Reference evapotranspiration (ET_ref) is a key parameter of hydro-meteorological studies as well as water resource planning. In this study, we adopted the Penman–Monteith FAO 56 model to estimate ET_ref and through the differential equation and detrending method to determine sensitivities and the contributions of four meteorological parameters to ET_ref based on daily weather data from 60 stations of Jiangsu province during 1961–2015. Results reveal that ET_ref and its trends in the three sub-regions of the Jiangsu province had a significant spatial heterogeneity. A significant decreasing tendency of ET_ref (p < 0.001) was observed in the Huaibei region, while a slightly increasing tendency was identified in the Jianghuai and Sunan regions. These changes of ET_ref were caused by a significant increasing trend in air temperature (TA) and significant decreasing trends in wind speed (WS), sunshine duration (SD) as well as a non-significant change trend in actual vapor pressure (VP). However, the VP was the meteorological parameter to which ET_ref was most sensitive, whereas ET_ref was more sensitive to TA and SD in the summer but less so in the winter; the least sensitive factor, WS, had the opposite trend. Across the whole region, WS contributed most to ET_ref, followed by SD, while the positive contribution of TA to ET_ref could not offset the negative contributions of WS and SD. Although the effect of VP on changes in ET_ref is small, it could not be ignored, especially in the winter. The reverse relationship between increasing TA and decreasing ET_ref, namely the “evaporation paradox,” occurred in Jiangsu province. Thus, the outcomes of this study will contribute to thorough insight into the response to changes in ET_ref to the provincial water planning and management in eastern China.

In this study, we evaluated the effectiveness of photochemical reflectance index (PRI) and non-photochemical quenching (NPQ) for assessing water stress in maize for the purpose of developing remote sensing techniques for monitoring water deficits in crops. Leaf-level chlorophyll fluorescence and canopy-level PRI were measured concurrently over a maize field with five different irrigation treatments, ranging from 20% to 90% of the field capacity (FC). Significant correlations were found between leaf-level NPQ (NPQ_leaf) and the ratio of chlorophyll to carotenoid content (Chl/Car) (R² = 0.71, p < 0.01) and between NPQ_leaf and the actual photochemical efficiency of photosystem II (ΔF/F_m′) (R² = 0.81, p < 0.005). At the early growing stage, both canopy-level PRI and NPQ_leaf are good indicators of water stress (R² = 0.65 and p < 0.05; R² = 0.63 and p < 0.05, respectively). For assessment of extreme water stress on plant growth, a relationship is also established between the quantum yield of photochemistry in PSII (ΦP) and the quantum yield of fluorescence (ΦF) as determined from photochemical quenching (PQ) and non-photochemical quenching (NPQ_leaf) of excitation energy at different water stress levels. These results would be helpful in monitoring soil water stress on crops at large scales using remote sensing techniques.

Accurate terrestrial evapotranspiration (ET) estimation and understanding the causes of ET variation are essential for water resource management and irrigation planning. In this research, the complementary relationship (CR) between actual evapotranspiration (ET_a) and potential evapotranspiration (ET_p) was evaluated. An Advection–Aridity (AA) model was calibrated and validated using eddy covariance measurements. The spatiotemporal variations of ET_a, ET_p and associated meteorological variables were examined through Mann–Kendall (MK) testing and Theil–Sen's estimator, using daily weather data from 137 meteorological stations in Huai River basin (HRB) during 1961–2014. Moreover, the influences of meteorological factors on ET_a and ET_p were quantified by the differential equation method. The results indicate that CR theory is applicable in the HRB and the calibrated AA model can simulate the ET_a well. ET_a exhibited a significant increasing trend before 1990 and then decreased significantly. However, ET_p decreased significantly before 1990 and then declined slightly. During 1961–1990, except for significant increasing relative humidity (RH), other meteorological variables exhibited decreasing trends. The aerodynamic component dominated ET_a and ET_p trends in general. The wind speed at 2‐m height (u₂) dominated ET_a trends except for summer and growing season and ET_p trends except for summer, when the dominant factor is net radiation (R _n). During 1991–2014, mean temperature (T _a) and RH showed distinct increasing and decreasing trends, respectively, whereas significant decline in u₂ palpably slowed. The absolute value of the radiative component was larger than that of the aerodynamic one. The dominant factor of ET_a trends shifted from u₂ to RH in spring and to R _n in autumn, winter and annual timescales. Moreover, the dominant factor of ET_p trends changed from u₂ to RH in spring, winter and annual timescales and to R _n in growing season and autumn. R _n always played a pivotal role in both ET_a and ET_p trends in summer.

Reference evapotranspiration (ET_ref) is an important study object for hydrological cycle processes in the context of drought-flood risks of the Huai River Basin (HRB). In this study, the FAO-56 Penman–Monteith (PM) model was employed to calculate seasonal and annual ET_ref based on 137 meteorological station data points in HRB from 1961 to 2014. The Mann–Kendall (MK) trend analysis was adopted together with Theil–Sen’s estimator to detect tendencies of ET_ref and climate factors. Furthermore, a developed differential equation method based on the FAO-56 PM model was applied to quantify the sensitivities of ET_ref to meteorological factors and their contributions to ET_ref trends. The results showed that the ET_ref demonstrated a strong spatially heterogeneity in the whole HRB at each time scale. ET_ref showed a significant decreasing trend in the upper-middle HRB and Yi-Shu-Si River Basin, especially at the annual time scale, in growing season and summer, while a generally increasing trend in ET_ref was detected in the lower HRB, and the significance only showed in spring. These phenomena could be reasonably explained by a significantly increasing mean temperature (TA), a significantly decreasing wind speed (WS), solar radiation (SR), and a slightly decreasing relative humidity (RH). The most sensitive factor to ET_ref was RH in most sub-regions and most time scales, except in the growing season and summer. Based on the developed differential equation method, the dominant factor of the decreasing ET_ref was WS in the annual time scale, spring, autumn, and winter in most sub-regions, except the lower HRB, which then shifted to SR in the growing season and summer. However, in the lower HRB, the significantly decreasing RH was the most dominant factor, especially in the annual time scale, growing season, and spring, which might be responsible for the slightly increasing ET_ref there.

Monitoring drought precisely and evaluating drought effects quantitatively can establish a scientific foundation for understanding drought. Although solar-induced chlorophyll fluorescence (SIF) can detect the drought stress in advance, the performance of SIF in monitoring drought and assessing drought-induced gross primary productivity (GPP) losses from lush to senescence remains to be further studied. Taking the 2019 drought in the middle and lower reaches of the Yangtze River (MLRYR) as an example, this study aims to monitor and assess this drought by employing a new global, OCO-2-based SIF (GOSIF) and vegetation indexes (VIs). Results showed that the GPP, GOSIF, and VIs all exhibited significant increasing trends during 2000–2020. GOSIF was most consistent with GPP in spatial distribution and was most correlated with GPP in both annual (linear correlation, R² = 0.87) and monthly (polynomial correlation, R² = 0.976) time scales by comparing with VIs. During July–December 2019, the precipitation (PPT), soil moisture, and standardized precipitation evapotranspiration index (SPEI) were generally below the averages during 2011–2020 and reached their lowest point in November, while those of air temperature (Tem), land surface temperature (LST), and photosynthetically active radiation (PAR) were the contrary. For drought monitoring, the spatial distributions of standardized anomalies of GOSIF and VIs were consistent during August–October 2019. In November and December, however, considering vegetation has entered the senescence stage, SIF had an obvious early response in vegetation physiological state monitoring compared with VIs, while VIs can better indicate meteorological drought conditions than SIF. For drought assessment, the spatial distribution characteristics of GOSIF and its standardized anomaly were both most consistent with that of GPP, especially the standardized anomaly in November and December. All the above phenomena verified the good spatial consistency between SIF and GPP and the superior ability of SIF in capturing and quantifying drought-induced GPP losses. Results of this study will improve the understanding of the prevention and reduction in agrometeorological disasters and can provide an accurate and timely method for drought monitoring.