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Assessing the remotely sensed Drought Severity Index for agricultural drought monitoring and impact analysis in North China

机译:评估干旱干旱指数用于华北地区农业干旱监测和影响分析

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Remote sensing can provide real-time and dynamic information for terrestrial ecosystems, facilitating effective drought monitoring. A recently proposed remotely sensed Drought Severity Index (DSI), integrating both vegetation condition and evapotranspiration information, shows considerable potential for drought monitoring at the global scale. However, there has been little research on regional DSI applications, especially concerning agricultural drought. As the most important winter wheat producing region in China, North China has suffered from frequent droughts in recent years, demonstrating high demand for efficient agricultural drought monitoring and drought impact analyses. In this paper, the capability of the MODIS DSI for agricultural drought monitoring was evaluated and the drought impacts on winter wheat yield were assessed for 5 provinces in North China. First, the MODIS DSI was compared with precipitation and soil moisture at the province level to examine its capability for characterizing moisture status. Then specifically for agricultural drought monitoring, the MODIS DSI was evaluated against agricultural drought severity at the province level. The impacts of agricultural drought on winter wheat yield during the main growing season were also explored using 8-day MODIS DSI data. Overall, the MODIS DSI is generally effective for characterizing moisture conditions at the province level, with varying ability during the main winter wheat growing season and the best relationship observed in April during the jointing and booting stages. The MODIS DSI agrees well with agricultural drought severity at the province level, with better performance in rainfed-dominated than irrigation-dominated regions. Drought shows varying impacts on winter wheat yield at different stages of the main growing season, with the most significant impacts found during the heading and grain-filling stages, which could be used as the key alert period for effective agricultural drought monitoring. (C) 2015 Elsevier Ltd. All rights reserved.
机译:遥感可以为陆地生态系统提供实时和动态信息,从而促进有效的干旱监测。最近提出的遥感干旱严重性指数(DSI)结合了植被状况和蒸散信息,显示出在全球范围内进行干旱监测的巨大潜力。但是,关于区域DSI应用的研究很少,特别是在农业干旱方面。作为中国最重要的冬小麦产区,近年来华北地区遭受了频繁的干旱,这表明对高效农业干旱监测和干旱影响分析的需求很高。本文评估了MODIS DSI在农业干旱监测方面的能力,并评估了干旱对华北5个省份冬小麦产量的影响。首先,将MODIS DSI与省级降水和土壤水分进行比较,以检验其表征水分状况的能力。然后专门针对农业干旱监测,对MODIS DSI进行了省级农业干旱严重程度评估。还使用8天的MODIS DSI数据探讨了主要生长期期间农业干旱对冬小麦单产的影响。总体而言,MODIS DSI通常可以有效地描述省份的水分状况,在主要的冬小麦生长季节,其能力各不相同,并且在拔节和孕穗期的4月观测到的最佳关系是最佳的。 MODIS DSI与省级农业干旱的严重程度非常吻合,在雨养为主的地区比灌溉为主的地区表现更好。在主要生长期的不同阶段,干旱表现出对冬小麦单产的不同影响,在抽穗期和灌浆期发现的影响最为显着,这可以用作有效监测农业干旱的关键预警期。 (C)2015 Elsevier Ltd.保留所有权利。

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