Terrestrial water energy coupling (WEC), in the form of the non-linear relationship between Soil Moisture (SM) and evaporative fraction (EF, ratio of actual and potential evapotranspiration), controls critical ecohydrological processes. We investigate and parameterize the evolution of global SM–EF coupling from the field to remote-sensing (RS)-footprint. The field-scale EF and SM were obtained from 163 eddy covariance (EC) and SM sensors at various network (Texas Water Observatory and FLUXNET) sites around the globe. Remote-sensing (RS)-scale EF and SM estimates were obtained from Moderate-resolution Imaging Spectroradiometer (MODIS) and Soil Moisture Active Passive (SMAP) sensors, respectively. We estimate the effective thresholds of the WEC regimes from both EC and satellite datasets to highlight the influence of subgrid-scale heterogeneity, scaling, and observational constraints on the evolution of WEC regimes from field to RS-footprint scale. We compare the critical WEC thresholds of the water- and energy-limited regimes with an SM drydown-based approach and highlight the similarities between both methods in partitioning dominant WEC regimes. EF and SM are strongly coupled in dryland arid and semi-arid regions compared to humid climates. WEC regimes and thresholds have strong interseason variability due to dynamic interactions between soil, vegetation, and atmosphere at the RS-footprint scale. In contrast, field-scale SM-EF coupling is influenced predominantly by agricultural /land-use practices and soil conditions. Hence, future development of Earth-System/Land-Surface models must account for the inter-scale differences in the coupling between terrestrial water and energy fluxes representative of the “ effective” processes at large spatial scales.

A document by Vinit Sehgal. Click on the document to view its contents.

A lack of high-density rootzone soil moisture (θRZ) observations limits the estimation of continental-scale, space-time contiguous θRZ dynamics. We derive a proxy of daily θRZ dynamics ― active rootzone degree of saturation (SRZ ) ― by recursive low-pass (LP) filtering of surface soil moisture (θS) within a terrestrial water-energy coupling (WEC) framework. We estimate the LP filter parameters and WEC thresholds for the piecewise-linear coupling between SRZ and evaporative fraction (EF) at remote sensing and field scale over Contiguous U.S. We use θS from Soil Moisture Active-Passive (SMAP) satellite and 218 in-situ stations, with EF from Moderate Resolution Imaging Spectroradiometer. The estimated SRZ  shows high validation skill against SMAP Level-4 estimates and in-situ θRZ, at the corresponding scale. The instantaneous hydrologic state of SRZ vis-à-vis the WEC thresholds is proposed as a rootzone soil moisture stress index (SMSRZ) for near-real-time operational agricultural drought monitoring― demonstrating high agreement with established drought metrics.  

A document by Vinit Sehgal. Click on the document to view its contents.

Understanding the global soil moisture (SM) dynamics and its governing controls beyond Darcy Scale is critical for various hydrologic, meteorological, agricultural, and environmental applications. In this study, we parameterize the pathways of the seasonal drydowns using global surface soil moisture (θ_RS) observation from SMAP satellite (between 2015 and 2019) at 36km X 36km. We develop a new data-driven non-parametric approach to identify the canonical shapes of θ_RS drydown, followed by a non-linear least-squares parameterization of the seasonal drydown pathways at each SMAP footprint. The derived parameters provide the effective soil water retention parameters (SWRPeff), land-atmospheric coupling strength, soil hydrologic regimes for SMAP footprint. Depending on footprint heterogeneity, climate and season, the characteristics curves comprising different drydown phases are discovered at SMAP footprints. Drydown curves respond to the within-footprint changes in the meteorological drivers, land-surface characteristics and the soil-vegetative and atmospheric dynamics. Drydown parameters display high inter-seasonal variability, especially in grasslands, croplands and savannah landscapes due to significant changes in the landscape characteristics and moisture patterns at the subgrid-scale. Soil texture exert influence on the characteristics soil water retention and drydown parameters only when the footprint mean θ_RS is low, specifically in arid and sparsely vegetated regions. The influence of soil texture on the inter-seasonal variability of SWRPeff is low compared to landuse and climate at RS-footprint scale. The global understanding of characteristics SM drydown features at SMAP footprints provides a significant step towards a scale-specific, effective soil hydrologic parameterization for various applications.

Flash droughts are characterized by an abrupt onset and swift intensification. Global surface soil moisture (θRS) from NASA’s Soil Moisture Active Passive (SMAP) satellite can facilitate a near-real-time assessment of emerging flash droughts at 36-km footprint. However, a robust flash drought monitoring using θRS must account for the i) short observation record of SMAP, ii) non-linear geophysical controls over θRS dynamics, and, iii) emergent meteorological drivers of flash droughts. We propose a new method for near-real-time characterization of droughts using Soil Moisture Stress (SMS, drought stress) and Relative Rate of Drydown (RRD, drought stress intensification rate) ─ developed using SMAP θRS (March 2015-2019) and footprint-scale seasonal soil water retention parameters and land-atmospheric coupling strength. SMS and RRD are nonlinearly combined to develop Flash Drought Stress Index (FDSI) to characterize emerging flash droughts (FDSI ≥ 0.71 for moderate to high RRD and SMS). Globally, FDSI shows high correlation with concurrent meteorological anomalies. A retrospective evaluation of select droughts is demonstrated using FDSI, including a mechanistic evaluation of the 2017 flash drought in the Northern Great Plains. About 5.2% of earth’s landmass experienced flash droughts of varying intensity and duration during 2015-2019 (FDSI ≥ 0.71 for >30 consecutive days), majorly in global drylands. FDSI shows high skill in forecasting vegetation health with a lead of 0-2 weeks, with exceptions in irrigated croplands and mixed forests. With readily available parameters, low data latency, and no dependence on model simulations, we provide a robust tool for global near-real-time flash drought monitoring using SMAP.

The increasing frequency and severity of flash droughts pose a threat to global food and water security and seasonal climate forecasts. We introduce a new tool for near-real-time global flash drought monitoring with SMAP leveraging the footprint-scale thresholds of soil hydrologic regimes (energy-limited wet phase, moisture limited transitional, and dry phase) and land-atmospheric coupling strength. We define two complementary indices based on SMAP soil moisture for measuring the severity and the rate of intensification of drought, namely, Soil Moisture Stress (SMS) and Relative Rate of Drydown (RRD), respectively. SMS and RRD are non-linearly combined to provide FDSI (Flash Drought Stress Index) ─ a composite indicator used for global flash drought monitoring. Several advantages of FDSI include non-reliance on long-term soil moisture records, sensitivity to changing land-surface heterogeneity, land-atmospheric interactions, and evolving meteorological anomalies. FDSI is extensively validated globally across multiple timescales (daily, weekly, and monthly) using a suite of vegetation and meteorological drought indices. We demonstrate the application of FDSI in the mechanistic evaluation of select recent flash droughts across the globe (Northern Great Plains in 2017, South Africa in 2015-2016, and Eastern Australia in 2019-2020), and the onset of the ongoing (since 2020) heatwave induced drought in the western U.S. Through this presentation, we introduce the viewers to the open-source web-based resources for accessing global FDSI estimates and related geospatial parameters.