This work aimed to analyze the soil quality and heavy metal contamination in the Jumar watershed of Jharkhand and suggests possible measures that could be taken to guarantee suitable management practices. Therefore, in the present work, the soil sampling was done at 8 locations, selected based on site visit. The GPS coordinates of the sampling sites were noted. The soil samples were collected during pre-monsoon and post-monsoon seasons for 2017 and 2018 at a depth of 20 cm from the top. Water samples were collected from the river flowing closer to the sampling points. Then, soil quality parameters such as pH; electrical conductivity; bulk density; moisture content; and surface water quality parameters such as pH, EC, TDS, DO, COD, BOD, alkalinity, turbidity, and nutrients (N & P) were studied. For heavy metal analysis (Pb, Zn, Cu, As, Ni), both soil and water samples were analyzed using an inductive coupled plasma-optical emission spectrophotometer (ICP-OES). Statistical tools like descriptive statistics, multivariate analysis, principal component analysis, correlation coefficient, and ANOVA were applied using SPSS version 21. The data indicate that the values of moisture content varied between 22.06 and 45.7%, soil bulk density varied between 1.20 and 1.55 g/cm 3 , pH varied between 7.79 and 8.17, and EC varied between 116.66 and 207.08 μS/cm. The concentrations of heavy metals in the pre-monsoon season were higher (Zn 0.183 mg/l, Cu 0.09 mg/l, Ni 0.061 mg/l) than those in the post-monsoon season (Zn 0.17 mg/l, Cu 0.076 mg/l, Ni 0.138 mg/l). The water quality index found using pH, EC, TDS, DO, COD, BOD, alkalinity, turbidity, BOD, COD, nutrients, and heavy metals indicated that most sites had excellent water quality, especially in the pre-monsoon period. But in the post-monsoon period of 2017, the water quality index showed that water was in poor condition. Overall water quality was found to be good. It was found that the soil had very slight traces of heavy metals and was slightly alkaline indicating the need for better watershed management practices for the future. PCA showed that the component variables like pH and EC were principal components specially for both pre-monsoon seasons, whereas through ANOVA, it was found that the variable has strong relationship among themselves.