Underwater localization is considered a critical technique in the Internet of Underwater Things (IoUTs). However, acquiring accurate location information is challenging due to the heterogeneous underwater environment and the hostile propagation of acoustic signals, especially when using received signal strength (RSS)-based techniques. Additionally, most current solutions rely on strict mathematical expressions, which limits their effectiveness in certain scenarios. To address these challenges, this study develops a quantum-behaved meta-heuristic algorithm, called quantum enhanced Harris hawks optimization (QEHHO), to solve the localization problem without requiring strict mathematical assumptions. The algorithm builds on the original Harris hawks optimization (HHO) by integrating four strategies into various phases to avoid local minima. The initiation phase incorporates good point set theory and quantum computing to enhance the population quality, while a random nonlinear technique is introduced in the transition phase to expand the exploration region in the early stages. A correction mechanism and exploration enhancement combining the slime mold algorithm (SMA) and quasi-oppositional learning (QOL) are further developed to find an optimal solution. Furthermore, the RSS-based Cramér–Raolower bound (CRLB) is derived to evaluate the effectiveness of QEHHO. Simulation results demonstrate the superior performance of QEHHO under various conditions compared to other state-of-the-art closed-form-expression- and meta-heuristic-based solutions.

Cave monitoring is the process of collecting observational data such as microclimate conditions, hydrogeochemistry and water movement in cave systems. The most common motivation is for speleothem science – the reconstruction of past climate and environmental variability from cave formations such as stalagmites. Applications also include the monitoring of potential recharge to aquifers, as well as cave conservation. PAGES-SISAL (Past Global Changes – Speleothem Isotope Synthesis and AnaLysis), an international working group focused on speleothem science, has created a new global database of cave monitoring data consisting of drip rates and drip water isotopes, and the modern carbonate precipitates that form from these drip waters (so called farmed carbonates, grown on artificial substrates). Moreover, we report meteoric precipitation amounts and water isotopes at or near to cave sites. The draft version of the database can be found at https://repo.researchdata.hu/privateurl.xhtml?token=43a43257-f06e-4dc5-9e96-6603eabe775f, which will be available under doi: 10.5158/ARP/29W5J3 upon publication. The database contains datasets from 75 caves, with summary information including meta-data on location, elevation, cave depth, lithology, measurement methods and citations for original publications. Speleothem records previously curated by SISAL in SISAL speleothem database versions and corresponding to monitored drip sites are also identified in the new SISAL monitoring database. To supplement observational data gaps and provide accessible and consistent climate data for users, surface climate (precipitation, evaporation, temperature) and meteoric water isotope data extracted from global climate model products are also included in the database.

For analysing karst hydrogeological systems, observations of karst springs and cave drips are considered indispensable. In addition to hydrometric observations, knowing the oxygen and hydrogen stable isotope ratios has improved the understanding of vadose zone and aquifer dynamics, likewise supporting system characterisation and modelling. However, limited accessibility and high costs of the analysis of stable isotopes in karst aquifers have hindered progress in karst research and impeded the accurate understanding of karst processes especially when it comes to comparative or large-scale studies. In this study, we present our workflow to compile the WoKaS-Iso database, the first extensive collection of time series data for Oxygen-18 and Deuterium isotopes in karst springs and cave drip water from diverse sources, encompassing publications, theses, reports, online archives, and collaborative initiatives worldwide. The database incorporates data sourced from 241 springs and 74 caves, of which 73 caves contain 365 individual drip sites and one cave contains input data only. In total, the database comprises 1007 time series, including 389 spring time series and 618 cave drip water time series. The compiled isotope records span the period from 1967 to 2024, with the strongest temporal coverage during the 2010s and continuing coverage into the early 2020s. Of these sites, 148 springs and 64 caves contain both δ ¹⁸ O and δ ² H records, while 93 springs and 9 caves contain only one isotope tracer. These datasets provide coverage across significant karst regions globally, spanning China, the USA, Europe, the Middle East, and Australia. Within datasets, 79 % for springs and 68 % for cave drip water exhibit resolutions finer than monthly intervals. In addition, by integrating isotopic records with ancillary environmental variables including spring discharge, cave drip rate, precipitation, and rainwater isotopes, the database offers a more comprehensive perspective on hydrological behaviours in karst aquifers, hence advancing hydrogeological characterisation and modelling. The WoKaS-Iso database not only deepens the understanding of the complex systems but also promotes sustainable water resource management as well as the potential to foster collaborative research. The database can be accessed at: https://doi.org/10.25532/OPARA-909 (Zang, 2025).

PAGES’ SISAL (Speleothem Isotope Synthesis and AnaLysis) working group (WG) created a set of databases hosting speleothem δ18O and δ13C records (Comas-Bru et al. 2017; Kaushal et al. 2024), and synthesized them to target overarching climate questions such as investigating long-term drivers of the global monsoon and for data-model comparisons (Comas-Bru et al. 2019). Over the course of 2024-2025, the WG created a new database called SISAL_monv1 hosting cave monitoring datasets from 75 cave sites across the Globe (Fig. 1) complementing existing SISAL databases. It aims to facilitate a more robust understanding of the speleothem oxygen-isotope records, by far the most ubiquitously measured and applied speleothem proxy. The SISAL_monv1 database will be available in late 2025. The latest installment in the set of SISAL databases (SISALv3, Kaushal et al. 2024) was incorporated into the SISALwebApp (Hatvani et al. 2024). Further upgrade of the webApp to query the SISAL_monv1will be released accompanying the database. The SISAL_monv1 database compiles the following data types to improve proxy interpretations: measured and modeled meteoric precipitation amount, measured and modeled meteoric precipitation δ18O and δ2H data; cave drip δ18O and δ2H data; cave drip rate; modern (“farmed”) calcite δ18O and δ13C values; as well as meta-data on the cave and its location (Fig. 1). To address data gaps and provide accessible, consistent climate data for users, the SISAL_monv1 database also incorporates surface climate (precipitation, evaporation, temperature) and meteoric water isotope data extracted from global climate model products (Yoshimura et al. 2008). This collection of variables provides baseline data to support investigations into the rainwater δ18O– drip water δ18O–speleothem carbonate δ18O relationships, including the development of proxy–model calibration approaches and exploration of local impacts (Hu et al 2021; Treble et al. 2022). When building the database, an automated quality control procedure was applied to all submitted data. Workbooks were shared with both data-entry personnel and original authors for validation of flagged issues. Final versions of the workbooks were sent to corresponding authors for final approval. The database will be especially valuable for researchers aiming to improve the interpretation of speleothem oxygen isotopes, for teams developing proxy system models to enable and support data-model comparison approaches to understanding climate, as well as for karst researchers working on karst water balance. The sql and csv versions of the database will be hosted in an open repository, together with example scripts to access the data. The SISAL_monv1 database will also be incorporated into the SISALwebApp by late 2025. We welcome feedback on PAGES' SISAL webApp and encourage participation and collaboration from interested researchers in different stages of their academic career and working in different geographical regions and allied disciplines. You can contact the SISAL Working Group here

Localization is a crucial technique for determining target locations in underwater acoustic internet of things (UAIoT) systems. However, the presence of stratified oceanic environments and anchor position uncertainties significantly undermine localization accuracy. To rigorously investigate their adverse effects on localization performance, this study presents a comprehensive theoretical analysis of hybrid RSS/TOA-based localization under stratified propagation and inaccurate anchors in UAIoT systems. First, a stratified acoustic propagation model is established, and the corresponding Cram $$\acute{\text e}$$ e ´ r-Rao lower bound (CRLB) is derived for RSS and TOA measurements. The analysis is then extended to a hybrid scenario incorporating anchor inaccuracy using the Banachiewicz-Schur theorem, resulting in a unified expression for the theoretical performance bound. Simulation results confirm the validity of the derived CRLB across diverse scenarios. Compared with using a single ranging modality, the derived lower-bound performance of the proposed hybrid RSS/TOA approach improves by at least 19.8% under accurate-anchor conditions and 24.1% under inaccurate-anchor conditions. The findings provide theoretical benchmarks and practical guidance for designing robust localization strategies in stratified oceanic environments.

For analysing karst hydrogeological systems, observations of karst springs and cave drips are considered indispensable. In addition to hydrometric observations, knowing the oxygen and hydrogen stable isotope ratios has improved the understanding of vadose zone and aquifer dynamics, likewise supporting system characterisation and modelling. However, limited accessibility and high costs of the analysis of stable isotopes in karst aquifers have hindered progress in karst research and impeded the accurate understanding of karst processes especially when it comes to comparative or large-scale studies. In this study, we present our workflow to compile the WoKaS-Iso database, the first extensive collection of time series data for Oxygen-18 and Deuterium isotopes in karst springs and cave drip water from diverse sources, encompassing publications, theses, reports, online archives, and collaborative initiatives worldwide. The database incorporates data sourced from 236 springs and 74 caves, comprising in total 997 time series (379 time series for the springs and 618 time series for the cave drip water). These datasets provide coverage across significant karst regions globally, spanning China, the USA, Europe, the Middle East, and Australia. Within datasets, 79% for springs and 68% for cave drip water exhibit resolutions finer than monthly intervals. In addition, by integrating isotopic records with ancillary environmental variables including spring discharge, cave drip rate, precipitation, and rainwater isotopes, the database offers a more comprehensive perspective on hydrological behaviours in karst aquifers, hence advancing hydrogeological characterisation and modelling. The WoKaS-Iso database not only deepens the understanding of the complex systems but also promotes sustainable water resource management as well as the potential to foster collaborative research. The database can be accessed at: https://doi.org/10.25532/OPARA-909.