Household-level poverty assessments and analyses of poverty dynamics in developing countries typically do not include environmental income. Using household (n = 427 in 2006, 2009 and 2012) total income panel data sets, with and without environmental income, from Nepal, we analysed the importance of environmental income in household-level poverty assessments (Foster-Greer-Thorbecke indices) and dynamics (movements in the Poverty Transition Matrix). Random effects logit and ordered logit models were applied to estimate variables covarying with poverty categories and compared for annual household incomes with and without environmental income. Using the without environmental income data set significantly changed the number of households classified as poor, as well as rates of movements in and out of poverty. Excluding household-level environmental income also distorted estimation of covariates of poverty incidence and poverty dynamics. Poverty incidence and dynamics models including environmental income perform better than those without. Rural poverty studies based on welfare measures excluding environmental income may thus be inaccurate for environmental reliant communities.