Molecular characteristics of dissolved organic phosphorus in watershed runoff: Coupled influences of land use and precipitation.

Land use and precipitation are two major factors affecting phosphorus (P) pollution of watershed runoff. However, molecular characterization of dissolved organic phosphorus (DOP) in runoff under the joint influences of land use and precipitation remains limited. This study used Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) to study the molecular characteristics of DOP in a typical P-polluted watershed with spatially variable land use and precipitation. The results showed that low precipitation and intense human activity, including phosphate mining and associated industries, resulted in the accumulation of aliphatic DOP compounds in the upper reaches, characterized by low aromaticity and low biological stability. Higher precipitation and widespread agriculture in the middle and lower reaches resulted in highly unsaturated DOP compounds with high biological stability constituting a higher proportion, compared to in the upper reaches. While, under similar precipitation, more aliphatic DOP compounds characterized by lower aromaticity and higher saturation were enriched in the lower reaches due to more influence from urban runoff relative to the middle reaches. Photochemical and/or microbial processes did result in changes in the characteristics of DOP compounds during runoff processes due to the prevalence of low molecular weight and low O/C bioavailable aliphatic DOP molecules in the upper reaches, which were increasingly transformed into refractory compounds from the upper to middle reaches. The results of this study can increase the understanding of the joint impacts of land use and precipitation on DOP compounds in watershed runoff.

Deforestation-induced runoff changes dominated by forest-climate feedbacks.

Large-scale deforestation alters water availability through its direct effect on runoff generation and indirect effect through forest-climate feedbacks. However, these direct and indirect effects and their spatial variations are difficult to separate and poorly understood. Here, we develop an attribution framework that combines the Budyko theory and deforestation experiments with climate models, showing that widespread runoff reductions caused by the indirect effect of forest-climate feedbacks can largely offset the direct effect of reduced forest cover on runoff increases. The indirect effect dominates the hydrological responses to deforestation over 63% of deforested areas worldwide. This indirect effect arises from deforestation-induced reductions in precipitation and potential evapotranspiration, which decrease and increase runoff, respectively, leading to complex patterns of runoff responses. Our findings underscore the importance of forest-climate feedbacks for improved understanding and prediction of climate and hydrological changes caused by deforestation, with profound implications for sustainable management of forests and water resources.

Sustainable flood control strategies under extreme rainfall: Allocation of flood drainage rights in the middle and lower reaches of the yellow river based on a new decision-making framework.

Climate change has exacerbated the frequency and magnitude of extreme rainfall, which has led to the perpetuation of flooding as a hazard to humans and society. China has begun to consider introducing Flood drainage rights (FDR), a sustainable flood control measure, into non-engineering measures as a complement to engineering measures for flood control. FDR represent the right of regions to discharge regional floodwaters caused by extreme rainfall into the river, and are the primary means of controlling the amount of floodwaters from regions when regional flood capacity is exceeded. However, existing studies on quantitative FDR allocation still have limitations, and some previous methods have resulted in allocation schemes that are not entirely reasonable and fair because they do not comprehensively consider the influencing factors of FDR or the allocation method is unreasonable. This paper explores the impact of flooding on rural and agricultural areas. We incorporate the factors of agricultural economy and security and construct a system of the allocation indicators of FDR composed of five principles: Natural Environmental Endowment, General Economic and Social Development, Agricultural Economy and Security, Macro policy regulation, and Respect for Historical Background. Second, considering the influence of expert judgment and data of different time nodes on the allocation of FDR, we introduce the concepts of expert weight and time weight into the allocation model of FDR, and construct a new set of framework for the allocation of FDR, i.e., "[(expert weight + subjective weight)+(time weight + objective weight)]+decision making model ". To reduce the loss of information during the transformation of subjective judgments, we also introduced triangular fuzzy numbers for the transformation between expert judgments and numbers. Finally, we take the five provinces in the middle and lower reaches of the Yellow River as an example. Using the data from 2010 to 2021, we obtain the final allocation scheme (proportion) of FDR as Henan (33.26%) > Shaanxi (23.08%) > Inner Mongolia (21.31%) > Shanxi (14.44%) > Shandong (7.91%). On this basis, this paper utilizes sensitivity analysis and comparative validation to demonstrate the rationality and effectiveness of the method, and identifies several indicators that have a greater impact on the results of the allocation of FDR. FDR can form part of a set of integrated flood management system together with flood control projects, which greatly alleviates the drainage conflicts arising from flooding caused by extreme precipitation. Under extreme rainfall conditions, FDR improves drainage efficiency and minimizes the overall damage caused by flooding in the watershed. This study can contribute to the sustainable development of the watershed and provide a reference for the promotion and utilization of sustainable flood control measures.

Assessment of fine and coarse tyre wear particles along a highway stormwater system and in receiving waters: Occurrence and transport.

Tyre wear has been identified as a major road-related pollutant source, with road runoff transporting tyre wear particles (TWP) to adjacent soil, watercourses, or further through stormwater systems. The aim of this study was to investigate the occurrence and transport of TWP along a stormwater system. Water and sediment have been sampled at selected points (road runoff, gully pots, wells, outlet to a ditch, and stream) through a stormwater system situated along a highway in Sweden during November and December 2022, and March 2023. As there is limited data on the size distribution of TWP in different environmental media, especially in the size fraction <20 µm, the samples were fractioned into a fine (1.6-20 µm) and a coarse (1.6-500 µm) size fraction. The samples were analysed using a combination of marker compounds (benzene, α-methylstyrene, ethylstyrene, and butadiene trimer) for styrene-butadiene rubbers with PYR-GC/MS from which TWP concentration was calculated. Suspended solids were analysed in the water samples, and organic content was analysed in the sediment samples. TWP was found at nearly all locations, with concentrations up to 17 mg/L in the water samples and up to 40 mg/g in the sediment samples. In the sediment samples, TWP in the size fraction 1.6-20 µm represented a significant proportion (20-60%). Correlations were found between TWP concentration and suspended solids in the water samples (r = 0.87) and organic content in the sediment samples (r = 0.72). The results presented in this study demonstrate that TWP can be transported to the surrounding environment through road runoff, with limited retention in the studied stormwater system.

Variation of nitrate sources affected by precipitation with different intensities in groundwater in the piedmont plain area of alluvial-pluvial fan.

A substantial reservoir of nitrogen (N) in soil poses a threat to the quality and safety of shallow groundwater, especially under extreme precipitation that hastens nitrogen leaching into groundwater. However, the specific impact of varying precipitation intensities on the concentration and sources of nitrate (NO3-) in groundwater across diverse hydrogeological zones and land uses remains unclear. This study aims to elucidate the fluctuations in NO3- concentration, sources, and controlling factors in shallow groundwater under different intensities of precipitation (extreme heavy precipitation and continuous heavy precipitation) in a typical alluvial-pluvial fan of the North China Plain by using stable isotopes (δ2H-H2O, δ18O-H2O, δ15N-NO3-, δ18O-NO3-), hydrochemical analyses and the SIAR model. Affected by extreme heavy precipitation the depleted isotopes of δ2H-H2O and δ18O-H2O in groundwater of the entire area suggested the rapid recharge of fast flow by precipitation. The enriched isotopes of δ2H-H2O and δ18O-H2O of north part in alluvial fan after continuous heavy precipitation showed the recharge of translatory flow of soil water. NO3-concentrations increased to 78.9 mg/L after extreme heavy precipitation and increased to 105.3 mg/L after continuous heavy precipitation when compared to those in normal year (56.8 mg/L) of north part of the alluvial fan. However, NO3- concentrations had slight variation after continuous heavy precipitation of south part of the fan due to the deep vadose zone. The contribution ratio of sources of NO3- in groundwater by using SIAR analysis revealed manure & sewage (MS) as the primary NO3- source (accounting for 59.7-78.1%) before extreme heavy precipitation, chemical fertilizer (CF) making a minor contribution (6.9-17.3%). Different precipitation events and land use types lead to changes in NO3- sources. Affected by extreme heavy precipitation, the contribution of MS decreased while CF increased, particularly in vegetables (26.2-28.1%) and farmland (29.2-34.7%). After continuous heavy precipitation, MS increased again, particularly in vegetables (50.0%) and farmlands (20.4-66.4%), with CF either increasing or remaining steady. This indicated that continuous heavy precipitation accelerated the leaching of nitrogen (organic manure application) stored in deep soil to groundwater and it has a larger influence on the increasing of NO3- concentrations of groundwater than extreme heavy precipitation which carried nitrogen (chemical fertilizer application) in shallow soil to groundwater by fast flow. These findings underscore the importance of considering soil chemical N stores and their implications for groundwater contamination mitigation under future extreme climate scenarios, particularly in agricultural management practices.

Parameter Estimation Using the Inverse Problem Method for Simulating Lateral Inflow and Runoff Depth in a small catchment of Amazon.

The inverse problem method can be applied to determine the properties of hydrological phenomena and estimate the parameters, which cannot be measured directly. This type of inverse focus can facilitate the implementation of the kinematic wave model (direct model-DM), to fill gaps for lateral inflow rate and runoff depth in watersheds. Thus, the goal of the study was the application of the inverse problem method (IP). The lateral inflow rate was generally obtained as a Fourier transform to represent any watersheds. The study was developed using a small catchment in the Amazon where intense rainfall events occur, producing runoff and sediments, which affect rural populations. Lateral inflow rate and runoff depth were derived using precipitation data and parameters estimated through the KINEROS2 (K2)/direct model (DM) model and the ensuing solution methods with MCMC (Markov chains Monte Carlo)/Fourier transform. The developed method was applied to four rainfall-runoff events, leading to a good fit between the observed and predicted data (Nash-Sutcliffe coefficients between 0.76 and 0.85 and RMSE values between 1.80 mm and 6.72 mm).

Temporal variation characteristics in the association between climate and vegetation in Northwest China.

Northwest China has undergone notable alterations in climate and vegetation growth in recent decades. Nevertheless, uncertainties persist concerning the response of different vegetation types to climate change and the underlying mechanisms. This study utilized the Normalized Difference Vegetation Index (NDVI) and three sets of meteorological data to investigate the interannual variations in the association between vegetation and climate (specifically precipitation and temperature) from 1982 to 2015. Several conclusions were drawn. (1) RNDVI-GP (relationship between Growing Season NDVI and precipitation) decreased significantly across all vegetation, while RNDVI-GT (relationship between Growing Season NDVI and temperature) showed an insignificant increase. (2) Trends of RNDVI-GP and RNDVI-GT exhibited great variations across various types of vegetation, with forests displaying notable downward trends in both indices. The grassland exhibited a declining trend in RNDVI-GP but an insignificant increase in RNDVI-GT, while no significant temporal changes in RNDVI-GP or RNDVI-GT were observed in the barren land. (3) The fluctuations in RNDVI-GP and RNDVI-GT closely aligned with variations in drought conditions. Specifically, in regions characterized by VPD (vapor pressure deficit) trends less than 0.02 hpa/yr, which are predominantly grasslands, a rise in SWV (soil water volume) tended to cause a reduction in RNDVI-GP but an increase in RNDVI-GT. However, a more negative trend in SWV was associated with a more negative trend in both RNDVI-GP and RNDVI-GT when the VPD trend exceeded 0.02 hPa/yr, primarily in forests. Our results underscore the variability in the relationship between climate change and vegetation across different vegetation types, as well as the role of drought in modulating these associations.

Understanding Environmental Fate: Soil Variability and Rainfall Influence on Triafamone and Ethoxysulfuron Leaching.

Considering the environmental impact of triafamone and ethoxysulfuron, it is crucial to investigate their leaching behaviour under different geographical conditions. The present study evaluates the effects of application rate, soil properties and rainfall conditions on leaching of these herbicides and their metabolites. Ethoxysulfuron leached up to 50-60 cm with 82.95 to 89.23% detected in leachates while triafamone leached only to 10-20 cm and was < 0.01 µg mL-1 in leachates. Highest leachability was observed in loamy sand followed by sandy loam and clay loam soil. M1 metabolite (N-(2-((4,6-dimethoxy-1,3,5-triazin-2-yl) (hydroxy) methyl) -6-fluorophenyl) -1,1-difluoro-N-methyl methane sulfonamide) was majorly present in 0 to 10 cm soil depth. With increase in rainfall, downward mobility of both parent and M1 increased. Amendment of loamy sand soil with farmyard manure reduced the leachability indicating it could mitigate groundwater pollution. However, the effect of different exogenous OM amendments on leaching behaviour of herbicides needs to be evaluated.

Spatial-temporal assessment of future population exposure to compound extreme precipitation-high temperature events across China.

Global warming has increased the probability of extreme climate events, with compound extreme events having more severe impacts on socioeconomics and the environment than individual extremes. Utilizing the Coupled Model Intercomparison Project Phase 6 (CMIP6), we predicted the spatiotemporal variations of compound extreme precipitation-high temperature events in China under three Shared Socioeconomic Pathways (SSPs) across two future periods, and analyzed the changes in exposed populations and identified influencing factors. From the result, we can see that, the CMIP6 effectively reproduces precipitation patterns but exhibits biases. The frequency of compound event rises across SSPs, especially under high radiative forcing, with a stronger long-term upward trend. Furthermore, the economically developed areas, notably China's southeastern coast and North China Plain, will be hotspots for frequent and intense compound extreme events, while other regions will see reduced exposure. Finally, in the long-term future (2070-2100), there is a noteworthy shift in population exposure to compound events, emphasizing the increasing influence of population factors over climate factors. This highlights the growing importance of interactions between population and climate in shaping exposure patterns.

Pollutant removal efficiency of bare and planted rain gardens with diverse planting mixtures.

This study examines the influence of planting mixture variations on the quality of the percolated water of the rain garden with and without plants. Six planting mixtures in experimental rain gardens have been used. It has been noted that pollutant removal efficiency of RG can exhibit variations based on specific parameters. Notably, RG6, utilizing a planting mix of 75% topsoil and 25% compost, demonstrated the highest performance. These results draw attention to the critical role of the specific planting mixtures in influencing the performance of vital parameters related to pollutant removal. The observation shows that RG5 exhibits exceptional removal efficiency in pH, Total Suspended Solids (TSS), Biological Oxygen Demand (BOD), and Chemical Oxygen Demand (COD), and RG6 performs best in electrical conductivity (EC), Total Dissolved Solids (TDS), Total Nitrogen (TN), and Total Phosphorus (TP) removal. In particular, when analyzing pollutant removal on a surface with Madagascar periwinkle plants, RG6 emerges as the most effective, achieving an impressive efficiency of approximately 49%. For the bare surface, pollutant removal efficiency is 40%. The study outcome will be useful in deciding the composition of the planting mixture, which will keep the rain garden to improve quality and quantitatively hydrological performance, lowering urban flooding magnitude.

Soil properties modulate actual evapotranspiration and precipitation impacts on crop yields in the USA.

Crop yields are affected by hydroclimatic and edaphic conditions, but their interacting roles are often neglected when assessing crop yields at the regional scale. Moreover, often used hydroclimatic conditions such as precipitation and temperature are not as physiologically linked to primary production and yields as actual evapotranspiration. Using statistical models, we quantified the combined effects of edaphic and hydroclimatic conditions on county yields of irrigated rice and rainfed corn, soybean, and spring and winter wheat in the USA (2000-2019). Precipitation and temperature, or actual evapotranspiration, aggregated during the growing season or before and after flowering/silk emergence, in interaction with soil sand content or bulk density, explained up to 87 % of the yield variability. However, actual evapotranspiration explained yields better than precipitation and temperature and their interactions for most combinations of crops and growth periods. At high actual evapotranspiration, yield plateaued or, for spring wheat, decreased. Yields were generally most sensitive to changes in hydroclimatic conditions during part of rather than the entire growing season, and most often after flowering. Soil texture and bulk density modulated the impacts of hydroclimatic conditions: corn and soybean yields were higher in finer soils compared with sandy soils under high evapotranspiration, but lower at low evapotranspiration. Additionally, the yield-maximizing precipitation decreased with sand content and increased with bulk density for most crops. Increasingly available actual evapotranspiration estimates, combined with soil properties, offer an alternative, and more physiologically-based, yield predictor over large climatic gradients to the more widely used precipitation and temperature.

Characterising polycyclic aromatic hydrocarbons in road dusts and stormwater in urban environments.

The presence of polycyclic aromatic hydrocarbons (PAHs) pollution on urban road surfaces is one of the major environmental concerns. However, knowledge on the distribution variability of PAHs in road dusts (RDS) and stormwater is limited, which would restrict the further risk evaluation and mitigation implementation of PAHs in road stormwater runoff. This study collected RDS samples and stormwater samples on fourteen urban roads in Shenzhen, China. This study investigated the variation of sixteen PAHs species in RDS and stormwater, and further evaluated the intrinsic and extrinsic factors which influence PAHs accumulation on urban road surfaces. The research outcomes showed significant differences on spatial distribution of PAHs in RDS and in stormwater. The land use types, industrial, commercial and port areas and vehicular volume have a positive relationship with PAHs abundance while dust particle size showed a negative correlation with PAHs abundance. For two phases in stormwater, fluctuation of PAHs with the rainfall duration in total dissolved solid (TDS) was more intensive than in dissolved liquid phase (DLP). This indicated when PAHs attached to RDS enter stormwater, most of PAHs still tend to be on solid particles than in liquid. The study outcomes are expected to contribute to efficient designs of PAHs polluted stormwater mitigation.

Correlations between local geoclimatic variables and hatchling body size in the sea turtles Caretta caretta and Chelonia mydas.

It has been widely demonstrated that air and sand temperatures influence the anatomy of sea turtle hatchlings. We examined the impact of precipitation during the nesting season on the hatchling body size of loggerhead and green turtles from 37 beaches worldwide. Longitudinal data collected between 2012 and 2018 from Florida (US) and from a sample on Bõa Vista Island (Cabo Verde) carried out in 2019 showed that loggerhead body size at hatching was negatively correlated with precipitation, while precipitation was not correlated with hatchling body size in green turtles. A meta-analysis revealed that precipitation is positively correlated with hatchling mass in loggerhead turtles, while it is positively correlated with straight carapace length and width in green turtle hatchlings. The strongest influence of precipitation was found in the middle of the incubation period of loggerhead turtles in Cabo Verde, and we posit that this is due to an increase in the uptake of water for embryonic growth. These findings highlight the great importance of understanding the correlated effects of regional environmental variables, such as precipitation, on the development of sea turtle hatchlings and will have an impact on the evaluation of ongoing conservation and climate change discussions.

Interspecific competition shapes bird species' distributions along tropical precipitation gradients.

The hypothesis that species' ranges are limited by interspecific competition has motivated decades of debate, but a general answer remains elusive. Here we test this hypothesis for lowland tropical birds by examining species' precipitation niche breadths. We focus on precipitation because it-not temperature-is the dominant climate variable that shapes the biota of the lowland tropics. We used 3.6 million fine-scale citizen science records from eBird to measure species' precipitation niche breadths in 19 different regions across the globe. Consistent with the predictions of the interspecific competition hypothesis, multiple lines of evidence show that species have narrower precipitation niches in regions with more species. This means species inhabit more specialized precipitation niches in species-rich regions. We predict this niche specialization should make tropical species in high diversity regions disproportionately vulnerable to changes in precipitation regimes; preliminary empirical evidence is consistent with this prediction.

Biofilm growth characteristic and footprint identification in gravity-driven ceramic membrane bioreactor with electro-coagulation under extreme conditions for roofing rainwater purification.

The identification of biofilm growth footprints influencing on the biofilm detachment and breakup can advance research into how biofilms form. Thus, a gravity-driven ceramic membrane bioreactor (GDCMBR) was used to investigate the growth, detachment and breakup of biofilm using rainwater pretreated by electrocoagulation under 70-days continuous operation. The in-situ ultrasonic time-domain reflectometry (UTDR) technique was applied to non-invasively determine the biofilm thickness. Initially, the biofilm was slowly thickening, but it would collapse and became thinner after accumulating to a certain level, and then it thickened again in a later period, following a cyclic pattern of 'thickening - collapsing - thickening'. This is because the biofilm growth is related with the accumulation of flocs, however, excessive floc formation results in the biofilm being overweight till reaching the thickness limit and thus collapsing. Subsequently, the biofilm gradually thickens again due to the floc production and continuous deposition. Although the biofilm was dynamically changing, the water quality of treatment of the biofilm always remained stable. Ammonia nitrogen and total phosphorus have been almost completely removed, while CODMn removal efficiency was around 25%. And total bacteria amount in the membrane concentrate was obviously higher than that in the influent with the greater microbial activity, demonstrating the remarkable enrichment effect on bacteria. The understanding of biofilm growth characteristic and footprint identification enables us to develop rational approaches to control biofilm structure for efficient GDCMBR performance and operation lifespan.

Interpretable machine learning guided by physical mechanisms reveals drivers of runoff under dynamic land use changes.

Human activities continuously impact water balances and cycling in watersheds, making it essential to accurately identify the responses of runoff to dynamic changes in land use types. Although machine learning models demonstrate promise in capturing the intricate interplay between hydrological factors, their "black box" nature makes it challenging to identify the dynamic drivers of runoff. To overcome this challenge, we employed an interpretable machine learning method to inversely deduce the dynamic determinants within hydrological processes. In this study, we analyzed land use changes in the Ningxia section of the middle Yellow River across four periods, laying the foundation for revealing how these changes affect runoff. The sub-watershed attributes and meteorological characteristics generated by the Soil and Water Assessment Tool (SWAT) model were used as input variables of the Extreme Gradient Boosting (XGBoost) model to simulate substantial sub-watershed rainfall runoff in the region. The XGBoost was interpreted using the SHapley Additive exPlanations (SHAP) to identify the dynamic responses of runoff to the land use changes over different periods. The results revealed increasingly frequent interchanges between the land use types in the study area. The XGBoost effectively captured the characteristics of the hydrological processes in the SWAT-derived sub-watersheds. The SHAP analysis results demonstrated that the promoting effect of agricultural land (AGRL) on runoff gradually weakens, while forests (FRST) continuously strengthen their restraining effect on runoff. Relevant land use policies provide empirical support for these findings. Furthermore, the interaction between meteorological variables and land use impacts the runoff generation mechanism and exhibits a threshold effect, with the thresholds for relative humidity (RH), maximum temperature (MaxT), and minimum temperature (MinT) determined to be 0.8, 25 °C, and 15 °C, respectively. This reverse deduction method can reveal hydrological patterns and the mechanisms of interaction between variables, helping to effectively addressing constantly changing human activities and meteorological conditions.

Compare individual and combined bioretention systems on the reduction of thermal pollution from stormwater runoff.

Urban surface temperatures are high in summertime, and thermal pollution caused by heat transfer from pavement to stormwater runoff is harmful to aquatic ecosystems. However, there is a lack of studies investigating the temperature change pattern during rainstorms and evaluating the effects of bioretention on dynamic characteristics of thermal pollution. Therefore, this study selected a 1.05 ha parking lot retrofitted with five individual bioretention cells in Beijing as the object to compare the temperature and volume of stormwater runoff before and after bioretention treatment. In the LID parking lot, the average EMT and EMXT (event maximum temperature) of runoff decreased by 2.28 °C and 4.18 °C, respectively, and the median percent thermal load reduction was 90.6%. Data analysis from 15 summer rainfall events showed that the sequence of factors affecting runoff EMT (event mean temperature) was average air temperature, max air temperature, max solar radiation, and rainfall peak 5-min intensity. Bioretention profoundly changed the thermal dynamic characteristics of stormwater runoff. Surface runoff temperatures generally showed a decreasing trend over time. The temperature change pattern of LID parking lot outflow was synchronized with that of the inflow and varied with different grades of precipitation. The probability of the peak temperature ahead of peak flow decreased from 80% to 53%, suggesting that 27% of the thermal first-flush effect of thermal pollution from the urban surface was alleviated by site-scale bioretention implementation. The site-scale bioretention combination had a lower effluent temperature and a higher thermal load reduction rate than single-scale solutions. These results fill the gap in research on the thermal pollution reduction process of bioretention. Furthermore, they can guide the optimization of bioretention design methods and strategies to protect urban water bodies from the stormwater runoff thermal pollution.

Interannual fluctuations in precipitation shape the trajectory of ecosystem respiration along a grazing exclusion chronosequence in a typical steppe in Inner Mongolia.

Grazing exclusion (GE), as an effective strategy for revitalizing degraded grasslands, possesses the potential to increase ecosystem respiration (Re) and significantly influence the capacity of grassland soils to sequester carbon. However, our current grasp of Re dynamics in response to varying durations of GE, particularly in the context of precipitation fluctuations, remains incomplete. To fill this knowledge gap, we conducted a monitoring of Re over a 40-year GE chronosequence within Inner Mongolia temperate typical steppe across two distinct hydrologically years. Overall, Re exhibited a gradual saturation curve and an increasing trend with the duration of GE in the wet year of 2021 and the normal precipitation year of 2022, respectively. The variance primarily stemmed from relatively higher microbial biomass carbon observed in the short-term GE during 2022 in contrast to 2021. Moreover, the impacts of GE on the sensitivities of Re to moisture and temperature were intricately tied to precipitation patterns. increasing significantly with prolonged GE duration in 2022 but not in 2021. Our study highlights the intricate interplay between GE duration, precipitation variability, and Re dynamics. This deeper understanding enhances our ability to predict and manage carbon cycling within typical steppe in Inner Mongolia, offering invaluable insights for effective restoration strategies and climate change mitigation.

Water quality and wetland vegetation responses to water level variations in a university stormwater reuse reservoir: Nature-based approaches to campus water sustainability.

In response to climate-driven water shortages, Duke University in 2014 constructed a water reuse reservoir and wetland complex (Pond) to capture urban stormwater and recycle water to provide campus cooling and reduce downstream loading of nutrients and sediment into Jordan Lake, a regional water supply. We postulated that even with significant water level changes due to withdrawals, the Pond would function to reduce downstream nutrients and sediment once wetland plants became established in the littoral zone. Throughout the project (2015-2021), baseflow nutrient concentrations downstream decreased, with Unfiltered Total Nitrogen (UTN) falling by 44 % and Unfiltered Total Phosphorus (UTP) by 50 %. Storm mean concentrations decreased by 31 % for UTN, 54 % for UTP, and 72 % for Total Suspended Solids (TSS). The annual reductions in mass fluxes (UTN, UTP, and TSS) were between 58 and 85 % across a range of storm intensities. Regardless of water level, temperature, pH, and oxygen concentrations downstream were not significantly changed. Between 2015 and 2020, a littoral survey of planted and naturally introduced species showed that wetter years resulted in a greater number of species across a gradient of three inundation zones (i.e., moist, wet, and aquatic). Conversely, dryer years resulted in fewer species across overlapping zones. The dominant plants that successfully colonized the Pond are all obligate wetland species despite the Pond's highly variable water depths and periods of inundation. The final plant populations were dominated by invasive native species supporting the self-design theory of plant succession as nearly half of the original planted species died. The reuse Pond design (pond-wetland complex) showed the capability of using stormwater runoff for campus cooling while improving water quality services and providing habitat for wetland plants. Thus, campuses with watershed runoff capture capability should consider a nature-based recycling approach as part of their water sustainability program.

Investigation of canopy interception characteristics in slope protection grasses: A laboratory experiment.

Canopy interception significantly affects hydrological processes such as infiltration, runoff and evapotranspiration. Research on grass canopy interception remains limited, and the experimental methods employed differ substantially. To thoroughly investigate the canopy interception characteristics of grass and clarify the methodological differences, five commonly utilized slope protection grass species in temperate regions were cultivated in a laboratory setting, and their canopy interception characteristics were experimentally investigated using the water-balance method (WBM), the water-wiping method (WWM) and the water-immersion method (WIM), respectively. The results showed that the WBM is more accurate for measuring canopy interception in grass, whereas both the WWM and the WIM underestimate grass canopy interception capacity. The canopy interception capacity measured by the WBM was 1.61-2.09 times higher than that of the WWM and 1.93-3.47 times higher than that of the WIM. Grey correlation analysis of the eight evaluated factors indicated that leaf area is the most influential factor affecting canopy interception in grass, followed by rainfall amount, dry mass, rainfall intensity, canopy projection area, leaf contact angle, fresh weight, and average height. There is a negative power function relationship between the interception ratio and the rainfall amount. With increasing rainfall intensity, the canopy interception capacity initially increases and then decreases, peaking at rainfall intensities of 15 to 20 mm/h. Leaf contact angle is a key quantifiable parameter that explains the differences in canopy interception among different grass species, and the canopy interception per unit leaf area decreases as the leaf contact angle increases. This study demonstrates that the WBM provides the most accurate measurements of grass canopy interception compared to the WWM and WIM, and highlights the leaf contact angle as a key factor in explaining interspecies differences. These findings could enhance the understanding of grass canopy interception and guide the selection of experimental methods.