Drought and salinity stress are considered to be the two main factors limiting crop productivity. With climate change, these stresses are projected to increase, further exacerbating the risks to global food security. Consequently, to tackle this problem, better agricultural management is required on the basis of improved drought and salinity stress monitoring capabilities. Remote sensing makes it possible to monitor crop health at various spatiotemporal scales and extents. However, remote sensing has not yet been used to monitor both drought and salinity stresses simultaneously. The aim of this paper is to review the current ability of remote sensing to detect the impact of these stresses on vegetation indices (VIs) and crop trait responses. We found that VIs are insufficiently accurate (0.02 ≤ R² ≤ 0.80) to characterize the crop health under drought and salinity stress. In contrast, we found that plant functional traits have a high potential to monitor the impacts of such stresses on crop health, as they are more in line with the vegetation processes. However, we also found that further investigations are needed to achieve this potential. Specifically, we found that the spectral signals concerning drought and salinity stress were inconsistent for the various crop traits. This inconsistency was present (a) between studies utilizing similar crops and (b) between investigations studying different crops. Moreover, the response signals for joint drought and salinity stress overlapped spectrally, thereby significantly limiting the application of remote sensing to monitor these separately. Therefore, to consistently monitor crop responses to drought and salinity, we need to resolve the current indeterminacy of the relationships between crop traits and spectrum and evaluate multiple traits simultaneously. Using radiative transfer models (RTMs) and multi-sensor frameworks allow monitoring multiple crop traits and may constitute a way forward toward evaluating drought and salinity impacts.

Drought impact monitoring is of crucial importance in light of climate change. However, we lack an understanding of the concomitant responses of ecosystems to a variety of drought characteristics and the links between drought and ecosystem anomaly characteristics for a comprehensive set of vegetation types to provide needed information for water management. In response, this study presents a new framework that allows us to explore the relationship between drought and its impact on ecosystems in greater detail. Specifically, our framework focuses on estimating jointly the hydrological and ecosystem temporal evolution and anomalies around a drought event using four pairs of metrics: onset-onset, duration-duration, intensity-intensity, and severity-severity of drought and vegetation damage. Additionally, we incorporated a metric on vegetation vulnerability based on changes in damage severity along a gradient of increasing drought severity. Based on this framework, we evaluated drought vulnerability patterns of various vegetation types across the Netherlands and Belgium in 2018 at high spatiotemporal resolution. Our results reveal a differential vulnerability of vegetation between ecosystems with increasing drought severity, which could aid future drought impact predictions. In particular, mosaic grasslands and tree/shrub croplands are highly sensitive to increasing drought severity. Individual characteristics (onset, duration, intensity and severity) of drought and vegetation damage behave differently in various vegetation types. For instance, broadleaved forests respond faster than other forests, while mixed forests suffer less damage than other types. The early warning threshold to drought for most vegetation types is around a Standardized Precipitation Evapotranspiration Index (SPEI) value of -1. The characterization of a suite of drought response characteristics through our impact analysis framework can be used in a wide variety of regions to understand current and possible future responses to drought.

Buckwheat is a promising pseudo cereal and its cultivation history can be traced back to thousands of years ago in China. Nowadays, buckwheat is not only an ordinary crop but also a symbol of healthy life because of its rich nutritional and pharmacological properties. In this research, the current suitable areas of 19 wild buckwheat species were analyzed by the MaxEnt model, which proved that southwestern China was the diversity center of buckwheat. Their morphological characteristics and geographical distribution were analyzed for the first time. In addition, it was found that the change of buckwheat cultivation in three periods might be related to the green revolution of main crops and national policies. Meanwhile, the Sustainable Yield Index (SYI) value of buckwheat in China was the lowest from 1959 to 2016. Through the MaxEnt model, the potentially suitable areas of wild buckwheat would contract while cultivated buckwheat would expand under climate change. Accordingly, the diversity of wild buckwheat will decrease. Therefore, it is necessary to protect buckwheat resources as much as possible to strengthen the development and utilization of buckwheat resources. Moreover, the promotion of buckwheat diversity will be an important trade-off between food security, population growth, and land use under climate change.

Global sustainable agricultural systems are under threat, due to increasing and co-occurring drought and salinity stresses. Combined effects of these stresses on agricultural crops have traditionally been evaluated in small-scale experimental studies. Consequently, large-scale studies need to be performed to increase our understanding and assessment of the combined impacts in agricultural practice in real-life scenarios. This study aims to provide a new monitoring approach using remote-sensing observations to evaluate the joint impacts of drought and salinity on crop traits. In our tests over the Netherlands at large spatial scale (138.74 km²), we calculated five functional traits for both maize and potato from Sentinel-2 observations, namely leaf area index (LAI), the fraction of absorbed photosynthetically active radiation (FAPAR), the fraction of vegetation cover (FVC), leaf chlorophyll content (Cab), and leaf water content (Cw). Individual and combined effects of the stresses on the seasonal dynamics in crop traits were determined using both one-way and two-way analyses of variance (ANOVAs). We found that both stresses (individual and co-occurring) affected the functional traits of both crops significantly (with R² ranging from 0.326 to 0.796) though with stronger sensitivities to drought than to salinity. While we found exacerbating effects within co-occurrent stresses, the impact level depended strongly on the moment in the growing season. For both crops, LAI, FAPAR, and FVC dropped the most under severe drought stress conditions. The patterns for Cab and Cw were more inhibited by co-occurring drought and salinity. Consequently, our study constitutes a way towards evaluating drought and salinity impacts in agriculture, with the possibility of potential large-scale application for sustainable food security.

Global sustainable agricultural systems are under threat, due to projected increases of co-occurring drought and salinity with climate change. Combined effects of drought and salinity on agricultural crops have traditionally been evaluated in small-scale experimental studies. As such the need exists for large scale studies that increase our understanding and assessment of the combined impacts in agricultural practice in real life scenarios. This study aims to provide a new approach to estimate and compare the impacts of drought, salinity and their combination on crop traits at large spatial (138.74 km²) and temporal extents in the Netherlands using remote sensing observations. Specifically, for both maize and potato, we calculated five functional traits from Sentinel-2 observations, namely: leaf area index (LAI), the fraction of absorbed photosynthetically active radiation (FAPAR), the fraction of vegetation cover (FVC), leaf chlorophyll content (Cab) and leaf water content (Cw). Individual and combined effects of the stresses on the seasonal dynamics in crop traits were determined using both one-way and two-way ANOVAs. We found that both stresses (individual and co-occurring) affected the functional traits of both crops significantly (with R² ranging from 0.326 to 0.796), though with stronger sensitivities to drought than to salinity. While we found exacerbating effects within co-occurrent stresses, the impact-level depended strongly on the moment in the growing season. For both crops, LAI, FAPAR and FVC dropped the most under severe drought stress conditions. The patterns for Cab and Cw were more inhibited by co-occurring drought and salinity. Consequently, our study constitutes a way towards evaluating drought and salinity impacts in agriculture with the possibility of potential large-scale application for a sustainable food security.