Assessment of spring water quality of Khandbari Municipality in Sankhuwasabha District, Eastern Nepal.

The study was carried out in the Khandbari Municipality, Sankhuwasabha District, Eastern Nepal to document the spring location and assess the water quality of the spring water for drinking and irrigation purposes. A total of 85 springs were mapped, which are located from 274 to 2176 m in altitude. Spring water samples were collected from 33 springs in the pre-monsoon (November, 2021) and 31 springs in the post-monsoon (March, 2022). Correlation matrices, t-test, principal component analysis (PCA), Piper diagram, Gibbs diagram, water quality index (WQI), United States Salinity Laboratory (USSL) diagram, and Wilcox diagram were applied for evaluating the spring water. All the physicochemical parameters were within the Nepalese National Drinking Water Quality Standard (NDWQS) and drinking water quality guidelines of the World Health Organization (WHO) except for pH in the pre-monsoon and iron in the post-monsoon season. The main contributors to the groundwater are Na+, Ca2+, Cl-, total dissolved solids (TDS), and total hardness, which exhibit significant correlations with electrical conductivity (EC) similar to TDS, suggesting their common source of origin. Based on the WQI, spring water is excellent in the post-monsoon and excellent and good in the pre-monsoon season. Furthermore, the spring water is excellent for irrigation purposes except for the percent sodium in the post-monsoon and the magnesium ratio in the pre-monsoon season. Gibbs diagram illustrates that spring water is mainly governed by rock and precipitation dominance in some springs. The PCA indicates that anthropogenic activities (mixing of human waste and agricultural run-off in the spring water) are the main causes of contamination. Piper trilinear diagram demonstrates carbonate dissolution and silicate weathering as major processes for controlling the spring water chemistry. The study reveals that 62.5% of spring water was contaminated with microbes. For benthic macroinvertebrates, 18 springs were sampled, where nine orders and 17 families were recorded in the pre-monsoon and six orders and ten families in the post-monsoon season. The main influencing variables for macroinvertebrate assemblages are elevation, discharge, NO3-, and NH3.

Application of deep neural network to capture groundwater potential zone in mountainous terrain, Nepal Himalaya.

This study aims to capture groundwater potential zones integrating deep neural network and groundwater influencing factors. The present work was carried out for Gopi khola watershed, mountainous terrain in Nepal Himalaya as the watershed mainly relies upon the groundwater assets; it is a need to explore groundwater potential for better management of the aquifer framework. Ten groundwater influencing factors were collected such as elevation, slope, curvature, topographic positioning index, topographic roughness index, drainage density, topographic wetness index, geology, lineament density, and land use thematic layers. Among those influencing factors, topographic roughness index was removed because of multicollinearity issue to reduce the dimension of the dataset. A spring inventory map of 145 spring locations was prepared using field survey method and an equal number of spring absence points were randomly generated. The 70% of spring and spring absence pixels were used as training dataset and remaining as test dataset. The final map was created based on predicted probabilities ranging from 0 to 1. The validation was done using the receiver operating characteristic curve, which shows that the area under the curve is 76.1% for the training dataset and 82.1% for the test dataset. The sensitivity analysis was performed using Jackknife test which shows that the lineament density is the most important factor. The experimental results demonstrated that deep neural network is highly capable to capture groundwater potential zone in mountainous terrain. The present study might be useful and preliminary work to exploit the groundwater. The consequences of the current study may be valuable to water administrators to settle on appropriate choices on the ideal utilization of groundwater assets for future arranging in the basic investigation zone.