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This research investigates spatiotemporal variations in ETo and the controlling factor of those variations using the modified Mann-Kendall test, empirical Bayesian kriging model, Morlet wavelet analysis (MWA), and cross-wavelet transform (XWT) model relying on daily climate data sets obtained from 18 meteorological stations for the period 1980–2017. Additionally, the stepwise linear regression analysis and partial correlation coefficient (PCC) were employed to determine the variables driving the changes in ETo. The investigation exhibited a decline in annual for −1.19 mm year−1 and seasonal (−0.40 mm decade−1 during pre-monsoon, −0.47 mm decade−1 during post-monsoon, −0.50 mm decade−1 during winter) ETo, which indicates the existence of “evapotranspiration paradox” in Bangladesh, similar to many regions across the globe. The trend test depicted that despite the increase in mean temperature (MT), a noteworthy decrease in sunshine duration (SD), and wind speed (WS) are the main reasons for the reduction in ETo. Spatial analysis of ETo revealed the highest annual values in the southwest while the lowest in the northwest. Two cycles, 1–3 and 3–5 years were found significant in the annual and seasonal ETo. The outcomes revealed coherence among ETo with meteorological factors at different time-frequency bands, which is noteworthy. Stepwise regression and PCC showed that the impact of meteorological factors on ETo varies on the annual and seasonal scales where MT, RH, and SD are the major factors responsible for the variations of ETo in both annual and seasonal scales. These outcomes of the research can be advantageous for designing irrigation and management of sustainable water resources to mitigate climate change impacts as well as controlling anthropogenic activities.

The Huai River Basin (HRB) has experienced significant climate and land use and land cover changes (LUCC) which have impacted the water cycle in recent times. However, little is understood about the impact of climate change and LUCC affecting evapotranspiration (ET). Thus, we investigate how surface ET response to climate change and LUCC in the HRB for the period from 2001 to 2014. ET and land cover types products (i.e., MOD16 and MCD12Q1, respectively) from MODerate-resolution Imaging Spectroradiometer (MODIS) were employed in this research. Water balance method and D20 pan evaporation data ( E pan ) as well as eddy covariance (EC) measurements were used to validate the MOD16 product, and the Theil–Sen’s slope estimator and Mann–Kendall (M-K) test were adopted to estimate the magnitude and significance of ET trends. Moreover, daily meteorological data of 137 weather stations from 2001 to 2014 were also employed to explore the correlation mechanism between ET and meteorological factors. The results showed that the accuracy of MOD16 product data were convincible and could be used to estimate ET in the HRB. The higher values of ET are mainly distributed in the south and lower values in the north. ET decreased significantly in all seasons except in spring, especially in winter. The results also depicted that the land-use type in the HRB is mainly croplands, followed by forests and grasslands. Croplands area showed a decreasing trend at a rate of −176.2 km 2 ·a −1 , grasslands area presents a w-type fluctuation decreasing trend with a rate of −35.8 km 2 ·a −1 , urban/built-up area increased at a rate of 138.3 km 2 ·a −1 , water bodies area decreased gradually at a rate of −1.38 km 2 ·a −1 , wetlands area increased significantly at a rate of 43.6 km 2 ·a −1 , and barren area decreased gradually at a rate of −9.5 km 2 ·a −1 . The average annual ET is closely related to land-use types and shows a significant downward trend in general. The corresponding ET magnitude is exhibited as follows: forests>grasslands>croplands>wetlands>water bodies>urban/build−up lands>barren. Results of the study also suggest water conditions (precipitation (Pre) and relative humidity (RH) decrease) are major controlling factors in the decline of ET. Overall, the LUCC has a smaller influence on ET than climate change in the HRB. This research will provide a better insight into climate change and LUCC impacts on water resources.

In the context of global climate change, the frequency of waterlogging is increasing. Therefore, to elucidate the effects of waterlogging under real precipitation conditions on the physiological characteristics of peanuts and the underlying mechanics and to provide a theoretical basis for timely protective measures, this study involved a waterlogging disaster simulation experiment in the field environment and a waterlogging stress control experiment in the potting environment. It was found that sufficient water had a positive effect on the growth and development of peanuts (Arachis hypogaea L.) during the 3–5 days period at the beginning of waterlogging. However, as the duration of waterlogging increased, excess water inhibited the growth of peanuts, with a stronger inhibitory effect on the development of pods. A comparison of the two different experimental models found that in the potting environment, water circulation was not smooth, and the intensity of waterlogging was higher than in the field environment experiment, resulting in the effect of waterlogging being advanced by one observation stage (2 days) in the potting environment. Furthermore, using a novel fluorescence imaging system, an analysis of variations in the physiological characteristics of leaf sections demonstrated that the chlorophyll fluorescence in the leaves of the peanut plant exhibited a specific pattern in response to waterlogging stress.

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.

Reference evapotranspiration (ETref) 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 ETref and through the differential equation and detrending method to determine sensitivities and the contributions of four meteorological parameters to ETref based on daily weather data from 60 stations of Jiangsu province during 1961–2015. Results reveal that ETref and its trends in the three sub-regions of the Jiangsu province had a significant spatial heterogeneity. A significant decreasing tendency of ETref (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 ETref 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 ETref was most sensitive, whereas ETref 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 ETref, followed by SD, while the positive contribution of TA to ETref could not offset the negative contributions of WS and SD. Although the effect of VP on changes in ETref is small, it could not be ignored, especially in the winter. The reverse relationship between increasing TA and decreasing ETref, 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 ETref to the provincial water planning and management in eastern China.

The precipitation enhancement operation data of aircraft from 2014 to 2019 and the global data assimilation system (NCEP GDAS) were used in this study. The transport process of the transmission of artificial precipitation enhancement seeding agents for aircraft was successfully simulated by the HYSPLIT model. The purpose of the study was to explore the applicability of the model in determining the artificial precipitation enhancement influence area and provide a technical method for evaluating the effect of artificial precipitation enhancement. The results show that (1) the HYSPLIT model can be used to track the transmission of aircraft precipitation enhancement seeding agents hourly. Suppose the seeding route satisfies the condition that the route and its interval area are the effective seeding area within 3 h after the end of the seeding agent. In that case, the seeding area’s boundary points can be used as dynamic change markers in the influence area. (2) The HYSPLIT model was used to simulate 24 aircraft precipitation enhancement seeding agent transmission processes. The transmission path for the seeding agent influence altitude layer was mostly southwest or west; the angle ranged from 225° to 268°; the horizontal transport distance of the seeding agent for three hours was 100–200 km; the vertical transmission direction was mostly upward; the range was 0–1200 m; the influence area decreased at the third h of seeding agent transport for 71% of the precipitation enhancement operations. (3) Based on the dynamic variations of 24 aircraft precipitation affected areas determined by the HYSPLIT model, and the contrast area selected by the similarity measurement method, 15 (63%) aircraft precipitation operations contributed to the increase in precipitation.

Water vapor transport is an important foundation and prerequisite for the occurrence of rainstorms. Consequently, the understanding of water vapor transport as well as the sources of water vapor during rainstorm processes should be considered as essential to study the formation mechanism of rainstorms. In this study, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model is adopted for backward tracking of water vapor transport trajectories and sources during the “7·20” extraordinary heavy rain process in Zhengzhou City of China that occurred on 20 July 2021. On this basis, the trajectory clustering method is applied to quantitatively analyze the contributions of water vapor sources, aiming to provide a basis for exploring the maintenance mechanism of this extreme rainstorm event. The spatio-temporal characteristics of this rainstorm event show that there are 4 consecutive days with the precipitation reaching or exceeding the rainstorm level across the whole Zhengzhou City, with the daily rainfall amounts at eight national meteorological stations all breaking their respective historical extreme values. The regional-averaged rainfall amount in Zhengzhou City is 527.4 mm, while the maximum accumulated rainfall amount reaches 985.2 mm at Xinmi station and the maximum hourly rainfall amount at Zhengzhou national meteorological station reaches 201.9 mm h−1. The water vapor sources for this rainfall process, ranked in descending order of contribution, are the Western Pacific, inland areas of Northwest China and South China, and South China Sea. The water vapor at lower levels is mainly transported from the Western Pacific and the South China Sea, while those from the inland areas of Northwest China and South China provide a supply of water vapor at upper levels to a certain extent. The water vapor at 950 hPa is mainly sourced from the Western Pacific and South China Sea, accounting for 56% and 44%, respectively. The water vapor at 850 hPa mainly derives from the Western Pacific and the inland areas of South China, contributing 58% and 34% of the total, respectively. The water vapor at 700 hPa mainly comes from the inland areas of Northwest China and South China Sea. Specifically, the water vapor from inland Northwest China contributes 44% of the total, acting as the primary source. The water vapor at 500 hPa is mainly transported from the inland areas of South China and Northwest China, with that from the inland South China (56%) being more prominent. The water vapor at all levels is mainly transported to the rainstorm region through the eastern and southern regions of China from the source areas. Additionally, there are some differences in the water vapor trajectories at a 6 h interval.

Reference evapotranspiration (ETref) 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 ETref 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 ETref and climate factors. Furthermore, a developed differential equation method based on the FAO-56 PM model was applied to quantify the sensitivities of ETref to meteorological factors and their contributions to ETref trends. The results showed that the ETref demonstrated a strong spatially heterogeneity in the whole HRB at each time scale. ETref 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 ETref 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 ETref 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 ETref 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 ETref there.

In the published publication [...]

Reference evapotranspiration (ET0) is essential for agricultural production and crop water management. The recent climate change affecting the spatiotemporal variation of ET0 in eastern China continues to still be less understood. For this purpose, the latest observed data from 77 meteorological stations in Anhui province were utilized to determine the spatiotemporal variations of ET0 by the use of the Penman–Monteith FAO 56 (PMF-56) model. Furthermore, the Theil–Sen estimator and the Mann–Kendall (M–K) test were adopted to analyze the trends of ET0 and meteorological factors. Moreover, the differential method was employed to explore the sensitivity of ET0 to meteorological factors and the contributions of meteorological factors to ET0 trends. Results show that the ET0 decreased significantly before 1990, and then increased slowly. The ET0 is commonly higher in the north and lower in the south. ET0 is most sensitive to relative humidity (RH), except in summer. However, in summer, net radiation (Rn) is the most sensitive factor. During 1961–1990, Rn was the leading factor annually, during the growing season and summer, while wind speed (u2) played a leading role in others. All meteorological factors provide negative contributions to ET0 trends, which ultimately lead to decreasing ET0 trends. During 1991–2019, the leading factor of ET0 trends changed to the mean temperature (Ta) annually, during the growing season, spring and summer, and then to Rn in others. Overall, the negative contributions from u2 and Rn cannot offset the positive contributions from Ta and RH, which ultimately lead to slow upward ET0 trends. The dramatic drop in the amount of u2 that contributes to the changes in ET0 in Region III is also worth noting.