Basin Scale Research Articles

Quantifying the consequences of unsustainable sand mining and cascade dams on aspects in a tropical river basin

Human interventions at the river basin scale, such as sand mining and hydropower dam construction, have profoundly affected hydrological and hydraulic alteration regimes, sediment budgets, and morphological changes worldwide. Quantifying the consequences of unsustainable ongoing sand mining and hydropower is crucial for obtaining sediment load data and managing hydrogeomorphology. In this study, comprehensive long-term consecutive four-field monitoring, statistical methods, and hydrological models (SWAT) were applied to quantify the spatiotemporal changes in long-term discharge and sediment load from 1996 to 2020 for the tropical river of the Vu Gia Thu Bon (VGTB) in the central region of Vietnam. The SWAT model was calibrated from 1996 to 2010, validated from 2011 to 2020 and showed good performance for daily discharge and monthly sediment. The evolution of river bathymetric data (2010, 2015, 2018, and 2021) was analysed to clarify the upstream sediment supply trapped in the riverbed and how the sand mining volume was removed. The results showed that the mean annual sediment in the Vu Gia and Thu Bon Rivers decreased by 57.3% and 23.8%, respectively, in the postdam period compared with the predam period. The thalweg elevation decreased at the Ai Nghia and Giao Thuy stations from 2010 to 2021 by 1.8 m and 3.9 m, respectively. The water level decreased by 21.1% at Ai Nghia and 44.3% at Giao Thuy. Dam development, sand mining, and changes in land use are the main factors responsible for flow discharge and sediment morphodynamic alterations. Morphological change have increased the water transfer rate from the Vu Gia River to the Thu Bon River through the Quang Hue channel. Downstream of the Vu Gia River, water transfer and riverbed incision have decreased flow discharge and water level and increased saltwater intrusion in recent years. As a result, water shortages induced by saltwater intrusion during drought periods have emerged as a significant constraint in hindering the domestic water supply and agricultural production.

The Rising Concern for Sea Level Rise: Altimeter Record and Geo-Engineering Debate

The Oceans from Space V Symposium, held in Venice, Italy, on 24–27 October 2022, devoted special sessions to sea level rise, as described by a series of satellite altimeters, and to remediations of consequent calamities in vulnerable mediterranean seas. It emerged that various aspects of climate change can be modelled in time as a Single Exponential Event (SEE), with a similar trend (a 54–year e–folding time) for CO2 concentration in the Earth’s atmosphere, global average sea surface temperature, and global average sea level. The sea level rise record, combining tide gauges data starting in 1850, as well as more recent altimeter data, for the last 30 years, is already 25 cm above historical values. If the curve continues to follow the exponential growth of the simple SEE model, it will reach about 40 cm by the year 2050, 1 m by 2100, and 2.5 m by 2150. As a result, dramatic impacts would be expected for most coastal areas in the next century. Decisive remediations, based on geo-engineering at the basin scale, are possible for semi-enclosed seas, such as the Mediterranean and Black Seas. Damming the Strait of Gibraltar would provide an alternative to the conclusion that coastal sites such as the City of Venice are inevitably doomed.

Basin scale sources of siltation in a contaminated hydropower reservoir

Siltation and the loss of hydropower reservoir capacity is a global challenge with a predicted 26 % loss of storage at the global scale by 2050. Like in many other Latin American contexts, soil erosion constitutes one of the most significant water pollution problems in Chile with serious siltation consequences downstream. Identifying the sources and drivers affecting hydropower siltation and water pollution is a critical need to inform adaptation and mitigation strategies especially in the context of changing climate regimes e.g. rainfall patterns. We investigated, at basin scale, the main sources of sediments delivered to one of the largest hydropower reservoirs in South America using a spatio-temporal geochemical fingerprinting approach. Mining activities contributed equivalent to 9 % of total recent sediment deposited in the hydropower lake with notable concentrations of sediment-associated pollutants e.g. Cu and Mo in bed sediment between the mine tributary and the reservoir sediment column. Agricultural sources represented ca. 60 % of sediment input wherein livestock production and agriculture promoted the input of phosphorus to the lake. Evaluation of the lake sediment column against the tributary network showed that the tributary associated with both dominant anthropogenic activities (mining and agriculture) contributed substantially more sediment, but sources varied through time: mining activities have reduced in proportional contribution since dam construction and proportional inputs from agriculture have increased in recent years, mainly promoted by recent conversion of steep lands from native vegetation to agriculture. Siltation of major hydropower basins presents a global challenge exemplified by the Rapel basin. The specific challenges faced here highlight the urgent need for co-design of evidence-led, context-specific solutions that address the interplay of drivers both within and without the basin and its communities, enhancing the social acceptability of sediment management strategies to support the sustainability of clean, hydropower energy production.

Sediment temperature characteristics and their relation to distribution patterns of two sentinel crab species in intertidal flats in western Japan

In the context of global climate change, monitoring focused on temperature and benthic animals in intertidal flats and the development of metrics to assess climate change and ecosystem responses are essential for a sustainable society. However, few studies have assessed the relationship between intertidal sediment temperature and the distribution of benthic animals. To address this gap, in the present study, intertidal sediment temperatures were observed in 12 intertidal flats in 11 survey areas over 335 days, from October 2, 2019, to August 31, 2020, using water temperature data loggers. The characteristics of intertidal sediment temperatures were variable among the survey areas, and a correlation analysis suggested that such characteristics are possibly influenced by various spatial-scale factors, such as geographical, basin, and habitat scales. Furthermore, two sentinel crab species, Macrophthalmus japonicus and Macrophthalmus banzai were collected, and the number of wintering individuals of each species was estimated based on their carapace width to analyze the changes in abundances of the two species in each survey area. The results show that the number of days with daily minimum temperature ≥ 19 °C was the factor that influenced the abundance rate, suggesting that M. japonicus and M. banzai populations may decrease and increase, respectively, according to future climate change in Japan. Our findings emphasize the importance of long-term monitoring of sediment temperatures and benthic animals in intertidal flats to evaluate the influence of future climate change.

Combining Hydrological Models and Remote Sensing to Characterize Snowpack Dynamics in High Mountains

Seasonal snowpacks, characterized by their snow water equivalent (SWE), can play a major role in the hydrological cycle of montane environments with months of snow accretion followed by episodes of melt controlling flood risk and water resource availability downstream. Quantifying the temporal and spatial patterns of snowpack accumulation and its subsequent melt and runoff is an internationally significant challenge, particularly within mountainous regions featuring complex terrain with limited or absent observational data. Here we report a new approach to snowpack characterization using open-source global satellite and modelled data products (precipitation and SWE) greatly enhancing the utility of the widely used Soil and Water Assessment Tool (SWAT). The paper focusses on the c. 23,000 km2 Chenab river basin (CRB) in the headwaters of the Indus Basin, globally important because of its large and growing population and increasing water insecurity due to climate change. We used five area-weighted averaged satellite, gridded and reanalysis precipitation datasets: ERA5-Land, CMORPH, TRMM, APHRODITE and CPC UPP. As well as comparison to local weather station data, these were used in SWAT to model streamflow for evaluation against observed streamflow at the basin outlet. ERA5-Land data provided the best streamflow match-ups and was used to infer snowpack (SWE) dynamics at basin and sub-basin scales. Snow reference data were derived from remote sensing and modelled SWE re-analysis products: ULCA-SWE and KRA-SWE, respectively. Beyond conventional auto-calibration and single-variable approaches we undertook multi-variable calibration using R-SWAT to manually adjust snow parameters alongside observed streamflow data. Characterization of basin-wide patterns of snowpack build-up and melt (SWE dynamics) were greatly strengthened using KRA-SWE data accompanied by improved streamflow simulation in sub-basins dominated by seasonal snow cover. UCLA-SWE data also improved SWE estimations using R-SWAT but weakened the performance of simulated streamflow due to under capture of seasonal runoff from permanent snow/ice fields in the CRB. This research highlights the utility and value of remote sensing and modelling data to drive better understanding of snowpack dynamics and their contribution to runoff in the absence of in situ snowpack data in high-altitude environments. An improved understanding of snow-bound water is vital in natural hazard risk assessment and in better managing worldwide water resources in the populous downstream regions of mountain-fed large rivers under threat from climate change.

In Situ Sampling of NOx Emissions from United States Natural Gas Flares Reveals Heavy-Tail Emission Characteristic.

Natural gas flaring is a common practice employed in many United States (U.S.) oil and gas regions to dispose of gas associated with oil production. Combustion of predominantly hydrocarbon gas results in the production of nitrogen oxides (NOx). Here, we present a large field data set of in situ sampling of real world flares, quantifying flaring NOx production in major U.S. oil production regions: the Bakken, Eagle Ford, and Permian. We find that a single emission factor does not capture the range of the observed NOx emission factors within these regions. For all three regions, the median emission factors fall within the range of four emission factors used by the Texas Commission for Environmental Quality. In the Bakken and Permian, the distribution of emission factors exhibits a heavy tail such that basin-average emission factors are 2-3 times larger than the value employed by the U.S. Environmental Protection Agency. Extrapolation to basin scale emissions using auxiliary satellite assessments of flare volumes indicates that NOx emissions from flares are skewed, with 20%-30% of the flares responsible for 80% of basin-wide flaring NOx emissions. Efforts to reduce flaring volume through alternative gas capture methods would have a larger impact on the NOx oil and gas budget than current inventories indicate.

New insight into and characterization of DOC, DON and CDOM for urban waters in the lower reaches of the Yellow River, China

Dissolved organic matter (DOM), usually measured as concentrations of dissolved organic carbon (DOC) and nitrogen (DON) and chromophoric dissolved organic matter (CDOM), plays a crucial role in the global carbon and nitrogen cycles in inland waters. The aim of this study is to characterize spatial variations of DOC, DON, and C:N molar ratios and CDOM using absorption spectroscopy and further determine their relationships using pearson correlations (r) for urban waters along trophic gradients in the lower reaches of the Yellow River (YR) of China. A dataset of 122 urban water samples were collected from four typical cities during 2021–2022. Principal component analysis (PCA) was performed to assess the relative distribution of these urban water samples. These urban waters can be grouped into two categories: mesotrophic waters (n = 57) and eutrophic waters (n = 65) based on trophic state index (TSI) threshold value of 50. Results revealed that there were significantly higher DOC, CDOM absorption and SUVA254 along with lower S275–295 and M (t-test, p < 0.01) in eutrophic waters compared with mesotrophic waters. DOC was significantly higher than DON (p < 0.01). DOC was highly related to DON (R2 = 0.649) and COD (R2 = 0.840) suggesting they were derived from a common source. CDOM absorption a(254) was strongly correlated with DOC (R2 = 0.770) and COD (R2 = 0.800). DON can be calculated based on the strong correlations between DOC and DON and then C:N molar ratios can be further obtained for these urban waters. These results implied that CDOM optical absorption a(254) can be viewed as the best indicators of DOC and associated with water quality parameters. These findings can help us to better understand DOC, DON and CDOM of DOM coupled cycling processes for urban waters with similar climatic and hydrologic conditions on basin scale in China.

Evaluating the groundwater quality in Northern Tarim Basin by resistivity inverted from magnetotelluric data

Groundwater is a potentially significant resource for agricultural and industrial uses in Tarim Basin, the largest arid endorheic basin in China. Hydrogeochemical and hydrogeologic researches have provided detailed information of groundwater chemical type, composition, ion content and flow. However, there is lacking in quantitative estimation of groundwater in whole basin scale subject to the limits of samples as well as the unclear underground structure. To address the problem, 3-D electrical resistivity model constructed from inversion of magnetotelluric (MT) data was used to calculate the Total Dissolved Solids (TDS) of groundwater based on previous experimental studies and empirical equations. The TDS model shows relatively high value in the east of the study area and in deep, primarily controlled by depth, flow direction, stratigraphy, and water table gradient. Groundwater can be classified into five categories in terms of TDS range in Standard for Groundwater Quality. Finally, the volume of each type and average available quantity of Classes I ∼ III (TDS < 1 g/L) per person were estimated by taking account of population distribution. Mapping groundwater TDS and volume reveals that human activities also play a role in groundwater salinity. The evaluation of groundwater quality and volume based on TDS provides a basis for future urban construction and development as well.

Water Quality Prediction Based on an Innovated Physical and Data Driving Hybrid Model at Basin Scale

The prediction of basin water quality has become an urgent need for water environment management, where water pollution is on the increase. Currently, physical models are primarily used for water quality predictions, but the models are not adaptable for the automatic future prediction of watershed water quality owing to their non-automatic boundary setting. The development of big data, which has led to artificial intelligence (AI) technology, has remedied the deficiency of physical models and has been widely used in water quality prediction. However, the accuracy of AI models depends only on the quantity and quality of dataset, which is applied on specific and discrete sections with enough data and difficult to extend to regions with limited monitoring data. Thus, we constructed migration and distribution gates to express the spatial influence of different variables from different sections on the water quality of a specific and discrete section. The temporal processes were expressed by degradation equation. The migration gate, distribution gate and degradation equations were incorporated into Long Short-Term Memory Network (LSTM) to improve the operation mechanism of the LSTM algorithm to create the Im-LSTM model, which considers both the temporal influence of a specific section and the spatial influence of other sections on a specific section at basin scale. Compared to ANN, LSTM, Im-LSTM showed the best performance for basin water quality prediction, especially for mainstream sections at sudden pollution process. Thus, the proposed Im-LSTM provides a new approach for water environment supervision.

Modelagem integrada de qualidade e quantidade para gestão de recursos hídricos: estudo de caso na Bacia do Alto Paranapanema

ABSTRACT This study introduces an integrated model for water resources planning and management that accounts for both the quantity and quality of water in watersheds and reservoirs. Therefore, it provides a comprehensive approach for better understanding and assessing water systems. The model facilitates analyses of the spatial and temporal dynamics of hydrological processes, pollutant transport, and the behavior of rivers and reservoirs. The study evaluated pollutant load transport in the Upper Paranapanema Basin by applying the Soil Moisture Accounting Procedure (SMAP) model, Muskingum method, Streeter-Phelps buildup/washoff model, and zero-dimensional (0D) models to estimate inflows to the Jurumirim reservoir. A Python-based public library was developed to model all hydrological processes. The model calibration yielded a NSE, KGE, PBIAS and RMSE result of 0.746, 0.778, 6.5% and 73.3 m 3 s − 1, respectively. Indicating a robust simulation that attests to the versatility and reliability of the proposed approach. The methodology outlined in this research enables comprehensive water quality simulation at basin scale, thereby serving as a tool for understanding water quantity and quality dynamics and support decision-making regarding water resource planning and management.

Seasonal and ocean basin scale variation in the food web baseline and trophic ecology of a wide-ranging Southern Ocean predator derived from amino acid δ15N trends

Seasonal and ocean basin scale variation in the food web baseline and trophic ecology of a wide-ranging Southern Ocean predator derived from amino acid δ15N trends

Integrated mapping of ecosystems and assessment of forest ecosystem services at river basin scale

Ecosystems provide various goods and services to society and their valuation is among the main objectives of the concept of ecosystem services (ES). The mapping of ecosystems is the main building block of the whole process of the Mapping and Assessment of Ecosystems and their Services (MAES). The analyses of the ecosystem data produced during the implementation of the national methodology for mapping ecosystems in Bulgaria (MAES BG) reveal some problems that may cause confusion in cases of integrated assessment of all ecosystem types. In this paper, we present an approach that enables formulation of a uniform spatial dataset based on the mapping of the main ecosystem types, that can be used for mapping of ES at a river basin scale. It has been applied to the upper part of the Ogosta River basin and the result is a topologically correct uniform spatial data layer. The approach gives one possible solution to problems related to the different sources of information and the discrepancies between ecosystem types in the national mapping of ecosystems in Bulgaria. It is based on the use of a uniform spatial framework that outlines the ecosystem types and sets the initial database for further mapping. This ensures a topologically correct spatial dataset for the ecosystems and a background for further updates for each ecosystem at the different levels of MAES typology. The most appropriate spatial basis for the territory of Bulgaria is the database for the physical blocks of the Ministry of Interior. Its application to the studied river basin gives encouraging results and can be used as an example for similar areas. Further development of the approach will ensure the mapping of the forest ecosystems at level 3 of the MAES BG typology and more precise delineation of the grassland, heathland, freshwater, and sparsely vegetated ecosystems.

Ecosystem accounting for water resources at the catchment scale, a case study for the Peloponnisos, Greece

The System of Environmental-Economic Accounts - Ecosystem Accounting (SEEA EA) has become the world’s leading natural capital accounting system. It provides a valuable decision-making tool for spatial planning and integrated development. SEEA implementation is a current key challenge for European Union (EU) Member States (MS), mainly due to high requirements on budget, technical capacity, and data, varying between countries. Within this frame, the objective of this paper is to demonstrate how the SEEA framework can be applied to analyse water ecosystems at river basin scale, building exclusively upon the officially registered, standardized national and EU datasets. We test how water resources can be accounted for using SEEA EA, with an additional component assessing water use based on SEEA Water. Within the EU Water Framework Directive (WFD), two reporting cycles of river basin management plans have been completed for water ecosystems, providing spatial and temporal datasets. This material together with numerous data available at EU and national levels, water-relevant databases and repositories, resulting from MS reporting obligations, are tested and utilised for water accounting. The Alfeios river basin in Western Peloponnisos Greece serves as the case study area for compiling extent accounts, condition accounts, and supply and use accounts for provisioning water ecosystem services (drinking and irrigation water) for the periods 2009–2015 and 2015–2021 (the two WFD reporting cycles). It is demonstrated that readily available EU datasets can support the initial mapping and compiling of water ecosystem accounts at local scale, as applied in Greece, and therefore potentially also in other EU countries with fragmented data scattered in various administrative services and authorities with overlapping responsibilities on water resources. It is also concluded that future WFD reporting cycles and revisions of the river basin management plans could be better structured to enable a more direct connection of the collected data to ecosystem accounts.

Analysis of the effect of rainfall center location on the flash flood process at the small basin scale

Abstract With the increasing frequency of extreme convective weather, the spatial–temporal variability of rainfall becomes more diversified. As a result of the insufficient quality of rainfall monitoring data in mountainous areas, the flash flood simulation usually does not consider the effect of the rainfall center location. In this work, the GPU Accelerated Surface Water Flow and Associated Transport hydrodynamic model is used to simulate the flash flood discharge process. The effect of the rainfall center location and the basin scale on the discharge process were analyzed based on simulated data. The results show that when the rainfall center is in the upstream and midstream basins, because of gravitational potential energy conversion, the total flood volume and the flood peak discharge increase to 2–10 times, and the peak time of flash flood caused by 100 mm rainfall amount can be advanced by up to 3,000 s compared to the 20 mm rainfall amount condition. The peak discharge and the delay of peak time increase with the increase of rain peak coefficient. In addition, the increase of the basin area enhances the effect of the rainfall center location. This work is helpful to quantify the effect of the rainfall center location, which can clarify the uncertainty of flash flood simulation caused by not considering the rainfall center factor.

Synergy Assessment of River Health Values from a Symbiotic Perspective: A Case Study of the Yellow River Basin in China

Rivers are important carriers of water transmission, water supply, and water nourishment, and the virtuous cycle of their ecosystems is directly related to the degree of completion of the construction of ecological civilization and the high-quality development of the national economy. From the perspective of symbiosis theory, this paper constructs a river health value assessment index system and analyzes the symbiotic synergistic effect of nine provinces in the Yellow River Basin in China from 2000 to 2020 by using a logistic symbiosis evolution model. Health values at the Yellow River Basin scale and the provincial administrative area scale were also analyzed, and it was found that (1) the Yellow River Basin experienced a period of sub-par river health in the past, but with the implementation of ecological protection and high-quality development strategy in recent years, the health of the river showed an trend of improvement during the period of 2017–2020; (2) at the provincial administrative scale, the Yellow River Basin has significant differences, which are manifested in the obvious differences between provinces in terms of the functional value of river health provision and the economic functional value. In order to reduce the regional differences, it is recommended that the provinces work together and give full play to their own characteristics and strengths in the management of the watershed, so as to make up for the weaknesses of regional development and realize the synergistic development of the watershed; and (3) in terms of symbiosis level, rivers in the Yellow River Basin generally show parasitic relationships, and most of them exhibit natural ecological diversity and competitiveness with socio-economics. Therefore, a more comprehensive consideration of the balanced development of each function is needed in river health management in the future to achieve integrated watershed health. These results suggest that the development of river ecological health in the Yellow River Basin requires the joint efforts of the whole of society as well as regional synergy and integrated management at the policy level to achieve more sustainable and balanced watershed development.

Good eutrophication status is a challenging goal for coastal waters

Our objective is to understand the effectiveness of local and international nutrient pollution mitigation efforts when targeting better water quality in the region’s coastal waters. To this end, we developed an integrated modeling framework for the Archipelago Sea located in the Baltic Sea in Northern Europe, conducted what-if analyses for various ambition levels of nutrient abatement, and studied the long-term consequences at the sea basin scale. We demonstrate that in outer parts of the Archipelago Sea, a good eutrophication status can be achieved if the current internationally agreed policy goals for nutrient abatement are successfully met. In inner coastal areas, current goals for phytoplankton biomass could be reached only through extreme mitigation efforts in all polluting sectors and large-scale application of yet poorly tested ecological engineering methods. This result calls for carefully considering the relevance of current threshold values for phytoplankton and its role as a dominant indicator of good ecological status.

Rapid mass losses of Urumqi River Basin glaciers, eastern Tianshan Mountains revealed from multi-temporal DEMs, 1964–2021

ABSTRACT Glacier volume changes have remarkable impacts on regional water resources; however, their estimation uncertainties remain large. In this study, the surface elevations of seven glaciers at the headwaters of the Urumqi River exhibited obvious thinning at the rate of 0.32 m a−1 from 1964 to 2021. Correlations between the ice volume change (dV) derived from surface elevation conversion and the area change (dS) were established for valley, cirque, and hanging glaciers. The ice volumes of valley, cirque, and hanging glaciers in the Urumqi River Basin decreased by 0.99 km3, 0.18 km3, and 0.59 km3, respectively, and the total ice volume decreased by 1.76 km3 during 1964–2021. Ice volume losses are accelerating. The correlation between dV and dS for valley glaciers produced a large estimation difference for the ice volume change of Urumqi Glacier No. 1 (UG1) compared with the glaciological mass balance (15%), while the estimation differences of ice volume changes for the three types of glaciers in the Urumqi River Basin were within acceptable limits (10%) based on the geodetic results. This new method has vast potential in estimating ice volume changes at the basin or regional scale, or even across western China.

Impact of Spatial Rainfall Scenarios on River Basin Runoff Simulation a Nan River Basin Study Using the Rainfall-Runoff-Inundation Model

This study aims to investigate the impact of spatial rainfall distribution scenarios from ground observation stations on runoff simulation using hydrological modeling specific to the Rainfall-Runoff-Inundation (RRI) model. The RRI model was applied with six different spatial distribution scenarios of input rainfall, including Inverse Distance Weight (IDW), Thiessen polygon (TSP), Surface Polynomial (SPL), Simple kriging (SKG), and Ordinary kriging (OKG), to simulate the runoff of a 13,000 km2 watershed, namely the Nan River Basin in Thailand. This study utilized data from the 2014 storm event, incorporating temporal information from 28 rainfall stations to estimate rainfall in the spatial distribution scenarios. The six statistics, Volume Bias, Peak Bias, Root Mean Square Error, Correlation, and Mean Bias, were used to determine the accuracy of the estimated rainfall and runoff. Overall, the Simple kriging (SKG) method outperformed the other scenarios based on the statistical values to validate with measured rainfall data. Similarly, SKG demonstrated the closest match between simulated and observed runoff, achieving the highest correlation (0.803), the lowest Root Mean Square Error (164.48 cms), and high Nash-Sutcliffe Efficiency coefficient (0.499) values. This research underscores the practical significance of spatial interpolation methods, such as SKG, in combination with digital elevation models (DEMs) and landuse/soil type datasets, in delivering reliable runoff simulations considering the RRI model on the river basin scale.

Basin Scale Soil Moisture Estimation with Grid SWAT and LESTKF Based on WSN.

This research utilized in situ soil moisture observations in a coupled grid Soil and Water Assessment Tool (SWAT) and Parallel Data Assimilation Framework (PDAF) data assimilation system, resulting in significant enhancements in soil moisture estimation. By incorporating Wireless Sensor Network (WSN) data (WATERNET), the method captured and integrated local soil moisture characteristics, thereby improving regional model state estimations. The use of varying observation search radii with the Local Error-subspace Transform Kalman Filter (LESTKF) resulted in improved spatial and temporal assimilation performance, while also considering the impact of observation data uncertainties. The best performance (improvement of 0.006 m3/m3) of LESTKF was achieved with a 20 km observation search radii and 0.01 m3/m3 observation standard error. This study assimilated wireless sensor network data into a distributed model, presenting a departure from traditional methods. The high accuracy and resolution capabilities of WATERNET's regional soil moisture observations were crucial, and its provision of multi-layered soil temperature and moisture observations presented new opportunities for integration into the data assimilation framework, further enhancing hydrological state estimations. This study's implications are broad and relevant to regional-scale water resource research and management, particularly for freshwater resource scheduling at small basin scales.

Extreme waves in the Caribbean Sea: spatial regionalization and long-term analysis

The extreme wave height distribution in the Caribbean Sea is studied using a new method based on the maximum basin-wide aggregate of significant wave height, Hs, values per month. Besides, by means of the Self-Organizing Maps (SOM) technique, we identify coherent geographical regions with similar extreme wave height variability in the Caribbean Sea. Our findings revealed three primary regions: the eastern side with comparatively lower values, the central region with intermediate values, and the western side with the highest extreme wave heights. The study also examines the wind forcing conditions driving the spatial and temporal variability of the extreme waves, highlighting the influence of the low-pressure belt dynamics as well as the role played by the Caribbean Low-Level Jet (CLLJ) index, and the impact of cold fronts and hurricanes on extreme wave heights. Additionally, we explore the relationship between the extreme wave height distribution and climatic indices, such as the Atlantic Multidecadal Oscillation (AMO), the Atlantic Meridional Mode (AMM), the North Atlantic Oscillation (NAO) and the Oceanic Niño (ONI). The results reveal that the spatial distribution of extreme wave heights in the Caribbean Sea is mostly ruled by the influence of the CLLJ, with correlations close to 80%. In addition, significant correlations were observed between the extreme wave heights and the ENSO in the central Caribbean, as well as positive correlations between the extreme wave heights and NAO in the eastern part of the basin, and significant values of correlation with the negative phases of AMO and AMM in the whole basin. We show that, unlike conventional (or broadly used) methods deployed to identify extreme wave height, such as percentile 99th, Hs99, our methodology allows a further assessment of the wind and climate forcing conditions associated with the extreme wave events. Although, we acknowledge that the method here presented has limitations to capture extreme wave height outliers, it has the advantage of being used concomitant with the wind forcing to develop multivariate wave climate analysis at basin scale, and could be extended to a more local scale when studying coastal processes.