The Inverse Distance Weight (IDW), Spline, and Ordinary Kriging (OK) methods are widely used for interpolating spatial data. Many GIS software options are available, particularly for spatial interpolation. This study aims to assess the accuracy of interpolation approaches based on Climate Hazards Group Infrared Precipitation with Station (CHIRPS) data in ArcGIS 10.8. The research used monthly precipitation data extracted from 147 rain gauge station locations in North Sumatra Province. Additionally, eight stations from BMKG's network were excluded from the interpolation process and instead used as validation data. Validation was conducted by calculating error statistics between the predicted and actual data at these excluded points. The predicted data was generated by interpolating values from the 147 rain gauge stations, excluding the eight points corresponding to the validation data locations. The interpolation was done using ArcGIS 10.8 with the IDW, Spline, and Kriging toolbox. A comparison was performed by assessing error parameters and Pearson correlation coefficients. According to the accuracy assessment, both IDW and OK show comparable performance; both are better than spline interpolation. In addition, the box plot chart demonstrated that the spline technique had a tendency to generate outlier values along the perimeters of the study area.

The Choushui River groundwater basin (CRGB) in Yunlin County, Taiwan, is a significant groundwater source for the western part of the region. However, increasing groundwater demand and human activities have triggered a potential crisis due to overexploitation. Therefore, groundwater potential zone (GWPZ) maps are crucial for mapping groundwater resources and water resource management. This study employs the normalized index–overlay method and fuzzy extended analytical hierarchy process (FE-AHP) to map GWPZs cost-effectively. The methodology objectively incorporates weightings from various thematic layers by normalizing and correlating parameters with observed groundwater availability (GA). Site-specific observations, including aquifer thickness, depth to the groundwater level, and porosity, inform GA calculations. Seven comprehensive layers derived from remote sensing (RS) data are processed to obtain weightings and ratings for the groundwater potential index (GWPI) in the CRGB. Selected parameters are categorized into hydrological processes, human interventions, geological, and surface profiles. Hydrological processes include precipitation, modified normalized difference water index (MNDWI), and drainage density. Human interventions consist of the enhanced vegetation index (EVI) and normalized difference building index (NDBI). Surface profiles encompass the terrain ruggedness index (TRI) and slope, enhancing the study’s multi-criteria approach. The observed GA validates the GWPZ accuracy, classifying zones into five categories. According to the GWPI of FE-AHP, about 59.56% of the CRGB area can be categorized as “moderate” to “very good” potential groundwater recharge zones. Pearson’s correlation coefficient between GWPI and GA, based on FE-AHP, outperforms the conventional AHP. This RS-based approach efficiently evaluates GA in aquifers with limited wells, highlighting crucial zones in CRGB’s proximal-fan and southeastern mid-fan for informed groundwater management strategies.

The scarcity of groundwater and precipitation stations has limited accurate assessments of basin-scale groundwater systems. This study proposes a workflow that integrates satellite and on-site observations to improve the spatial and temporal resolution of the groundwater level and enable recharge estimations for the Choushui River groundwater basin (CRGB) in Western Taiwan. The workflow involves multiple data processing steps, including analysis of correlation, evaluation of residuals, and geostatistical interpolation based on kriging methods. The observed groundwater levels and recharge are then the basis to assess spatial-temporal interactions between groundwater and recharge in the CRGB from 2006 to 2015. Results of correlation analyses show the high correlation between the groundwater level and the land surface elevation in the study area. However, the multicollinearity problem exists for the additional precipitation data added in the correlation analyses. The correlation coefficient, root mean square error, and normalized root mean square parameters indicate that the Regression Kriging (RK) performs better the groundwater variations than the Ordinary Kriging (OK) dose. The data-driven approach estimates an annual groundwater recharge of approximately 1.40 billion tons, representing 37% of the yearly precipitation. The correlation between groundwater levels and groundwater recharge exhibits low or negative correlation zones in the groundwater basin. These zones might have resulted from multipurpose pumping activities and the river and drainage networks in the area. The event-based precipitation and groundwater level have shown strong recharge behavior in the low-land area of the basin. Artificial weir operations at the high-land mountain pass might considerably influence the groundwater and surface water interactions.

This study aims to explore the contrasting characteristics of large-scale circulation that led to the precipitation anomalies over the northern parts of Sumatra Island. Further, the impact of varying the Asian–Australian Monsoon (AAM) was investigated for triggering the precipitation variability over the study area. The moisture budget analysis was applied to quantify the most dominant component that induces precipitation variability during the JJA (June, July, and August) period. Then, the composite analysis and statistical approach were applied to confirm the result of the moisture budget. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Anaysis Interim (ERA-Interim) from 1981 to 2016, we identified 9 (nine) dry and 6 (six) wet years based on precipitation anomalies, respectively. The dry years (wet years) anomalies over the study area were mostly supported by downward (upward) vertical velocity anomaly instead of other variables such as specific humidity, horizontal velocity, and evaporation. In the dry years (wet years), there is a strengthening (weakening) of the descent motion, which triggers a reduction (increase) of convection over the study area. The overall downward (upward) motion of westerly (easterly) winds appears to suppress (support) the convection and lead to negative (positive) precipitation anomaly in the whole region but with the largest anomaly over northern parts of Sumatra. The AAM variability proven has a significant role in the precipitation variability over the study area. A teleconnection between the AAM and other global circulations implies the precipitation variability over the northern part of Sumatra Island as a regional phenomenon. The large-scale tropical circulation is possibly related to the PWC modulation (Pacific Walker Circulation).

Tornado wind often occurs in Humbang Hasudutan (Humbahas), North Sumatra. Even though the map of tornado vulnerability has constructed by The National Agency for Disaster Countermeasure (BNPB), but several regions did not yet have this map due to limited observation data. This study’s objective is to map the vulnerability of tornado in Humbahas using satellite data where the satellite data has more significant quality in area coverage and time-series data. The Composite Mapping Analysis (CMA) has been used to model the vulnerability map. There were three factors has used in this model, such as rainfall, land cover, and slope. Based on the tornado vulnerability map, there was an 802,406.24 ha area (74.63%) in Humbahas, classified as “high” risk to Tornado disaster. There was 271,945.46 ha (25.29%), which assigned as “moderate” risk. About 786.51 ha (0.07%) of the Humbahas area has a “low” risk of tornado disaster. As a result, the study area has a “moderate” to “high” risk of tornado wind disaster, then the adaption and mitigation plans need to be done in handling tornado hazard in this region.

POTENSI PANAS LAUT SEBAGAI ENERGI BARU TERBARUKAN DI PERAIRAN KEPULAUAN NUSA TENGGARA TIMUR DENGAN METODE OCEAN THERMAL ENERGY CONVERSION (OTEC)