Accurate measurement of leaf chlorophyll concentration (LChl) in the field using a portable chlorophyll meter (PCM) is crucial to support methodology development for mapping the spatiotemporal variability of crop nitrogen status using remote sensing. Several PCMs have been developed to measure LChl instantaneously and non-destructively in the field, however, their readings are relative quantities that need to be converted into actual LChl values using conversion functions. The aim of this study was to investigate the relationship between actual LChl and PCM readings obtained by three PCMs: SPAD-502, CCM-200, and Dualex-4. Field experiments were conducted in 2016 on four crops: corn (Zea mays L.), soybean (Glycine max L. Merr.), spring wheat (Triticum aestivum L.), and canola (Brassica napus L.), at the Central Experimental Farm of Agriculture and Agri-Food Canada in Ottawa, Ontario, Canada. To evaluate the impact of other factors (leaf internal structure, leaf pigments other than chlorophyll, and the heterogeneity of LChl distribution) on the conversion function, a global sensitivity analysis was conducted using the PROSPECT-D model to simulate PCM readings under different conditions. Results showed that Dualex-4 had a better performance for actual LChl measurement than SPAD-502 and CCM-200, using a general conversion function for all four crops tested. For SPAD-502 and CCM-200, the error in the readings increases with increasing LChl. The sensitivity analysis reveals that deviations from the calibration functions are more induced by non-uniform LChl distribution than leaf architectures. The readings of Dualex-4 can have a better ability to restrict these influences than those of the other two PCMs.

This study investigates the capability of spectral indices for estimating winter wheat leaf and canopy water content using radiative transfer modeling and field measurements. An irrigation treatment experiment was conducted to investigate response of crop growth to water supply in 2014 and 2015. Plant sampling and canopy spectral reflectance were measured in the two growing seasons. The main goal was to evaluate the potential of selected spectral indices formulated with the Sentinel-2 bands for winter wheat water status assessment. A global sensitivity analysis using reflectance simulated by the PROSPECT-5 and SAILH models showed that leaf water contributed the most to the variation of spectral water indices derived from leaf reflectance but had reduced contribution when the indices were derived from canopy reflectance. Correlation between canopy water content (C _{w, C} ) and canopy spectral water indices was significant, although it was impacted by canopy structural descriptors such as the leaf inclination angle and the leaf area index. Satisfactory estimation of w, C could be achieved using the normalized difference water index (NDWI) (R ² = 0.68, RMSE _cv = 0.148 kg·m ^-2 , and n = 463). The estimated C _{w, C} at the jointing stage was significantly correlated with grain yield. A map of C _{w, C} was generated from Sentinel-2 image acquired on March 30, 2016, showing spatial variation of winter wheat canopy water status comparable with the drought indicators reported by the Meteorological Bureau at the regional scale. It also showed variations at the field scale. Hence, there is a great potential to use the NDWI derived from Sentinel-2 data for detecting crop response to water stress and provide support to irrigation decision.

Changes in soil moisture and soil temperature result from the combined effects of several environmental factors. Scientific determination of the response characteristics of soil moisture and soil temperature to environmental factors is critical for adjusting the sloping land use structure and improving the ecological environment in China’s loess hilly region. Soybean sloping fields, maize terraced fields, jujube orchards, and grasslands in the loess hilly region were selected as the research areas. The change in characteristics of soil moisture and soil temperature, as well as their interactions and statistical relationships with meteorological factors, were analyzed using continuously measured soil moisture, soil temperature, and meteorological factors. The results revealed that air temperature and humidity were the main controlling factors affecting soil moisture changes in the 0–60 cm soil layer of soybean sloping fields and grasslands in the normal precipitation year (2014) and the dry year (2015). Humidity and wind speed were the main meteorological factors affecting soil moisture changes in the maize terraced field. Air temperature had a significant negative effect on soil moisture in the jujube orchard. Soil moisture and soil temperature were all negatively correlated under the four sloping land use types. In normal precipitation years, atmospheric humidity had the greatest direct and comprehensive effect on soil moisture in soybean sloping fields, maize terraced fields, and grasslands; soil temperature had a relatively large impact on soil moisture in jujube orchards. The direct and comprehensive effects of soil temperature on soil moisture under all sloping land use types were the largest and most negative in the dry year. Air temperature had a high correlation with soil temperature in the 0–60 cm soil layer under the four sloping land use types, and the grey relational grade decreased as the soil layer deepened. The coefficient of determination between the 0–20 cm soil temperature and air temperature in the maize terraced field was low, indicating a weak response to air temperature. The above findings can serve as a scientific foundation for optimizing sloping land use structures and maximizing the efficient and sustainable utilization of sloping land resources in China’s loess hilly region.