估的准确性,以半干旱黄土高原陇东地区为例,利用15个冬小麦种植县1965-2020年逐日降水资料、MCI指数,1978-2020年冬小麦产量资料、干旱灾情资料,以及1981-2014年生育期观测资料,探索建立冬小麦干旱灾损评估新指标WDI,以因旱减产率和干旱指标之间的关系参考历史灾情确定等级阈值,基于WDI分析陇东地区冬小麦干旱时空分布特征。结果表明:WDI在评估干旱对冬小麦产量影响方面优于气象干旱指数;从3个代表站WDI年际变化看,环县波动幅度最大且数值最小,其次是西峰,处于阴湿地区的华亭波动幅度最小且数值最大。20世纪90年代初至21世纪初波动最剧烈。从年代变化看,20世纪90年代全生育期、拔节~开花期WDI平均值分别为-10.6、-5.4,为各年代最低,处于干旱期;21世纪10年代WDI平均值则分别为4.4、2.6,为各年代最高,处于相对湿润期。在空间分布上,干旱频率由东南向西北增大,重度以上干旱主要发生在陇东西部和中北部。冬小麦全生育期、拔节~开花期轻中旱发生频率分别为34%~52%、41%~57%,重度以上干旱频率均为4%~18%,评估结果与历史实况基本一致。WDI兼顾气象学与生物学意义,能较好表征冬小麦产量损失、干旱时空特征分析,可用于冬小麦干旱监测和评估业务。

Impact of Droughts on Winter Wheat Yield in Different Growth Stages during 2001–2016 in Eastern China

Remote sensing can provide near real-time and dynamic monitoring of drought. The drought severity index(DSI), based on the normalized difference vegetation index(NDVI) and evapotranspiration/potential evapotranspiration(ET/PET), has been used for drought monitoring. This study examined the relationship between the DSI and winter wheat yield for prefecture-level cities in five provinces of eastern China during 2001–2016. We first analyzed the spatial and temporal distribution of droughts in the study area. Then the correlation coefficient between drought-affected area and detrended yield of winter wheat was quantified and the impact of droughts of different intensities on winter wheat yield during different growth stages was investigated. The results show that incipient drought during the wintering period has no significant impact on the yield of winter wheat, while moderate drought in the same period can reduce yield. Drought affects winter wheat yield significantly during the flowering and filling stages. Droughts of higher intensity have more significant negative effects on the yield of winter wheat. Monitoring of droughts and irrigation is critical during these periods to ensure normal yield of winter wheat. This study has important practical implications for the planning of irrigation and food security.

Comparison of three remotely sensed drought indices for assessing the impact of drought on winter wheat yield

Agricultural drought threatens food security.Numerous remote-sensing drought indices have been developed,but their different principles,assumptions and physical quantities make it necessary to compare their suitability for drought monitoring over large areas.Here,we analyzed the performance of three typical remote sensing-based drought indices for monitoring agricultural drought in two major agricultural production regions in Shaanxi and Henan provinces,northern China(predominantly rain-fed and irrigated agriculture,respectively):vegetation health index(VHI),temperature vegetation dryness index(TVDI)and drought severity index(DSI).We compared the agreement between these indices and the standardized precipitation index(SPI),soil moisture,winter wheat yield and National Meteorological Drought Monitoring(NMDM)maps.On average,DSI outperformed the other indices,with stronger correlations with SPI and soil moisture.DSI also corresponded better with soil moisture and NMDM maps.The jointing and grain-filling stages of winter wheat are more sensitive to water stress,indicating that winter wheat required more water during these stages.Moreover,the correlations between the drought indices and SPI,soil moisture,and winter wheat yield were generally stronger in Shaanxi province than in Henan province,suggesting that remote-sensing drought indices provide more accurate predictions of the impacts of drought in predominantly rain-fed agricultural areas.

基于植被状态指数的县域冬小麦干旱时空变化特征分析

[目的]分析县域冬小麦干旱的时空异质性,为抗旱减灾提供辅助决策支持。[方法]基于GF1,Landsat,Sentinel-2等中高分辨率遥感数据,选取植被状态指数(Vegetation Condition Index,VCI)作为干旱监测指标,计算2011—2021年禹州市冬小麦VCI,逐年分析禹州市冬小麦干旱分布情况,并通过变异系数、线性趋势法、重心迁移和标准差椭圆等方法,对禹州市冬小麦干旱的稳定性、变化趋势、时空变化等特征进行了多维度分析。[结果](1)空间上,2011—2021年禹州市冬小麦干旱主要分布在北部和西部的山岗丘陵区,干旱面积和干旱强度由平原区向山岗区逐渐延展扩大;变异系数与变化百分率均值分别为0.62,13.12%,冬小麦干旱稳定性与变化趋势空间分布一致性高;重心迁移轨迹总距离和标准差椭圆扁率从无旱到重旱逐渐变小,标准差椭圆面积逐渐变大,表明干旱空间分布由集中趋于分散;(2)时间上,禹州市冬小麦每年都有轻旱发生,中旱和重旱平均2~4年发生一次,2012—2014年连续3年旱情较重,中旱和重旱总占比均超过35%,其次为2016年和2018年。[结论]近11年来禹州市冬小麦干旱总体上呈现向好的发展态势,大部分区域冬小麦旱情改善较为明显,对于旱情严重且不稳定区域需加强防控力度。

北方冬小麦干旱灾损风险区划

本文基于风险分析的原理,利用北方冬麦区长年小麦产量资料和气象资料,建立了适用于北方冬小麦干旱灾损风险评估的指标体系,包括自然水分亏缺率风险指数、减产率风险指数和抗灾性能趋势向量系数等风险评估指标的意义、表达模式和估算技术、计算和分区。结果表明,北方冬小麦各项风险评估指标均具有明显的区域差异和一定的连片性。在此基础上,构建了北方冬小麦干旱灾损综合风险指数模式,估算并确定了其综合风险区划指标,以此为依据将北方冬麦区划分为高、较高、中和低4个风险区。冬小麦干旱灾损高风险区在陕西中北部、山西中部的部分地区和河北沧州的部分地区;较高风险区在山西中部的部分地区、河北的唐山地区和西部的部分地区;中风险区在陕西中部、山西南部、河北中东部的部分地区;低风险区在陕西中南部、河南中北部、北京市、天津市、河北中南部和山东省。

基于遥感DSI指数的干旱与冬小麦产量相关性分析

利用2000—2012年MODIS ET/PET和NDVI数据集构建干旱指数(DSI),监测山东省和河南省冬小麦主产区的农业干旱,并在地级市尺度上进一步评估冬小麦关键生育期干旱对冬小麦产量的影响。结果表明:2010年9月—2011年2月山东省特大干旱过程显示的DSI不仅能监测气象干旱,还能较好地反映农业干旱在空间上的差异性以及时间上的演变。不同冬小麦生育期干旱对冬小麦产量影响不同,灌浆期干旱对冬小麦产量的影响最大,干旱致使土壤水分亏缺,影响了作物正常的灌浆强度,进而导致作物减产;其次是拔节期;返青期干旱对产量基本没有影响。

冬小麦抗旱性鉴定指标的研究

研究了小麦抗旱性鉴定的部分产量指标、形态指标和生理指标。通过对４个产量指标分析，确认抗旱指数优于抗旱系数、干旱敏感指数和产量因素降低指数，抗旱指数既能反映品种的抗旱性能，又能体现品种在旱地条件下的产量水平，可作为小麦杂种稳定世代鉴定抗旱性的可靠指标。对于大量品种资源和杂种分离世代材料的抗旱性鉴定，可用胚芽鞘长度和拔节期叶面积指数为指标。该指标简便易行、快速经济。小麦灌浆期叶片脯氨酸含量与品种的抗旱性无明显相关。

华北冬小麦作物气候干旱指数研究

作为农业干旱指标,降水距平百分率未考虑底墒作用,不同发育期水分对产量影响不同。利用降水距平百分率指数构建了华北冬小麦作物气候冬小麦干旱指数。该指数将冬小麦不同发育阶段的水分产量反应系数应用到降水距平干旱指数中,同时量化底墒对冬小麦生长发育过程中起到的重要作用。通过对河南省卢氏县冬小麦历年干旱和减产率进行计算和分析,结果表明,作物气候指标负距平百分率和减产率的相关性明显高于降水负距平百分率和减产率的相关性。作物气候冬小麦干旱指数在评估冬小麦干旱时要优于降水距平百分率,将作物和气候干旱相结合能更准确地评估冬小麦干旱,弥补降水距平百分率作为农业干旱指数只涉及气候干旱的不足。

不同基因型冬小麦抗旱性鉴定及相关抗旱指标分析

【目的】研究干旱胁迫对冬小麦形态指标的影响和不同材料间抗旱性的差异。【方法】采用田间干旱胁迫和室内模拟干旱辅助试验相结合的方法,在种子萌发期和生育中后期,对不同品系(种)相关指标进行研究分析。【结果】发芽率、发芽势、根数、芽鞘长和贮藏物质转运率的抗胁迫系数与种子抗旱性之间关系达显著或极显著水平,可以作为种子萌发期的鉴定指标;产量、株高、穗长和收获穗数与抗旱指数相关显著或极显著,可以作为田间抗旱性鉴定指标。种子萌发期鉴定指标与田间鉴定指标之间相关不显著,说明种子萌发期与生育后期抗旱性是独立的遗传性状。【结论】冬小麦抗旱性评价应对各生育时期鉴定指标的指示结果进行综合考虑。

陕西省冬小麦干旱时空变化特征分析

利用陕西省1981-2013年22个气象站点的逐日气象数据、冬小麦生育期及产量资料,在考虑水分敏感系数与底墒期降水的基础上,分生育期构建了陕西省冬小麦的干旱指数,并且采用统计模型分离干旱对产量的影响程度,按关键生育期划分干旱指数等级范围并分析其时空变化规律。结果表明:陕西省冬小麦整个生育期干旱频率与干旱减产率有北高南低的分布规律;陕北、关中及陕南部分地区近30a冬小麦干旱有增强趋势,而各生育期的减产率变化趋势则不尽相同。

不同品种冬小麦冠层温度与抗旱性和水分利用效率的关系研究

本试验利用红外测温仪于2006-2007年在甘肃陇东旱塬,测定了40个冬小麦品种灌浆期冠层温度,研究了冠层温度与抗旱指数和水分利用效率之间的关系,研究结果表明,不同水分条件下40个冬小麦品种灌浆期冠层温度、抗旱指数和水分利用效率差异均达到了极显著水平,水分利用效率和冠层温度与抗旱指数之间相关性分析表明,抗旱指数与水分利用效率之间存在显著的正相关关系(r=0.769***);抗旱指数与冠层温度呈极显著负相关(r=-0.772***),7个抗旱性强的品种其冠层温度较40个品种(系)平均值低1℃,11个抗旱性弱的品种则高出40个品种(系)平均值0.68℃,说明冠层温度能够反映品种抗旱性。

不同冬小麦品种产量和节水性状差异及对供水的反应

以24个冬小麦品种(系)为材料,在不同的灌水处理下,研究了产量、产量构成因素和抗旱指数的品种差异。结果表明,灌水处理间与品种间产量差异均极显著,灌水与品种互作差异显著。2水处理产量高于4水。石4185,冀 5579,石麦12等19个品种2水处理产量高于4水,多丰2000,师栾02-1,良星99等5个品种4水产量高于2水。分别以2水处理和4水处理下的产量作为水地产量计算抗旱指数,得出抗旱型,不抗旱型和中间型比例分别为4．2％, 29．2％,66．6％和20．8％,20．8％,58．4％。综合分析认为石麦12,冀5579和石新618等产量和节水综合性状较好的品种更适于节水栽培。

安徽省冬小麦种植保险天气指数设计与应用

利用安徽省宿州市1993-2009年的逐日气象数据并结合区域冬小麦生育期的主要农业气象灾害,通过对历史产量损失与主要灾害的气象指标进行对比分析,为设计小麦种植天气指数保险产品,确定了干旱指数、倒春寒指数、干热风指数、阴雨日数指数Ⅰ、阴雨日数指数Ⅱ共5个小麦关键生育期天气指数。通过历史天气指数赔付率与历史产量损失率的对比,定义基差风险函数和最小化基差风险,确定指数保险赔付的触发值及赔付标准。将设计的保险产品在安徽省宿州市试验应用,2010-2012年成功销售推广1300hm2,总保费约11万元,因触发干旱指数,实际赔付额超过22万元。表明天气指数保险产品的应用,能客观、快捷地提供灾害的经济补偿。