Soil moisture-atmosphere coupling accelerates global warming

Importance of soil moisture conservation in mitigating climate change

A troubling feedback loop, where drier soil contributes to hotter climates, has been widely recognized. This study, drawing on climate model simulations, reveals that maintaining current global soil moisture levels could significantly alleviate 32.9% of land warming under low-emission scenarios. This action could also postpone reaching critical warming thresholds of 1.5 °C and 2.0 °C by at least a decade. Crucially, preserving soil moisture at current levels could prevent noticeable climate change impacts across 42% of the Earth's land, a stark deviation from projections suggesting widespread impacts before the 2060s. To combat soil drying, afforestation in mid-to-low latitude regions within the next three decades is proposed as an effective strategy to increase surface water availability. This underscores the substantial potential of nature-based solutions for managing soil moisture, benefiting both climate change mitigation and ecological enhancement.

Basin Scale Soil Moisture Estimation with Grid SWAT and LESTKF Based on WSN

This research utilized in situ soil moisture observations in a coupled grid Soil and Water Assessment Tool (SWAT) and Parallel Data Assimilation Framework (PDAF) data assimilation system, resulting in significant enhancements in soil moisture estimation. By incorporating Wireless Sensor Network (WSN) data (WATERNET), the method captured and integrated local soil moisture characteristics, thereby improving regional model state estimations. The use of varying observation search radii with the Local Error-subspace Transform Kalman Filter (LESTKF) resulted in improved spatial and temporal assimilation performance, while also considering the impact of observation data uncertainties. The best performance (improvement of 0.006 m3/m3) of LESTKF was achieved with a 20 km observation search radii and 0.01 m3/m3 observation standard error. This study assimilated wireless sensor network data into a distributed model, presenting a departure from traditional methods. The high accuracy and resolution capabilities of WATERNET's regional soil moisture observations were crucial, and its provision of multi-layered soil temperature and moisture observations presented new opportunities for integration into the data assimilation framework, further enhancing hydrological state estimations. This study's implications are broad and relevant to regional-scale water resource research and management, particularly for freshwater resource scheduling at small basin scales.