Surface Water Balance Research Articles

A Distinct Role for Aerosol and GHG Forcing in Historical CMIP6 Evapotranspiration Trends

AbstractEvapotranspiration (ET) is crucial for the global water balance, plant growth, and freshwater availability. It connects the surface water balance with surface energy fluxes, making its accurate representation vital for climate projections. However, global climate models (GCMs) struggle with ET representation due to resolution limitations and simplified depictions of soil, plant, and atmosphere interactions. Simulated future changes in ET are uncertain, and the role of driving processes remain unclear. Here, we explore the utility of a simple and interpretable method to disentangle these varying drivers. We investigate the sensitivity of JJA ET to different atmospheric variables through simple linear models predicting ET from atmospheric variables only. The model consistently yields good results across GCMs or forcing scenarios. We find that GCMs have shown strong decreases and subsequent increases in ET over the historical period, related to changes in net surface radiation. For future climate projections, decreases in water availability compete with higher available surface radiation, making future projections uncertain. Single forcing GCM realizations show that historical ET trends in densely populated regions have been more influenced by aerosol emissions than greenhouse gases. Finally, we investigate which atmospheric variables explain most short‐term (year‐to‐year) and long‐term (decadal) changes. While water availability may be the most important driver of short‐term variability, for certain regions, radiation trends dominate long‐term forcing. This paper leverages a simple approach to provide a comprehensive and understandable view into recent and future changes in ET, reconciling the evidence provided by more complex case studies.

Impact of Long-Term Drought on Surface Water and Water Balance Variations in Iran: Insights from Highland and Lowland Regions

Droughts have a significant impact on surface water resources, especially in arid and semi-arid regions. Computational and data handling limitations have constrained previous time-series analyses. However, advances in cloud computing services and remote sensing technology allow for a more detailed examination. This study integrates multi-source satellite-derived data with a cloud computing platform to assess the impact of long-term drought on surface water and water balance in Iran from 2000 to 2021. Given the varying effects of drought on highlands and lowlands, the analysis was conducted at three levels: the entire country, the highlands, and the lowlands. The results of this study reveal imbalances between water balance from 2000 to 2021, with notable disparities observed during 2000–2007, 2009–2014, and 2016–2019. The results also show varying drought trends (e.g., −1.22 in 2000 and −0.73 in 2021), with severe conditions captured in 2008 (SPI: −1.92). Additionally, our analysis illustrated that lowlands were more impacted by droughts compared to highlands. Long-term drought and permanent surface water had correlation values of 0.33 across the country, 0.33 in the highlands, and 0.31 in the lowlands. For seasonal surface water, coefficients were 0.18 for the entire country, 0.16 for the highlands, and 0.18 for the lowlands. Overall, long-term drought had minimal effect on reducing surface water. These findings show that drought is only part of the explanation for the decrease in surface water resources.

Impacts of forest canopy heterogeneity on plot-scale hydrometeorological variables - Insights from an experiment in the humid boreal forest with the Canadian Land Surface Scheme

High latitude regions, including the circumpolar boreal biome, are experiencing important changes in the availability of usable surface water because of climate change. In this context, an adequate representation of the land-atmosphere interaction is critical to ensure optimal management of current and future water resources, forest management, and climate prediction. However, the task is particularly intricate in high-latitude boreal forest, as land surface model faces several challenges due to the unique environmental conditions and ecological characteristics. The objective of this study is to quantify the impact of forest landscape heterogeneity, specifically stand leaf-area index (LAI), soil texture, and drainage regime, on surface water and energy balance in a small boreal high-latitude sub-catchment. To this end, hydrometeorological conditions at seventeen 20×20 m plots in a 1-km2 boreal forest sub-basin are simulated using the Canadian Land Surface Scheme (CLASS), a land surface model, at the point scale. The subplot-scale soil texture, drainage regime, and vegetation characteristics and type are based as closely as possible on field measurements and observations for the 17 plots. The model-driven experiment comprises two sets of simulations using CLASS, each employing the same model setup and run for the 17 experimental plots. The main set employs meteorological forcing from a local micrometeorological tower within the sub-basin to investigate the plot-to-plot variability of albedo, energy fluxes, and soil state variables. A second set of simulations is conducted using meteorological forcing from the ERA5-Land reanalysis, which spans from 1986 to 2022. This data provides a longer time series, enabling a more accurate representation of the interannual climatic variability in the sub-basin. The results of the main and secondary sets of CLASS simulations are used to assess the plot-to-plot and temporal variability of several key hydrometeorological variables by calculating a monthly spread. In brief, the following conclusions and broader implications can be drawn from the findings: i) The simulated total annual evapotranspiration remains relatively uniform between plots despite notable variation in its partitioning from plot to plot. ii) In the presence of a full snowpack, the albedo exhibits substantial heterogeneity at the subplot scale, linked to the canopy's LAI. iii) Local soil properties, drainage regime, and vegetation structure and type exhibit substantial influence on the plot-to-plot variability in soil water content. iv) When parameterized with localized observations and measurements, CLASS can represent and be responsive to the complex dynamics of energy and water fluxes at the plot scale within the heterogeneous surface of boreal forests.

Impact of land use/land cover change on surface water hydrology in Akaki river catchment, Awash basin, Ethiopia

Watershed reactions to environmental changes is critical for water resource use and management planning. The change in land use/land cover (LUCC) alters surface water hydrology and water balance, subsequently it affects the availability of water resources. This study examined Akaki River catchment surface hydrological responses to future land use scenarios. The future LULC simulated using Cellular Automata-Markov Chain (CA-Markov) model in IDRISI software for 2031, 2041, and 2051 under Business as Usual (BAU) and Forest Patch Protection (FPP) scenarios. Water yield (WY), sediment export (SE), and soil loss (SL) were simulated using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The findings indicate that under BAU, forest and settlement areas increased 42.64% and 31.47%, whereas water body, grass land, and agriculture dropped 31.99%, 25.72%, and 10.4%, respectively, from 2021 to 2051. The FPP scenario shows a 66.42% increase in forest coverage and a 31.97% decrease in cultivated land between 2021 and 2051. Overall settlement expansion will expand by 31.44%, while water body and grassland will decline by 11.12% and 24.9%. As a result of LULC changes in BAU scenario, the proportions of WY (4.36%), SE (26%), and SL (22.45%) increased. The hydrological components exhibited more gradual variations of 0.55%, 18.8%, and 14.24% for the WY, SE, and SL, respectively, under the FPP scenario. Therefore, the alteration has resulted in a concerning state within the area, necessitating the implementation of comprehensive management techniques to restore the hydrology of the catchment.

The influence of different tree species and age on the surface water balance of a small commercial forestry catchment

Acacia mearnsii and Eucalyptus dunnii plantations play an important role in the South African economy as a source for a variety of wood products. However, these species are commonly associated with high evapotranspiration (ET) which may cause streamflow reduction, affecting downstream water users who are reliant on the stream for survival. The potential future increase in exotic plantations worldwide necessitates understanding the impact of these different species on the water balance, hence the streamflow. At the Two Streams research catchment in South Africa, intense hydrological observations (streamflow, ET and weather) have been conducted on A. mearnsii for almost two decades. In 2018, the catchment was clear-felled with subsequent replanting of E. dunnii and hydrological measurements continued. This provided an opportunity to present observations of the surface water balance of the catchment. However, gaps in the data at various times prevented a compilation of a continuous hydrological record. Therefore, three window periods, with complete records of streamflow, ET and precipitation, and with similar weather conditions, were compared. Only the interception loss (Il) was estimated using the Von Hoyningen-Huene method. First window, A. mearnsii trees were three years old (Amear3), second window, A. mearnsii trees were seven years old (Amear7) and the third window, E. dunnii trees were three years old (Edun3). Results indicated a negative catchment surface water balance for all window periods. During the Amear7 window period, the Il was highest compared to the young crops, which reduced effective precipitation, in turn contributing to the lowest measured streamflow. The negative surface water balance and high ET, suggests that trees were accessing water not quantified in the surface water balance. Crops of all three window periods were found to have the potential to significantly reduce the streamflow, which may in turn affect downstream water users. Further research using isotopes to trace the sources of water used by trees in the system is suggested.

Spatio-Temporal Behavior of Land Surface Temperatures (LSTs) in Central Chile, Using Terra MODIS Images

Land surface temperature (LST) is one of the most important variables in the physical processes of surface energy and water balance. The temporal behavior of LST was analyzed between the latitudes 32°00′ S and 34°24′ S (Valparaíso and Metropolitana regions of Chile) for three summer months (December, January, and February) in the 2000–2017 period, using the Terra MODIS image information and applying the Mann–Kendall test. The results show an increase in LST in the study area, particularly in the Andes mountain range in January (5240 km2), which mainly comprises areas devoid of vegetation and eternal snow and glaciers, and are zones that act as water reserves for the capital city of Santiago. Similarly, vegetated areas such as forests, grasslands, and shrublands also show increasing trends in LST but over smaller surfaces. Because this study is regional, it is recommended to improve the spatial and temporal resolutions of the images to obtain conclusions on more local scales.

Orinoco revisited: Comprehensive analysis of the Orinoco River basin present and future hydroclimate

The Orinoco River basin, ranked as South America’s third-largest catchment, is pivotal in contributing to the Atlantic Ocean’s water volume. This study provides a comprehensive update on the basin’s surface water balance, examining trends using gridded precipitation and total evaporation datasets. We also explore projected changes in precipitation until the end of the 21st century, focusing on the RCP8.5 climate change scenario. To achieve this, we utilize data from regional climate models designed by the CORDEX-CORE experiment, selecting an ensemble that excels in performance across South America and Central America. We estimate the accuracy of reference datasets in capturing water balance dynamics. We identify increasing trends in precipitation and total evaporation across most of the basin, enhancing our understanding of its long-term hydrological balance. Notably, the Andean and Guianese sectors of the basin contribute equally to half of the mean surface runoff, although the latter encompasses only 30% of the total area. This underscores the key role of the Guianese shield sub-basins. In regional climate modeling, despite some underestimation, the model runs for the CORDEX South America domain simulate effectively the precipitation across the basin. Regarding climate scenarios, our analysis using the RCP8.5 scenario projects an average annual precipitation reduction of around 45% for the entire basin. These findings emphasize the urgency of adopting measures to mitigate potential adverse effects on the Orinoco River basin’s hydrological sustainability in response to evolving climate patterns.

Vegetation greening accelerated hydrological drought in two-thirds of river basins over China

Although the vegetation-greening-induced water supply reduction has been widely recognized, little is known about the impacts of vegetation greening on hydrological drought. Here Standardized Water Availability Index (SWAI, based on surface water-balance), driven by evapotranspiration (ET, with vegetation dynamics), was developed to quantify the impacts of vegetation greening on hydrological drought at multiple timescales over China from 1982 to 2015. The ET with vegetation dynamics was modeled by the improved PT-JPL model, and was validated with in-situ observed data from 8 flux tower sites and 4 on-site field experiments (covered with 12 different land-cover types in China). SWAI was also validated with monthly runoff records (from 59 gauging stations over different climatic regimes in China), and proved to effectively capture the response of water surplus/deficit to vegetation dynamics. Results reveal that percentage drought-affected areas increased (increased by 2 % to 9 %) and drought intensity enhanced in two-thirds of Chinese river basins due to vegetation greening. Moreover, in nearly half of the river basins in China, drought duration increased by 0.035–0.131 months, and drought frequency increased by 0.016–0.085 months/34-year. Hydrological drought accelerated by vegetation greening mainly occurred in arid and semi-arid river basins (water-limited areas), while it was not obvious in humid and sub-humid river basins due to limited energy for ET in these areas. Our work and findings provide new insights for understanding the vegetation-induced water resource shortage and have potential applications for government and water managers to timely monitor and assess the balance between ecological restoration and water resources.

Simulating the Thermal Regime and Surface Energy Balance of a Permafrost‐Underlain Forest in Mongolia

AbstractForests overlap with large parts of the northern hemisphere permafrost area, and representing canopy processes is therefore crucial for simulating thermal and hydrological conditions in these regions. Forests impact permafrost through the modulation of radiative fluxes and exchange of turbulent fluxes, precipitation interception and regulation of transpiration. Forests also feature distinct soil layers of litter and organic matter, which play central roles for the infiltration and evaporation of water, while also providing thermal insulation for deeper ground layers. In this study, we present a new module within the CryoGrid community model to simulate forest ecosystems and their impact on the surface water and energy balance. The module includes a big‐leaf vegetation scheme with adaptations for canopy heat storage and transpiration. Furthermore, we account for the effect of surface litter layers on water and energy transfer. We show that the model is capable of simulating radiation, snow cover and ground temperatures below a deciduous needleleaf forest on a north‐facing slope in the Khentii Mountains in Central Mongolia. A sensitivity analysis of topographic aspect and ecosystem configuration confirms the important role of the litter layers for the energy and water balance of the ground. Furthermore, it suggests that the presence of permafrost is primarily linked to topographic aspect rather than the presence of forest at this site. The presented model scheme can be used to study the development of the ground thermal regime in forests, including the state of permafrost, under different climate, ecosystem, and land use scenarios.

Multi-Source Dataset Assessment and Variation Characteristics of Snow Depth in Eurasia from 1980 to 2018

Snow is an indicator of climate change. Its variation can affect surface energy, water balance, and atmospheric circulation, providing important feedback on climate change. There is a lack of assessment of the spatial characteristics of multi-source snow data in Eurasia, and these data exhibit high spatial variability and other differences. Therefore, using data obtained from the Global Historical Climatology Network Daily (GHCND) from 1980 to 2018, snow depth information from ERA5, MERRA2, and GlobSnow is assessed in this study. The spatiotemporal variation characteristics and the primary spatial modes of seasonal variations in snow depth are analyzed. The results show that the snow depth, according to GlobSnow data, is closer to that of the measured site data, while the ERA5_Land and MERRA2 data are overestimated. The annual variations in snow depth are consistent with seasonal variations in winter and spring, with an increasing trend in the mountains of Central Asia and Siberia and a decreasing trend in most of the rest of Eurasia. The dominant patterns of snow depth in late autumn, winter, and spring are all north–south dipole patterns, and there is overall consistency in summer.

The Role of Parameterizations and Model Coupling on Simulations of Energy and Water Balances – Investigations With the Atmospheric Model WRF and the Hydrologic Model WRF‐Hydro

AbstractThe distributed hydrologic model WRF‐Hydro can operate in a fully‐coupled mode with the atmospheric Weather, Research and Forecasting (WRF) model. WRF‐Hydro enhances the modeling of terrestrial hydrologic processes in coupled WRF/WRF‐Hydro by simulating lateral surface and subsurface water flows. The objectives of this study are (a) to examine the effect of WRF‐Hydro on the surface energy and water balance in fully‐coupled WRF/WRF‐Hydro simulations and (b) to examine the impact of five WRF physics parameterizations on WRF‐Hydro streamflow. The study area is the Mediterranean island of Cyprus and 31 mountainous watersheds. The domain‐average soil moisture was 20% higher in the coupled WRF/WRF‐Hydro, relative to the standalone WRF model, during a 1‐year simulation. The higher soil moisture could explain the increase in latent heat (36%) and evapotranspiration (33%). The increase in these fluxes was less with a modification in the model transpiration parameterization to represent nocturnal transpiration and the use of remote sensing leaf area index data. The simulated precipitation of the coupled model increased up to 3%, relative to WRF. Two‐year long WRF‐Hydro simulations gave a median Nash‐Sutcliffe Efficiency for daily streamflow of the 31 watersheds of 0.5 for observed precipitation forcing and between −1.9 and 0.2 for the forcing of the five WRF parameterizations. This study showed that the enhancement of the standalone WRF model with lateral water flow processes in the coupled mode with WRF‐Hydro modifies the terrestrial energy and water balance. The improved terrestrial process representation should be considered for future hydrological cycle studies with WRF.

The Projected Response of the Water Cycle to Global Warming Over Drylands in East Asia

AbstractClimate change exacerbates the threat of water scarcity over the drylands in East Asia (DEA), the world's most densely populated arid region. The water cycle continuously supplies water to support all life. Previous studies have focused on the change in individual hydrological components over DEA; however, how the projected water cycle changes under climate warming remains unclear. We demonstrate the projected response of the water cycle to global warming in different seasons utilizing the Coupled Model Intercomparison Project Phase 6. Winter in the DEA presents an intensification of the water cycle, reflected in coherent increases in evapotranspiration (E), precipitation (P), runoff, and surface soil moisture. In contrast, summer will experience a weakened water cycle in the northwestern DEA, while the southeastern part exhibits the opposite trend. From the surface and atmospheric water balance perspective, we further attribute the changes in E and P to gain a more comprehensive understanding. The increasing E is attributed to the combined effects of P and the vapor pressure deficit during summer, whereas it is dominated by P in winter. The increased P in summer is primarily attributed to the horizontal dynamic and vertical thermodynamic components associated with the strengthening and westward expansion of East Asia summer monsoon in the future. During winter, the increased P is mainly due to the vertical dynamic and horizontal thermodynamic components associated with the enhancement of vertical ascending motion and increased moisture.

Evaluation of surface urban energy and water balance scheme (SUEWS) using scaled 2D model experiments under various seasons and sky conditions

Urban energy balance models are essential for better understanding of urban climate processes and mitigating urban heat island intensity. In this study, the Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated using scaled outdoor experiments of idealized city models consisting of street canyons (aspect ratio H/W = 2, H = 0.5) and hollow concrete building models, under various seasonal and sky conditions in a humid subtropical climate in 2020, using three evaluation approaches. The results indicate that the model effectively simulates net all-wave radiation (Q∗), with the coefficient of determination (R2) exceeding 0.970. Storage heat flux (ΔQS) derived from the Objective Hysteresis Model (OHM) is compared to those obtained from the residual term method (RTM) and element surface temperature method (ESTM), revealing the RTM tend to overestimate ΔQS compared to the observation-based ESTM. Compared to using default OHM coefficients, applying fitted OHM coefficients obtained under seasons and sky conditions improves the simulations of ΔQS and sensible heat flux (QH), reducing statistical errors by approximately 50% for ΔQS and increasing R2 in rainy summer from 0.353 to 0.793 for QH, respectively. Additionally, the improved available energy simulation suggests the importance of accurately partitioning between QH and latent heat flux (QE) for the future development of SUEWS.

Urban Ecohydrology: Accounting for Sub‐Grid Lateral Water and Energy Transfers in a Land Surface Model

AbstractAlthough urbanization fundamentally alters water and energy cycles, contemporary land surface models (LSMs) often do not include key urban vegetation processes that serve to transfer water and energy laterally across heterogeneous urban land types. Urban water/energy transfers occur when rainfall landing on rooftops, sidewalks, and driveways is redirected to lawns or pervious pavement and when transpiration occurs from branches overhanging impervious surfaces with the corresponding root water uptake takes place in nearby portions of yards. We introduce Noah‐MP for Heterogenous Urban Environments (Noah‐MP HUE), which adds sub‐grid water transfers to the widely used Noah‐MP LSM. We examine how sub‐grid water transfers change surface water and energy balances by systematically increasing the amount of simulated water transfer for four scenarios: tree canopy expanding over pavement (Urban Tree Expansion), tree canopy shifting over pavement (Urban Tree Shift), and directing impermeable runoff onto surrounding vegetation (Downspout Disconnection) or into an engineered pavement (Permeable Pavement). Even small percentages of sub‐grid water transfer can reduce runoff and enhance evapotranspiration and deep drainage. Event‐scale runoff reduction depends on storm depth, rainfall intensity, and antecedent soil moisture. Sub‐grid water transfers also tend to enhance (reduce) latent (sensible) heat. Results highlight the importance not only of fine‐scale heterogeneity on larger scale surface processes, but also the importance of urban management practices that enhance lateral water transfers and water storage–so‐called green infrastructure–as they change land surface fluxes and, potentially, atmospheric processes. This work opens a pathway to directly integrate those practices in regional climate simulations.

Quantitative Changes in the Surface Frozen Days and Potential Driving Factors in Northern Northeastern China

Surface freezing and thawing processes pose significant influences on surface water and energy balances, which, in turn, affect vegetation growth, soil moisture, carbon cycling, and terrestrial ecosystems. At present, the changes in surface freezing and thawing states are hotspots of ecological research, but the variations of surface frozen days (SFDs) are less studied, especially in the permafrost areas covered with boreal forest, and the influence of the environmental factors on the SFDs is not clear. Utilizing the Advanced Microwave Scanning Radiometer for EOS (AMSRE) and Microwave Scanning Radiometer 2 (AMSR2) brightness temperature data, this study applies the Freeze–Thaw Discriminant Function Algorithm (DFA) to explore the spatiotemporal variability features of SFDs in the Northeast China Permafrost Zone (NCPZ) and the relationship between the permafrost distribution and the spatial variability characteristics of SFDs; additionally, the Optimal Parameters-based Geographical Detector is employed to determine the factors that affect SFDs. The results showed that the SFDs in the NCPZ decreased with a rate of −0.43 d/a from 2002 to 2021 and significantly decreased on the eastern and western slopes of the Greater Khingan Mountains. Meanwhile, the degree of spatial fluctuation of SFDs increased gradually with a decreasing continuity of permafrost. Snow cover and air temperature were the two most important factors influencing SFD variability in the NCPZ, accounting for 83.9% and 74.8% of the spatial variation, respectively, and SFDs increased gradually with increasing snow cover and decreasing air temperature. The strongest explanatory power of SFD spatial variability was found to be the combination of air temperature and precipitation, which had a coefficient of 94.2%. Moreover, the combination of any two environmental factors increased this power. The findings of this study can be used to design ecological environmental conservation and engineer construction policies in high-latitude permafrost zones with forest cover.

CO2 uptake of urban vegetation in a warming Nordic city

Many cities are committed to reducing greenhouse gas emissions, improving air quality, and reducing air temperatures through climate actions. Maintaining or increasing carbon sinks in urban green areas is relevant, as the sinks compensate a part of the emissions in addition to reducing emissions themselves. This research assesses the magnitude of carbon dioxide (CO2) net uptake (i.e. respiration and CO2 uptake by photosynthesis) and local 2-m air temperature in Helsinki, Finland, using an urban ecosystem model SUEWS (The Surface Urban Energy and Water Balance Scheme), and examines their potential future changes due to climate change. The model was run at an hourly resolution within the entire city at a spatial resolution of 250 × 250 m2. Two separate simulations were considered: the present climate by simulating years 2014–2019 and the future climate in the 2050s following the climate scenario RCP8.5. Each modelled grid was further divided into natural and built surfaces using Local Climate Zones (LCZs) to determine how vegetation in forests and various urban vegetation types contributes to cooling and carbon sequestration. According to our simulations, the urban green space in Helsinki annually sequestered 36.3 ± 7.7 kt C in 2015–2019, offsetting circa 7% of the city’s anthropogenic emissions. The mean annual temperatures varied by 2.1∘C between natural and built areas within the city. Although urban forests were the strongest sinks (0.3 kg C m−2 year−1), urban neighbourhoods contributed 47% of Helsinki’s net carbon sinks. Local temperatures were expected to increase with the RCP8.5 climate scenario on average by 1.3∘C within the simulated area and CO2 net uptake by 11%, without altering existing green spaces. Overall, this research highlights the significance of urban green as carbon sinks and how climate change may influence their role in mitigating greenhouse gas emissions and local climate conditions in urban environments.

How Accurately Are Climatological Characteristics and Surface Water and Energy Balances Represented for the Colombian Amazon Basin?

Context: The Colombian Amazon basin (CAB) is characterized by having many areas with few or no in situ observations. To help fix this shortcoming, there are different gridded datasets that represent meteorological variable estimates from in situ, satellite-based, merged, and model-based products. However, before using them, it is necessary to evaluate their performance.Methods: We analyzed the capacity of five grid datasets to represent the annual cycle, the annual means, and the interquartile range of temperature and the variables that intervene in the surface water and energy balances of the CAB. The five datasets were a regional climate model (REMO) and four reanalyses (ERA40, ERA-Interim, NCEP/NCAR, and NCEP-v2). For the temperature and precipitation analyses, the Delaware, GPCP, CPC, CMAP, and CMAP-v2 datasets were also taken into account. Results: The average annual temperature cycle in the CAB has an unimodal behavior, with higher values between October and March. Only Delaware and ERA-Interim describe this behavior and exhibit values close to those of the observations. The average annual cycle of precipitation is also unimodal, with higher values between March and July. Delaware, GPCP, CPC, and ERA-Interim describe this behavior, although ERA-Interim overestimates precipitation. Additionally, the four reanalyses, especially ERA-Interim, show an unexpected trend of increase in mean annual precipitation. As for the water balance, the precipitation and runoff maps of ERA-Interim and REMO show higher values in the foothills and east of 73 degrees W, a pattern that shows better agreement with the observations than those of the other datasets. ERA-Interim, REMO, and ERA-40 meet the closure condition of both the long-term water and the energy budgets. However, REMO and ERA-Interim overestimated precipitation, ERA-40 underestimated it, and ERA-Interim overestimated solar radiation. This implies that some of the other variables for the water and energy balances are also poorly estimated. Conclusions: The five gridded datasets that allow studying surface water and energy balances are not adequate, so better models and reanalyses are required.

Improving monthly mean land surface temperature estimation by merging four products using the generalized three-cornered hat method and maximum likelihood estimation

Land surface temperature (LST) is a critical parameter associated land surface energy and water balance at the land–atmosphere interface. Monthly mean LST (MMLST) is used not only as an input parameter for land surface models, but also as an indicator for general climate trend studies. Four MMLST products (i.e., NESDC, TPDC, ZENODO, and ERA5) were generated by different research teams and institutes using different algorithms. In this study, a new method was presented to improve MMLST estimation by merging these four products using the generalized three-cornered hat (TCH) method and maximum likelihood estimation (MLE). The generalized TCH method was used to simultaneously calculate the relative uncertainties of these four MMLST products during the period 2003–2019. In general, the smallest uncertainties are obtained for the TPDC MMLST product in most areas of the globe, whereas the largest uncertainties are achieved for the ERA5 MMLST product, especially in high-latitude regions. The MLE method was used to merge these four MMLST products and to generate a new MMLST product in consideration of the uncertainty of each individual MMLST product. In situ measurements at 25 stations from the AmeriFlux and SURFRAD networks during the period 2003–2019 were used to evaluate the accuracies of the individual and merged MMLST products. The largest root mean squared error (RMSE) of approximately 2.4 K is obtained for the TPDC MMLST product, whereas the smallest RMSE of around 1.6 K is reached for the merged MMLST product. The NESDC, ZENODO, and ERA5 MMLST products have similar RMSE of approximately 2 K. The results indicate that the merged MMLST product outperforms each individual MMLST product. The merged MMLST product shows promising prospects for climate- and global-scale studies and applications.

Long term analysis of international wetlands in Iran: Monitoring surface water area and water balance

Wetlands have rich biological diversity and productivity, and support unique ecological functions. However, wetlands worldwide are under threat owing to the pressures of development and climate change. We analysed the extent and water balance of 21 important wetlands in Iran from 1990 to 2022 based on Landsat 5, 7, 8, and 9, and Sentinel-2 satellite images and ERA5-land in the Google Earth Engine (GEE) platform. We performed morphometric analyses using NKU-MAN and the Mann-Kendall test to estimate the trends for wetland water bodies. Most seasonal water balance maxima occurred in January, followed by February and, in some cases, in the adjacent months, whilst the minima primarily occurred in May (nine wetlands) and June (five wetlands). Most importantly, the results revealed a gradual decrease in the size of the water bodies over the course of the study period, although this trend was not statistically significant for all water bodies. The findings of this study provide information that can be used by policymakers, planners, scientists, and residents to assess and manage sustainable water usage in wetland watersheds in a changing climate.

A study of the impact of landscape heterogeneity on surface energy fluxes in a tropical climate using SUEWS

This study employs an evaluated Surface Urban Energy and Water Balance Scheme (SUEWS) model driven by Local Climate Zone (LCZ)-derived urban canopy parameters to explore landscape heterogeneity's impacts on the partitioning of surface energy fluxes and heat stress variations in Lagos, Nigeria. The results reveal that LCZ-based SUEWS effectively replicates the diurnal patterns of air temperature (Tair), relative humidity (RH), and land surface temperature (LST). The root mean square error (RMSE) for simulated Tair and RH ranges from 0.4 °C to 1.2 °C and 1.8% to 8.0%, respectively. While a nighttime warm bias in LST is observed, it reduces during the daytime. Significant spatial variability in turbulent heat fluxes and LST among LCZs is noted, with core urban LCZs experiencing notable increases in sensible heat flux and LST, while suburban LCZs exhibit higher latent heat flux values. Anthropogenic heat flux peaks in high compact low-rise LCZ 3, reaching a maximum of 95 W/m2. Remarkably, no significant difference is found in the diurnal heat stress cycle among LCZs, despite consistently elevated heat stress levels in high compact LCZs. These findings offer valuable insights into quantifying surface energy flux variabilities and spatio-temporal heat stress patterns in a densely populated tropical city- Lagos Nigeria.