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Water use efficiency (WUE), defined as the ratio of gross primary productivity and evapotranspiration at the ecosystem scale, is a critical variable linking the carbon and water cycles. Incorporating a dependency on vapor pressure deficit, apparent underlying WUE (uWUE) provides a better indicator of how terrestrial ecosystems respond to environmental changes than other WUE formulations. Here we used 20th century simulations from four terrestrial biosphere models to develop a novel variance decomposition method. With this method, we attributed variations in apparent uWUE to both the trend and interannual variation of environmental drivers. The secular increase in atmospheric CO2 explained a clear majority of total variation (66 ± 32%: mean ± one standard deviation), followed by positive trends in nitrogen deposition and climate, as well as a negative trend in land use change. In contrast, interannual variation was mostly driven by interannual climate variability. To analyze the mechanism of the CO2 effect, we partitioned the apparent uWUE into the transpiration ratio (transpiration over evapotranspiration) and potential uWUE. The relative increase in potential uWUE parallels that of CO2, but this direct CO2 effect was offset by 20 ± 4% by changes in ecosystem structure, that is, leaf area index for different vegetation types. However, the decrease in transpiration due to stomatal closure with rising CO2 was reduced by 84% by an increase in leaf area index, resulting in small changes in the transpiration ratio. CO2 concentration thus plays a dominant role in driving apparent uWUE variations over time, but its role differs for the two constituent components: potential uWUE and transpiration.

Evapotranspiration (ET) is dominated by transpiration (T) in the terrestrial water cycle. However, continuous measurement of transpiration is still difficult, and the effect of vegetation on ET partitioning is unclear. The concept of underlying water use efficiency (uWUE) was used to develop a new method for ET partitioning by assuming that the maximum, or the potential uWUE is related to T while the averaged or apparent uWUE is related to ET. T/ET was thus estimated as the ratio of the apparent over the potential uWUE using half-hourly flux data from 17 AmeriFlux sites. The estimated potential uWUE was shown to be essentially constant for 14 of the 17 sites, and was broadly consistent with the uWUE evaluated at the leaf scale. The annual T/ET was the highest for croplands, i.e., 0.69 for corn and 0.62 for soybean, followed by grasslands (0.60) and evergreen needle leaf forests (0.56), and was the lowest for deciduous broadleaf forests (0.52). The enhanced vegetation index (EVI) was shown to be significantly correlated with T/ET and could explain about 75% of the variation in T/ET among the 71 site-years. The coefficients of determination between EVI and T/ET were 0.84 and 0.82 for corn and soybean, respectively, and 0.77 for deciduous broadleaf forests and grasslands, but only 0.37 for evergreen needle leaf forests. This ET partitioning method is sound in principle and simple to apply in practice, and would enhance the value and role of global FLUXNET in estimating T/ET variations and monitoring ecosystem dynamics.

Hydrological models are widely used to assess the impact of climate variability and land use change on streamflow. However, it is uncertain whether these models are capable of simulating the impact given parameter interactions and inter-annual climate variability for large dry catchments. Two such catchments with extensive land clearing were selected to test three models – AWBM, Sacramento and SimHyd – in terms of their capacity to simulate streamflow during periods of vastly different levels of forest cover. AWBM outperformed others, and thus was further simplified as AWBM_Ca with minimum performance deterioration to have only one transferable parameter: the average storage capacity, Ca. A reduction of 21–28% in the Ca value for the post-clearing period indicates a decrease in the amount of water stored for transpiration and consequently an increase in runoff-generation capacity. AWBM_Ca can be used to predict the impact of forest cover change on streamflow with different Ca values. [ABSTRACT FROM AUTHOR]

Spatial and temporal variations in the level of dust activity can provide valuable information for policymaking and climate research. Recently, Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products have been successfully used for retrieving dust aerosol optical depth (DAOD), especially over bright dust source areas, and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) aerosol reanalysis provides DAOD and additionally other dust-aerosol-related parameters. In this study, spatial and temporal variations in dust activity in Australia were analyzed using MODIS and MERRA-2 combined (M&M) DAOD and MERRA-2 near-surface dust concentrations and estimated PM 10 for the period 1980–2020. Validation results show that M&M DAOD has an expected error of ±(0.016+0.15τ) compared to the ground observations at the AErosol RObotic NETwork (AERONET) dust storms on populated areas sites. MERRA-2 near-surface dust concentrations show a power-law relationship with visibility data collected at meteorological stations with an r2 value from 0.18 to 0.44, and the estimated MERRA-2 PM 10 shows similar temporal variations and correlates with ground-based PM 10 data with an r2 value from 0.14 to 0.44 at six selected stations in Australia. Moreover, MERRA-2 horizontal dust flux shows the same major dust pathways as those in previous studies and similar dust emissions and deposition areas identified using ground-based observations. Dust events based on DAOD over eastern Australia are concentrated in the north in December, are concentrated in the south in February, and can occur anywhere in January. Near-surface dust concentration was found to be the highest (over 200 µ g m -3) over the center of Lake Eyre basin in central Australia and radially decreased toward the coast to below 20 µ g m -3 via the two main pathways in the southwest and northeast. The ratio of near-surface dust concentration to PM 10 shows a similar spatial pattern. Total dust emission was estimated to be 40 Mt (megatonnes) per year over the period 1980–2020, of which nearly 50 % was deposited on land and the rest exported away from the Australian continent. [ABSTRACT FROM AUTHOR]

Check‐dams are structures used extensively around the world for soil and water conservation. However, existing models for check‐dams are unable to simulate the Sediment Trap Efficiency (STE) at the catchment scale. A numerical model was developed to simulate the SEdiment Deposition upstream of Check‐Dams (SEDCD) and integrated into a distributed sediment yield model, the Digital Yellow River Model (DYRIM). Two versions of the SEDCD model were evaluated: the SV version which used the Saint–Venant equation to simulate the unsteady flow, and the BW version, which used a modified backwater equation (based on a quasi‐steady approximation) to improve computational efficiency. Sediment deposition and the associated bed profile adjustment were simulated with the sediment conservation equation and the non‐equilibrium suspended sediment transport equation. The SEDCD model was first validated in the laboratory using experimental data from a scale‐down check‐dam. The bed profiles predicted using both versions of the SEDCD model showed good agreement with the observations, with NSE values over 0.9 in most profiles. When integrated into the DYRIM and applied to the Xiaoli River Basin (818 km2) on the Loess Plateau, which has 183 active check‐dams, the SEDCD‐DYRIM combination predicted the STE for an extreme rainstorm event in 2017 with good accuracy and high computational efficiency. The SEDCD‐BW‐DYRIM simulated the hourly discharge and sediment concentration with high accuracy (NSE values of 0.79 and 0.71, respectively) and provided single‐event STEs (R2 value of 0.99) comparable to those of the SEDCD‐SV model, with an approximately 30 times faster runtime efficiency than the SEDCD‐SV model. The SEDCD‐BW model is a powerful and efficient tool to assess the effect of check dams on sediment dynamics at the catchment scale. [ABSTRACT FROM AUTHOR]

Severe water erosion occurs during extreme storm events. Such an exceedingly severe storm occurred in Zhengzhou in central China on 20 July 2021 (the 7.20 storm). The magnitude and frequency of occurrence of this storm event were examined in terms of how erosive it was. To contextualize this extreme event, hourly rainfall data from 2420 automatic meteorological stations in China from 1951 to 2021 were analyzed to (1) characterize the spatial and temporal distribution of the rainfall amount and rainfall erosivity of the 7.20 storm, (2) evaluate the average recurrence interval of the maximum daily and event rainfall erosivity, and (3) establish the geographical distribution of the maximum daily and event rainfall erosivity in China. The center of the 7.20 storm moved from southeast to northwest in Henan Province, and the most intense period of rainfall occurred in the middle and late stages of the storm. Zhengzhou Meteorological Station happened to be aligned with the center of the storm, with a maximum daily rainfall of 552.5 mm and a maximum hourly rainfall intensity of 201.9 mm h -1. The average recurrence intervals of the maximum daily rainfall erosivity (43354±1863 MJ mm ha -1 h -1) and the maximum event rainfall erosivity (58874±2351 MJ mm ha -1 h -1) were estimated to be about 19 200 and 53 700 years, respectively, assuming the log-Pearson type-III distribution, and these were the maximum rainfall erosivities ever recorded among 2420 meteorological stations in mainland China up to 2022. The 7.20 storm suggests that the most erosive of storms does not necessarily occur in the wettest places in southern China, and these can occur in mid-latitude around 35 ∘ N with a moderate mean annual rainfall of 566.7 mm in Zhengzhou. [ABSTRACT FROM AUTHOR]

Spatial and temporal variations in the level of dust activity can provide valuable information for policy making and climate research. Recently, MODIS aerosol products have been successfully used for retrieving dust aerosol optical depth (DAOD), especially over bright dust source areas and MERRA-2 aerosol reanalysis provides DAOD, and additionally other dust aerosol-related parameters. In this study, spatial and temporal variations in dust activity in Australia were analyzed using MODIS and MERRA-2 combined (M&M) DAOD and MERRA-2 near-surface dust concentrations/estimated PM10 for the period from 1980–2020. Validation results show that M&M DAOD has an expected error of ±(0.016+0.15τ) compared to the ground observations at the AERONET sites. MERRA-2 near-surface dust concentrations show a power law relationship with visibility data collected at meteorological stations with an r2 value from 0.18 to 0.44, and the estimated MERRA-2 PM10 shows similar temporal variations and correlates with ground-based PM10 data with an r2 value from 0.14 to 0.44 at six selected stations in Australia. Moreover, MERRA-2 dust flux shows the same major dust pathways as those in previous studies and similar dust emissions/deposition areas. Dust events based on DAOD over eastern Australia are concentrated in the north in December, in the south in February, and can occur anywhere in January. Near-surface dust concentration was found to be the highest (over 200 μg/m3) over the center of Lake Eyre Basin in central Australia and radially decreased to the coast to below 20 μg/m3 via the two main pathways in the southwest and northeast. The ratio of near-surface dust concentration to PM10 shows a similar spatial pattern. Total dust emission was estimated to be 40 MT (mega-tonnes) per year over the period 1980–2020, of which nearly 50 % was deposited on land and the rest exported away from the Australian continent. [ABSTRACT FROM AUTHOR]