Search

Satellite based remote sensing offers one of the few approaches able to monitor the spatial and temporal development of regional to continental scale droughts. A unique element of remote sensing platforms is their multi-sensor capability, which enhances the capacity for characterizing drought from a variety of perspectives. Such aspects include monitoring drought influences on vegetation and hydrological responses, as well as assessing sectoral impacts (e.g., agriculture). With advances in remote sensing systems along with an increasing range of platforms available for analysis, this contribution provides a timely and systematic review of multi-sensor remote sensing drought studies, with a particular focus on drought related datasets, drought related phenomena and mechanisms, and drought modeling. To explore this topic, we first present a comprehensive summary of large-scale remote sensing datasets that can be used for multi-sensor drought studies. We then review the role of multi-sensor remote sensing for exploring key drought related phenomena and mechanisms, including vegetation responses to drought, land-atmospheric feedbacks during drought, drought-induced tree mortality, drought-related ecosystem fires, post-drought recovery and legacy effects, flash drought, as well as drought trends under climate change. A summary of recent modeling advances towards developing integrated multi-sensor remote sensing drought indices is also provided. We conclude that leveraging multi-sensor remote sensing provides unique benefits for regional to global drought studies, particularly in: 1) revealing the complex drought impact mechanisms on ecosystem components; 2) providing continuous long-term drought related information at large scales; 3) presenting real-time drought information with high spatiotemporal resolution; 4) providing multiple lines of evidence of drought monitoring to improve modeling and prediction robustness; and 5) improving the accuracy of drought monitoring and assessment efforts. We specifically highlight that more mechanism-oriented drought studies that leverage a combination of sensors and techniques (e.g., optical, microwave, hyperspectral, LiDAR, and constellations) across a range of spatiotemporal scales are needed in order to progress and advance our understanding, characterization and description of drought in the future. • Multi-sensor observations provide advantages in addressing knowledge gaps. • Drought related remote sensing datasets are identified for multi-sensor studies. • Key drought phenomena and mechanisms benefiting from multi-sensors are highlighted. • Recent advances for multi-sensor drought monitoring models are synthesized. • Challenges and opportunities using multi-sensors for drought studies are provided. [ABSTRACT FROM AUTHOR]

• 17O-excess was used to distinguish dew equilibrium or kinetic fractionation. • Dew underwent kinetic fractionation associated with evaporation in Gobabeb. • Dew with temperature over 14.7 °C was influenced by evaporation in Indianapolis. • Dew did not experience significant evaporation in Nice. • Relative humidity is a main factor explaining different dew evaporation processes. With increasing aridity in many regions, dew is likely to play an increasingly important role in the ecohydrological processes in many ecosystems, especially in arid and semiarid regions. Few studies investigated the role of evaporation during dew formation and how it varies under different climate settings. 17O-excess, as a new tracer, could be used to extract information of evaporation dynamics from natural water samples (e.g., precipitation, river, and lake). Therefore, to fill the knowledge gap in evaporation mechanisms during dew formation, we report the isotopic variation (δ2H, δ18O, δ17O, and 17O-excess) of dew and precipitation from three distinct climatic regions (i.e., Gobabeb in the central Namib Desert, Nice in France with Mediterranean climate, and Indianapolis in the central United States with humid continental climate). We examined whether dew formed in different climate settings was affected by different degree of evaporation using observed isotopic values and evaporation models during the formation processes, and modeled the effects of key meteorological variables (i.e., temperature and relative humidity) on 17O-excess variations. The results showed that dew in Gobabeb experienced kinetic fractionation associated with evaporation under non-steady state conditions during dew formation with enriched δ18O and low 17O-excess values. Dew formations with temperatures over 14.7 °C in Indianapolis were also influenced by evaporation under non-steady state conditions. However, dew formation in Nice did not experience significant evaporation. Evaporation processes (equilibrium or kinetic fractionation) occurring during nights with heavy dew under three climate settings were mainly related to the variation of atmosphere relative humidity. The 17O-excess tracer provides a new method to distinguish the different evaporation processes (equilibrium or kinetic fractionation) during dew formation and our result provides an improved understanding of dew formation. [ABSTRACT FROM AUTHOR]

• A modified isotope-based method was developed to estimate the evapotranspiration partitioning, and it can be applied on various time scales. • The modified method and the traditional method are equivalent at a 15-minute time scale. • The modified method is capable of partitioning evapotranspiration at high-frequency and distributed the high sensitivity parameter δ ET into other three less sensitive parameters. • The high-frequency method is advantageous in avoiding the extrapolation of the keeling plot regression line, and enabling the calculation of confidence interval of evapotranspiration partition. • The high-frequency method might be useful when investigating evapotranspiration partitioning under short-term extreme weather events and flush agricultural irrigation. To better understand water and energy cycles, numerous efforts to partition evapotranspiration (ET) into evaporation (E) and transpiration (T) have been made over the recent half century. One of the analytical methods is the isotopic approach. The isotopic composition of ET (δ ET) is a crucial parameter in the traditional isotope-based ET partitioning model, which however, has considerable uncertainty and high sensitivity. Here we proposed a modified T fraction in total ET (F T) calculation using Keeling plot slope (k), the atmospheric vapor concentration (C v), and the isotopic composition of atmospheric vapor (δ v), to avoid the direct use of δ ET. Following the traditional method, we used the Craig-Gordon model for the isotopic composition of evaporation (δ E) and chamber method for the isotopic composition of transpiration (δ T) in our modified method. The modified F T calculation method (F T (m)) can be applied at a 15-min time scale using the average values (F Ti (mp)) and at a 1 Hz time scale for high-frequency method (F Ti). The modified method was verified by both theoretical derivations and field observations. F Ti (mp) was equivalent to those using the traditional isotopic method at a 15-min time scale. However, F Ti eliminated the highly sensitive parameter δ ET , and redistributed the sensitivity of δ ET into three less sensitive parameters. Additionally, F Ti has two main advantages. First, the high-frequency method avoids the extrapolation of the Keeling plot regression line intercept. Second, the high-frequency method can produce a 95% confidence interval of F T in a measurement cycle (e.g., 15 min). The calculated confidence interval was different from that of traditional uncertainty analysis. The high-frequency method might be useful when investigating evapotranspiration partitioning under short-term extreme weather events and flush agricultural irrigation. [ABSTRACT FROM AUTHOR]