Impact of climate variation and change on Mid-Atlantic Region hydrology and water resources

Citation
R. Neff et al., Impact of climate variation and change on Mid-Atlantic Region hydrology and water resources, CLIMATE RES, 14(3), 2000, pp. 207-218
Citations number
42
Categorie Soggetti
Environment/Ecology
Journal title
CLIMATE RESEARCH
ISSN journal
0936577X → ACNP
Volume
14
Issue
3
Year of publication
2000
Pages
207 - 218
Database
ISI
SICI code
0936-577X(20000502)14:3<207:IOCVAC>2.0.ZU;2-S
Abstract
The sensitivity of hydrology and water resources to climate variation and c limate change is assessed for the Mid-Atlantic Region (MAR) of the United S tates. Observed streamflow, groundwater, and water-quality data are shown t o vary in association with climate variation; Projections of future streamf low, groundwater, and water quality are made using models determined from t hese associations and are applied to 2 transient general circulation model (GCM) scenarios. Regional streamflow increases in one scenario, but decreas es in the other; both scenarios result in changes in the seasonality of pea k flows. Response of groundwater to climate change depends on the GCM scena rio used. Canadian Climate Center (CCC) scenarios suggest recharge will occ ur earlier in the year, and that seasonal fluctuations in groundwater level s will be less extreme. Hadley Center scenarios suggest recharge will occur earlier in the medium term, but later in the long term, with seasonal fluc tuations in general being more extreme. Both scenarios show that nutrient l oads can be expected to increase in winter and spring because of the expect ed increase in streamflow. Projected decreases in streamflow and associated nutrient fluxes in July and August could ameliorate problems associated wi th estuarine stratification and eutrophication in late summer. These projec tions demonstrate that future hydrology and water resources will be influen ced by climate change, but that uncertainty in accurately projecting that i nfluence will continue until model scenarios improve.