Advances in Land Surface Models and Indicators for Drought Monitoring and Prediction

Abstract

Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land-surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snow pack evolution now support a range of drought indicators that better reflect coupled water, energy and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts.

Implementation and Evaluation of a Unified Turbulence Parameterization Throughout the Canopy and Roughness Sublayer in Noah‐MP Snow Simulations

“…Land surface models (LSMs) simulate terrestrial water and surface energy budgets as a key component of drought and flood predictions (Peters‐Lidard et al., 2021; Sheffield et al., 2012; Viterbo et al., 2020), climate projections (Chotamonsak et al., 2011; Kurkute et al., 2020), weather predictions (Xia et al., 2015), and climate data records (Livneh et al., 2013; Maurer et al., 2002; Xia, Ek, et al., 2012; Xia, Mitchell, et al., 2012; Y. Zhang et al., 2018). Predicting terrestrial water and surface energy budgets requires accurate representation of water, energy and momentum exchanges between the land surface and the atmosphere (Goudriaan, 1977; Harman, 2012; Raupach et al., 1996; Raupach & Thom, 1981; Yi, 2008).…”

Editorial: Challenges of Hydrological Drought Monitoring and Prediction

“…A combination of IMERG and CHIRPS2 resulted in a reduction of the number of dry days and an increase in the frequency of low rainfall days, which led to a better simulation of surface soil moisture, surface runoff, and evapotranspiration. This is particularly relevant for a better characterization of hydrological droughts through the use of land surface models, with the potential to provide relevant information for water managers (Quintana-Seguí et al, 2020;Peters-Lidard et al, 2021).…”

Changes in land use enhance the sensitivity of tropical ecosystems to fire-climate extremes

“…Precipitation shortages represent the meteorological factors driving the anomalous dry conditions. Deficits of soil moisture resulting from the imbalance between moisture supply on the land surface and the losses from evaporation and runoff are typically used to characterize agricultural droughts 48 – 50 . Maps of root zone soil moisture anomalies for the dry season (Aug-Nov) across 2017 to 2020 (Fig.…”