Basin Scale Research Articles

Global‐Scale Evaluation of Coastal Ocean Alkalinity Enhancement in a Fully Coupled Earth System Model

AbstractThe Paris Agreement plans for “net‐zero” carbon dioxide (CO2) emissions during the second half of the 21st century. However, reducing emissions from some sectors is challenging, and “net‐zero” permits carbon dioxide removal (CDR) activities. One CDR scheme is ocean alkalinity enhancement (OAE), which proposes dissolving basic minerals into seawater to increase its buffering capacity for CO2. While modeling studies have often investigated OAE at basin or global scale, some proposals focus on readily accessible coastal shelves, with TA added through the dissolution of seafloor olivine sands. Critically, by settling and dissolving sands on shallow seafloors, this retains the added TA in near‐surface waters in direct contact with atmospheric CO2. To investigate this, we add dissolved TA at a rate of ∼29 Teq y−1 to the global shelves (<100m) of an Earth system model (UKESM1) running a high emissions scenario. As UKESM1 is fully coupled, wider effects of OAE‐mediated increase in ocean CO2 uptake –e.g. atmospheric xCO2, air temperature and marine pH– are fully quantified. Applying OAE from 2020 to 2100 decreases atmospheric xCO2 ∼10 ppm, and increases air‐to‐sea CO2 uptake ∼8%. In‐line with other studies, CO2 uptake per unit of TA added occurs at a rate of ∼0.8 mol C (mol TA)−1. Significantly for monitoring, advection of added TA results in ∼50% of CO2 uptake occurring remotely from OAE operations, and the model also exhibits noticeable land carbon reservoir changes. While practical uncertainties and model representation caveats remain, this analysis estimates the effectiveness of this specific OAE scheme to assist with net‐zero planning.

Hydrogeochemical evolution and water–rock interaction processes in the multilayer volcanic aquifer of Yogyakarta-Sleman Groundwater Basin, Indonesia

Volcanic aquifers have become valuable resources for providing water to approximately 2.5 million people in the Yogyakarta-Sleman Groundwater Basin, Indonesia. Nevertheless, hydrogeochemical characteristics at the basin scale remain poorly understood due to the complexity of multilayered aquifer systems. This study collected sixty-six groundwater samples during the rainy and dry seasons for physicochemical analysis and geochemical modeling to reveal the hydrogeochemical characteristics and evolution in the Yogyakarta-Sleman Groundwater Basin. The results showed that groundwater in the unconfined and confined aquifers exhibited different hydrogeochemical signatures. The Ca–Mg–HCO3 facies dominated groundwater from the unconfined aquifer. The groundwater facies evolved into a mixed Ca–Mg–Cl type along the flow direction towards the discharge zone. Meanwhile, groundwater from the confined aquifer showed mixed Ca–Na–HCO3, Na–HCO3, and Na–Cl–SO4 facies. The presence of Mg in the confined aquifer was replaced by Na, which was absorbed in the aquifer medium, thus showing the ion exchange process. The main geochemical processes can be inferred from the Gibbs diagram, where most groundwater samples show an intensive water–rock interaction process mainly influenced by the weathering of silicate minerals. Additionally, only groundwater samples from the confined aquifer were saturated with certain minerals (aragonite, calcite, and dolomite), confirming that the groundwater followed the regional flow system until it had sufficient time to reach equilibrium and saturation conditions. This study successfully explained the hydrogeochemical characteristics and evolution of a multilayer volcanic aquifer system that can serve as a basis for groundwater basin conservation.

Mechanisms Underpinning the Net Removal Rates of Dissolved Organic Carbon in the Global Ocean

AbstractWith almost 700 Pg of carbon, marine dissolved organic carbon (DOC) stores more carbon than all living biomass on Earth combined. However, the controls behind the persistence and the spatial patterns of DOC concentrations on the basin scale remain largely unknown, precluding quantitative assessments of the fate of this large carbon pool in a changing climate. Net removal rates of DOC along the overturning circulation suggest lifetimes of millennia. These net removal rates are in stark contrast to the turnover times of days to weeks of heterotrophic microorganisms, which are the main consumers of organic carbon in the ocean. Here, we present a dynamic “MICrobial DOC” model (MICDOC) with an explicit representation of picoheterotrophs to test whether ecological mechanisms may lead to observed decadal to millennial net removal rates. MICDOC is in line with >40,000 DOC observations. Contrary to other global models, the reactivity of DOC fractions is not prescribed, but emerges from a dynamic feedback between microbes and DOC governed by carbon and macronutrient availability. A colimitation of macronutrients and organic carbon on microbial DOC uptake explains >70% of the global variation of DOC concentrations, and governs characteristic features of its distribution. Here, decadal to millennial net removal rates emerge from microbial processes acting on time scales of days to weeks, suggesting that the temporal variability of the marine DOC inventory may be larger than previously thought. With MICDOC, we provide a foundation for assessing global effects on DOC related to changes in heterotrophic microbial communities in a future ocean.

Variable drivers trigger future change in water yield capacity of terrestrial ecosystems in Africa: An intensification of reduction and unevenness

Predicting the water-related services of terrestrial ecosystems in a changing climate is of great significance for managing rich ecosystems in water-scarce areas. Water yield capacity (WYC), which characterizes water resource availability, was thrown into sharp focus of this study. The spatiotemporal trends of WYC and their dynamics by potential climate shifts were evaluated based on calculative WYC and climate zones for historical period (2001–2018) and future scenarios (both 2050 and 2100 under SSP1-2.6 or SSP5-8.5 scenarios). The multiple factors affecting WYC in the recent past were identified as the basis for explaining the future tendency in WYC. All analyses were conducted from the perspective of holistic continental scale and specific basin scale so as to explore the contrast between various scales. The results showed that the total WYC both in whole Africa and the four major basins (the Congo, the Nile, the Niger and the Zambezi) are projected to decrease in 2050 and 2100 compared with that in 2018, under both SSP1-2.6 or SSP5-8.5 scenarios describing future pathways with low or high greenhouse gas emissions, respectively. The areas producing WYC will be more concentrated, suggesting that the proportion of areas contributing to the top 50% of this function across Africa will drop from current 10.5% to 4.94% in 2100 under SSP5-8.5 scenario. As climate zones are likely to shift in the future, the WYC will reduce most in the areas experiencing the conversion between tropical monsoon and tropical rainforest climates. In addition, WYC was driven by precipitation, temperature, net primary productivity (NPP) and landscape pattern (connectivity and diversity), which had spatial scale effect. The results add evidence for unstable availability of water resources provided by terrestrial ecosystems in a multi-scale manner.

Estimating the CSLE Biological Conservation Measures’ B-Factor Using Google Earth’s Engine

The biological conservation measures factor (B) in the Chinese Soil loss Equation (CSLE) model is one of the main components in evaluating soil erosion, and the accurate calculation of the B-factor at the regional scale is fundamental in predicting regional soil erosion and dynamic changes. In this study, we developed an optimal computational procedure for estimating and mapping the B-factor in the Google Earth Engine (GEE) cloud computing environment using multiple data sources through data suitability assessment and image fusion. Taking the Yanhe River Basin in the Loess Plateau of China as an example, we evaluated the availability of daily precipitation data (CHIRPS, ERA5, and PERSIANN-CDR data) against the data at national meteorological stations. We estimated the B-factor from Sentinel-2 data and proposed a new method, namely the trend migration method, to patch the missing values in Sentinel-2 data using three other remote sensing data (MOD09GA, Landsat 7, and Landsat 8). We then calculated and mapped the B-factor in the Yanhe River Basin based on rainfall erosivity, vegetation coverage, and land use types. The results show that the ERA5 precipitation dataset outperforms the CHIRPS and PERSIANN-CDR data in estimating rainfall and rainfall erosivity, and it can be utilized as an alternative data source for meteorological stations in soil erosion modeling. Compared to the harmonic analysis of time series (HANTS), the trend migration method proposed in this study is more suitable for patching the missing parts of Sentinel-2 data. The restored high-resolution Sentinel-2 data fit nicely with the 10 m resolution land use data, enhancing the B-factor calculation accuracy at local and region scales. The B-factor computation procedure developed in this study is applicable to various river basin and regional scales for soil erosion monitoring.

Vegetation Greening and Its Response to a Warmer and Wetter Climate in the Yellow River Basin from 2000 to 2020

Vegetation greening is time-dependent and region-specific. The uncertainty of vegetation greening under global warming has been highlighted. Thus, it is crucial to investigate vegetation greening and its response to climate change at the regional scale. The Yellow River Basin (YRB) is a vital ecological barrier in China with high ecological vulnerability and climatic sensitivity. The relationship between vegetation greening and climate change in the YRB and the relative contribution of climate change remain to be explored. Using the Enhanced Vegetation Index (EVI) and meteorological observation data, the spatiotemporal patterns of vegetation greening across the YRB in response to climate change at the basin and vegetation sub-regional scales from 2000 to 2020 were analyzed. The impact of human activities on regional greening was further quantified. Results showed that approximately 92% of the basin had experienced greening, at average annual and growing season rates of 0.0024 and 0.0034 year–1, respectively. Greening was particularly prominent in the central and eastern YRB. Browning was more prevalent in urban areas with a high intensity of human activities, occupying less than 6.3% of the total basin, but this proportion increased significantly at seasonal scales, especially in spring. Regional greening was positively correlated with the overall warmer and wetter climate, and the partial correlation coefficients between EVI and precipitation were higher than those between EVI and temperature. However, this response varied among different seasonal scales and vegetation sub-regions. The combined effects of climate change and human activities were conducive to vegetation greening in 84.5% of the YRB during the growing season, while human activities had a stronger impact than climate change. The relative contributions of human activities to greening and browning were 65.15% and 70.30%, respectively, mainly due to the promotion of ecological rehabilitation programs and the inhibition of urbanization and construction projects.

Improvement of evapotranspiration simulation study in the Hailar River basin under the influence of vegetation dynamics

In arid and semi-arid areas with <400 mm of precipitation, evapotranspiration (ET) accounts for about 80% of precipitation and is the main water consumer in the watershed. However, vegetation greening in recent years will increase ET and exacerbate the aridity of the area by affecting soil moisture in the root system. Vegetation changes are regional and spatially heterogeneous, therefore, in order to characterize ET changes under vegetation dynamics, it is necessary to expand the spatial scale of ET simulation. However, widely used evapotranspiration simulation models, such as the Shuttleworth-Wallace model (SW model), are deficient in reflecting the direct and indirect effects of vertical (i.e., soil depths) and horizontal (i.e., vegetation dynamics) directions. Based on field sampling and constructed structural equation model (SEM), we found that vegetation dynamics affect evapotranspiration not only directly, but also indirectly by affecting soil moisture at different depths. On this basis, we defined the weighting coefficients of 0.85 and 0.15 for grassland vegetation zones, 0.3, 0.15, 0.20, 0.25, 0.10 for forest-grass interspersed zones, and 0.20, 0.55, 0.25 for forested zones, respectively, based on the SEM results. Different soil moisture weighting coefficients were defined within different vegetation type zones and the improved SW model is called S-W-α. Comparing the simulation results with the measured data, S-W-α improved the ET simulation accuracy in this region by 33.92% and the improved ET spatial trend can respond to the dynamic changes of vegetation. Replacing the ET module in the Block-wise use of TOPMODEL and Muskingum-Cunge method mode (BTOP model) with the modified S-W-α, the results show that the simulation accuracy of the improved model is increased by 25%, and the Nash is higher than 75% for both the rate period and the validation period, which realizes the extension of the model from the point scale to the basin scale. The modified model may provide technical support for simulation of evapotranspiration and management of ecosystem health in ecologically fragile areas.

A Deep U-Net-ConvLSTM Framework with Hydrodynamic Model for Basin-Scale Hydrodynamic Prediction

Traditional hydrodynamic models face the significant challenge of balancing the demands of long prediction spans and precise boundary conditions, large computational areas, and low computational costs when attempting to rapidly and accurately predict the nonlinear spatial and temporal characteristics of fluids at the basin scale. To tackle this obstacle, this study constructed a novel deep learning framework with a hydrodynamic model for the rapid spatiotemporal prediction of hydrodynamics at the basin scale, named U-Net-ConvLSTM. A validated high-fidelity hydrodynamic mechanistic model was utilized to build a 20-year hydrodynamic indicator dataset of the middle and lower reaches of the Han River for the training and validation of U-Net-ConvLSTM. The findings indicate that the R2 value of the model surpassed 0.99 when comparing the single-step prediction results with the target values. Additionally, the required computing time fell by 62.08% compared with the hydrodynamic model. The ablation tests demonstrate that the U-Net-ConvLSTM framework outperforms other frameworks in terms of accuracy for basin-scale hydrodynamic prediction. In the multi-step-ahead prediction scenarios, the prediction interval increased from 1 day to 5 days, while consistently maintaining an R2 value above 0.7, which demonstrates the effectiveness of the model in the missing boundary conditions scenario. In summary, the U-Net-ConvLSTM framework is capable of making precise spatiotemporal predictions in hydrodynamics, which may be considered a high-performance computational solution for predicting hydrodynamics at the basin scale.

A tolerant hydrologic technique for real-time selection of optimum QPFs from NWPMs for flood warning applications.

The most important information required to successfully issue a flood warning is the quantitative precipitation forecasts (QPFs). This is important to run subsequent rainfall-runoff simulations. A rainfall-runoff simulation derives its accuracy mainly from the accuracy of the input QPFs. The dynamically based global numerical weather prediction models (NWPMs) are strong candidate sources of QPFs. A main problem is the real-time selection of which NWPM should be used to provide the QPFs for flood warning simulations. This paper develops an automated technique to solve this problem. The technique performs real-time comparisons with measured rainfall fields using a novel 'tolerant' hydrologic approach. The 'tolerant' approach performs the comparison on the basin scale and allows for timing shifts in the forecasts. This is because QPFs can be good but only a few hours early or late. Two events are used for illustration, and the proposed real-time application in flood warning is presented. The developed technique, employing the tolerant approach, could eliminate the effects of the timing shifts and, accordingly, succeeded to select the QPFs to be used. A Python package was developed for automation. The developed technique is expected to also be useful for offline assessments of historical performances of NWPMs.

CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale

Abstract. This work presents the new model called CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment), a tool for geo-hydrological hazard evaluation. CRHyME is a physically based and spatially distributed model written in the Python language that represents an extension of the classic hydrological models working at the basin scale. CRHyME's main focus consists of simulating rainfall-induced geo-hydrological instabilities such as shallow landslides, debris flows, catchment erosion and sediment transport into a river. These phenomena are conventionally decoupled from a hydrological routine, while in CRHyME they are simultaneously and quantitatively evaluated within the same code through a multi-hazard approach. CRHyME is applied within some case studies across northern Italy. Among these, the Caldone catchment, a well-monitored basin of 27 km2 located near the city of Lecco (Lombardy), was considered for the calibration of solid-transport routine testing, as well as the spatial-scale dependence related to digital terrain resolution. CRHyME was applied across larger basins of the Valtellina (Alps) and Emilia (Apennines) areas (∼2600 km2) which have experienced severe geo-hydrological episodes triggered by heavy precipitation in the recent past. CRHyME's validation has been assessed through NSE (Nash–Sutcliffe efficiency) and RMSE (root mean square error) hydrological-error metrics, while for landslides the ROC (receiver operating characteristic) methodology was applied. CRHyME has been able to reconstruct the river discharge at the reference hydrometric stations located at the outlets of the basins to estimate the sediment yield at some hydropower reservoirs chosen as a reference and to individuate the location and the triggering conditions of shallow landslides and debris flows. The good performance of CRHyME was reached, assuring the stability of the code and a rather fast computation and maintaining the numerical conservativity of water and sediment balances. CRHyME has shown itself to be a suitable tool for the quantification of the geo-hydrological process and thus useful for civil-protection multi-hazard assessment.

Downscaling Climatic Variables at a River Basin Scale: Statistical Validation and Ensemble Projection under Climate Change Scenarios

Climatic statistical downscaling in arid and topographically complex river basins remains relatively lacking. To address this gap, climatic variables derived from a global climate model (GCM) ensemble were downscaled from a grid resolution of 2.5° × 2.5° down to the station level. For this purpose, a combination of multiple linear and logistic regressions was developed, calibrated and validated with regard to their predictions of monthly precipitation and daily temperature in the Jordan River Basin. Seasonal standardized predictors were selected using a backward stepwise regression. The validated models were used to examine future scenarios based on GCM simulations under two Representative Concentration Pathways (RCP4.5 and RCP8.5) for the period 2006–2050. The results showed a cumulative near-surface air temperature increase of 1.54 °C and 2.11 °C and a cumulative precipitation decrease of 100 mm and 135 mm under the RCP4.5 and RCP8.5, respectively, by 2050. This pattern will inevitably add stress to water resources, increasing management challenges in the semi-arid to arid regions of the basin. Moreover, the current application highlights the potential of adopting regression-based models to downscale GCM predictions and inform future water resources management in poorly monitored arid regions at the river basin scale.

Elevational patterns of fish functional and phylogenetic community structure in a monsoon climate river basin

AbstractAimUnderstanding the patterns and drivers of biodiversity across space and time is commonly based on species diversity, which may ignore species' functional role and evolutionary history and result in an incomplete understanding of community assembly. It is suggested that integrating species, functional, and phylogenetic diversity could provide a more holistic assessment of community assembly in natural ecosystems. This study aimed to explore the elevational patterns and environmental drivers of multiple facets of fish diversity and community structure in a subtropical river during the wet and dry seasons.LocationThe Chishui River basin, China.MethodsWe investigated the responses of fish species richness, functional richness, and phylogenetic diversity to elevation in different seasons. Moreover, we compared functional dispersion and mean pairwise distance with those obtained from null models to infer assembly mechanisms shaping community structure. Additionally, we examined the environmental drivers (e.g. water chemistry, temperature, and river size) of fish diversity and community structure.ResultsFish species richness, functional richness, and phylogenetic diversity showed a negative relationship with elevation in the Chishui River basin. Fish communities tended to be on average functionally random but phylogenetically clustered. Furthermore, phylogenetic structure exhibited a decreasing pattern along the elevational gradient. Despite no significant seasonal changes for fish diversity (except for phylogenetic diversity), fish communities became more phylogenetically overdispersed and clustered at low and high elevations in the dry season. Additionally, the responses of fish diversity and community structure to environmental variables were not synchronous.ConclusionsAt the basin scale, environmental filtering was prevalent in shaping fish phylogenetic structure, whereas stochasticity was likely more important for functional structure. Moreover, the ecological mechanisms shaping individual fish communities switched from limiting similarity to environmental filtering as elevation increased, and the underlying forces at two ends of the elevational gradient became more prominent in the dry season.

Spatiotemporal characteristics of meteorological drought events in 34 major global river basins during 1901–2021

Meteorological drought is a crucial driver of various types of droughts; thus, identifying the spatiotemporal characteristics of meteorological drought at the basin scale has implications for ecological and water resource security. However, differences in drought characteristics between river basins have not been clearly elucidated. In this study, we identify and compare meteorological drought events in 34 major river basins worldwide using a three-dimensional drought-clustering algorithm based on the standardised precipitation evapotranspiration index on a 12-month scale from 1901 to 2021. Despite synchronous increases in precipitation and potential evapotranspiration (PET), with precipitation increasing by more than three times the PET, 47 % (16/34) of the basins showed a tendency towards drought in over half their basin areas. Drought events occurred frequently, with more than half identified as short-term droughts (lasting less than or equal to three months). Small basins had a larger drought impact area, with major drought events often originating from the basin boundaries and migrating towards the basin centre. Meteorological droughts were driven by changes in sea surface temperature (SST), especially the El Niño Southern Oscillation (ENSO) or other climate indices. Anomalies in SST and atmospheric circulation caused by ENSO events may have led to altered climate patterns in different basins, resulting in drought events. These results provide important insights into the characteristics and mechanisms of meteorological droughts in different river basins worldwide.

An integrated assessment model of the impacts of agricultural intensification: Trade‐offs between economic benefits and water quality under uncertainty

AbstractWe integrate a model that simulates biophysical processes in soils and water with spatial and temporal heterogeneity at the basin scale with an economic model of decisions under uncertainty, to simultaneously evaluate the economic and environmental effects of farming practices and land uses that characterise agricultural intensification. The introduction of uncertainty allows the evaluation of economic impacts both due to changes in average profits and in their volatility. Through our model integration, we endogenously tackle the trade‐offs between economic benefits and environmental outcomes, in terms of nutrient levels in water. Results show that a sizable increase in economic benefits from supplemental irrigation comes from lower risk premiums. Medium‐to‐high increments of fertiliser rates in irrigated crops are dominated in terms of economic benefits by low fertiliser rate increments. We find that water quality deteriorates with intensive farming practices. However, the magnitude of the trade‐offs between economic benefits and water quality is mixed and depends on the nutrient and level of risk aversion considered. The ability of our model to quantify and document the mentioned effects is a relevant input to inform the decision‐making process of agricultural and environmental authorities, often characterised by competing and opposing objectives.

The noise is the signal: spatio-temporal variability of production and productivity in high elevation meadows in the Sierra Nevada mountain range of North America

There are expectations that increasing temperatures will lead to significant changes in structure and function of montane meadows, including greater water stress on vegetation and lowered vegetation production and productivity. We evaluated spatio-temporal dynamics in production and productivity in meadows within the Sierra Nevada mountain range of North America by: (1) compiling Landsat satellite data for the Normalized Difference Vegetation Index (NDVI) across a 37-year period (1985–2021) for 8,095 meadows &amp;gt;2,500 m elevation; then, (2) used state-space models, changepoint analysis, geographically-weighted regression (GWR), and distance-decay analysis (DDA) to: (a) identify meadows with decreasing, increasing or no trends for NDVI; (b) detect meadows with abrupt changes (changepoints) in NDVI; and (c) evaluate variation along gradients of latitude, longitude, and elevation for eight indices of temporal dynamics in annual production (mean growing season NDVI; MGS) and productivity (rate of spring greenup; RSP). Meadows with no long-term change or evidence of increasing NDVI were 2.6x more frequent as those with decreasing NDVI (72% vs. 28%). Abrupt changes in NDVI were detected in 48% of the meadows; they occurred in every year of the study and with no indication that their frequency had changed over time. The intermixing of meadows with different temporal dynamics was a consistent pattern for monthly NDVI and, especially, the eight annual indices of MGS and RSP. The DDA showed temporal dynamics in pairs of meadow within a few 100 m of each other were often as different as those hundreds of kilometers apart. Our findings point strongly toward a great diversity of temporal dynamics in meadow production and productivity in the SNV. The heterogeneity in spatial patterns indicated that production and productivity of meadow vegetation is being driven by interplay among climatic, physiographic and biotic factors at basin and meadow scales. Thus, when evaluating spatio-temporal dynamics in condition for many high elevation meadow systems, what might often be considered “noise” may provide greater insight than a “signal” embedded within a large amount of variability.

Impacts of irrigation development on water quality in the San Salvador watershed (Part 2)

Intensive agricultural activities pose a significant threat to water quality as critical non-point sources of pollution. Effective mitigation strategies demand understanding the causes and processes of water pollution. This study aimed to quantify the impacts of irrigation development on water quality and assess best management practices for sustainable agriculture intensification. Employing the calibrated SWAT model for the San Salvador watershed (baseline scenario), two scenarios were implemented and evaluated: the first one depicted irrigation development from a future reservoir, and the second integrated riparian buffer zones to minimize nutrient and sediment losses. Notably the baseline scenario did not achieve nutrient water quality objectives. Results revealed that irrigation development increases nutrient yields, driving the future reservoir toward eutrophication. Implementing riparian buffer zones reduced nutrient loss, but additional measures are necessary for sustainable environmental goals at the basin scale. This research contributes with valuable insights for formulating effective management strategies to minimize nutrient pollution in water and safeguard water quality and biodiversity in the basin.

Distribution characteristics of reactive silicon in six water bodies in the Yangtze River Basin in China

Terrestrial silicon (Si) from biogeochemically weathered rocks and soils into oceans must pass through several water bodies, resulting in some Si immobilized. Hence, the knowledge on Si distribution characteristics in different water bodies at a basin scale is helpful to understand Si immobilization. A total of 65 surface sediments and corresponding overlying water samples were sampled from six water bodies (Dianchi Lake, DL; Dadu River, DR; Tuojiang River, TR; Honghu Lake, HL; Donghu Lake, DhL; Taihu Lake, TL) in the Yangtze River Basin of China, total dissolved Si (TDSi) in overlying water and exchangeable Si (Ex-Si), active non-biogenic Si (NBSi), and total acid dissolved Si (TADSi) in sediments were analyzed. Water chemical parameters (pH, EC, and TDP) and sediment components (LOI, TN, TP, and TADFe) showed that the water environment characteristics of six water bodies differed. TDSi differed among regions and between lakes and rivers, significantly higher in water bodies in the upper reaches and rivers than the middle or lower reaches and lakes (p < 0.05), respectively. Ex-Si in sediments in the upper reaches was significantly higher than in the middle or lower reaches (p < 0.05), except for DhL, whose Ex-Si was the highest. Mean TADSi and active NBSi were significantly higher in lakes than rivers (p < 0.05). Oxidation of sediments significantly increased TDSi in overlying water and active NBSi in sediments (p < 0.01). Si forms in six water bodies significantly depended on components of the sediments (e.g. active Ca2+, Mg2+, Fe, and Al3+) and water chemical parameters (p < 0.05). Our results suggest that immobilization of Si in water bodies in the Yangtze River Basin depends on the types of water bodies and sediments, lakes and Fe–Al dominated sediments have a high potential to immobilize Si, but anthropogenic interference should not be ignored.

Sea surface temperature reconstruction in the Pacific Ocean using multi-elemental proxy in Porites and Diploastrea corals: Application to Palau Archipelago

Massive reef-building Porites corals are commonly studied to obtain long-term reconstructions of past sea surface temperature (SST) using temperature-sensitive elemental proxies, such as Sr/Ca or Li/Mg ratios. Most recently, a multi-proxy approach combining these two ratios (e.g. D'Olivo et al., 2018) and the SrU method (DeCarlo et al., 2016) have proved to be more robust to reconstruct paleo-temperatures. To date, no study has been carried out on the application of these new approaches on the Diploastrea heliopora coral, another massive reef-building genus that can potentially provide longer temperature records. Moreover, only a few studies have assessed coral SST calibrations at the scale of the Indo-Pacific basin and compared SST reconstructions obtained from two massive coral genera from the same site.In this study, we investigated the elemental composition of the topmost portion of 34 modern tropical Porites and 6 Diploastrea colonies collected during the Tara Pacific expedition (2016–2018) from various hydrological contexts in the Pacific Ocean. We derived and discussed annual Sr/Ca, Li/Mg, combined Sr/Ca-Li/Mg and Sr/Ca-Li/Ca-Mg/Ca and SrU vs. SST calibrations as well as potential intra-colonial and genus specific effects and evaluated the use of these basin-wide calibration equations. Overall, multi-ratio and multi-genera SST calibrations perform better than single-ratio calibrations and seem to improve temperature reconstructions.These new SST calibrations were applied to two colonies of Porites and Diploastrea collected from the same site in the North-West of the Palau archipelago located in the western Pacific Ocean to evaluate the applicability of universal calibrations based on different proxies and their combination. Coral-based SST records spanning the last 141 years show decadal changes and recent warming episodes that are related to major El Niño Southern Oscillation events. However, differences in reconstruction remain between both genera in the long-term trends, amplitudes, and absolute temperatures, depending on which genus or temperature proxy is considered.

Assessing the impact of distributed snow water equivalent calibration and assimilation of Copernicus snow water equivalent on modelled snow and streamflow performance

AbstractAccuracy of the Copernicus snow water equivalent (SWE) product and the impact of SWE calibration and assimilation on modelled SWE and streamflow was evaluated. Daily snowpack measurements were made at 12 locations from 2016 to 2019 across a 4104 km2 mixed‐forest basin in the Great Lakes region of central Ontario, Canada. Sub‐basin daily SWE calculated from these sites, observed discharge, and lake levels were used to calibrate a hydrologic model developed using the Raven modelling framework. Copernicus SWE was bias corrected during the melt period using mean bias subtraction and was compared to daily basin average SWE calculated from the measured data. Bias corrected Copernicus SWE was assimilated into the models using a range of parameters and the parameterizations from the model calibration. The bias corrected Copernicus product agreed well with measured data and provided a good estimate of mean basin SWE demonstrating that the product shows promise for hydrology applications within the study region. Calibration to spatially distributed SWE substantially improved the basin scale SWE estimate while only slightly degrading the flow simulation demonstrating the value of including SWE in a multi‐objective calibration formulation. The particle filter experiments yielded the best SWE estimation but moderately degraded the flow simulation. The particle filter experiments constrained by the calibrated snow parameters produced similar results to the experiments using the upper and lower bounds indicating that, in this study, model calibration prior to assimilation was not valuable. The calibrated models exhibited varying levels of skill in estimating SWE but demonstrated similar streamflow performance. This indicates that basin outlet streamflow can be accurately estimated using a model with a poor representation of distributed SWE. This may be sufficient for applications where estimating flow is the primary water management objective. However, in applications where understanding the physical processes of snow accumulation, melt and streamflow generation are important, such as assessing the impact of climate change on water resources, accurate representations of SWE are required and can be improved via multi‐objective calibration or data assimilation, as demonstrated in this study.

Ecological health assessment of the Qinghe River Basin: analysis and recommendations

Abstract The assessment of ecosystem health at the scale of a large river basin is currently an important direction in environmental science and landscape ecology research. This study focuses on the ecological health assessment of the Qinghe River Basin. Following the Guidelines for Eco-health Assessment of Basin (Trial), a framework was designed to construct an assessment system. The aquatic and terrestrial systems of the Basin were selected, and the ecological pattern, ecological function, and ecological pressure were evaluated. The comprehensive assessment index, i.e., whole health index (WHI), was used to evaluate the overall situation of the basin, providing a comprehensive reflection of its state. The results indicate that the comprehensive index of ecological health assessment for the Qinghe River Basin is 58.66, indicating an average evaluation grade. By evaluating the health of the ecological system in the Qinghe River Basin, this study has gained an understanding of the current situation and identified major issues in the area. The study also proposes suggestions for future sustainable development and effective management of the Qinghe River Basin. These findings hold significant practical importance for the comprehensive protection and development of the area.