Increasing drought is considered one of the major threats associated with climate change in central Europe. To provide an objective, quantitative tool that represents current drought conditions, the Czech Drought Monitor System (CzechDM) was established in 2012. Like other drought monitoring systems worldwide, the CzechDM uses several approaches to provide drought data. However, the CzechDM is unique internationally due to its utilization of a network of voluntary reporters (farmers) who complete a weekly online questionnaire to provide information about soil water content and the impacts of drought on crop yield. In this study, the results from the questionnaires from individual farms were aggregated by district. Reporters’ data were compared and validated with the outputs of the SoilClim model (a core tool of the CzechDM) and with other drought monitoring tools, such as the water balance model, the soil water index and the evaporative stress index. The soil water content estimated by the reporters was significantly correlated (on average $r$ = 0.8) with the outputs of the SoilClim model. Conversely, the correlation between the drought impacts on yield estimated by the reporters and the SoilClim outputs was lower (on average $r$ = 0.4), suggesting that in situ observations by farmers provide additional insights into the occurrence of drought impacts. Importantly, it was found that farmers reported significant drought impacts on yield earlier in the season than any other methods (models or remote sensing). The main findings of this study are that the drought monitoring provided by reporters is a useful and reliable component of the CzechDM. We conclude that weekly reports by farmers represent a significant enhancement to drought monitoring and have potential for use in developing automated approaches that combine in situ, modeling and remote sensing data within a data fusion or machine learning framework.

日益严重的干旱被认为是与中欧气候变化相关的主要威胁之一。为了提供代表当前干旱状况的客观、定量工具，捷克干旱监测系统 (CzechDM) 于 2012 年成立。与全球其他干旱监测系统一样，捷克干旱监测系统使用多种方法来提供干旱数据。然而，CzechDM 在国际上是独一无二的，因为它利用了一个自愿记者（农民）网络，他们每周完成一份在线问卷，以提供有关土壤水分含量和干旱对作物产量影响的信息。在这项研究中，各个农场的问卷结果按地区汇总。记者的数据与 SoilClim 模型（捷克 DM 的核心工具）和其他干旱监测工具（如水平衡模型、土壤水分指数和蒸发应力指数）的输出进行了比较和验证。记者估算的土壤含水量显着相关（平均$r$ = 0.8) 与 SoilClim 模型的输出。相反，记者估计的干旱对产量的影响与 SoilClim 产出之间的相关性较低（平均$r$ = 0.4），这表明农民的实地观察为干旱影响的发生提供了额外的见解。重要的是，与其他任何方法（模型或遥感）相比，农民在本季早些时候报告了干旱对产量的显着影响。本研究的主要发现是，记者提供的干旱监测是捷克 DM 的一个有用且可靠的组成部分。我们得出结论，农民的每周报告代表了对干旱监测的显着增强，并且有可能用于开发自动化方法，将原位、建模和遥感数据结合在数据融合或机器学习框架内。