Ch.3. Precipitation  The significance of precipitation data? Basis for all the hydrological evaluation  The T-  18 O Correlation in Precipitation For.

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Presentation transcript:

Ch.3. Precipitation  The significance of precipitation data? Basis for all the hydrological evaluation  The T-  18 O Correlation in Precipitation For global average (Dansgaard, 1964), ○  18 O = 0.695T – 13.6‰ VSMOW ○  D = 5.6T-100 ‰ VSMOW ○  18 O = (0.338 ± 0.028) T monthly – ‰ VSMOW Yutsever and Gat (1981) ○ The deviation from it caused by local geographic effect

Fig. 3-1 The mean annual d18O-values for precipitation as a function of theglobal T–d18O relationship for precipitation, modified from Dansgaard, 1964 (left). Temperature is mean annual air temperature (MAAT) of the sampling station (modified from Dansgaard, 1964at the station. Data from the extensive IAEA Global Network for Isotopes in Precipitation (GNIP) shows this relationship to be a combination of regional T–d18O lines, with strong differences between marine, continental and interior stations, from Rozanski et al., 1993 (diagram on right).

Latitude effect ○ Due rain out w/ Rayleigh distillation ○ The gradient become increasingly steep as latitude increases ○ Very shallow gradients in lower latitude ○ Note the ocean current and ‘continental effect’.

Fig. 3-2 Mean d 18 O distribution in precipitation on a global basis, for stations with at least 24 months of records. (based on IAEA World Meteorological Precipitation monitoring data summarized by Rozanski et al., 1992).

Continental effect ○ Due to regional topographic and climatic effect ○ Depleted as going from coast to the inland area ○ Strong seasonal variation ○ Continentality (Berry & Chorley, 1987), k: To measure the regional geographic parameters influencing rainout

 Local Effects on T-  18 O Dependent on the local physiographical setting, including local topography, proximity to surface water bodies, seasonal changes etc. Altitude effects

Fig. 3-6 The relationship between altitude and d 18 O in precipitation in Val Corsaglia, maritime piedmont of the Italian Alps (Bortolami, 1978). Samples were collected in October 1974 and April 1976, representing months of the fall and spring seasons with similar mean monthly temperatures. The mean gradient for these data is –0.31 ‰ d 18 O per 100-m rise.

SiteRegionAltitude (m asl)Gradient (‰ per 10 0 m) Reference d 18 O d2Hd2H Jura MountainsSwitzerland –0.2Siegenthaler et al.,, 1983 Black ForestSwitzerland –0.19Dubois and Flück, 1984 Mont BlancFrance –0.5 * –4 Moser and Stichler, 1970 Coast MountainsBritish Columbia –0.25Clark et al., 1982 PiedmontWestern Italy –0.31–2.5Bortolami, 1978 Dhofar MonsoonSouthern Oman0-800–0.10Clark, 1987 Saiq PlateauNorthern Oman –0.20Stanger, 1986 Mount CamerounWest Africa0-4095–0.155Fontes et al., 1977 Table 3-1 Range of values for the  18 O-elevationaltitude gradient in different studies

Seasonal effect ○ Due to the seasonal variation in T ○ Can be utilized for Rates of gw circulation Watershed respond to pptn Time of most recharge

Condensation of coastal fog ○ The isotopic composition of the precipitation become quite close to that of sea water

The kinetic effect of secondary evaporation ○ Surface water & groundwater above LMWL? Fig Secondary evaporation effects causing meteoric waters to plot above the LMWL. A — Re-evaporation of local groundwaters in Kenya. (modified from Ingraham and Matthews, 1988). B — Evaporation of local surface waters in the northern Yukon condensing as cave ice in fossil karst terrain. In both cases, the condensed phase is in equilibrium with the vapour (equilibrium fractionation during condensation) and so plots on a line with slope ~ 8.

 Ice cores & Paleotemperature