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• A novel framework of sequential long-term ET data assimilation was proposed. • Joint assimilation of LAI and ET with EnKF-SSPE performs best for wheat. • Joint assimilation of SM and ET with EnKF-SSPE performs best for maize. • Assimilating LAI and ET play a significant role for wheat and maize, respectively. • EnKF-SSPE outperforms EnKF for long-term crop modeling when crop cultivars might change. Recently, data assimilation (DA) has garnered significant attention. Integration of DA approaches and crop models could diminish model uncertainties and improve the precision of model simulations. While previous research extensively focused on assimilating leaf area index (LAI) or soil moisture (SM), the feasibility and effectiveness of assimilating evapotranspiration (ET) have been rarely explored. In this study, we proposed a novel framework of ET assimilation. Then, together with commonly assimilated LAI and SM, we evaluated the performance of this new method in simulating the key indicators (i.e., LAI and ET in daily and interannual scales, and the crop yield) based on the long-term eddy covariance observations and well-calibrated crop model. DA strategies we utilized to evaluate consist of two approaches (i.e., Ensemble Kalman filter (EnKF) and EnKF with simultaneous state-parameter estimation (EnKF-SSPE)) and combinations of three assimilated observations (i.e., LAI, SM, and ET). Our results demonstrate that joint assimilation of LAI and ET with EnKF-SSPE performs best for wheat while joint assimilation of SM and ET with EnKF-SSPE is the best for maize. For a single observation, LAI and ET play a dominant role in DA for wheat and maize, respectively. This is because the interannual variability of wheat growth is primarily influenced by agricultural management (e.g., cultivar change) and can be represented by LAI. For maize which is mostly rainfed, water stress usually occurs. Therefore, ET, with its ability to reflect the water stress status, proves to be effective. EnKF-SSPE outperforms EnKF, exhibiting potential in revealing the parameter evolution during long-term crop modeling, especially when crop cultivars are regularly renewed. This study evaluates different observations and methods through DA based on a newly proposed sequential ET assimilation framework, which might be illuminating for future applications of DA. [ABSTRACT FROM AUTHOR]

• A Soil-Water Conservation parameterization scheme was developed based on the GBEHM. • It revealed the spatiotemporal hydrological changes in the YRB during 1982–2019. • Impacts of the climate change and SWC measure on the runoff change were quantified. Intensive Soil and Water Conservation (SWC) has been conducted in the Yellow River basin (YRB) since the 1950s, which has greatly altered the eco-hydrological processes and particularly led to the runoff reduction. However, previous hydrological models performed in the YRB rarely simulated the SWC explicitly to quantify its spatiotemporal impacts. This study developed a SWC parameterization scheme based on the distributed physically-based model named Geomorphology-Based Ecohydrological Model (GBEHM). The hillslope SWC (HSWC) was parameterized as an additional surface storage capacity and simulated together with hillslope hydrological processes. The check dams along the river networks (i.e., river-networks SWC, RSWC) were parameterized as reservoirs and simulated together with the flow routing. The enhanced model (GBEHM-SWC) was first calibrated and validated using natural streamflow and remote sensing-based evapotranspiration. Then it was applied to analyze the hydrological changes from 1982 to 2019 in the YRB. Our simulation showed that, compared with the first period (1982–2000), the climatic factors (especially an increase of annual precipitation by 27.3 mm) would cause an increase of annual natural runoff by 2.9 mm (2.17 billion m3) in the second period (2001–2019). But in fact, the observed annual natural runoff decreased by 4.3 mm in the second period, which was caused by the reduction effects of the HSWC and RSWC by 3.8 and 3.7 mm (2.84 and 2.74 billion m3), respectively. Regarding the spatial distribution, the simulated natural runoff increased above Lanzhou and decreased on the Loess Plateau. The SWC impacts showed high spatial heterogeneity over the YRB, which offered useful information to evaluate the SWC measures. [ABSTRACT FROM AUTHOR]

This study presented a two-year data set of sensible heat and water vapor fluxes above a humid subtropical montane Cypress forest, located at 1650 m a.s.l. in northeastern Taiwan. The focuses of this study were to investigate (1) the diurnal and seasonal variations of canopy resistance and fluxes of sensible heat and water vapor above this forest; and (2) the mechanism of why a fixed canopy resistance could work when implementing the Penman–Monteith equation for diurnal hourly evapotranspiration estimation. Our results showed distinct seasonal variations in canopy resistance and water vapor flux, but on the contrary, the sensible heat flux did not change as much as the water vapor flux did with seasons. The seasonal variation patterns of the canopy resistance and water vapor flux were highly coupled with the meteorological factors. Also, the results demonstrated that a constant (fixed) canopy resistance was good enough for estimating the diurnal variation of evapotranspiration using Penman–Monteith equation. We observed a canopy resistance around 190 (s/m) for both the two warm seasons; and canopy resistances were around 670 and 320 (s/m) for the two cool seasons, respectively. In addition, our analytical analyses demonstrated that when the average canopy resistance is higher than 200 (s/m), the Penman–Monteith equation is less sensitive to the change of canopy resistance; hence, a fixed canopy resistance is suitable for the diurnal hourly evapotranspiration estimation. However, this is not the case when the average canopy resistance is less than 100 (s/m), and variable canopy resistances are needed. These two constraints (200 and 100) were obtained based on purely analytical analyses under a moderate meteorological condition (Rn = 600 W·m−2, RH = 60%, Ta = 20°C, U = 2 m·s−1) and a measurement height around two times of the canopy height. [ABSTRACT FROM AUTHOR]

Highlights • A framework for evaluating the hydrological impacts of dam construction is proposed. • Impacts of small dam construction on hydrological conditions are investigated. • Operation of the small hydropower stations for preventing low flow reduction is suggested. Abstract The hydrological alterations induced by dam construction modify natural flora and fauna habitats and impair ecosystem stability. Although many studies have documented the impacts of large dams on streamflow, few have described the effects of small dam construction on hydrological conditions. The cumulative effects of intensive small dams may also cause severe ecological problems. To evaluate the impacts of dam construction on the indicators of hydrological alterations, a framework that combined a hydrological model and the post bias correction method was proposed. The hydrological alterations of two individual rivers in the Jiulong River basin that experienced impacts from intensifying small hydropower reservoirs, the North River and the West River, were analyzed using the proposed framework. The results show that the framework can successfully avoid misleading the impacts of dam construction on monthly runoff and multi-minimum values detected by the previously common method that did not separate the impacts of climate change and dam construction on flow regime. The small hydropower-dominated North River and the flood-control-dominated West River exhibited generally consistent change patterns of unchanging monthly river discharge, reduced high pulse count, reduced rise and fall rates, and increased number of reversals. Conversely, the changes to several Indicators of Hydrologic Alterations (IHA) differed between the two rivers. The flood-control-dominated West River exhibited 1) increased indicators, such as the base flow index, multi-day minimum flow and high pulse duration and 2) decreased multi-day maximum flow and low pulse count. Unlike the West River, the hydropower-dominated North River experienced 1) increased low pulse count and 2) decreased indicators such as multi-day minimum flow and low pulse duration. Our results implied that the ecological impacts of the small hydropower-dominated North River may exceed those of the flood-control-dominated West River. Therefore, the minimum ecological water demand should be considered not only in the large reservoirs operation, but also in the operation of small hydropower reservoirs. [ABSTRACT FROM AUTHOR]

Estimation of evapotranspiration (ET) and yield over cropland is essential for water resources management and food security. Particularly the estimation at long-term and regional scales still needs to be investigated. In this study, a remotely sensed and water-carbon coupled model was combined with a process-based crop growth simulation method to simultaneously estimate ET and yield. The developed model was tested for two of the most important crops (wheat and maize) with years of observations. Leaf area index determined by various remote sensing indices and individually calibrated parameters for wheat and maize were considered to improve crop ET and gross primary production (GPP) estimates. The parameters well reflected different physiological properties that C4 maize has a smaller stomatal conductance coefficient and a larger sensitivity in response to initial light than C3 wheat. Comparing with 20 years of measurements, the root mean square error (RMSE) of ET and GPP for winter wheat was 0.57 mm d−1 and 1.65 g C m−2 d−1, and for maize were 0.80 mm d−1 and 2.92 g C m−2 d−1, respectively. Besides, crop growth simulation including biomass accumulation and allocation agreed well with the measurements. Coefficient of determination was mostly larger than 0.66, and RMSE of yield was 554.7 and 1346.6 kg hm−2 for wheat and maize, respectively. Finally, the spatiotemporal crop water productivity (WP) of winter wheat and summer maize in the North China Plain during 2001–2018 were quantified. The increased WP of winter wheat while the larger WP of maize than that of wheat were discovered. The developed model helps to examine regional crop ET and yield and provides critical information on agricultural water management. • Combining a remotely sensed and water-carbon coupled model with a crop growth simulation method. • Three modelling experiments were conducted to improve ET and GPP estimates. • Simultaneously estimated ET, GPP and yield were evaluated by years of observations. • ET and yield of wheat and maize over the NCP from 2001 to 2018 were examined. • Wheat water productivity with a significantly increased trend was generally lower than that of maize. [ABSTRACT FROM AUTHOR]

Understanding the interannual variability (IAV) and investigating the physical and biological controls on the IAV of evapotranspiration (ET) is fundamental for better simulating the hydrological processes in cropland where ET is the dominant component of water cycle. However, this topic has not been fully studied, although the number of long-term field observations is growing. By using a combination of long-term field observations (10 years) and agro-hydrological modelling, this study attempted to examine the IAV of ET and the physical and biological controls on the IAV of ET in an irrigated cropland in the North China Plain. This study reveals that the IAV of ET was only 7% in the selected dry subhumid area, which was much smaller than that of water supply (i.e., the sum of precipitation and irrigation). Moreover, the water supply was not the primary controlling factor that influenced the IAV of annual ET. Biological factors, including the leaf area index and bulk stomatal conductance, were found to be the dominant contributors to the IAV of annual ET. Irrigation was an essential water source for crop growth, particularly for winter wheat growth, whereas its contribution to the IAV of ET was smaller than that of precipitation because of the sufficient amount of irrigation. This study demonstrates that the variability of biological factors should be adequately represented in eco-hydrological models to accurately simulate the IAV of annual ET. [ABSTRACT FROM AUTHOR]

The North China Plain (NCP) has a severe water shortage. About 70% groundwater has been exploited for irrigation. Winter wheat – summer maize and pears are typical representative cereal crops and commercial fruit trees in this area, respectively. Water budget for the typical cropland and orchard ecosystems has a significant importance for agricultural production, especially in the NCP. Therefore, evapotranspiration (ET) and water balance were studied in the annual winter wheat – summer maize rotation (cropland) and pear orchard. Latent and sensible heat fluxes were measured by eddy covariance. Annual ET for pear trees was 764 mm and for both crops was 690 mm. The difference of ET between these two ecosystems was about equal to one irrigation. Transpiration was the main loss with the mean proportion of 63% for crops and 76% for pear trees. Wheat growth period is in the dry season and requires much more irrigation than maize. Mainly transpiration (80%) occurred from April through September in the both ecosystems which was also the growing period for pear trees. The annual precipitation was 469 mm and 444 mm in the pear orchard and cropland, respectively, although 80% of it occurred from June to September. Compared with the precipitation, annual mean water deficit was 294 mm for the pear trees and 244 mm for crops. The water shortage was severe in May while surplus water presented in July and August. Energy and ET fluxes were determined by atmospheric demand and the response of plants as controlled by plant phenology and crop selection. As the water shortage situation becomes more serious in the NCP, sustainability of the agricultural ecosystems could be improved by changing crop planting patterns, specifically, increasing the area ratio of maize to pear trees. [ABSTRACT FROM AUTHOR]

Abstract: Runoff and river routing schemes play important roles in land surface models (LSMs) because they regulate the soil moisture, heat flux, and vegetation dynamics of land surface processes and account for the carbon and nutrient transport in river channels. However, these schemes are often simplistic and conceptual. Hence, in this study, we focused on (1) evaluating these schemes in the Community Land Model (CLM) and (2) altering the model representations using physically based schemes based on a study of the Yellow River basin. For runoff simulation, CLM exhibits limitations in water‐limited areas, especially areas with aridity index values greater than 2. Additionally, CLM greatly overestimates runoff, and produces negative Nash‐Sutcliffe efficiency (NSE) coefficients, few quick flow variations, high quick flow index values, and large root mean square errors of total water storage. These issues were greatly improved by implementing schemes of physically based overland flow, lateral soil water flow, and interchange between groundwater and river water. Furthermore, for the river routing scheme, the use of 1‐D kinematic wave routing improved previously unrealistic aspects of the flood hydrographs (e.g., incorrect flood peak values and times) of the original CLM. Moreover, compared with using the grid element‐based river routing approach in CLM, the computational costs were reduced by up to 45% by implementing the flow interval element method. Finally, our results indicate that parameter calibration in CLM minimally improved the simulation performance in water‐limited areas, while physically based schemes generated better results. [ABSTRACT FROM AUTHOR]

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from −0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) and gross primary production (GPP) over agroecosystems could be noticeably altered by climate change and human activities. A better understanding of the impacts on water-carbon interactions and the underlying mechanisms, are crucial to improve water use efficiency (WUE). Comparing to 23 site-years of observations, regional ET dataset and statistical yields, the Remote Sensing-based cropland Ecohydrological Model (ReSEM) was validated to estimate the spatiotemporal dynamics of ET, GPP and WUE for dryland agroecosystems in the North China Plain (NCP) from 2001 to 2018. Spatially, the distributions of mean annual ET, GPP and WUE were comparable which changed obviously in different climatic conditions while varied slightly between various irrigation areas. The significantly increased WUE occurred in 38.6 % cropland, mainly located in the humid south regions with less irrigation requirement and the central sub-humid areas along the Yellow River with access to surface irrigation. The averaged increasing trend of WUE in the heavily irrigated semi-arid areas was relatively low. The temporal dynamic of regional mean WUE indicated a significantly increased rate of 0.026 gC kg−1H 2 O per year during 2001–2018. The spatiotemporal trends of WUE were mainly resulted from the significantly increased GPP rather than ET. The experimental simulations demonstrated that agricultural management dominated the interannual trend of WUE, whose relative contribution (79.5 %) was obviously larger than that of air CO 2 concentration (40.2 %) and climate variable change (−19.7 %). Besides, the effects of agricultural management on WUE were further divided based on the classified six cropping systems, 82.4 % of which was attributed to the management of winter wheat-summer maize rotation system. This study sheds light on the improvement of WUE for dryland agroecosystem under changing environments and highlights the dominant impact of agricultural management. • Spatiotemporal dynamics of ET, GPP and WUE in the NCP were quantified. • The significantly increased WUE occurred in 38.6 % cropland resulting from GPP rather than ET. • WUE dominated by agricultural management increased at a rate of 0.026 gC kg−1H 2 O y−1. • CO 2 and climate variable change contributed 40.2 % and − 19.7 % of variation in WUE. • The impacts of agricultural management on WUE were divided by six cropping systems. [ABSTRACT FROM AUTHOR]

Increasing evidence shows that Aβ oligomers are key pathogenic molecules in Alzheimer’s disease. Among Aβ oligomers, dimer is the smallest aggregate and toxic unit. Therefore, understanding its structural and dynamic properties is quite useful to prevent the formation and toxicity of the Aβ oligomers. In this study, we performed molecular dynamic simulations on four Aβ42 dimers, 2NCb, CNNC, NCNC and NCCN, within the hydrated DPPC membrane. Four Aβ42 dimers differ in the arrangements of two Aβ42 peptides. This study aims to investigate the impact of aggregation pattern of two Aβ peptides on the structural stability of the Aβ42 dimer and its disruption to the biological membrane. The MD results demonstrate that the NCCN, CNNC and NCNC have the larger structural fluctuation at the N-terminus of Aβ42 peptide, where the β-strand structure converts into the coil structure. The loss of the N-terminal β-strand further impairs the aggregate ability of Aβ42 dimer. In addition, inserting Aβ42 dimer into the membrane can considerably decrease the average APL of DPPC membrane. Moreover this decrease effect is largely dependent on the distance to the location of Aβ42 dimer and its secondary structure forms. Based on the results, the 2NCb is considered as a stable dimeric unit for aggregating the larger Aβ42 oligomer, and has a potent ability to disrupt the membrane. [ABSTRACT FROM AUTHOR]

Changes in seasonally frozen ground at high elevations under the effects of global warming and their ecohydrological impacts are important for understanding changes in regional water resources and ecosystems. This study estimates the spatio-temporal variability in the maximum thickness of seasonally frozen ground (MTSFG) in the Qilian Mountains in the northeastern Tibetan Plateau from 1960 to 2014 by using a variant of the Stefan solution. The present study analyzes changes in streamflow and vegetation to reveal the ecohydrological impacts of changes in the MTSFG. Results indicate that the MTSFG shows a mean decreasing trend of 7.4 cm/10a in the past 55 years in correspondence to the significantly increasing air temperature (0.34 °C/10a). The greatest decreasing trend of the MTSFG is at elevations of 3400–3800 m. The annual baseflow has increased significantly in most of the sub-basins for which the increasing precipitation is the main factor. The MTSFG is another major factor for the increase in baseflow during the cold season (from November to April) according to the results of gray relational analysis. The leaf area index (LAI) during the growing season has increased by 0.045/10a since 2000, and the start of growing season has advanced by 1.8–2.1 d/10a at elevations of 3000–3800 m, where the vegetation cover is the densest. Furthermore, results of correlation analysis show that the topsoil moisture increases with the MTSFG decreases. Results of gray relational analysis show that the decrease in MTSFG is the main reason for the advancing green-up dates and increasing LAI in the initial period of the growing season. Our results show that the ecohydrological processes are changing along with frozen soil degradation in the northeastern Tibetan Plateau. [ABSTRACT FROM AUTHOR]

[Display omitted] • Tree mycorrhizal associations drive soil N cycling pattern in subtropical forests. • Soil nitrate N decreased with increasing ectomycorrhizal (ECM) tree dominance. • ECM tree and associated fungi reduce soil N mineralization and nitrification rates. • High NAGase activity and C:N ratio but low pH was found in ECM-dominated soils. Trees and their associated arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) fungi drive carbon (C) and nitrogen (N) cycling patterns. However, the mechanisms underpinning this relationship and the degree to which mycorrhiza mediate the effects of forest tree composition on soil N cycling outside of the temperate zone remain unclear. Here, we conducted field surveys to establish a natural gradient with increasing ECM tree dominance in subtropical forests, and explored the effects of tree mycorrhizal associations on soil N cycling. Across this mycorrhizal gradient, we quantified soil available N, microbial biomass N, net N transformation rates, as well as N -acquiring enzyme activities, litterfall biomass and quality, and soil pH during the one-year growing season. We found that with increasing ECM tree dominance, the dissolved organic N and nitrate N decreased, while the microbial biomass N increased linearly. Soils dominated by AM trees had 1.8–2.3 times larger mineral N contents, net N mineralization rate, and net nitrification rate than ECM-dominated stands, suggesting a rapid N cycling in AM-dominated stands. ECM trees and their associated fungi reduce the net N mineralization rate in topsoil mainly by producing recalcitrant litterfall (i.e., higher C:N) and by secreting β- N -acetylglucosaminidase to deplete N directly from soil organic matter, which together increased N limitation for free-living decomposers. The low pH and high C:N ratio in ECM-dominated soils inhibit the proliferation of ammonia-oxidizers and thus decrease the net nitrification rate. Our results demonstrate that the increasing ECM tree dominance increase soil N -acquiring enzyme activity and C:N ratio but decrease pH value, all of them critically mediating soil N availability. Consequently, by altering the relative abundances of tree mycorrhizal associations shifts in forest composition under global changes and plantation establishment can be expected to result in altered soil N cycling. [ABSTRACT FROM AUTHOR]

• modeling of crop growth and ET based on long-term eddy covariance observations. • Climatic factors basically dominated the trend of ET and WUE for both crops. • Cropland management dominated the trend of phenology for both crops. • Rising temperature shortened reproductive phase and reduced yield for both crops. • Elevated CO 2 concentration exhibited minor but significant impacts. Comprehensive understanding of how climate change and cropland management affect crop growth and water consumption is essential but unclear in the North China Plain (NCP) which is one of the major winter wheat and summer maize production regions. By combining an agro-hydrological model with 16-year eddy covariance observation, we quantified the impacts of climatic factors and key management (i.e., sowing date and irrigation) on the trend of key phenological stages, leaf area index (LAI), crop yield, evapotranspiration (ET), and water use efficiency (WUE) at a typical irrigated site in the NCP. We found that the advance of start and end of season was mainly caused by advanced sowing date and rising temperature which also shortened the reproductive phase; however, the growing season length (GSL) was remarkably shortened by advanced sowing date. Although LAI and yield of both crops were increasing, they were mainly negatively affected by rising temperature while slightly promoted by elevated CO 2 concentration. LAI and yield of maize were also greatly improved by increasing radiation and irrigation, and wheat's growth was considerably hampered by excessive irrigation. Increasing ET was mainly ascribed to increasing radiation and decreasing humidity, but slightly inhibited by elevated CO 2 concentration. Increasing WUE was mainly inhibited by the rising temperature and decreasing humidity while improved slightly by elevated CO 2 concentration. Besides, we inferred that increase in LAI, yield, ET, and WUE of wheat is most likely to be attributed to the renewal of cultivars, the delay of key phenological stages, and prolongation of GSL for both crops was also possibly caused by the renewal of cultivars. Our study provided a first comprehensive insight into the long-term coupled variation of crop growth and evapotranspiration in this region. [ABSTRACT FROM AUTHOR]

• Spatiotemporal variations of rainfall erosivity were analyzed based on hourly data. • Rainfall erosivity based on hourly data and daily data were compared. • Rainfall amount and intensity led to high spatial heterogeneity of rainfall erosivity. • Rainfall erosivity increased in the 1990 s while annual rainfall amount not. • Half of the variability of rainfall erosivity was explained by rainfall amount. Understanding spatial and temporal variations in rainfall erosivity is essential for estimating the variability in soil erosion. However, rainfall erosivity in the middle Yellow River Basin is usually calculated based on daily rainfall data, which fails to consider the impact of the changing rainfall intensity at the subdaily scale. In this study, we collected hourly rainfall data from 355 meteorological stations within and around the region to calculate rainfall erosivity during 1960–2017. We found that the rainfall erosivity calculated based on hourly data had much larger variability than that calculated based on daily data, and the calculated spatial and temporal variability were substantially different in periods when the rainfall intensity was highly variable. Based on our new estimation, we found that the spatial distribution of rainfall erosivity was highly heterogeneous, with high erosivity values in the Loess Regions and Rocky Mountain Regions with high soil erodibility and low erosivity values in the Aeolian Regions and Soft Sandstone Regions with low soil erodibility. This heterogeneity was mainly due to the distinct spatial distribution patterns of rainfall amount and rainfall intensity. Although the long-term increasing trend of rainfall erosivity was statistically insignificant from 1960 to 2017, its rate of increase was higher than that of the annual rainfall amount. Decadal changes showed a slight decrease from the 1960 s to the 1980 s and an increase since the 1990 s, which was substantially different from the decadal changes in the annual rainfall amount. These differences in temporal variability were mainly caused by the contribution of changing rainfall intensity, which was greater in the Aeolian Regions and Soft Sandstone Regions than in the other subregions. Our study highlighted the importance of considering the changing rainfall intensity at a subdaily scale in semiarid and semihumid climate zones and provided the first estimation of the long-term variability in rainfall erosivity based on hourly rainfall data in this region. [ABSTRACT FROM AUTHOR]

Soil moisture plays an important role in the coupled water, energy, and carbon cycles. In addition to surface processes such as evapotranspiration, the boundary fluxes that influence soil moisture are closely related to surface or subsurface runoff. To elucidate how uncertainties in representing surface and subsurface hydrology may influence simulations of the carbon cycle, numerical experiments were performed using version 4 of the Community Land Model with two widely adopted runoff generation parameterizations from the TOPMODEL and Variable Infiltration Capacity (VIC) model under the same protocol. The results showed that differences in the runoff generation schemes caused a relative difference of 36% and 34% in global mean total runoff and soil moisture, respectively, with substantial differences in their spatial distribution and seasonal variability. Changes in the simulated gross primary production (GPP) were found to correlate well with changes in soil moisture through its effects on leaf photosynthesis (An) and leaf area index (LAI), which are the two dominant components determining GPP. Soil temperature, which is influenced by soil moisture, also affects LAI and GPP for the seasonal-deciduous and stress-deciduous plant functional types that dominate in cold regions. Consequently, the simulated global mean GPP differs by 20.4% as a result of differences in soil moisture and soil temperature simulated between the two models. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling. [ABSTRACT FROM AUTHOR]

• Hydrological and sedimentary changes from 1981 to 2015 in the UCPRB of Thailand are analyzed. • The hydrological and sedimentary responses to deforestation are quantified. • Precipitation increase and deforestation dominated the runoff increase, and deforestation dominated the sediment increase. Deforestation has been reported to increase annual streamflow, baseflow, and sediment load in many parts of the world. However, studies about the hydrological effects of deforestation are scant in the tropical monsoon region. In this study, these effects were examined in the Upper Chao Phraya River basin (UCPRB) which is a typical tropical monsoon basin and is an important area of water resources in Thailand. A significant breakpoint for annual streamflow and annual precipitation in the entire UCPRB is identified as 1993, and this breakpoint is also identified for annual baseflow in most upstream sub-basins during the past decades (1981–2015). Significant increasing trend is detected in the annual suspended sediment load of the Wang River sub-basin. Land use maps generated by a CA-Markov model suggest that continuous deforestation occurred during the study period. The contributions of climate change and deforestation to the hydrological and sedimentary changes are then attributed within the Budyko Framework. Precipitation increment dominates the annual streamflow increment in the entire UCPRB and the annual baseflow increment in the Ping River sub-basin, and deforestation dominates the annual streamflow increment in the upstream sub-basins, the annual baseflow increment in most of the upstream sub-basins, and the increasing suspended sediment load in the Wang River sub-basin. The hydrological and sedimentary response to deforestation is then quantified. In the entire UCPRB, one percent reduction of the forest cover can increase the annual streamflow by 1.9%. In the upstream sub-basins, one percent reduction of the forest cover can increase the annual streamflow and annual baseflow by 2.5%–5.4% and 2.6%–6.7%, respectively. One percent reduction of the forest cover can increase the annual suspended sediment load by 8.7%. These findings will help develop better understanding of land use management in the UCPRB for water-soil conservation. [ABSTRACT FROM AUTHOR]

Highlights: [•] Decreasing precipitation was the primary cause of the decrease in runoff. [•] Rising atmospheric CO2 concentration had a limited impact on the change in runoff. [•] Inclusion of dynamic vegetation phenology is important in hydrological modelling. [Copyright &y& Elsevier]

• Eight methods were used to partition evapotranspiration. • The methods were evaluated by two-stage soil evaporation theory and meta-analysis. • Transpiration Estimation Algorithm (TEA) was most suitable for wheat and maize. • New method based on the optimal stomatal model performed similarly with TEA. • Interannual variability of transpiration and evaporation was quite different. Partitioning of evapotranspiration (ET) is important for understanding surface-atmosphere interactions, hydrological cycle, and plant water use strategy. Here, we applied seven widely used eddy covariance (EC)-based methods and 15-year EC measurements in a winter wheat-summer maize rotation cropland in North China Plain to partition ET into soil evaporation (E) and plant transpiration (T). Then the two-stage theory of bare soil evaporation was employed to evaluate these partitioning methods. This innovative evaluation approach is particularly suitable for this kind of ecosystem, requires no direct measurements of ET components, and avoids spatial mismatching between the source areas of reference values and EC-based ET. Combining the two-stage theory and the meta-analysis, we found that among seven partitioning methods, only the Transpiration Estimation Algorithm (TEA) (hereafter, N18 method) utilizing a machine learning approach not only simulated the dynamics of 14-day transpiration fraction of ET (T/ET) quite well, but also yielded reliable 14-day and mean growing season magnitudes of T/ET for both crops. Furthermore, we developed a new partitioning method based on the stomatal slope parameter in the optimality-based unified stomatal optimization (USO) model. The newly developed method showed similar performances with N18 method on partitioning ET of both crops at our site. By using the N18 method and the newly developed method, we revealed that the multi-year mean growing season T/ET (± standard deviation) was 0.72 ± 0.03 and 0.77 ± 0.04 for maize and wheat, respectively. For the interannual variability of ET and its components, only T of maize increased significantly during 2005–2019 at our site. Moreover, it was found that E had the highest interannual variability followed by T and then T/ET for both crops. [ABSTRACT FROM AUTHOR]

• We derived a high-quality ET product from the largest number of flux sites till now. • ET trend was insignificant but exhibited a reversal during 1982-2015. • Water balance showed no significant trend during 1982-2015. • Precipitation dominated ET and water balance trends over the whole region. • The revegetation programs dominated ET in some areas. As an important part of global semi-arid grassland, adequately understanding the spatio-temporal variability of evapotranspiration (ET) and water balance (WB, defined as precipitation-ET) over the temperate semi-arid grassland of China (TSGC) could advance our understanding of climate, hydrological and ecological processes over global semi-arid areas. Based on the largest number of in-situ ET measurements (13 flux towers) within the TSGC, we applied the support vector regression (SVR) method to develop a high-quality ET dataset for the TSGC from 1982 to 2015. The model performed well in validation against flux tower‐measured data and comparison with water-balance derived ET. The annual ET ranged from 226 to 294 mm yr-1 with an average of 250 mm yr-1 and an insignificant trend during 1982-2015. Nevertheless, ET increased significantly during 1982-1998, and turn to decrease during 1999-2011. Regional WB, which approximately represents water availability, fluctuated without a significant trend for entire period. But the annual mean WB at 1999-2011 decreased by 26.1% compared with that before 1998. On average, ET was dominated by climatic factors, especially precipitation, rather than human activities. The reversal of ET trend after 1998 was predominantly explained by the slow increase of precipitation, the stalled increase of temperature, and the significantly decreasing radiation. The revegetation programs exacerbated the evaporative water consumption significantly in some areas after 1998, such as Yellow River Basin. The variation of WB was mainly driven by precipitation, whether in time or space. In addition, the spatio-temporal difference between our SVR ET dataset with four widely used global ET datasets (i.e., GLEAM, FLUXCOM, MODIS, and BESS) suggested that none of these four products can capture both the magnitude and variability of ET well in the TSGC, and local observations are of great importance. [ABSTRACT FROM AUTHOR]

The irrigated areas in the northern region of China are important food production areas. Therefore, studies on the variability of the carbon balance in these agro-ecosystems are fundamental for the management of carbon sequestration. This paper simulated the long-term variability of the carbon balance in a typical irrigated area along the lower Yellow River from 1984 to 2006, using a process-based ecosystem model called the Simple Biosphere Model, version 2. The mean annual gross primary production (GPP), mean annual net assimilation rate (NAR), mean annual soil respiration ( R), and mean annual net ecosystem exchange (NEE) were 1733, 1642, 1304, and −338 g C m a, respectively. A significant increasing trend in the seasonal total NAR during the wheat growing season, and a significant decreasing trend in the seasonal total NAR during the maize growing season were detected. However, no significant trend was found in the annual NAR, R, and NEE. The average carbon sequestration was 1.93 Tg C a when the grain harvest was not taken into account, and the carbon sequestration amount during the maize season was higher than that during the wheat season. However, the agro-ecosystem was a weak carbon source with a value of 0.23 Tg C a, when the carbon in the grain was assumed emitted into the atmosphere. [ABSTRACT FROM AUTHOR]

Abstract: Using the eddy covariance technique, three years (October 2005–September 2008) of water and energy flux measurements were obtained for a winter wheat/summer maize rotation cropland in the North China Plain. This region is critical for food production in China, and is prone to significant water shortages and drought. Seasonal and interannual variability in evapotranspiration (ET) were examined in terms of relevant controlling factors. The annual ET was 595 and 609mm in the periods of 2005–2006 and 2006–2007, respectively. The average seasonal ET in the wheat and maize field was 401 and 212mm, respectively. Seasonal variability in ET was primarily explained by the variations in equilibrium evaporation (ET eq) and canopy conductance (G s). Daily evapotranspiration ranged from 1.0 to 7.8mmday−1 during the wheat season and reached up to 5.1mmday−1 during the maize season. The maximum midday average G s was 32mms−1 for wheat and 17mms−1 for maize. During the rapid growth stages, the average midday LE/R n (LE is latent heat flux, R n is net radiation) was 83% for wheat and 57% for maize, indicating a higher water consumption for wheat than for maize. On an annual basis, latent heat flux accounted for about 59% of the net radiation, suggesting that more energy is partitioned into evapotranspiration in this agroecosystem site. Regional irrigation promoted sensible heat advection from the surrounding drier surface during the wheat seasons. Monthly ET totals enhanced by sensible heat advection accounted for 27% of the ET eq during the rapid growing season of wheat. [Copyright &y& Elsevier]

• None of WUE metrics showed a significant trend during 2005-2019. • Interannual variability of G 1 was dominated by soil water content. • Global RS-based products cannot capture interannual variations of EWUE. Based on fifteen-year observations, we explored the interannual variations of five water use efficiency (WUE) indicators (i.e., standard ecosystem WUE (EWUE), plant-canopy WUE (PWUE), inherent WUE (IWUE), underlying WUE (uWUE) and stomatal slope (G 1)) over a typical winter wheat-summer maize rotation cropland in the North China Plain. The results showed that none of WUE indicators had a significant interannual trend. PWUE showed the lowest interannual variability and could be regarded as stationary for these two crops. G1 was stationary for wheat which was under an essentially constant soil water condition, whereas exhibited a strong fluctuation for maize experiencing more variable soil water content (SWC) than wheat. IWUE and uWUE were non-stationary for both crops. SWC and leaf area index (LAI) dominated EWUE for maize and wheat, respectively. PWUE was dominated by the shortwave solar radiation (R g) in maize seasons and not significantly affected by any meteorological or biophysical factors in wheat seasons. For IWUE and uWUE, air temperature (T a) and LAI were the most important drivers in maize and wheat seasons, respectively. Atmospheric CO 2 concentration (C a) and vapor pressure deficit (VPD) were not revealed as important controllers. These findings reflected that the meteorological and biophysical regulatory mechanisms of WUE indicators at the ecosystem level were quite different from that at the leaf level. But G 1 was an exception due to that for both maize and wheat, G 1 was only significantly affected by SWC. Moreover, we found that none of the remote sensing (RS)-based global products performed satisfactorily on capturing interannual variations of EWUE for both crops. These results cautioned that using these global RS-based products to explore the interannual variations of EWUE for the cropland ecosystem may lead to substantial bias. [ABSTRACT FROM AUTHOR]

• An effective scheme to map long-term and large-scale distribution of winter wheat-summer maize was proposed. • The impacts of different temporal resolutions of MODIS data and sample categories on classification were investigated. • The spatio-temporal change of winter wheat-summer maize planting area during 2001–2018 in the North China Plain was analyzed. • The study provided important information for agricultural water resources management. Discriminating winter wheat-summer maize distribution is fundamental for agricultural water resources management in the North China Plain (NCP) which confronts severe conflicts between food production and agricultural water scarcity. However, how the planting area changed since 2000 is still unclear. Therefore, the winter wheat-summer maize from 2001 to 2018 was identified by using the maximum likelihood algorithm of supervised classification based on the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) product. Three schemes with different temporal resolutions of MODIS data and sample categories were compared to obtain the most reasonable identification results. The results reveal that using 16-day 0.0025° MODIS NDVI data and six sample categories including winter wheat-summer maize, winter wheat-rice, spring maize, cotton, other one cropping systems and other double cropping systems is an effective way for tracking the variation of winter wheat-summer maize distribution. The winter wheat-summer maize planting area showed an insignificant increasing trend at a rate of 34.2 km2/year (p = 0.955, CV = 7.49%) during 2001–2018, while it decreased at the rate of −5065.2 km2/year (p = 0.074) after 2012. Spatially, the planting area shrunk in northern NCP, the piedmont plain of the Taihang Mountains, the west of dry sub-humid zone and the southwest part of the NCP, accounting for 58.6% of the counties during 2001–2018; while 17.3% of the counties significantly expanded winter wheat-summer maize in the irrigation district along the Yellow River in Shandong province, the southeast of Hebei Plain and the central humid zone. Our results provide fundamental information for quantifying the change of crop water consumption and optimizing crop water resource allocation. [ABSTRACT FROM AUTHOR]

Runoff decrease triggered or exacerbated by human activities over the past decades on the Loess Plateau has been drawing nationwide concerns; quantifying human-induced runoff-altering factors is of great significance for decision-making on maintaining regional water, ecological and economic security. Sediment-trapping dams (STDs) construction and revegetation are the two major soil-water conservation practices regarded to have caused runoff reduction, while their hydrologic effects on the basin scale have not been separated quantitatively. In this study, we chose the Huangfuchuan River Basin as a case study area, and proposed a physically-based attribution framework with the ability to account for the hydrologic effects of STDs, revegetation, and climate change simultaneously and attribute runoff decrease of the basin among these factors. The model-based attribution results revealed that STDs construction caused a 45% (48%) runoff reduction from 1976 to 1988 to 1989–2000 (2001–2014) and revegetation was responsible for a 30% runoff decrease from 1976 to 1988 to 2001–2014, while the daily simulation implied that the hydrologic effect of revegetation affected daily runoff magnitudes more consistently than that of STDs. Our study demonstrates that STDs construction was the prime contributor to runoff decrease in the case study area and suggests that STDs should be taken into account in similar studies on the Loess Plateau in the future. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is referred to as the water tower of Asia, where water storage and precipitation have huge impacts on most major Asian rivers. Based on gravity recovery and climate experiment data, this study analyzed the terrestrial water storage (TWS) changes and estimated areal precipitation based on the water balance equation in four different basins, namely, the upper Yellow River (UYE), the upper Yangtze River (UYA), the Yarlung Zangbo River (YZ), and the Qiangtang Plateau (QT). The results show that the TWS change exhibits different patterns in the four basins and varies from −13 to 2 mm/year from 2003 to 2017. The estimated mean annual precipitation was 260 ± 19 mm/year (QT), 697 ± 26 mm/year (UYA), 541 ± 36 mm/year (UYE), and 1160 ± 39 mm/year (YZ) which performed better than other precipitation products in the TP. It indicates a potential method for estimating basin-scale precipitation through integrating basin average precipitation from the water balance equation in the poorly gauged and ungauged regions. [ABSTRACT FROM AUTHOR]

• Wheat ET increased significantly and maize ET decreased significantly. • The high mean annual ET occurred in the well-irrigated area and humid region. • Human activities controlled ET trend in wheat season. • Climate change dominated ET trend in maize season. Accurate evapotranspiration (ET) estimation is important for understanding hydrological cycle and water resources management in the cropland. Based on eight flux sites within the North China Plain (NCP) and the surrounding area, which were integrated together for the first time, we applied support vector regression method to develop ET dataset for the cropland in NCP from 1982 to 2015 with 1/12° spatial resolution and eight-day temporal interval. The mean annual ET over cropland within NCP was 575 mm yr−1 with a non-significant increasing trend. In wheat season, the seasonal ET increased significantly at the rate of 1.28 mmyr−2 with a mean value of 238 mmyr−1; in maize season, the mean value of seasonal ET was 221 mmyr−1 with a decreasing trend of −0.95 mmyr−2. The comparatively high mean annual ET values occurred primarily in the well irrigated area near the Taihang Mountains, irrigation districts along the Yellow River and the humid region. The attribution analysis which combined multiple regression with the first difference method revealed that human activities dominated ET trend at annual scale as well as in wheat season, with relative contributions of 52% and 56%, respectively. While in maize season, ET trend was mostly controlled by climate change with relative contribution of 77%. Among the climate factors, in wheat season, the significantly increasing air temperature was the principal climatic cause of ET increase which was partly offset by the significantly decreasing wind speed; while in maize season, the significant ET decline was primarily resulted from the significantly decreasing net radiation and wind speed. Compared with our ET dataset, the four widely used global or national ET datasets significantly underestimated ET in wheat season, especially in the extensively irrigated areas, suggesting that local observations are crucial for regional studies. [ABSTRACT FROM AUTHOR]

Background: Hodgkin Lymphoma (HL) is a type of aggressive malignancy in lymphoma that has high incidence in young adults and elderly patients. Identification of reliable diagnostic markers and efficient therapeutic targets are especially important for the diagnosis and treatment of HL. Although many HL-related molecules have been identified, our understanding on the molecular mechanisms underlying the disease is still far from complete due to its complex and heterogeneous characteristics. In such situation, exploring the molecular mechanisms underlying HL via systems biology approaches provides a promising option. In this study, we try to elucidate the molecular mechanisms related to the disease and identify potential pharmaceutical targets from a network-based perspective. Results: We constructed a series of network models. Based on the analysis of these networks, we attempted to identify the biomarkers and elucidate the molecular mechanisms underlying HL. Initially, we built three different but related protein networks, i.e., background network, HL-basic network and HL-specific network. By analyzing these three networks, we investigated the connection characteristic of the HL-related proteins. Subsequently, we explored the miRNA regulation on HL-specific network and analyzed three kinds of simple regulation patterns, i.e., co-regulation of protein pairs, as well as the direct and indirect regulation of triple proteins. Finally, we constructed a simplified protein network combined with the regulation of miRNAs on proteins to better understand the relation between HL-related proteins and miRNAs. Conclusions: We find that the HL-related proteins are more likely to connect with each other compared to other proteins. Moreover, the HL-specific network can be further divided into five sub-networks and 49 proteins as the backbone of HL-specific network make up and connect these 5 sub-networks. Thus, they may be closely associated with HL. In addition, we find that the co-regulation of protein pairs is the main regulatory pattern of miRNAs on the protein network in the HL-specific network. According to the regulation of miRNA on protein network, we have identified 5 core miRNAs as the potential biomarkers for diagnostic of HL. Finally, several protein pathways have been identified to closely associated with HL, which provides deep insights into underlying mechanism of HL. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (PV) generation has become the major type of solar energy utilization as the world's energy demand grows. However, the layout of large-scale public PV plants changes the original underlying conditions and has an impact on the local surface energy budget and distribution. Based on the ecohydrological model T&C, taking the fixed utility-scale PV plants as the typical object proposes a PV module, and the T&C-PV model is developed to simulate the impact of PV plants on the regional surface energy budget. Compared with the original T&C model, a substantially improvement of the simulation of energy flux in the PV plant paved underlying surface has been achieved in the T&C-PV model. This model is applied to PV power plants in Xinjiang Province, China, and the results show that the sensible heat flux increased by 12% and the latent heat flux decreased by 25%, with the percentage of transpiration decreasing from 90.1% to 74.5% and the percentage of evaporation increasing from 9.9% to 25.5% after the PV power plants are set up. • Developed a PV module to simulate the energy budget of PV panels. • Established a T&C-PV model based on the ecohydrological model T&C. • Evaluate the change of heat flux near surface under the PV panel. • Quantitively estimate the influence of the PV plant on energy balance. [ABSTRACT FROM AUTHOR]

Climate change and underlying surface change are two main factors affecting the hydrological cycle. In respect of climate change, precipitation alters not only in magnitude, but also in intensity, which can be represented by precipitation depth. To further understand the spatial variation of the impact of precipitation, potential evapotranspiration, precipitation depth and the water storage capacity during 1960–2010, 224 catchments located from arid areas to humid areas across China were analyzed in this paper based on the Choudhury-Porporato equation within the Budyko hypothesis. The results show that underlying surface change is the major driving force of runoff change in the Songhua Basin, the Liaohe Basin and the Haihe Basin, while climate change dominates runoff change in other basins. Climate change causes runoff increase in most catchments, except for some catchments in the Yellow River Basin and the Yangtze River Basin. Specifically, changes in precipitation depth induce runoff increase in almost each catchment and show a considerable contribution rate (14.8% on average, larger than 20% in 32% catchments). The contribution of precipitation depth change has little correlation with the aridity index, while positively correlates to the significance of trend in precipitation depth. This study suggests that precipitation depth is an important aspect that should be taken into consideration in attribution of runoff change. The findings in this study provide a sight for future researches in attribution analysis within the Budyko framework. [ABSTRACT FROM AUTHOR]

[Display omitted] • We simulated the eco-hydrological process of the TSGC from 1901 to 2016. • LAI, GPP, and WUE showed significant increasing trends, dominated by rising CO 2. • Water yield showed a decreasing trend, dominated by warming and rising CO 2. • Changes in vegetation and water resources were more prominent in sandy grassland. • Warming was a suppressant of vegetation growth in typical steppe regions. As an important part of global semi-arid grassland, adequately understanding how eco-hydrological processes in the Temperate Semi-Arid Grassland of China (TSGC) respond to environmental change over a century-long time scale is of critical importance to environmental change adaptation and mitigation policy in the semi-arid region. We investigated the dynamics and driving forces of key eco-hydrological variables (leaf area index (LAI), gross primary production (GPP), evapotranspiration (ET), water yield (WY), and water use efficiency (WUE)) of 8 typical locations within the TSGC during the period 1901–2016, using a well-tested mechanistic eco-hydrological model, seamlessly integrating land-surface energy balance, hydrological and carbon cycle, vegetation dynamics, and soil biogeochemistry. Results show that dominated by the elevated CO 2 , the annual LAI, GPP, and WUE increased significantly during 1901–2016, indicating that the environmental conditions were conducive to vegetation growth. Warming conditions were a promoter of vegetation growth in sandy grassland but a suppressant in typical steppe due to water stress increase. For the same reason, ET of sandy grassland exhibited a significant increasing trend, in response to warming, while that of typical steppe had an insignificant decreasing trend, controlled by the precipitation decline. Warming and the vegetation growth acceleration due to the elevated CO 2 negatively influenced WY, which showed a decreasing trend, especially in the sandy grassland, suggesting the reduction of available water resources. Overall, our results revealed that this region, especially sandy grassland, exhibited an "enhanced vegetation but decreased water yield" trend under environmental changes occurred in the past century. [ABSTRACT FROM AUTHOR]

Summary Drought severity not only depends on weather anomaly, but is also related to terrestrial hydrological condition to a large extent. In this study, we analyzed droughts using indices based on precipitation and soil moisture during the period of 1960–2010 in Haihe basin, which is a typical drought-prone region in North China. The Soil Moisture Drought Severity (SMDS) and Standardized Precipitation Index (SPI) are used to evaluate drought severity. SMDS is calculated based on the monthly soil moisture of upper 50 cm from the simulation by Community Land Model (CLM 4.0) and SPI is calculated based on gridded precipitation at 0.05° resolution (5 km × 5 km approximately), which is spatially interpolated from observations. During the last 51 years, 36 severe drought events (affecting areas greater than 20,000 km 2 and durations longer than 3 months) have been identified based on SMDS, and 41 drought events identified based on SPI. Results derived from SMDS indicate that there is a significant increasing trend in the drought affected area, and that the drought event occurred in 1999 has the largest affected area. Compared with the drought events derived from SMDS, the events derived from SPI have shorter durations but larger affected areas on average. Although the mean NDVI of the whole basin has been increasing since the 1980s, the two declining periods of 1992–1994 and 1999–2003 show fairly good agreement with the drought events identified in the same periods. The Anomaly of Normalized Difference Vegetation Index (A-NDVI) is introduced as NDVI anomaly from its trend line, thus the negative value of A-NDVI can reflect the drought impact on vegetation reasonably. Result indicates that both the SMDS and SPI are significantly correlated with A-NDVI, and correlation between annual SMDS and A-NDVI is higher than that of SPI. [ABSTRACT FROM AUTHOR]

• Dual source λET model was improved for film mulched cropland with shallow groundwater. • Ignoring film mulching leads to overestimation of λE and then λET. • Responses of the resistances in SW model to λET and its components were quantified. • Average T/ET during maize growing season was as high as 0.78–0.84. • Path analysis revealed the dominated effects of Hc and WTD on maize λET. Evapotranspiration (ET) is a key link in terrestrial water cycle and influenced by complex environmental factors in cropland. Accurate assessment of crop ET over heterogeneous underlying surfaces remains challenging. In this study, the dual source Shuttleworth-Wallace (SW) model was modified to estimate λET (latent heat corresponding to ET) through incorporating the effects of film mulching and shallow groundwater. λET and latent heat from transpiration (λT) were measured in a maize field in northwest China during 2017 and 2018 to assess the performance of the original (SW) and modified (SWM) models. Results indicate that the overestimation of latent heat from soil evaporation (λE) due to ignoring film mulching could be obviously mitigated by SWM. Besides, considering capillary rise from shallow groundwater in SWM improved not only λET estimates but also the accuracy of canopy resistance parameter. The SWM model outperformed the SW model that the slopes of fitting lines for λET and λT increased from 0.60 to 0.79 to 0.77–0.99 at daily scale and Nash-Sutcliffe Efficiency coefficient exceeded 0.86. Relative error and RMSE were decreased to below 0.15 and 19.88 W m−2, respectively. The estimations of λET and λT by SWM were also improved at hourly scale. Seasonal variation and partition of λET between two years were comparable and average T/ET for the entire growing season was about 78 %-84 %, which was largest at the heading stage. Path analysis on the responses of λET to the environmental factors recognized the greatest direct effect of crop height or leaf area index, and identified the significantly direct control of shallow groundwater on λT in this area. The study presented an improved dual source model to better quantify λET, which would benefit water resources management for film mulched croplands with shallow groundwater. [ABSTRACT FROM AUTHOR]

The typical steppe in Inner Mongolia is an important component of the Eurasian steppes. It plays a dominant role in preventing desertification and against sandstorms, but highly sensitive and vulnerable to climate change. Based on long-term observed precipitation data and remotely sensed Normalized Difference Vegetation Index (NDVI) images, the non-stationary behavior of summer precipitation and its linkage with vegetation change were investigated, by means of incorporating time-varying and physical based explanatory covariates in non-stationary modeling. Results indicated that time-dependent models exhibited good performance to reproduce the temporal variations of eco-hydrological variables. The non-stationarity of summer precipitation was prominently visible for the majority of sites during the period from 1957 to 2017, with the mean behavior described as a linear or nonlinear time-varying pattern. In general, the steppe has experienced a decreasing trend in summer precipitation, but whether the decline tends to maintain or weaken or strengthen depends on the spatial location of the site studied. Differences appeared in the changes of vegetation in summer from 1998 to 2017 in different sub-regions. Evidences for the presence of stationary evolution was found in most sub-regions in the middle part, together with a linear increase in the westernmost sub-regions while a non-linear decrease in the easternmost sub-regions. Covariate analyses further highlighted the role of precipitation variabilities in the modeling of the NDVI-related vegetation dynamics over the steppe. The potential relations of summer precipitation to vegetation growth were characterized as both linear and non-linear positive forms. In particular, precipitation extremes could be responsible for the occurrences of exceptional cases in vegetation condition. The fluctuations in summer precipitation have crucial significance for future predictions of vegetation succession. Findings from this study would lead to additional insights to understanding the effect of climate change on grassland ecosystem processes. [ABSTRACT FROM AUTHOR]

Aβ42 peptides can form helix and sheet structure under different conditions. The conformational conversion is closely associated with Aβ peptides aggregation and their neurotoxicity. But the transition from helix to sheet is not be clearly understood. In this study we performed microsecond timescale MD simulations of Aβ42 peptide to investigate the conformation transition from α-helix to β-sheet. Markov state model (MSM) was built to facilitate identification of crucial intermediate states and possible transition pathway. Based on the analysis, we found that the region Y10-A21 in the middle of Aβ42 peptide plays an initial role in this transition. MSM model revealed that the collapse of helical structure in this region might trigger the formation of sheet structure. Moreover, we further simulated the aggregation of Aβ42 peptides with different conformations. We found that the Aβ42 peptides forming sheet structure have higher aggregation potential compared with peptides with helix structure. These results demonstrate that we can prevent the aggregation of Aβ42 peptides by stabilizing the helix structure in the region of Y10-A21. In addition, this study provides new insight into better understanding the conformational transition and aggregation of Aβ42 peptides. [Display omitted] • Explore the conformational transition of Aβ42 peptide from helix to sheet. • Collapse of helix at residue Y10-A21 initiates the helix-to-sheet transition of Aβ42 peptide. • Identified the intermediates and possible path of conformation transition using MSM. • The Aβ42 peptides forming sheet structure possess higher aggregation potential. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) from agricultural land is the most common form of water consumption in the North China Plain. Based on in situ measurements by an eddy covariance (EC) system, the present study tested the surface energy balance system (SEBS) model for estimating surface energy fluxes from a wheat/maize rotation cropland. Applicability of the SEBS model using Moderate Resolution Imaging Spectroradiometer (MODIS) land products to estimate ET was further validated. The model proved to be appropriate to measure heat flux during the wheat-growing season, but underestimated the sensible heat flux during the maize-growing season. Although the SEBS model performed better during the wheat-growing season, the relative error of the latent heat flux was within 20% in both wheat- and maize-growing seasons. Results showed that the SEBS model using remote sensing data could provide a reasonable estimate of the surface energy fluxes from an irrigated cropland in the North China Plain. [ABSTRACT FROM AUTHOR]

Soil salinization problems are widespread in the Hetao plain, Inner Mongolia, resulting from arid climate conditions, a shallow saline water table, poor irrigation water management, and insufficient drainage. This study follows previous research aimed at evaluating crop water use and controlling the salinity build-up in the region, namely using weighing and static water table lysimeters to parameterize a water balance model aimed at the development of appropriate irrigation scheduling. Two sets of five static water table lysimeters, which fixed depths ranged from 1.25 to 2.25 m, were used over two maize crop seasons. The mechanistic HYDRUS-1D model was further used to daily predict measured data on soil water contents, boundary fluxes in the interface between the saturated and unsaturated zones, the electrical conductivity of the soil saturation paste extract (EC e), and the actual crop evapotranspiration (ET c act). The soil water balance helped quantify the combined effect of water and salinity stresses on root water uptake as well as groundwater fluxes into the rootzone. The salt balance showed that the salinity build-up was much related to irrigation and capillary fluxes, and that the autumn irrigation carried out during the non-growing season was essential for controlling soil salinity. The efficiency of the autumn irrigation much depended on groundwater depth and the amount of water applied for salt leaching, with the best results found for the lysimeters with water table depths at 2.0 and 2.25 m (85–100%) for irrigation depths ≥ 220 mm. The lysimeters with shallower water tables never showed a leaching efficiency higher than 88%. This research shows that the sustainability of irrigation in Hetao depends on finding adequate solutions for controlling the depth of the saline groundwater, minimizing capillary fluxes to the rootzone, and developing consequent approaches for autumn irrigation leaching. • Soil water contents and fluxes, EC e , and ET c act were measured using water table lysimeters. • The HYDRUS-1D model successfully simulated lysimeter data during two seasons. • The water table depth influenced the effectiveness of autumn irrigation leaching. • The leaching efficiency only increased by improving soil drainage conditions. • Reducing autumn irrigation depth (<200 mm) promoted soil salinization. [ABSTRACT FROM AUTHOR]

Satellite-based precipitation products (e.g., Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) and its predecessor, Tropical Rainfall Measuring Mission (TRMM)) are a critical source of precipitation estimation, particularly for a region with less, or no, hydrometric networking. However, the inconsistency in the performance of these products has been observed in different climatic and topographic diverse regions, timescales, and precipitation intensities and there is still room for improvement. Hence, using a projected ensemble algorithm, the regional precipitation estimate (RP) is introduced here. The RP concept is mainly based on the regional performance weights derived from the Mean Square Error (MSE) and the precipitation estimate from the TRMM product, that is, TRMM 3B42 (TR), real-time (late) (IT) and the research (post-real-time) (IR) products of IMERG. The overall results of the selected contingency table (e.g., Probability of detection (POD)) and statistical indices (e.g., Correlation Coefficient (CC)) signposted that the proposed RP product has shown an overall better potential to capture the gauge observations compared with the TR, IR, and IT in five different climatic regions of Pakistan from January 2015 to December 2016, at a diurnal time scale. The current study could be the first research providing preliminary feedback from Pakistan for global precipitation measurement researchers by highlighting the need for refinement in the IMERG. [ABSTRACT FROM AUTHOR]

Quantifying the relative contributions of different factors to runoff change is helpful for basin management, especially in the context of climate change and anthropogenic activities. The effect of snow change on runoff is seldom evaluated. We attribute the runoff change in the Heihe Upstream Basin (HUB), an alpine basin in China, using two approaches: a snowmelt-based water balance model and the Budyko framework. Results from these approaches show good consistency. Precipitation accounts for 58% of the increasing runoff. The contribution of land-cover change seems unremarkable for the HUB as a whole, where land-cover change has a major effect on runoff in each sub-basin, but its positive effect on increasing runoff in sub-basins 1 and 3 is offset by the negative effect in sub-basin 2. Snow change plays an essential role in each sub-basin, with a contribution rate of around 30%. The impact of potential evapotranspiration is almost negligible. EDITOR D. KoutsoyiannisASSOCIATE EDITOR S. Huang [ABSTRACT FROM PUBLISHER]

The net anthropogenic nitrogen input (NANI) is an important nutrient source that causes eutrophication in water bodies. Understanding the spatio-temporal variation of NANI is important for regional environment assessment and management. This paper calculated NANI in the upper Yangtze River basin (YRB), upstream of the Three Gorges Dam (TGD), from 1990 to 2012, and analyzed its spatio-temporal characteristics. Over the past 23 years of the study, the average annual NANI increased from 3200 kg N km to 4931 kg N km. The major components were fertilizer N application, atmospheric N deposition, and net food and feed N import. In the northwest high mountainous region with a sparse population, the main component was atmospheric N deposition. Fertilizer N application and net food and feed N import were concentrated in the Chengdu Plain because of the high population density and large areas of farmland. This research found that NANI increased with rapid urbanization and increasing population. The Pearson correlation results illustrated that the spatial distributions of NANI and its major components were affected by land cover/use, agricultural GDP and total population. Increasing NANI has been the major cause of the degrading stream water quality over the past 20 years and is becoming a major threat to the water quality of the TGD reservoir. [ABSTRACT FROM AUTHOR]

Solar radiation is the external driving force of the Earth's climate system. In different spatial and temporal scales, meteorological elements have different responses and lag periods to solar activity (SA), climatic oscillation (CO), geographic factors (GF) and other influencing factors. However, such studies are not abundant and in-depth in the world. To further understand the "solar-climate-water resource" system, this study considers China as the study area and investigates the monthly data of temperature (T) and precipitation (P) during 1900–2020 that were obtained from 3836 grid stations. The strong interaction and lag distribution between T or P with SA and CO were studied and influence weights of SA, CO, and geographical factors (GF) of each grid station were calculated. A multivariate hysteretic decomposition model was established to simulate and quantitatively decompose the periodic lag considering the factors of the earth's revolution. It is found that the strong interaction/lag periods obtained in a long-time scale can be decomposed into several periods shorter than the SA period. The distribution of strong interaction/lag periods is nested with topography and echoes with cities. The underlying surface conditions and urbanization are also important factors affecting the T and P lag. There are two distinct dividing lines in the lag period and influencing factor pattern of T and P. The T dividing line moves through valleys where water or mountain ranges meet, where the gap facilitates monsoon movement across regions, while the P dividing line is a zone of dramatic terrain, where tall mountains block water vapor transport. In the lag trend of T, the northern region of China has the longest lag period, and the lag period of surrounding regions tends to converge to the northern region. The lag period caused by SN in southwest China is larger than that in northwest China, while the lag effect of CO is opposite in the above two regions. The lag trend of P also has the above characteristics, but the difference is that the lag period in central China is the longest. • Two distinct dividing lines in the hysteresis distribution of T and P respectively. • MHDM descripts how lag of SA to T & P decomposed into CO, SY & GF. • Weight distribution of SA, GF and CO in RGB false color synthesis. [ABSTRACT FROM AUTHOR]

Arid and semiarid regions are the focus of terrestrial ecological vulnerability as a consequence of their distinctive geography and rapid evolution of anthropogenic controls. To understand the evapotranspiration (ET) variation in ecofragile regions, this study obtained seven years of eddy covariance (EC) observations from the Yulin site in Mu Us Sandy Land, and further proposed a framework to separate the impact of meteorological and anthropogenic controls on ET based on EC observations and Simple Biosphere Model-V2 (SiB 2). The observed annual ET ranged from 336 mm·year−1 to 430 mm·year−1. Anthropogenic controls, namely, land cover change into bare soil, alfalfa, and potato, had obvious impacts on ET, which led to − 16.0%, 26.1% and 14.3% of the change in ET during the vegetation-growing period (April-October), respectively. At the annual scale, if alfalfa is planted, ET rises to ~120% that of natural vegetation; if potato is planted, ET remains largely the same. Remarkably, during the crop growing period of potato (June-September), ET of potato rises to ~150% that of natural vegetation. At this ecofragile region, it will take ~ 3–4 years to recover to the natural situation. This study provided a framework for delineating the contribution of meteorological and anthropogenic impacts on ET and a theoretical basis for ecological restoration and vegetation amelioration in semiarid regions. • Observed 7-year variations of ET using EC system in a changing ecofragile region. • During crop growing period (Jul 2016-Jun 2017), alfalfa led to ~20% increase in ET. • During crop growing period (Jun-Sep 2017), potato led to ~50% increase in ET. • In Mu Us Sandy Land, it will take ~ 3–4 years to recover from destructed vegetation. [ABSTRACT FROM AUTHOR]

The seasonal-cycle amplitude (SCA) of the atmosphere-ecosystem carbon dioxide (CO2) exchange rate is a useful metric of the responsiveness of the terrestrial biosphere to environmental variations. It is unclear, however, what underlying mechanisms are responsible for the observed increasing trend of SCA in atmospheric CO2 concentration. Using output data from the Multi-scale Terrestrial Model Intercomparison Project (MsTMIP), we investigated how well the SCA of atmosphere-ecosystem CO2 exchange was simulated with 15 contemporary terrestrial ecosystem models during the period 1901-2010. Also, we made attempt to evaluate the contributions of potential mechanisms such as atmospheric CO2, climate, land-use, and nitrogen deposition, through factorial experiments using different combinations of forcing data. Under contemporary conditions, the simulated global-scale SCA of the cumulative net ecosystem carbon flux of most models was comparable in magnitude with the SCA of atmospheric CO2 concentrations. Results from factorial simulation experiments showed that elevated atmospheric CO2 exerted a strong influence on the seasonality amplification. When the model considered not only climate change but also land-use and atmospheric CO2 changes, the majority of the models showed amplification trends of the SCAs of photosynthesis, respiration, and net ecosystem production (+0.19 % to +0.50 % yr-1). In the case of land-use change, it was difficult to separate the contribution of agricultural management to SCA because of inadequacies in both the data and models. The simulated amplification of SCA was approximately consistent with the observational evidence of the SCA in atmospheric CO2 concentrations. Large inter-model differences remained, however, in the simulated global tendencies and spatial patterns of CO2 exchanges. Further studies are required to identify a consistent explanation for the simulated and observed amplification trends, including their underlying mechanisms. Nevertheless, this study implied that monitoring of ecosystem seasonality would provide useful insights concerning ecosystem dynamics. [ABSTRACT FROM AUTHOR]

Summary Drought frequency analysis is a prerequisite for drought resistance planning and drought risk management. Drought is a spatio-temporal dynamic process, usually characterized by its duration, spatial extent, and severity. Copula based multivariate frequency analysis has been widely used to calculate drought frequency. However, the spatial extent is scarcely considered in previous studies, due to the fact that drought event is usually identified either for a fixed spatial scale or for a fixed temporal scale. This study develops a regional drought frequency analysis model based on trivariate copulas by considering the spatio-temporal variations of drought events. Drought duration, drought affect area, and drought severity are identified first, and their trivariate joint distribution is constructed later. The model is applied for drought frequency analysis in Southwest China during 1961–2012. A variety of probability distribution functions and copula functions (including elliptical, symmetric and asymmetric Archimedean) are used as candidate choices, and the most appropriate ones are selected based on goodness of fit using different methods. The robustness of drought frequency analysis is then evaluated and discussed. The results show that drought frequency analysis needs to fully consider the three characteristic parameters (duration, affect area, and severity) reflecting drought spatio-temporal variability. And the drought return period estimated by the copula-based trivariate frequency analysis appropriately integrates the effects of drought duration, affect area and severity, which is a reliable drought statistical measurement. The 2009–2010 drought, which has a return period of about 94 years, is the most severe one in Southwest China during the period of 1961–2012. The Joe and Gumbel copulas are found to be more suitable to estimate the joint distribution of drought duration, affect area and severity, and the Asymmetric (nested) function forms perform better than the symmetric functions. [ABSTRACT FROM AUTHOR]

Modeling the hydrological processes at catchment scale requires a flexible distributed scheme to represent the catchment topography, river network and vegetation pattern. This study has developed a distributed scheme for eco-hydrological simulation in the upper Heihe River. Based on a 1 km × 1 km grid system, the study catchment is divided into 461 sub-catchments, whose main streams form the streamflow pathway. Furthermore, a 1 km grid is represented by a number of topographically similar 'hillslope-valley' systems, and the hillslope is the basic unit of the eco-hydrological simulation. This model is tested with a simplified hydrological simulation focusing on soil-water dynamics and streamflow routing. Based on a 12-year simulation from 2001 to 2012, it is found that variability in hydrological behavior is closely associated with climatic and landscape conditions especially vegetation types. The subsurface and groundwater flows dominate the total river runoff. This implies that the soil freezing and thawing process would significantly influence the runoff generation in the upper Heihe basin. Furthermore, the runoff components and water balance characteristics vary among different vegetation types, showing the importance of coupling the vegetation pattern into catchment hydrological simulation. This paper also discusses the model improvement to be done in future study. [ABSTRACT FROM AUTHOR]

Motivated by the question of whether and how a state-of-the-art regional chemical transport model (CTM) can facilitate characterization of CO2spatiotemporal variability and verify CO2fossil-fuel emissions, we for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate CO2. This paper presents methods, input data, and initial results for CO2simulation using CMAQ over the contiguous United States in October 2007. Modeling experiments have been performed to understand the roles of fossil-fuel emissions, biosphere–atmosphere exchange, and meteorology in regulating the spatial distribution of CO2near the surface over the contiguous United States. Three sets of net ecosystem exchange (NEE) fluxes were used as input to assess the impact of uncertainty of NEE on CO2concentrations simulated by CMAQ. Observational data from six tall tower sites across the country were used to evaluate model performance. In particular, at the Boulder Atmospheric Observatory (BAO), a tall tower site that receives urban emissions from Denver, CO, the CMAQ model using hourly varying, high-resolution CO2fossil-fuel emissions from the Vulcan inventory and CarbonTracker optimized NEE reproduced the observed diurnal profile of CO2reasonably well but with a low bias in the early morning. The spatial distribution of CO2was found to correlate with NOx, SO2, and CO, because of their similar fossil-fuel emission sources and common transport processes. These initial results from CMAQ demonstrate the potential of using a regional CTM to help interpret CO2observations and understand CO2variability in space and time. The ability to simulate a full suite of air pollutants in CMAQ will also facilitate investigations of their use as tracers for CO2source attribution. This work serves as a proof of concept and the foundation for more comprehensive examinations of CO2spatiotemporal variability and various uncertainties in the future.Implications: Atmospheric CO2 has long been modeled and studied on continental to global scales to understand the global carbon cycle. This work demonstrates the potential of modeling and studying CO2 variability at fine spatiotemporal scales with CMAQ, which has been applied extensively, to study traditionally regulated air pollutants. The abundant observational records of these air pollutants and successful experience in studying and reducing their emissions may be useful for verifying CO2 emissions. Although there remains much more to further investigate, this work opens up a discussion on whether and how to study CO2 as an air pollutant. [ABSTRACT FROM AUTHOR]

Highlights: [•] The elasticity of runoff was derived based on the Choudhury–Yang equation. [•] Quantify impacts of changes in climate and land use/cover on the catchment runoff. [•] Attributing the dominant cause for runoff decrease in 33 hilly catchments in the Haihe River. [ABSTRACT FROM AUTHOR]

Highlights: [•] Water, energy and CO2 fluxes over irrigated lands were observed for 4 years in the NCP. [•] Water, energy, and carbon balances were analyzed at seasonal and interannual scales. [•] Water deficit in wheat season and surplus in maize season were quantified. [•] Shifting wheat–maize double cropping to maize single can lead to a more sustainable future. [ABSTRACT FROM AUTHOR]