###### Abstract  
Drought is one of the most devastating disasters and a serious constraint on agricultural development. The reflectance-based vegetation indices (VIs), such as Normalized Difference Vegetation Index (NDVI), have been widely used for drought monitoring, but there is a lag in the response of VIs to the changes of photosynthesis induced by drought. Solar-induced chlorophyll fluorescence (SIF) is closely related to photosynthesis of vegetation and can capture changes induced by drought timely. This study investigated the capability of SIF for drought monitoring. An intelligent irrigation control system (IICS) utilizing the Internet of Things was designed and constructed. The soil moisture of the experiment plots was controlled at 60-80% (well-watered, T1), 50-60% (mild water stress, T2), 40-50% (moderate water stress, T3) and 30-40% (severe water stress, T4) of the field water capacity using the IICS based on data collected by soil moisture sensors. Meanwhile, SIF, NDVI, Normalized Difference Red Edge (NDRE) and Optimized Soil Adjusted Vegetation Index (OSAVI) were collected for a long time series using an automated spectral monitoring system. The differences in the responses of SIF, NDVI, NDRE and OSAVI to different drought intensities were fully analyzed. This study illustrates that the IICS can realize precise irrigation management strategies and the construction of regulated deficit irrigation treatments. SIF significantly decreased under mild stress, while NDVI, NDRE and OSAVI only significantly decreased under moderate and severe stress, indicating that SIF is more sensitive to drought. This study demonstrates the excellent ability of SIF for drought monitoring and lays the foundation for the future application of SIF in agricultural drought monitoring. drought; SIF; vegetation index; winter wheat Article Exploring the Ability of Solar-Induced Chlorophyll Fluorescence for Drought Monitoring Based on an Intelligent Irrigation Control System  
[PERSON], [PERSON], [PERSON], [PERSON], [PERSON], X. Exploring the Ability of Solar-Induced Chlorophyll Fluorescence for Drought Monitoring Based on an Intelligent Irrigation Check for Updates
To implement irrigation strategies accurately, the levels of water stress must be clearly understood. According to the type of water stress, irrigation strategies can be implemented based on the soil water balance (WB), soil moisture monitoring methods, and plant water stress degrees [10]. The WB approach has been widely employed to determine irrigation requirements for various crops. In this method, the water input into the plant-soil system needs to be counterpoised with the output [11]. Crop evapotranspiration (ETc), which considers both soil evaporation and plant transpiration, is the most important component of the WB [12; 13]. ETc is estimated by the product of the crop coefficient Kc and the reference crop evapotranspiration (ETo). The formula is expressed as ETc = Kc \(\times\) ETo, where Kc estimates the amount of evapotranspiration by integrating the biophysical and physical differences between a reference plant and the target plant, while ETo expresses the requirements for crops under certain environmental conditions. The advantage of the WB-based irrigation method is that it can predict the water demand of crops at a specific growth stage, and the irrigation strategy can be reasonably adjusted according to this feature [14]. However, the accuracy of this method in terms of its practical applications is questioned, because even for specific crops, the value of Kc may vary due to planting density and direction [15], plant variety [16] and canopy structure [17]. In addition, it is difficult to accurately obtain the parameters of the WB method. Therefore, the simple irrigation strategy is based on soil moisture measurements. By setting upper and lower thresholds, irrigation begins when the soil moisture decreases to the lower threshold, and irrigation stops when the soil moisture rises to the upper threshold [18; 19].