The accuracy of numerical simulations of a landslide-induced tsunami depends on the landslide characteristics, such as landslide geometry and geotechnical parameters. However, owing to the difficulty in sampling and measuring submarine landslides, rough assumptions of landslide parameters typically lead to significant uncertainties. In the 2018 Palu event, the earthquake was followed by immediate cascading disasters of coastal subsidence, both land and submarine landslides and a tsunami. This scenario provides opportunities to analyze landslide phenomena on land to characterize the submarine landslide causing the tsunami. This study proposes a new approach of using shear-stress parameters obtained from liquefaction analyses as input for landslide-induced tsunami simulation. To obtain the submarine landslide parameter, using the finite element method we modeled the liquefaction happened in Jono-Oge located near Palu Valley area. The shear-stress in this area was quite small with the range 1.5–3.5 kPa. We found that tsunami simulation yielded better accuracy by applying the stress value range obtained from the liquefaction analysis on land (1.5 kPa) rather than the typically adopted stress value for general cases (20 kPa). The result from the tsunami simulation using two-layer method with identical landslide location and geometry showed that shear-stress value of landslide mass gave quite a significant effect to the tsunami height.

The Korteweg–de Vries (KdV) equation is a foundational model in geophysical fluid dynamics (GFD), governing the propagation of long internal and surface gravity waves in stratified and shallow ocean environments where the interplay between nonlinear steepening and frequency-dependent dispersion gives rise to solitons. Although the analytical tractability of the KdV equation through inverse scattering is well established, systematic numerical exploration of multi-soliton interactions remains valuable for benchmarking solvers, probing conservation properties under varied oceanic initial conditions, and building intuition for more complex ocean wave phenomena. This article presents sangkuriang, an open-source Python library that solves the KdV equation using Fourier pseudo-spectral spatial discretization and adaptive eighth-order Runge–Kutta time integration. The implementation leverages just-in-time (JIT) compilation to achieve research-grade computational efficiency on standard hardware, making it readily accessible for coastal and ocean engineering applications, including idealized modeling of internal solitary waves on continental shelves, rapid parameter studies for solitary wave propagation in stratified basins, and pedagogical investigations of nonlinear dispersive wave dynamics. The solver is validated through four progressively complex idealized scenarios motivated by oceanic wave dynamics: isolated soliton propagation, symmetric interactions, overtaking collisions, and three-body interactions. High-fidelity conservation of mass, momentum, and energy is demonstrated, with relative errors remaining below $\mathcal{O}\left({10}^{-4}\right)$ across all test cases. Measured soliton velocities align with theoretical predictions within 5%, confirming the capture of the amplitude-dependent dispersion characteristic of oceanic solitary waves. Complementary diagnostics, including spectral entropy and recurrence quantification analysis (RQA), verify that the numerical solutions preserve the regular phase-space structure characteristic of integrable Hamiltonian systems. These results establish sangkuriang as a robust, lightweight platform for reproducible numerical investigation of idealized nonlinear dispersive wave dynamics relevant to coastal and ocean engineering applications.

Turbidity serves as a crucial indicator of coastal water health and productivity. Twenty years of remote sensing data (2003–2022) from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) satellite were used to analyze the spatial and temporal variations in turbidity, as measured by total suspended matter (TSM), in the Berau Coastal Shelf (BCS), East Kalimantan, Indonesia. The BCS encompasses the estuary of the Berau River and is an integral part of the Coral Triangle, renowned for its rich marine and coastal habitats, including coral reefs, mangroves, and seagrasses. The aim of this research is to comprehend the seasonal and interannual patterns of turbidity and their associations with met-ocean parameters, such as wind, rainfall, and climate variations like the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). The research findings indicate that the seasonal spatial pattern of turbidity is strongly influenced by monsoon winds, while its temporal patterns are closely related to river discharge and rainfall. The ENSO and IOD climate cycles exert an influence on the interannual turbidity variations, with turbidity values decreasing during La Niña and negative IOD events and conversely increasing during El Niño and positive IOD events. Furthermore, the elevated turbidity during negative IOD and La Niña coincides with rising temperatures, potentially acting as a compound stressor on marine habitats. These findings significantly enhance our understanding of turbidity dynamics in the BCS, thereby supporting the management of marine and coastal ecosystems in the face of changing climatic and environmental conditions.

In multi-hazard environments, women’s social reproductive labor often constitutes a foundation of community survival, yet remains undertheorized in disaster scholarship. This study contributes to an active scholarly conversation by examining Daya Annisa, a women-led grassroots organization in Bantul Regency, Yogyakarta, Indonesia, a region under continuous geological stress from the Sunda Megathrust, the Opak Fault, and Mount Merapi. Drawing on in-depth interviews and focus group discussions analyzed through Social Reproduction Theory (SRT), with a Strengths, Weaknesses, Opportunities, and Threats (SWOT) framework reinterpreted as an analytical lens on the structural conditions of reproductive labor, the analysis traces four interlinked practices: preparedness embedded in arisan and pengajian gatherings, community-based vulnerability mapping, trust-based crisis response, and informal post-disaster livelihoods. The paper argues that resilience in such settings is best understood not as a passive capacity to absorb shocks, but as the active, gendered, and largely uncompensated labor through which communities are materially sustained when formal systems are stretched. Three policy shifts follow: long-term flexible funding calibrated to continuous reproductive preparedness; institutional integration of community-generated vulnerability data with appropriate privacy and inclusion safeguards; and inclusion of grassroots women’s organizations as autonomous decision-making actors in disaster governance.

Title: Numerical Simulations Using Various Models for Tsunamis Due to a Fluid or Rigid Bodies Falling Down a Uniform Slope | Keywords: tsunami, landslide, rigid body, numerical simulation, hydraulic experiment | Author: Taro Kakinuma, Mitsuru Yanagihara, Tsunakiyo Iribe, Kuninori Nagai, Chisato Hara, Natsuki Hamada, Tatsuya Nakagaki, Karina Aprilia Sujatmiko, Ikha Magdalena, Kaori Nagai, Rika Kannonji, Songgui Chen, Tomoki Shirai, and Taro Arikawa

Collective motion in fish schools exemplifies emergent self-organization, yet computational tools for simulating these dynamics remain fragmented. We present Dewi-Kadita , an open-source Python library implementing the three-dimensional Couzin zone-based model with comprehensive entropy diagnostics tailored for marine collective behavior research. The library introduces seven information-theoretic metrics—school cohesion entropy, polarization entropy, depth stratification entropy, angular momentum entropy, nearest-neighbor entropy, velocity correlation entropy, and school shape entropy—that characterize organizational features inaccessible to classical order parameters. These combine into a heuristic oceanic schooling index (OSI), providing a single scalar descriptor of collective disorder for exploratory use. Illustrative simulations across four canonical configurations (swarm, torus, dynamic parallel, highly parallel) reproduce three phase behaviors: the swarm maintains disorder (polarization P < 0.1 , OSI ≈ 0.71 ), while the highly parallel state achieves alignment ( P = 0.998 , OSI = 0.24 ) with vanishing velocity correlation entropy. The torus configuration exhibits partial decay toward alignment, consistent with known finite-size effects in periodic domains; we offer this interpretation as the most plausible mechanism, and the library exposes the domain-size parameter for direct user verification. The entropy framework successfully discriminates the torus and dynamic parallel configurations, which exhibit comparable order parameter magnitudes through different organizational mechanisms. Numba just-in-time compilation accelerates pairwise interactions by 10 – 100 × , enabling simulations of 150 – 250 agents over 1000 – 2000 time steps within five minutes on standard workstations. NetCDF4 output ensures interoperability with oceanographic analysis tools. The library addresses the need for standardized, reproducible infrastructure in collective behavior modeling analogous to molecular dynamics codes. The presented simulations are purely idealized; quantitative application to empirical schooling data requires future species-specific calibration and validation.