Conversations in Water: Can We Finally Predict How Vegetation Responds to Drought?

Vegetation is a central control on the hydrological cycle: it governs evapotranspiration, soil moisture dynamics, and the partitioning of water and energy at the land surface. Predicting how vegetation responds to drought is therefore key to predicting the water cycle itself — yet it remains one of hydrology’s hardest problems, since plant water use varies with root depth, soil type, land management, and compounding stressors like heat. Recent years have brought real methodological progress: higher-resolution remote sensing, machine learning and hybrid physics-ML models, better representation of root-zone soil moisture and land-surface water fluxes, and improved coupling between climate, land-surface, and hydrological models.This article collection invites opinion/perspective papers from researchers and practitioners on where prediction of vegetation-drought interactions has genuinely advanced the water cycle science, and where gaps remain. We welcome perspectives addressing:Which numerical simulation or machine learning approaches best capture vegetation’s role in evapotranspiration and soil-water dynamics under drought.How new observational and remote sensing data streams (satellite, drone, sensor networks) are improving estimates of land-surface water fluxes.The persistent modeling gaps — legacy drought effects, land-atmosphere feedbacks, ecosystem thresholds — that still limit water cycle prediction.What it will take to move from research-grade skill scores to actionable predictions for water resources management and climate adaptation.We are looking for Opinion or Perspective papers that take a clear stance and spark debate, from contributors across hydrology, remote sensing, data assimilation, and climate science. Topic editors: Frontiers In Water Source: https://www.frontiersin.org/research-topics/84080/conversations-in-water-can-we-finally-predict-how-vegetation-responds-to-drought