Water quality and hydrochemical assessments of thermal springs, Gandaki Province, Nepal.

Thermal springs are the sites where the water temperature lies above ambient temperature. They are widely used for power generation, hot water spas, balneotherapy, agriculture, laundering, and aquaculture. In Nepal, many thermal springs are reported but scientific understanding on water quality and hydrogeochemistry of the springs is very limited. In this study, a total of 28 physico-chemical parameters were measured in water samples collected from 12 thermal springs from Gandaki Province, Nepal. Correlation matrix and multivariate statistical analysis such as principal component analysis (PCA) and cluster analysis were used to understand the water quality and hydrogeochemistry of the hot water springs. The pH, temperature, electrical conductivity, total dissolved solids, and turbidity in the hot water springs ranged from 7.3 to 8.8, 31.6-64.3 °C, 206-16270 µS/cm, 115-6637 mg/L, and 0.21-63.7 NTU; respectively. The dominance order of major anions and cations were: Cl- > HCO3- > SO42- > NO3- > F- and Na+ > Ca2+ > K+ > Mg2+; respectively. Comparison of the water quality parameters with the WHO and National Water Quality Standards suggested that the majority of the parameters were within the safe limit. Out of 9 heavy metals and trace elements analyzed Zn2+, Ni2+, Cr3+, Cd+2, Hg (total), and Pb2+ were found below the safe limit but Fe (total), As (total) and Cu (total) were found higher than the WHO safe limit in total of 3, 5 and 1 sampling sites; respectively. The water quality index (WQI), sodium absorption ratio (SAR), and magnesium hazard (MH) ratio in the hot water springs ranged from 40.9 to 573, 2.2-49.3, 7.1-70.8; respectively. The result of PCA analysis showed that four principal components are required to explain hydrogeochemistry. Cluster analysis suggested that the sampling sites can be grouped into three distinct clusters based on total dissolved solids. Interestingly, the classification of hydrochemical facies using a Piper diagram suggested that 7 out of 12 thermal springs have Na-Cl type water. Finally, a perspective on the suitability of the hot springs for hot water spas and balneotherapy and policy recommendation is provided.

Determinants of Herpetofaunal Diversity in a Threatened Wetland Ecosystem: A Case Study of the Ramaroshan Wetland Complex, Western Nepal.

Wetlands are among the highly threatened ecosystems due to anthropogenic activities. The Ramaroshan Wetland Complex (RWC) of Achham District, Nepal is one of the high-altitude wetlands facing human induced degradation and loss. Herpetofauna are key bio-indicators of environmental health and habitat quality and are useful to assess habitat conditions of such threatened ecosystems. This study quantified the land use and land cover (LULC) change in the RWC and documented the diversity and distribution pattern of herpetofauna. The LULC in the area (13.94 Km2) was analyzed for 1989, 2000, 2010 and 2021 by supervised classification of remote sensing images. Surveys were conducted along 25 transects, each of 200 m in length and environmental variables were recorded for every observation of herpetofauna. The LULC analysis revealed an overall loss of 16% of the total water body between 1989 (0.25 Km2) and 2021 (0.21 Km2). Eleven species of herpetofauna (five amphibians and six reptiles) within five families and two orders (i.e., Anura and Squamata), were recorded with low diversity (H' = 1.88312) and evenness (E = 0.3642) indices. The herpetofauna had a hump-shaped distribution along the elevation gradient with the highest richness and abundance at 2300 m asl. Amphibian abundance decreased with increasing distance to nearest water sources, whereas reptile abundance increased. Amphibians were more abundant in agricultural field and marsh land, whereas reptile abundance was higher around human settlements. Results indicate that the wetland area in the RWC is declining at an alarming rate and, in turn, might account for the low diversity and abundance of the herpetofauna.

Sinkhole susceptibility mapping in Marion County, Florida: Evaluation and comparison between analytical hierarchy process and logistic regression based approaches.

Sinkholes are the major cause of concern in Florida for their direct role on aquifer vulnerability and potential loss of lives and property. Mapping sinkhole susceptibility is critical to mitigating these consequences by adopting strategic changes to land use practices. We compared the analytical hierarchy process (AHP) based and logistic regression (LR) based approaches to map the areas prone to sinkhole activity in Marion County, Florida by using long-term sinkhole incident report dataset. For this study, the LR based model was more accurate with an area under the receiver operating characteristic (ROC) curve of 0.8 compared to 0.73 with the AHP based model. Both models performed better when an independent future sinkhole dataset was used for validation. The LR based approach showed a low presence of sinkholes in the very low susceptibility class and low absence of sinkholes in the very high susceptibility class. However, the AHP based model detected sinkhole presence by allocating more area to the high and very high susceptibility classes. For instance, areas susceptible to very high and high sinkhole incidents covered almost 43.4% of the total area under the AHP based approach, whereas the LR based approach allocated 20.7% of the total area to high and very high susceptibility classes. Of the predisposing factors studied, the LR method revealed that closeness to topographic depression was the most important factor for sinkhole susceptibility. Both models classified Ocala city, a populous city of the study area, as being very vulnerable to sinkhole hazard. Using a common test case scenario, this study discusses the applicability and potential limitations of these sinkhole susceptibility mapping approaches in central Florida.