Incorporating land-use changes and surface-groundwater interactions in a simple catchment water yield model

Pressure on limited water resources and the environment requires better understanding of how landscape change impacts river flow. Rainfall-runoff models have traditionally focused on estimating total river flows with less emphasis on modelling the groundwater component or the consequences of different land-use change scenarios. In this paper, we present the GWlag model, a water-generation model that predicts river flows with explicit accounting of the impacts of catchment land-use change and surface groundwater interactions. The paper firstly describes the theory that underpins the model and its calibration then presents a case study application in the Tarcutta Creek catchment of the Murray Darling Basin, Australia. The case study aims at: (i) demonstrating the ability of the model to predict daily river flows; (ii) modelling the impacts of hypothetical plantation forestry expansions on river flows; and (iii) showing the impacts of reduced recharge on the low-flow regime using three indices, namely, Q(90)/Q(50) (where Q(n) refers to nth percentile flow), slope of low-flow part of flow duration curve, and % of zero-flow days. Results showed that predicted flows agreed favourably to those observed at the gauge especially during low-flow conditions. The hypothetical plantation expansion from 32% to 87% of the catchment area has resulted in reductions of 48% and 32%, in Q(50) and Q(20), respectively. The low-flow indices demonstrated the great sensitivity of low flow to reductions in recharge with the trend of the low-flow response changing to non-linear for recharge reductions beyond 10%. GWlag daily river flow predictions compared favourably to those obtained from four other rainfall-runoff models in terms of the Nash-Sutcliffe model efficiency (E). However, GWlag produced the highest E-value for log-transformed flows thus highlighting the model's superior predictive capability during low-flow conditions. Crown Copyright (C) 2012 Published by Elsevier Ltd. All rights reserved.