Natural hazard risk assessment generally focuses on a single hazard type, such as earthquakes, landslides, or floods. This emphasis tends to consider physical processes in isolation. However, most locations are simultaneously at risk to multiple, interacting hazards that generate cascading effects or synergies. Although scholars have proposed a multi-hazard risk framework based on probabilities, the quality and quantity of data required for such an approach are often unavailable in developing countries. Using geospatial and socioeconomic data, this study represents a first step in assessing multi-hazard risk in the city of Dharan, Nepal. Three hazards—landslides, floods, and earthquakes—were considered for an integrated hazard assessment using statistical methods and the Analytic Hierarchy Process (AHP). We employed a Social Vulnerability Index (SoVI) to create a vulnerability map of the study area, which was then combined with a multi-hazard hazard map to produce a total risk map. Our results indicate that eastern Dharan along the Seuti River and southwestern Dharan on the left bank of the Sardu River are at high risk to multiple hazards. Central Dharan and the hills in the western portion of the city are categorized as low risk areas. Data limitations, such as availability and spatial resolution, did not allow for dynamic modeling; however, our results identified the spatial extent of low to high risk areas, which can inform future disaster planning. For example, the methodology and results of this study could assist in the development of disaster risk reduction programs and policies.

The impacts of natural hazards are typically measured in terms of loss of human lives and economic damage, and recent studies demonstrate that deaths attributed to natural hazards have increased. Using the publicly available DesInventar database, we examined spatial and temporal patterns of natural hazard mortality from 1971 to 2011 at the district and village levels of Nepal and identified natural hazards that contributed most to mortality. Spatial clusters of mortality at the district and village levels were detected using local and global spatial autocorrelation measures (Moran's I). Landslides (41.91%) and floods (32.52%) accounted for approximately three quarters of natural hazard mortalities over the study period. A Global Moran's I test positively confirmed clustering at both the district (0.199, p < .001) and village (0.256, p < .001) levels, whereas a Local Moran's I test further detected clustering in the central and terai regions, where dynamic geologic and geomorphic processes combined with human-environment interaction constitute major risk factors. A better understanding of multihazard mortality patterns across geographic landscapes and time has the potential to aid policy makers, planners, and local officers to more efficiently allocate scarce capital and human resources to reduce mortality.

This article presents a modified water poverty index that captures several waterscape attributes to better understand complex issues surrounding water. Household surveys (n = 300), water quality tests (n = 375) and qualitative methods were deployed to examine 14 post-tsunami settlements in Nagapattinam and Karaikal Districts (India) through the lens of water. Data were used to develop a contextualized, participant-driven water poverty index to measure water poverty at several scales. Statistical tests revealed significant differences between the two districts (p ≤ .0001) and between rural and urban areas within each district (p ≤ .0001). Three weight schemes (one dictated entirely by research participants) produced analogous outcomes though predicated on different indicator arrangements.

This article scrutinizes the boiling of water in Tamil Nadu and Puducherry, India. Boiling, as it is commonly practiced, improves water quality, but its full potential is not being realized. Thus, the objective is to refine the method in practice, promote acceptability, and foster the scalability of boiling and household water treatment (HWT) writ large. The study is based on bacteriological samples from 300 households and 80 public standposts, 14 focus group discussions (FGDs), and 74 household interviews. Collectively, the data fashion both an empirical and ethnographic understanding of boiling. The rate and efficacy of boiling, barriers to and caveats of its adoption, and recommendations for augmenting its practice are detailed. While boiling is scientifically proven to eliminate bacteria, data demonstrate that pragmatics inhibit their total destruction. Furthermore, data and the literature indicate that a range of cultural, economic, and ancillary health factors challenge the uptake of boiling. Fieldwork and resultant knowledge arrive at strategies for overcoming these impediments. The article concludes with recommendations for selecting, introducing, and scaling up HWT mechanisms. A place-based approach that can be sustained over the long-term is espoused, and prolonged exposure by the interveners coupled with meaningful participation of the target population is essential.

This study provides high-resolution modeling of daily water budget components at Hydrologic Unit Code (HUC)-12 resolution for 50 watersheds of the South Atlantic Gulf (SAG) region in the southeastern U.S. (SEUS) by implementing the Soil and Water Assessment Tool (SWAT) model in the form of a near real-time, semi-automated framework. A near real-time hydrologic simulation framework is implemented with a lead time of nine months (March–December 2017) by integrating the calibrated SWAT model with National Centers for Environmental Prediction coupled forecast system model version 2 (CFSv2) weather data to forecast daily water balance components. The modeling exercise is conducted as a precursor for various future hydrologic studies (retrospective or forecasting) for the region by providing a calibrated hydrological dataset at high spatial (HUC-12) and temporal (1-day) resolution. The models are calibrated (January 2003–December 2010) and validated (January 2011–December 2013) for each watershed using the observed streamflow data from 50 United States Geological Survey (USGS) gauging stations. The water balance analysis for the region shows that the implemented models satisfactorily represent the hydrology of the region across different sub-regions (Appalachian highlands, plains, and coastal wetlands) and seasons. While CFSv2-driven SWAT models are able to provide reasonable performance in near real-time and can be used for decision making in the region, caution is advised for using model outputs as the streamflow forecasts display significant deviation from observed streamflow for all watersheds for lead times greater than a month.