TY - JOUR
T1 - Land cover and water yield
T2 - Inference problems when comparing catchments with mixed land cover
AU - Van Dijk, A. I.J.M.
AU - Peña-Arancibia, J. L.
AU - Bruijnzeel, L. A.
PY - 2012
Y1 - 2012
N2 - Controlled experiments provide strong evidence that changing land cover (e.g. deforestation or afforestation) can affect mean catchment streamflow (Q). By contrast, a similarly strong influence has not been found in studies that interpret Q from multiple catchments with mixed land cover. One possible reason is that there are methodological issues with the way in which the Budyko framework was used in the latter type studies. We examined this using Q data observed in 278 Australian catchments and by making inferences from synthetic Q data simulated by a hydrological process model (the Australian Water Resources Assessment system Landscape model). The previous contrasting findings could be reproduced. In the synthetic experiment, the land cover influence was still present but not accurately detected with the Budyko- framework. Likely sources of interpretation bias demonstrated include: (i) noise in land cover, precipitation and Q data; (ii) additional catchment climate characteristics more important than land cover; and (iii) covariance between Q and catchment attributes. These methodological issues caution against the use of a Budyko framework to quantify a land cover influence in Q data from mixed land-cover catchments. Importantly, however, our findings do not rule out that there may also be physical processes that modify the influence of land cover in mixed land-cover catchments. Process model simulations suggested that lateral water redistribution between vegetation types and recirculation of intercepted rainfall may be important.
AB - Controlled experiments provide strong evidence that changing land cover (e.g. deforestation or afforestation) can affect mean catchment streamflow (Q). By contrast, a similarly strong influence has not been found in studies that interpret Q from multiple catchments with mixed land cover. One possible reason is that there are methodological issues with the way in which the Budyko framework was used in the latter type studies. We examined this using Q data observed in 278 Australian catchments and by making inferences from synthetic Q data simulated by a hydrological process model (the Australian Water Resources Assessment system Landscape model). The previous contrasting findings could be reproduced. In the synthetic experiment, the land cover influence was still present but not accurately detected with the Budyko- framework. Likely sources of interpretation bias demonstrated include: (i) noise in land cover, precipitation and Q data; (ii) additional catchment climate characteristics more important than land cover; and (iii) covariance between Q and catchment attributes. These methodological issues caution against the use of a Budyko framework to quantify a land cover influence in Q data from mixed land-cover catchments. Importantly, however, our findings do not rule out that there may also be physical processes that modify the influence of land cover in mixed land-cover catchments. Process model simulations suggested that lateral water redistribution between vegetation types and recirculation of intercepted rainfall may be important.
UR - http://www.scopus.com/inward/record.url?scp=84867532173&partnerID=8YFLogxK
U2 - 10.5194/hess-16-3461-2012
DO - 10.5194/hess-16-3461-2012
M3 - Article
SN - 1027-5606
VL - 16
SP - 3461
EP - 3473
JO - Hydrology and Earth System Sciences
JF - Hydrology and Earth System Sciences
IS - 9
ER -