Peatland ecosystems are globally important carbon stores. Disturbances, such as drainage and climate drying, act to lower peatland water table depths, consequently enhancing soil carbon release and subsidence rates. Here, we conduct a global meta-analysis to quantify the relationship among water table depth, carbon release and subsidence. We find that the water table decline stimulated heterotrophic, rather than autotrophic, soil respiration, which was associated with an increase in subsidence rate. This relationship held across different climate zones and land uses. We find that 81% of the total annual soil respiration for all drained peatlands was attributable to tropical peatlands drained for agriculture and forestry and temperate peatlands drained for agriculture. Globally, we estimate that, drained peatlands release 645 Mt C yr^–1(401–1025 Mt C yr^–1) through soil respiration, equivalent to approximately 5% of global annual anthropogenic carbon emissions. Our findings highlight the importance of conserving pristine peatlands to help mitigate climate change.

Quantifying terrestrial evapotranspiration (ET) and soil moisture dynamics accurately is crucial for understanding the global water cycle and surface energy balance. We present a novel, long-term dataset of global ET and soil moisture derived from the newly developed Simple Terrestrial Hydrosphere model, version 2 (SiTHv2). This ecohydrological model, driven by multi-source satellite observations and hydrometeorological variables from reanalysis data, provides daily global ET-related estimates (e.g., total ET, plant transpiration, soil evaporation, intercepted evaporation) and three-layer soil moisture dynamics at a 0.1° spatial resolution. Validation with in-situ measurements and comparisons with mainstream global ET and soil moisture products demonstrate robust performance of SiTHv2 in both magnitude and temporal dynamics of ET and soil moisture at multiple scales. The comprehensive water path characterization in the SiTHv2 model makes this seamless dataset particularly valuable for studies requiring synchronized water budget and vegetation response to water constraints. With its long-term coverage and high spatiotemporal resolution, the SiTHv2-derived ET and soil moisture product will be suitable to support analyses related to the hydrologic cycle, drought assessment, and ecosystem health.

Accurate estimation of terrestrial evapotranspiration (E) is critical to understand the world's energy and water cycles. MOD16 is the core algorithm of the widely used global E data set (the Moderate Resolution Imaging Spectroradiometer [MODIS] E product). However, it exhibits considerable uncertainties in some regions. Based on the data from 175 flux towers, we identified the key parameters of the MOD16 algorithm using the Sobol’ sensitivity analysis method across biomes. The output of the MOD16 algorithm was sensitive to eight parameters. Among them, β, which is treated as a constant (0.2 kPa) across biomes in the original MOD16 algorithm, was identified as the parameter to which the algorithm was most sensitive. We used the differential‐evolution Markov chain method to obtain the proper posterior distributions for each key parameter across a range of biomes. The values of the key parameters for the different biomes were accurately estimated by differential‐evolution Markov chain in comparison with data from the flux towers. We then evaluated the performances of the original MOD16 and the optimized MOD16 and compared them at multiple spatial scales (i.e., site, catchment, and global). We obtained relatively consistent and more reliable E simulations using the optimized MOD16 at all three scales. In the future, more attention should be paid to uncertainties in the algorithm's structure and its parameterizations of soil moisture constraint, canopy resistance, and energy partitioning.