Selective incorporation of trend into seasonal streamflow climatology

Abstract

Probabilistic climatology forecasts of seasonal streamflow up to 12 months ahead are incredibly useful for water resource planning, informing risk-based management strategies. However, the assumption of a stationary distribution for such climatology forecasts fails to account for observed trends present in many streamflow gauge records, which can result in unnecessary bias and excessive spread in the forecasts. For example, where drying trends have led to reduced flow, water resources may be overestimated based on a higher historical mean flow. While trended climatology forecasts are sometimes far better than un-trended climatology forecasts, most of the time they are worse, in part due to t..