Measuring cotton water status using water-related vegetation indices at leaf and canopy levels

Drought is one of the major environmental threats in the world. In recent years, the damage from droughts to the environment and economies of some countries has been extensive, and drought monitoring has caused widespread concerns. Remote sensing has a proven ability to provide spatial and temporal measurements of surface properties, and it offers an opportunity for the quantitative assessment of drought indicators such as the vegetation water content at different levels. In this study, sites of cotton field in Shihezi, Xinjiang, Northwest China were sampled. Four classical water content parameters, namely the leaf equivalent water thickness (EWT leaf ), the fuel moisture content (FMC), the canopy equivalent water thickness (EWT canopy ) and vegetation water content (VWC) were evaluated against seven widely-used water-related vegetation indices, namely the NDII (normalized difference infrared index), NDWI 2130 (normalized difference water index), NDVI (normalized difference vegetation index), MSI (moisture stress index), SRWI (simple ratio water index), NDWI 1240 (normalized difference water index) and WI (water index), respectively. The results proved that the relationships between the water-related vegetation indices and EWT leaf were much better than that with FMC, and the relationships between vegetation indices and EWT canopy were better than that with VWC. Furthermore, comparing the significance of all seven water-related vegetation in- dices, WI and NDII proved to be the best candidates for EWT detecting at leaf and canopy levels, with R 2 of 0.262 and 0.306 for EWT leaf-WI and EWT canopy -NDII linear models, respectively. Besides, the prediction power of linear regression technique (LR) and artificial neural network (ANN) were compared using calibration and validation dataset, respectively. The results indicated that the performance of ANN as a predictive tool for water status measuring was as good as LR. The study should further our understanding of the relationships between water-related vegetation indices and water parameters.     

归一化水体指数用于河南省干旱监测适用性分析

利用30 m分辨率的归一化植被指数（NDVI）图像信息熵对河南省气象站周边地表异质性进行分析,选取观测站周围地表较为均匀的站点实测土壤水分数据,通过计算归一化水体指数（NDWI）与实测土壤水分之间的相关系数,分析比较NDWI用于干旱监测的适用性。研究表明：信息熵方法可有效地对土壤水分观测数据进行筛选;在时间序列上,各站点实测值与NDWI具有负相关关系,在增强型植被指数EVI>0.4时相关性更高,说明在植被覆盖高的区域NDWI对土壤水分的反演更为敏感;空间上,根据地形将河南省分为北部、中部、南部和西部4个区域并选取第121、201、313天的土壤水分数据来分析与NDWI之间的相关性,在地形较为平坦的中北部地区NDWI与土壤水分之间负相关性最稳定且相关系数较高。根据NDWI空间分布可知,2014年河南省大部分地区均遭受了干旱,且干旱地区大部分位于平原,特别是北方地区受灾严重。总体来说,NDWI用于平原地区对作物进行干旱监测精度较高,并可预测干旱发展趋势及程度。     

Response of hydrological drought to meteorological drought in the eastern Mediterranean Basin of Turkey

The hydrographic eastern Mediterranean Basin of Turkey is a drought sensitive area. The basin is an important agricultural area and it is necessary to determine the extent of extreme regional climatic changes as they occur in this basin. Pearson's correlation coefficient was used to show the correlation between standardized precipitation index(SPI) and standardized streamflow index(SSI) values on different time scales. Data from five meteorological stations and seven stream gauging stations in four sub-basins of the eastern Mediterranean Basin were analyzed over the period from 1967 to 2017. The correlation between SSI and SPI indicated that in response to meteorological drought, hydrological drought experiences a one-year delay then occurs in the following year. This is more evident at all stations from the mid-1990 s. The main factor causing hydrological drought is prolonged low precipitation or the presence of a particularly dry year. Results showed that over a long period(12 months), hydrological drought is longer and more severe in the upper part than the lower part of the sub-basins. According to SPI-12 values, an uninterrupted drought period is observed from 2002–2003 to 2008–2009. Results indicated that among the drought events, moderate drought is the most common on all timescales in all sub-basins during the past 51 years. Long-term dry periods with moderate and severe droughts are observed for up to 10 years or more since the late 1990 s, especially in the upper part of the sub-basins. As precipitation increases in late autumn and early winter, the stream flow also increases and thus the highest and most positive correlation values(0.26–0.54) are found in January. Correlation values(ranging between –0.11 and –0.01) are weaker and negative in summer and autumn due to low rainfall. This is more evident at all stations in September. The relation between hydrological and meteorological droughts is more evident, with the correlation values above 0.50 on longer timescales(12-and 24-months). The results presented in this study allow an understanding of the characteristics of drought events and are instructive for overcoming drought. This will facilitate the development of strategies for the appropriate management of water resources in the eastern Mediterranean Basin, which has a high agricultural potential.     

三种复合干旱指数在我国三大农业主产区的适用性分析

利用多源遥感数据,通过与SPI-3的线性相关分析及实际旱情的对比,研究了三种复合干旱指数(PADI、OVDI、TVDI)在我国三类(冬小麦、夏玉米、水稻)农业主产区的适用性。结果表明:三种复合干旱指数不适用于水稻区的干旱监测;在三类农业区的干旱监测中,指数PADI、TVDI对干旱量化结果较为准确(干旱持续时间、严重程度、空间分布等),OVDI对旱情严重程度的判断偏重;指数TVDI、OVDI适合大范围的旱情监测,且TVDI监测结果更为准确;PADI指数由于结合了作物信息,对干旱的量化更全面,适宜于小范围的旱情监测,但对输入信息的要求较高。     

Drought trend analysis in a semi-arid area of Iraq based on Normalized Difference Vegetation Index,Normalized Difference Water Index and Standardized Precipitation Index

Drought was a severe recurring phenomenon in Iraq over the past two decades due to climate change despite the fact that Iraq has been one of the most water-rich countries in the Middle East in the past.The Iraqi Kurdistan Region(IKR)is located in the north of Iraq,which has also suffered from extreme drought.In this study,the drought severity status in Sulaimaniyah Province,one of four provinces of the IKR,was investigated for the years from 1998 to 2017.Thus,Landsat time series dataset,including 40 images,were downloaded and used in this study.The Normalized Difference Vegetation Index(NDVI)and the Normalized Difference Water Index(NDWI)were utilized as spectral-based drought indices and the Standardized Precipitation Index(SPI)was employed as a meteorological-based drought index,to assess the drought severity and analyse the changes of vegetative cover and water bodies.The study area experienced precipitation deficiency and severe drought in 1999,2000,2008,2009,and 2012.Study findings also revealed a drop in the vegetative cover by 33.3%in the year 2000.Furthermore,the most significant shrinkage in water bodies was observed in the Lake Darbandikhan(LDK),which lost 40.5%of its total surface area in 2009.The statistical analyses revealed that precipitation was significantly positively correlated with the SPI and the surface area of the LDK(correlation coefficients of 0.92 and 0.72,respectively).The relationship between SPI and NDVI-based vegetation cover was positive but not significant.Low precipitation did not always correspond to vegetative drought;the delay of the effect of precipitation on NDVI was one year.     

基于广西岩溶和非岩溶地貌的干旱遥感监测模型研究

根据MODIS植被指数和陆面温度,建立植被状态指教(VCI)、温度条件指数(TCI)和植被-温度指数(DI)模型;采用广西2004年10～11月数据,利用相关系数、全距和变异系数对3个干旱监测模型应用于广西岩溶区和非岩溶区大范围干旱监测的适用性进行了论证分析,结果表明:植被-温度指数模型(DI)最适用,温度条件指数(TCI)次之,植被状态指数(VCI)则较难胜任.并使用植被-温度指数DI模型监测了广西2005年秋旱,经与干旱实况对比,干旱指数DI的监测结果与实况相符,表明植被-温度指数遥感监测模型能准确反映出广西岩溶和非岩溶地貌环境的干旱时空变化特征,适用于广西大范围的干旱监测.     

基于条件植被温度指数的干旱监测研究

以黑龙江军川农场为研究区域,应用Landsat TM卫星遥感数据计算和反演归一化植被指数和地表温度,采用条件植被温度指数(VTCI)的方法对该区域进行土壤表层水分监测.通过与同一时期的LST和NDVI模型的反演结果进行对比,结果表明:VTCI与该模型的纹理特征相似,干旱的分布规律几乎一致.应用土壤表层含水量数据对干旱监测结果进行验证,验证结果表明VTCI与土壤表层含水量有较好的线性相关性,进一步证实了VTCI是一种实时的干旱监测方法.     

基于核熵成分分析的综合干旱指数的构建与应用

针对传统单变量干旱指数难以全面表征干旱及部分综合干旱指数难以反映多变量之间的非线性关系等问题，采用标准化降水蒸散发指数（SPEI）、标准化径流指数（SRI）及标准化土壤湿度指数（SSMI）3个单变量指数分别表征气象干旱、水文干旱和农业干旱，利用核熵成分分析法（KECA）构造综合干旱指数（SMDI），采用M-K趋势检验、小波分析及典型历史旱情验证等方法分析干旱的时空变化特征以及干旱指数的适用性。以黑河流域中上游为例，结果表明：研究区全年77.6%的区域表现为干旱不显著加重的趋势；在流域尺度上，干旱存在43 a的长周期，15~23 a的中周期，3~8 a的短周期；20世纪90年代夏、秋两季及21世纪以来春、冬两季干旱发生频率较高，且整体夏旱发生频率最高；1969年春、1997年秋和2009年冬的典型历史旱情验证表明SMDI优于其他3种单变量干旱指数。说明基于KECA构建的SMDI是一种有效的干旱监测指数，在黑河流域中上游干旱监测中有好的适用性。     

基于生成对抗网络模型的SMAPL4土壤水分产品降尺度分析

土壤水分是地表和大气水热过程交换的重要纽带,对于农业生产以及优化种植结构具有重要意义,NASA卫星下的SMAPL4是一种以被动微波遥感技术为手段对土壤湿度监测的产品,具有可穿透云层和全天候监测等能力,但其较低空间分辨率很难满足小尺度或小区域范围的实际研究需求。鉴于此,根据云南省姚安县高原灌区特殊的地理位置,引用相关系数推演得出与研究区土壤水分空间分布有关的解释变量,沿用随机森林算法,耦合1 km包含地表温度和归一化植被指数的MODIS地表产品,建立基于RF全局窗口线性回归的1 km级被动微波土壤水分空间降尺度模型;而后堆叠地表温度(LST)、归一化植被指数(NDVI)、降水量(Prec)、地表蒸散量(ET)等4个变量形成条件生成对抗网络框架,并使用均方误差(RMSE)和条件生成对抗性损失函数训练神经网络来建立低分辨率和高分辨率映射关系,随即获得降尺度后土壤水分空间分布结果;最后将实际采样和监测站点提供数据做空间平均聚合后,与SMAPL4原始结果的CGAN、RF降尺度结果进行对比分析。结果表明：LST、NDVI、Prec、ET与土壤水分的相关性均值均大于0.44,具有相关关系,条件生成对抗网络降尺度结果对指标R²和Bias表现效果最好,均值分别为0.7和0.032;RF降尺度结果对RMSE的效果最好,均值为0.006。同比SMAPL4原始数据,RF结果空间分布更为平滑,但极值差异性较大;CGAN结果能有效表征土壤含水空间分布状况,其数据变异性和极值表征能力更为突出。经RMSE与对抗性损失函数训练后,认为0.2~0.28的值域分布为降尺度后的研究区土壤水分数值分布结果。     

Assessment of desertification in Eritrea: land degradation based on Landsat images

Remote sensing is an effective way in monitoring desertification dynamics in arid and semi-arid regions. In this study, we used a decision tree method based on NDVI(normalized difference vegetation index), SAVI(soil adjusted vegetation index), and vegetation cover proportion to quantify and analyze the desertification in Eritrea using Landsat data of the 1970 s, 1980 s and 2014. The results demonstrate that the NDVI value and the annual mean precipitation declined while the temperature increased over the past 40 a. Strongly desertified land increased from 4.82×10~4 km~2(38.5%) in the 1970 s to 8.38×10~4 km~2(66.9%) in 2014: approximately 85% of the land of the country was under serious desertification, which significantly occurred in arid and semi-arid lowlands of the country(eastern, northern, and western lowlands) with relatively scarce precipitation and high temperature. The non-desertified area, mostly located in the sub-humid eastern escarpment, also declined from approximately 2.1% to 0.5%. The study concludes that the desertification is a cause of serious land degradation in Eritrea and may link to climate changes, such as low and unpredictable precipitation, and prolonged drought.     

华南农作物覆盖区土壤水分ENVISAT-ASAR与MODIS数据联合反演算法研究

准确、及时地获取大面积地表土壤水分信息在农业科学领域具有较大的应用潜力。本文以地域特色突出的广东省徐闻县为试验区,联合使用双极化ENVISAT-ASAR数据和光学遥感MODIS数据,充分利用MODIS数据的高重复覆盖率,提取试验日期内的归一化差分水指数(NDWI),计算各试验点所对应的植被含水量(VWC)数据,相较于NDVI,NDWI具有不易饱和的特点,更加适合于本次研究所在的高植被覆盖区。最后利用"水—云模型"从ASAR数据总的后向散射中去除植被的影响,建立裸土后向散射系数与实测土壤含水量之间的关系,拟合结果VV极化优于HH极化,相关系数为VV极化R=0.865,HH极化R=0.676,总体上针对农作物覆盖地表土壤水分变化的估算算法还需要更进一步发展和改进,以提高反演精度。     

Spatio-temporal patterns of drought in North Xinjiang,China, 1961–2012 based on meteorological drought index

Drought, which is one of the most frequently occurring severe hazards with long time scales and covering wide geographical areas, is a natural phenomenon resulting in significant economic losses in agriculture and industry. Drought is caused by an imbalance between the inputs of and the demand for water which is insufficient to meet the demands of human activities and the eco-environment. As a major arid and semi-arid area and an important agricultural region in Northwest China, North Xinjiang(NX) shows great vulnerability to drought. In this paper, the characteristics of inter-annual and seasonal drought were analyzed in terms of drought occurrence and drought coverage, by using the composite index of meteorological drought and the data of daily precipitation, air temperature, wind speed, relative humidity and sunshine duration from 38 meteorological stations during the period 1961–2012. Trend analysis, wavelet analysis and empirical orthogonal function were also applied to investigate change trend, period and regional characteristics, respectively. In NX, annual and seasonal drought occurrence and drought coverage all showed a decreasing trend that was most significant in winter(with rates of –0.26 month/10 a and –15.46%, respectively), and drought occurrence in spring and summer were more frequent than that in autumn and winter. Spatially, drought was severe in eastern regions but mild in western regions of NX. Annual and seasonal drought occurrence at 38 meteorological stations displayed decreasing trends and were most significant in "Shihezi-Urumqi-Changji", which can help to alleviate severe drought hazards for local agricultural production and improve human livelihood. NX can be approximately classified into three sub-regions(severe drought region, moderate drought region and mild drought region), which were calculated from annual drought frequencies. The cross wavelet transform suggested that SOI(Southern Oscillation Index), AOI(Arctic Oscillation Index), AAOI(Antarctic Oscillation Index), PAOI(Pacific/North American Oscillation Index) and NAOI(North Atlantic Oscillation Index) have significant correlation with the variation of drought occurrence in NX. To prevent and mitigate the occurrence of drought disasters in NX, agricultural and government managers should pay more attention to those drought events that occur in spring and summer.     

Responses of leaf water potential and gas exchange to the precipitation manipulation in two shrubs on the Chinese Loess Plateau

Regulation of leaf gas exchange plays an important role in the survival of trees and shrubs under future climate change. However, the responses of leaf water potential and gas exchange of shrubs in semi-arid areas to the precipitation alteration are not clear. Here, we conducted a manipulated experiment with three levels of precipitation, i.e., a control with ambient precipitation, 50% above ambient precipitation(irrigation treatment), and 50% below ambient precipitation(drought treatment), with two common shrubs, Salix psammophila C. Wang & C. Y. Yang(isohydric plant, maintaining a constant leaf water potential by stomatal regulation) and Caragana korshinskii Kom.(anisohydric plant, having more variable leaf water potential), on the Chinese Loess Plateau in 2014 and 2015. We measured the seasonal variations of predawn and midday leaf water potential(Ψpd and Ψmd), two parameters of gas exchange, i.e., light-saturated assimilation(An) and stomatal conductance(gs), and other foliar and canopy traits. The isohydric S. psammophila had a similar An and a higher gs than the anisohydric C. korshinskii under drought treatment in 2015, inconsistent with the view that photosynthetic capacity of anisohydric plants is higher than isohydric plants under severe drought. The two shrubs differently responded to precipitation manipulation. Ψpd, An and gs were higher under irrigation treatment than control for S. psammophila, and these three variables and Ψmd were significantly higher under irrigation treatment and lower under drought treatment than control for C. korshinskii. Leaf water potential and gas exchange responded to manipulated precipitation more strongly for C. korshinskii than for S. psammophila. However, precipitation manipulation did not alter the sensitivity of leaf gas exchange to vapor-pressure deficit and soil moisture in these two shrubs. Acclimation to long-term changes in soil moisture in these two shrubs was primarily attributed to the changes in leaf or canopy structure rather than leaf gas exchange. These findings will be useful for modeling canopy water-carbon exchange and elucidating the adaptive strategies of these two shrubs to future changes in precipitation.     

干旱区精河流域地表温度的模型反演研究

以精河流域绿洲为研究区,使用Landsat ETM⁺数据,采用单窗算法和普适性单通道算法对研究区地表温度进行反演,并将这两种算法的反演结果与研究区MODIS温度产品(MODIS LST)进行比较。结果表明：(1) 单窗算法和普适性单通道算法反演的结果总体趋势比较接近,研究区整体的平均温度相差约2k;(2) 采用改进型土壤调整植被指数(MSAVI)代替归一植被指数(NDVI)计算地表比辐射率可有效提高反演精度,并且同等条件下单窗算法的反演精度高于普适性单通道算法,两种算法的反演结果与MODIS LST的相关系数分别是0.9255和0.8651;(3) 在城镇区域,普适性单通道算法反演结果与MSAVI的相关性高于单窗算法,相关系数为0.8136,说明普适性单通道算法更适合干旱区大范围城镇地表温度的反演研究。     

基于SPI指数的宁夏中部干旱带1960—2012年干旱特征研究

研究宁夏中部干旱带的干旱特征可为区域农牧业发展和防灾减灾提供科学决策依据.利用1960-2012年的各站点气象观测资料,计算标准化降水指数(SPI),并借助集合经验模态分解、功率谱分析和重新标度极差分析等方法,对近50年来的干旱特征和变化趋势进行了研究.研究结果表明,宁夏中部干旱带在1960-2012年间发生中旱以上的干旱事件达到了总干旱次数的30％以上;干旱波动周期的多尺度分解显示,该区域存在着0.5a尺度的轻旱,1 a尺度的中旱,3a尺度的重旱和10 a尺度的特旱;平均干旱强度的年际波动周期特征中,有平均超过65％的贡献来自于3.25-4 a左右的干旱周期波动,而平均超过14％的贡献来自于5.78-6.5 a左右的干旱周期波动;总体来看,宁夏中部干旱带的干旱趋势处于增强态势,且具有长程依赖性,即未来还将持续干旱,但不同季节的干旱趋势特征又表现出一定的差异.     

Land surface temperature retrieval for arid regions based on Landsat-8 TIRS data:a case study in Shihezi,Northwest China

Scientific interest in geophysical information about land surface temperature （LST） is ever increasing, as such information provides a base for a large number of applications, including environmental and agricultural monitoring. Therefore, the research of LST retrieval has become a hot topic. Recent availability of Landsat-8 satel- lite imagery provides a new data source for LST retrieval. Hence, exploring an adaptive method with reliable ac- curacy seems to be essential. In this study, basing on features of Landsat-8 TIRS thermal infrared channels, we re-calculated parameters in the atmospheric transmittance empirical models of the existing split-window algorithm, and estimated the ground emissivity with the help of the land cover classification map of the study area. Further- more, a split-window algorithm was rebuilt by virtual of the estimation model of the updated atmospheric transmit- tance and the ground emissivity, and then a remote sensing retrieval for the LST of Shihezi city in Xinjiang Uygur autonomous region of Northwest China was conducted on the basis of this modified algorithm. Finally, precision validation of the new model was implemented by using the MODIS LST products. The results showed that the LST retrieval from Landsat-8 TIRS data based on our algorithm has a higher credibility, and the retrieved LST is more consistent with the MODIS LST products. This indicated that the modified algorithm is suitable for retrieving LST with competitive accuracy. With higher resolutions, Landsat-8 TIRS data may provide more accurate observation for LST retrieval.     

基于主成分分析和层次分析法相结合的陕西省农业干旱风险评估

农业干旱灾害发生机理复杂,评价指标众多,为确定合理的干旱风险评价指标,以陕西省为研究对象,提出基于主成分分析和层次分析法(AHP)相结合的农业干旱风险评价指标体系和评估方法。运用主成分分析,结合陕西省干旱成因及特点,基于风险四要素(危险性、暴露性、脆弱性和抗旱能力)筛选并构建了农业干旱风险评价指标体系,采用AHP评估了陕西省农业干旱风险。结果表明,在考虑地区抗旱能力情况下,陕西省农业干旱风险从北向南,从东向西均呈现出递减趋势,北部榆林地区和东部渭南、商洛地区,农业干旱风险较高。通过主成分分析和AHP相结合的评价体系,可以合理选取评价指标,缩减指标个数;准确评估干旱风险,指出风险要素来源,为抗旱部门有效识别致灾因子,提出相应的抗旱减灾方法。     

基于Suomi NPP/VIIRS数据的青海省东部农业区夏季土壤水分监测模型的应用研究

土壤水分是量度干旱程度最重要的指标，如何对其有效监测与预警一直是各界致力解决的重大科学问题。基于Suomi NPP/VIIRS数据的温度植被干旱指数TVDI、归一化植被水分指数NDWI、植被状况指数VCI,分别构建了青海省东部农业区3种土壤水分监测模型，利用连续的野外定点观测数据及生态站点观测数据进行模型检验，并在2017年夏旱过程进行了应用检验。结果表明：2012—2016年模型回代检验中，TVDI指数模型表现最优(RMSE为4.4%),其次为VCI指数模型(RMSE为4.7%),NDWI指数模型表现最差(RMSE为5.2%);2018—2020年夏季互助遥感检验场定点观测检验中，TVDI指数模型表现最好(RMSE为3.8%),VCI指数模型次之(RMSE为5.0%),NDWI指数模型表现最差(RMSE为8.8%);2017年夏季干旱过程中，TVDI指数模型反演的旱情发展过程及分布范围与实际旱情情况相符，而NDWI指数模型反演的旱情分布范围明显偏小，VCI指数模型甚至不能反映旱情缓解、解除期的变化。     

Evaluation of CRU TS,GPCC, AgMERRA,and AgCFSR meteorological datasets for estimating climate and crop variables: A case study of maize in Qazvin Province,Iran

In the past few decades, meteorological datasets from remote sensing techniques in agricultural and water resources management have been used by various researchers and managers. Based on the literature, meteorological datasets are not more accurate than synoptic stations, but their various advantages, such as spatial coverage, time coverage, accessibility, and free use, have made these techniques superior, and sometimes we can use them instead of synoptic stations. In this study, we used four meteorological datasets, including Climatic Research Unit gridded Time Series (CRU TS), Global Precipitation Climatology Centre (GPCC), Agricultural National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications (AgMERRA), Agricultural Climate Forecast System Reanalysis (AgCFSR), to estimate climate variables, i.e., precipitation, maximum temperature, and minimum temperature, and crop variables, i.e., reference evapotranspiration, irrigation requirement, biomass, and yield of maize, in Qazvin Province of Iran during 1980-2009. At first, data were gathered from the four meteorological datasets and synoptic station in this province, and climate variables were calculated. Then, after using the AquaCrop model to calculate the crop variables, we compared the results of the synoptic station and meteorological datasets. All the four meteorological datasets showed strong performance for estimating climate variables. AgMERRA and AgCFSR had more accurate estimations for precipitation and maximum temperature. However, their normalized root mean square error was inferior to CRU for minimum temperature. Furthermore, they were all very efficient for estimating the biomass and yield of maize in this province. For reference evapotranspiration and irrigation requirement CRU TS and GPCC were the most efficient rather than AgMERRA and AgCFSR. But for the estimation of biomass and yield, all the four meteorological datasets were reliable. To sum up, GPCC and AgCFSR were the two best datasets in this study. This study suggests the use of meteorological datasets in water resource management and agricultural management to monitor past changes and estimate recent trends.     

干旱对苜蓿叶片葫芦巴碱含量和渗透调节能力的影响

以3个抗旱性不同的苜蓿品种(肇东、准葛尔和CW200 )为研究材料,研究了干旱胁迫下苜蓿叶片葫芦巴碱含量的变化和渗透调节能力.结果表明 :干旱胁迫下3个苜蓿品种叶片水势降低,脯氨酸含量增加,渗透调节能力(OA)提高.在干旱胁迫下,准葛尔和肇东两个品种叶片中葫芦巴碱含量明显增加,而CW200叶片中葫芦巴碱含量增加不明显;肇东和CW200在干旱4天后,准葛尔在干旱8天后,叶片中葫芦巴碱含量下降.因此,葫芦巴碱在轻度干旱下可能起到渗透调节物质的作用,严重干旱下该作用减弱.