干旱是中国发生最频繁、影响范围最广、造成损失最大的自然灾害之一。干旱的频繁发生和长期持续，不仅会给社会经济特别是农业生产带来巨大的损失，还会造成水资源短缺、荒漠化加剧、沙尘暴频发等诸多生态和环境方面的不利影响。渭河流域地处中国西北地区东部，旱灾频发，对当地水资源管理、生态环境和社会经济造成巨大影响。因此，系统揭示渭河流域干旱时空分布特征，厘清植被对典型干旱事件的响应规律，量化干旱对作物产量的影响，对于理解气候变化的影响和开展流域防灾减灾管理具有重要意义。本研究以渭河流域为研究区，基于多尺度标准化降水蒸散指数（Standardized Precipitation Evapotranspiration Index, SPEI），分析1980−2018年的干旱时空分布特征，以0.05°空间分辨率的日光诱导叶绿素荧光（Solar-induced Chlorophyll Fluorescence, SIF）数据作为植被生长状况的指标，辨识了冬小麦对典型干旱事件的响应过程，利用相关分析和五年时间窗口方法，定量评估了干旱对冬小麦产量的影响。本文的主要研究成果如下：

（1）利用渭河流域25个气象站点1980−2018年月值气象数据集，基于Penman-Monteith蒸散模型计算多个时间尺度SPEI，分析渭河流域气象干旱的演变、趋势、影响范围、发生频率和持续时间等时空变化特征。结果表明：1980−2018年渭河流域有明显的干湿周期变化，但整体上呈变干的趋势，干旱时段主要集中在1995−2009年，其中以2000−2009年的干旱站次比最大，平均达到36%，且干旱持续时间最长，约3.6个月，1980−1989年干旱持续时间最短，约1.6个月。渭河流域秋季总体呈湿润变化趋势，而春季和夏季干旱在不断加剧，是区域年际干旱的主要驱动力。渭河流域干旱以危害性较小的轻中旱为主，但2000年前后出现严重及极端干旱的站次相对较多。不同时间尺度各等级干旱发生频率的变化规律表现一致，均呈现出干旱等级越高发生频率越低的态势，且极端干旱在年际尺度内发生次数较为频繁，从空间上看渭河流域东北部是干旱多发区。

（2）选取渭河流域在2000−2018年内发生的一次典型干旱事件，以GOSIF高精度数据作为植被生长状况的指标来辨识研究区冬小麦对此次干旱事件的响应过程。结果表明：在渭河流域2004年2−7月的典型干旱事件中，4月份的干旱等级最高，影响面积最广，70.19%的区域SIF表现出较为明显的负异常；此次干旱中冬小麦从2月开始就低于SIF参考值，表明冬小麦SIF对干旱的响应最及时，并于7月SIF下降比例达到最大值为18.44%，这表明此次干旱事件严重影响了该地区冬小麦的生长，且其影响几乎贯穿了冬小麦的整个生长发育阶段，这可能威胁到该年渭河流域的冬小麦产量。另外，当渭河流域处于干旱事件末期的轻中旱状态时，SIF负异常却达到了最大值-3.310，表明SIF在干旱监测方面的灵敏性极高，即GOSIF数据在监测渭河流域植被尤其是冬小麦作物植被对干旱的响应方面具有很大的潜力。

（3）利用Pearson相关方法探究不同时间尺度SPEI对粮食作物及冬小麦气象产量的影响，并建立五年时间窗口分析各地级市每一次干旱事件对冬小麦产量的影响，统计评估不同等级干旱引起的冬小麦产量变化。结果表明：各时间尺度SPEI与粮食气象产量在1−12月份内主要呈正相关关系，但与冬小麦气象产量的相关系数主要在冬小麦生长季节内为正，且长期干旱对冬小麦气象产量的影响更为显著，尤其是在冬小麦的生长中后期阶段。冬小麦生育阶段中的分蘖期和返青−扬花期对干旱最为敏感，此时发生干旱将严重影响该年的冬小麦产量。1990−2018年内不同等级干旱造成的冬小麦产量变化率空间上均呈北重南轻、西重东轻的分布特征，且干旱等级越高，冬小麦减产程度越高。另外，在灌溉区冬小麦存在减产情况，但减产程度相比于雨养区更轻，这表明灌溉农业的发展对于干旱带来的减产效应具有缓解作用，但无法完全缓解干旱的影响。

Drought is one of the natural disasters that occur most frequently, have the widest impact and cause the greatest losses in China. The frequent and long-lasting droughts have not only brought huge losses to the social economy, especially agricultural production, but also caused many adverse effects on the ecological environment such as water shortage, desertification, and sandstorms. The Wei River Basin is located in the eastern part of Northwest China, and droughts are frequent in this region, which has a great impact on local water resources management, ecological environment and social economy. Therefore, systematically revealing the spatial- temporal characteristics of drought in the Wei River Basin, clarifying the response discrepancies of different vegetation types to a typical drought event, and quantifying the impact of drought on crop yield are of great significance for understanding the influence mechanism of climate change and carrying out disaster prevention and mitigation management in the basin. In this study, the spatial-temporal characteristics of drought in the Wei River Basin from 1980 to 2018 were analyzed based on the multi-scale Standardized Precipitation Evapotranspiration Index (SPEI), and the response of winter wheat to a typical drought event was identified by using the solar-induced Chlorophyll Fluorescence (SIF) data with a spatial resolution of 0.05° as an indicator of vegetation growth. Moreover, the Pearson correlation and five-year time window method were used to quantitatively evaluate the impact of drought on winter wheat yield. The main research results are as follows:

(1) Based on the monthly meteorological data set of 25 stations in the Wei River Basin from 1980 to 2018 and the Penman-Monteith equation, the SPEI of multiple time scales were calculated, and the spatial-temporal characteristics of drought were analyzed, including its evolution, trend, affected area, frequency and duration. The results showed that there was an obvious periodic variation of dry-wet status in the Wei River Basin during the past 39 years, but a drying trend was appeared as a whole. The drought period was mainly concentrated in 1995−2009, among which the drought occurring stations ratio in 2000−2009 was the largest, with an average value of 36%. The longest drought duration was occurred in 2000−2009, about 3.6 months, and the shortest drought duration was occurred in1980−1989, about 1.6 months. There was a trend of wetness in autumn, while the droughts in spring and summer was increasingly intensified, which was the main driving force of the inter-annual drought in the Wei River Basin. The droughts in the Wei River Basin were dominated by mild and moderate droughts, but there were relatively more stations with severe and extreme droughts around 2000. The variation of drought frequency for different drought levels at different time scales was consistent, showing that the higher the drought level, the lower the frequency. In addition, extreme droughts occurred more frequently at the annual scale, and the northeastern region of the Wei River Basin was a drought-prone area in space.

(2) A typical drought event occurred from 2000 to 2018 in the Wei River Basin was selected, and the high-precision GOSIF data were used as the indicator of vegetation growth to identify the response of winter wheat to this drought event. The results showed that during the typical drought event in the Wei River Basin from February to July in 2004, the drought level in April was the highest and the affected area was the most extensive, and 70.19% of the vegetation-covered area exhibited large negative SIF standardized anomalies. Moreover, SIF of winter wheat was lower than the SIF reference value since February, which demonstrated that SIF of winter wheat had the timeliest response to drought; in July, the SIF value decreased the most, reaching 18.44%, indicating that the drought has seriously affected the growth of winter wheat, and its impact almost throughout the entire growing season of winter wheat, which may threaten the winter wheat yield in the Wei River Basin this year. In addition, when the study area was in a state of mild to moderate drought at the end of the drought event, the SIF negative anomalies reached the maximum value of -3.310, indicating that the sensitivity of SIF in drought monitoring is extremely high, that is, GOSIF has great potential for monitoring the response of vegetation to drought in the Wei River Basin.

(3) The Pearson correlation method was used to explore the impact of the multi-scale SPEI on the climatic yield of crops and winter wheat, and a five-year time window was established to analyze the impact of each drought event on winter wheat yield in each city, and quantitatively evaluate the changes in winter wheat yield caused by different levels of drought. The results showed that the multi-scale SPEI and climatic yield of crops were mainly positively correlated from January to December, but the correlation coefficients between SPEI and climatic yield of winter wheat were mainly positive in the growing season, and the long-term drought had a greater impact on winter wheat climatic yield, especially in the middle and late growth stages. The tillering stage and the regreening-flowering stage in the growth of winter wheat were the most sensitive to drought, and the occurrence of drought at this time would seriously affect the winter wheat yield in that year. The yield change rates caused by different grades of drought in 1990−2018 all showed a spatial distribution that heavier in the north than in the south, and heavier in the west than in the east. The higher the drought grade was, the higher the yield reduction of winter wheat was. In addition, there was a decrease in winter wheat yield in the irrigated area, but the decrease degree was lighter than that in the rain-fed area, which indicated that the development of irrigated agriculture could alleviate the yield reduction effect caused by drought, but could not completely alleviate the impact of drought.

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