Earth

The Seulawah Agam volcano, located in Aceh, hosts one of Indonesia’s largest unexploited geothermal resources that is included in the Indonesian Green Energy Program. Previous studies of the Seulawah geothermal system (SGS) have used partial data and methods without developing a comprehensive conceptual model of the reservoir and its fluid flow and heat transfer patterns. This study aims to characterize the groundwater flow and heat transfer patterns of the SGS through numerical modeling based on integrated geological, geophysical, and geochemical data. Numerical modeling was conducted along two representative transects: Ie Seum, Ie Jue, and Kawah van Heutsz manifestations. MODFLOW 6 was used to model groundwater flow and heat transfer using a new conceptual model derived from magnetotelluric data, chemical composition and physical properties of the fluid, isotopic data, and mineragraphic data. The low resistivity anomalies are closely related to fluid discharges beneath the Ie Seum and Ie Jue areas. The depth of the Ie Seum reservoir is around 1.0–2.5 km, with estimated temperatures of 120–242 °C, while the depth of the Ie Jue and Kawah van Heutsz reservoirs is between 0.8 and 2.5 km, with estimated temperatures of 150–316 °C. The modeling suggests that the Ie Seum and the Ie Jue–Kawah van Heutsz systems represent regional groundwater and intermediate-local flow regimes, respectively. It is suggested that drilling be conducted around the local Ie Jue hydrothermal system, which is more economical given the shallower reservoir and higher temperature.

Hazard risk monitoring of groundwater depletion and land subsidence due to excessive groundwater extraction is crucial for groundwater resource development, especially in densely populated, small-island developing sites. The island of Bali, Indonesia, represents such an urban environment at risk of land subsidence arising from groundwater depletion. The total percentage of groundwater depletion was calculated and interpolated spatially using measurements of groundwater level from 2008 to 2017 at 18 monitoring well sites available in the area. Furthermore, time-series synthetic-aperture radar (SAR) interferometry processing was applied to estimate the temporal change in land displacement using the Phased Array type L-band SAR (PALSAR) data from 2007 to 2010. The result of downward displacement, signifying subsidence, corresponded with the Global Navigation Satellite System (GNSS) data measurements at stations distributed in the observed subsided areas, i.e., CDNP and CPBI. The displacement varied consistently with changes in groundwater level. In regard to maintaining groundwater utilization, the hazard–risk relation of the groundwater depletion, i.e., low (<10%), moderate (10–25%), and high (>25%), and the presence/absence of subsidence were utilized to classify groundwater conservation into safe, vulnerable, critical, and damaged zones. This application can be considered effective in providing spatial information for sustainable groundwater management.

Multi-criteria methods are widely used in sustainability assessments because of their ability to handle large and complex datasets. The MIVES method (Integrated Value Model for Sustainability Assessment) has proven to be a versatile and adaptable tool that can be applied to both products and services across a variety of research fields. However, evidence of its integration with other analytical tools is still limited. This study combines the MIVES method with Geographic Information Systems (GIS) to evaluate the sustainability of tourism activities in seven destinations in southern Costa Rica, all located near national parks and nature reserves. First, a MIVES-based model was designed to compute sustainability indices across environmental, economic, and social dimensions, using thirteen normalized and weighted indicators. These calculations produced specific sustainability values for each destination analyzed. The results were then integrated into GIS using ArcGIS Pro 3.6, representing each requirement and indicator as a geographic layer with the corresponding sustainability value. This made it possible to create spatial maps that visually identify the destinations best positioned within the protected natural areas in terms of sustainability, as well as the indicators that most strongly influence each site’s performance—positively or negatively. The destinations that received the highest sustainability scores were Ojochal, La Palma, Puerto Jiménez, and Carate–Matapalo, with averages ranging from 60% to 61%, while Bahía Drake, Bahía Ballena, and Sierpe showed the lowest values, averaging between 58% and 59%. Of the three domains, the social dimension received the highest evaluation, followed by the environmental dimension and, finally, the economic dimension. Overall, all destinations achieved satisfactory sustainability levels, with an overall mean index of 0.60. The visual representation of results simplifies interpretation and serves as a valuable tool to support decision-making for sustainable tourism management.