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The WAter Cycle Multi-mission Observation Strategy – EvapoTranspiration (WACMOS-ET) project has compiled a forcing data set covering the period 2005–2007 that aims to maximize the exploitation of European Earth Observations data sets for evapotranspiration (ET) estimation. The data set was used to run four established ET algorithms: the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), the Penman–Monteith algorithm from the MODerate resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Surface Energy Balance System (SEBS) and the Global Land Evaporation Amsterdam Model (GLEAM). In addition, in situ meteorological data from 24 FLUXNET towers were used to force the models, with results from both forcing sets compared to tower-based flux observations. Model performance was assessed on several timescales using both sub-daily and daily forcings. The PT-JPL model and GLEAM provide the best performance for both satellite- and tower-based forcing as well as for the considered temporal resolutions. Simulations using the PM-MOD were mostly underestimated, while the SEBS performance was characterized by a systematic overestimation. In general, all four algorithms produce the best results in wet and moderately wet climate regimes. In dry regimes, the correlation and the absolute agreement with the reference tower ET observations were consistently lower. While ET derived with in situ forcing data agrees best with the tower measurements (R2  =  0.67), the agreement of the satellite-based ET estimates is only marginally lower (R2  =  0.58). Results also show similar model performance at daily and sub-daily (3-hourly) resolutions. Overall, our validation experiments against in situ measurements indicate that there is no single best-performing algorithm across all biome and forcing types. An extension of the evaluation to a larger selection of 85 towers (model inputs resampled to a common grid to facilitate global estimates) confirmed the original findings.

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the Global Energy and Water Cycle Exchanges (GEWEX) LandFlux project, four commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley–Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman–Monteith-based Mu model (PM-Mu) and the Global Land Evaporation Amsterdam Model (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to the coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance. Using surface flux observations from 45 globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overall statistical performance (0.72; 61 W m−2; 0.65), followed closely by GLEAM (0.68; 64 W m−2; 0.62), with values in parentheses representing the R2, RMSD and Nash–Sutcliffe efficiency (NSE), respectively. PM-Mu (0.51; 78 W m−2; 0.45) tended to underestimate fluxes, while SEBS (0.72; 101 W m−2; 0.24) overestimated values relative to observations. A focused analysis across specific biome types and climate zones showed considerable variability in the performance of all models, with no single model consistently able to outperform any other. Results also indicated that the global gridded data tended to reduce the performance for all of the studied models when compared to the tower data, likely a response to scale mismatch and issues related to forcing quality. Rather than relying on any single model simulation, the spatial and temporal variability at both the tower- and grid-scale highlighted the potential benefits of developing an ensemble or blended evaporation product for global-scale LandFlux applications. Challenges related to the robust assessment of the LandFlux product are also discussed.

Accurate estimation of actual evapotranspiration (ET) is critical for understanding hydrothermal cycles and ecosystem functioning in arid regions, where water scarcity governs ecological resilience. To address persistent gaps in ET quantification, this study integrates multi-source remote sensing data, energy balance modeling, and ground-based validation that significantly enhances spatiotemporal ET accuracy in the vulnerable desert steppe ecosystems. The study utilized meteorological data from several national stations and Landsat-8 imagery to process monthly remote sensing images in 2019. The Surface Energy Balance System (SEBS) model, chosen for its ability to estimate ET over large areas, was applied to derive modeled daily ET values, which were validated by a large-weighted lysimeter. It was shown that ET varied seasonally, peaking in July at 6.40 mm/day, and reaching a minimum value in winter with 1.83 mm/day in December. ET was significantly higher in southern regions compared to central and northern areas. SEBS-derived ET showed strong agreement with lysimeter measurements, with a mean relative error of 4.30%, which also consistently outperformed MOD16A2 ET products in accuracy. This spatial heterogeneity was driven by greater vegetation coverage and enhanced precipitation in the southeast. The steppe ET showed a strong positive correlation with surface temperatures and vegetation density. Moreover, the precipitation gradients and land use were primary controllers of spatial ET patterns. The process-based SEBS frameworks demonstrate dual functionality as resource-optimized computational platforms while enabling multi-scale quantification of ET spatiotemporal heterogeneity; it was therefore a reliable tool for ecohydrological assessments in an arid steppe, providing critical insights for water resource management and drought monitoring.

Current earth observation models do not take into account the influence of water salinity on the evaporation rate, even though the salinity influences the evaporation rate by affecting the density and latent heat of vaporization. In this paper, we adapt the SEBS (Surface Energy Balance System) model for large water bodies and add the effect of water salinity to the evaporation rate. Firstly, SEBS is modified for fresh-water whereby new parameterizations of the water heat flux and sensible heat flux are suggested. This is achieved by adapting the roughness heights for momentum and heat transfer. Secondly, a salinity correction factor is integrated into the adapted model. Eddy covariance measurements over Lake IJsselmeer (The Netherlands) are carried out and used to estimate the roughness heights for momentum (~0.0002 m) and heat transfer (~0.0001 m). Application of these values over the Victoria and Tana lakes (freshwater) in Africa showed that the calculated latent heat fluxes agree well with the measurements. The root mean-square of relative-errors (rRMSE) is about 4.1% for Lake Victoria and 4.7%, for Lake Tana. Verification with ECMWF data showed that the salinity reduced the evaporation at varying levels by up to 27% in the Great Salt Lake and by 1% for open ocean. Our results show the importance of salinity to the evaporation rate and the suitability of the adapted-SEBS model (AquaSEBS) for fresh and saline waters.

We propose a long-term parameterization scheme for two critical parameters, zero-plane displacement height (d) and aerodynamic roughness length (z0m), that we further use in the Surface Energy Balance System (SEBS). A sensitivity analysis of SEBS indicated that these two parameters largely impact the estimated sensible heat and latent heat fluxes. First, we calibrated regression relationships between measured forest vertical parameters (Lorey’s height and the frontal area index (FAI)) and forest aboveground biomass (AGB). Next, we derived the interannual Lorey’s height and FAI values from our calibrated regression models and corresponding forest AGB dynamics that were converted from interannual carbon fluxes, as simulated from two incorporated ecological models and a 2009 forest basis map These dynamic forest vertical parameters, combined with refined eight-day Global LAnd Surface Satellite (GLASS) LAI products, were applied to estimate the eight-day d, z0m, and, thus, the heat roughness length (z0h). The obtained d, z0m and z0h were then used as forcing for the SEBS model in order to simulate long-term forest evapotranspiration (ET) from 2000 to 2012 within the Qilian Mountains (QMs). As compared with MODIS, MOD16 products at the eddy covariance (EC) site, ET estimates from the SEBS agreed much better with EC measurements (R2 = 0.80 and RMSE = 0.21 mm·day−1).

Passive techniques in the riser tubes of the simple solar water heater (SSWH) are helpful to enhance the effective conversion of the solar energy into the thermal energy. In the present work, the effectiveness of providing of spherical internal surface irregularities (SISIs) has been analyzed. Three aspects, namely (a) effect of the flow Re variation, (b) effect of the distribution pattern of the SISI for equal total number of SISI and (c) effect of the variation the number of the SISI projections for a given riser tube length, have been studied. Various thermohydraulic features like pressure drop, skin friction coefficient, surface Nusselt number, velocity and temperature contours have been observed as a measure of comparison for these three aspects of analysis. A 3D, steady-state analysis was carried out for laminar flow of the single-phase flow through riser tubes having various arrangements of SISI. The flow Reynolds number from 400 to 1000 range has been studied for water and water-based nanofluids using the ANSYS Fluent software. Summarily, it was concluded that the application of SISI leads to natural thermal enhancement for SSWH; however, its distribution pattern also matters.

Evapotranspiration is usually estimated in remote sensing from single temperature value representing both soil and vegetation. This surface temperature is an aggregate over multiple canopy components. The temperature of the individual components can differ significantly, introducing errors in the evapotranspiration estimations. The temperature aggregate has a high level of directionality. An inversion method is presented in this paper to retrieve four canopy component temperatures from directional brightness temperatures. The Bayesian method uses both a priori information and sensor characteristics to solve the ill-posed inversion problem. The method is tested using two case studies: 1) a sensitivity analysis, using a large forward simulated dataset, and 2) in a reality study, using two datasets of two field campaigns. The results of the sensitivity analysis show that the Bayesian approach is able to retrieve the four component temperatures from directional brightness temperatures with good success rates using multi-directional sensors (Srspectra [approximate]0.3, Srgonio [approximate]0.3, and SrAATSR [approximate]0.5), and no improvement using mono-angular sensors (Sr [approximate]1). The results of the experimental study show that the approach gives good results for high LAI values (RMSEgrass =0.50 K, RMSEwheat =0.29 K, RMSEsugar beet =0.75 K, RMSEbarley =0.67 K); but for low LAI values the results were unsatisfactory (RMSEyoung maize =2.85 K). This discrepancy was found to originate from the presence of the metallic construction of the setup. As these disturbances, were only present for two crops and were not present in the sensitivity analysis, which had a low LAI, it is concluded that using masked thermal images will eliminate this discrepancy.

The regional heat flux exchange between heterogeneous landscapes and the nearby surface layer (SL) is a key issue in the study of land-atmosphere interactions over arid areas such as the Heihe River basin in northwestern China and in high elevation areas such as the Tibetan Plateau. Based on analysis of the land surface heterogeneity and its effects on the overlying air flow, the use of SL observations, atmospheric boundary layer (ABL) observations, and satellite remote sensing (RS) measurements along with three parameterization methodologies (here, termed as the RS, tile, and blending approaches) have been proposed to estimate the surface heat flux densities over heterogeneous landscapes. The tile and blending approaches have also been implemented during HEIhe basin Field Experiment (HEIFE), the Coordinated Enhanced Observing Period (CEOP) Asia-Australia Monsoon Project on the Tibetan Plateau (CAMP/Tibet), the Arid Environment Comprehensive Monitoring Plan’ 95 (AECMP′95), and the DunHuang Experiment (DHEX). The results showed that these two proposed parameterization methodologies can be accurately used over heterogeneous land surfaces.

Key policy highlights Transformations to sustainability require alternatives to the paradigms and policies that have generated social-ecological destruction and the Anthropocene. Diverse relational approaches to transformations have been articulated by Indigenous, humanities and social sciences scholars, practitioners, and activists from Global South and North. Efforts to apply such approaches through universal frameworks or toolboxes may miss the significance of relational approaches, which are often defined by their attentiveness to unfolding relations among particular places, peoples, and ecologies. A relevant concept for engaging diverse relational approaches to transformations may be that of the uncommons – interests in common which are not the same interests. Relational approaches suggest practices of sustainability transformations as ‘walking together in a world of many worlds’.

The development of membrane-based materials that exhibit the range and robustness of autonomic functions found in biological systems remains elusive. Droplet interface bilayers (DIBs) have been proposed as building blocks for such materials, owing to their simplicity, geometry, and capability for replicating cellular phenomena. Similar to how individual cells operate together to perform complex tasks and functions in tissues, networks of functionalized DIBs have been assembled in modular/scalable networks. Here we present the printing of different configurations of picoliter aqueous droplets in a bath of thermoreversible organogel consisting of hexadecane and SEBS triblock copolymers. The droplets are connected by means of lipid bilayers, creating a network of aqueous subcompartments capable of communicating and hosting various types of chemicals and biomolecules. Upon cooling, the encapsulating organogel solidifies to form self-supported liquid-in-gel, tissue-like materials that are robust and durable. To test the biomolecular networks, we functionalized the network with alamethicin peptides and alpha-hemolysin (αHL) channels. Both channels responded to external voltage inputs, indicating the assembly process does not damage the biomolecules. Moreover, we show that the membrane properties may be regulated through the deformation of the surrounding gel.