the global network of isotopes in rivers …...the global network of isotopes in rivers (gnir)...

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^ THE GLOBAL NETWORK OF ISOTOPES IN RIVERS (GNIR) INTEGRATION OF WATER STABLE ISOTOPES IN RIVERINE RESEARCH AND MANAGEMENT J. Halder, S. Terzer, L.I. Wassenaar, L.J. Araguás-Araguás, P.K. Aggarwal Isotope Hydrology Section, International Atomic Energy Agency, Vienna, Austria, [email protected] The Global Network of Isotopes in Rivers (GNIR) is a global environmental observation programme, which serves as an essential world-wide repository for riverine isotope data and facilitates public dissemination of contributed riverine isotopic data. GNIR is a complimentary programme to the IAEA’s well-established Global Network of Isotopes in Precipitation (GNIP). What is the aim of GNIR? z Collect and disseminate time-series and synoptic collections of riverine isotope data from the world’s rivers (Fig. 1); z It relies upon voluntary partnerships with institutions and researchers for riverine sample collections and isotopic analyses (Fig. 2); z GNIR is publicly accessible through the Water Isotope System for Data Analysis, Visualization and Electronic Retrieval (WISER) interface at https://nucleus.iaea.org/wiser. What can river isotope observaon tell us? z The stable isotope ratios of the water molecule ( 18 O/ 16 O, 2 H/ 1 H) are powerful recorders of river recharge sources (direct precipitation, runoff, soil water, groundwater, lakes, snow, and ice) (Fig. 3); z Long-term patterns of isotopes in rivers generally correlate with that of local precipitation but can also deviate significantly, indicating important hydrological processes (e.g. water sources mixing, evaporation) in the catchment (Figs 3 and 4); z Variations of the isotopic composition over time can trace changes in hydrological processes, but also human and environmental impacts occurring between rainfall input and river discharge (Fig. 5). Get involved in GNIR At the IAEA, we are happy to receive archived, published data, and new proposals for GNIR stations. To propose a new GNIR station, please contact the GNIR team ([email protected]). The IAEA may provide support to GNIR stations by providing bottles or by analysing water stable isotopes at the Isotope Hydrology Laboratory in Vienna. Bibliography BURGMAN, J.O., ERIKSSON, E., WESTMAN, F., Oxygen-18 variation in river waters in Sweden, unpublished report, Uppsala University (1981). HALDER, J., TERZER, S., WASSENAAR, L.I., ARAGUÁS-ARAGUÁS, L.J., AGGARWAL, P.K., The Global Network of Isotopes in Rivers (GNIR): Integration of water isotopes in watershed observation and riverine research, Hydrol. Earth Syst. Sci. (2014). KATTAN, Z., “Chemical and isotopic compositions of the Euphrates River water, Syria”, iMonitoring isotopes in rivers: Creation of the Global Network of Isotopes in Rivers (GNIR), IAEA-TECDOC-1673, Vienna (2012). MOOK, W.G., The oxygen-18 content of rivers, Mitt. Geol.-Paläont. Inst. Univ. Hamburg, SCOPE/UNEP Sonderband 52 (1982) 565–570. TALMA, S., LORENTZ, S., WOODBORNE, S., “South African contribution to the rivers CRP“, Monitoring isotopes in rivers: Creation of the Global Network of Isotopes in Rivers (GNIR), IAEA-TECDOC-1673, Vienna (2012). TERZER, S., WASSENAAR, L.I., ARAGUAS-ARAGUAS, L.J., AGGARWAL, P.K., Global isoscapes for δ 18 O and δ 2 H in precipitation: improved prediction using regionalized climatic regression models, Hydrol. Earth Syst. Sci. 17 (2013) 4713–4728. Fig. 1. GNIR Staons. The figure shows the 2730 GNIR sampling sites for water stable isotopes from 56 countries, covering all connents. The GNIR database covers rivers of all lengths and sizes, including lakes and reservoirs falling within the course of rivers. Sampling sites are either a part of synopc, longitudinal, or me-series studies. Fig. 2. GNIR sampling. Water samples are usually taken monthly as grab samples. Fig. 2 shows GNIR sampling in the Red River Delta, Viet Nam (Photo: Trinh Anh Duc). -22 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2 CC-RCWIP average δ 18 O P (‰) -22 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 GNIR average δ 18 O R (‰) R 2 = 0.88 Lena River Indus and Gila River Rivers Western & South Africa and arid USA Yellowstone River St. Lawrence and Skelleſte River Evaporaon Snow, ice, permafrost Fig. 3. Comparison of measured and modelled catchment isotope data. This figure depicted the comparison between the predicted amount- weighted upstream catchment precipitaon (δ 18 O P ) against measured (un-weighted) isotopic composion at the GNIR river observaon staons 18 O R ). The applicaon of the CC-RCWIP model is described in detail in Terzer et al. (2013) and Halder et al. (2014). GNIR staons for which the CC-RCWIP predicted overly posive δ 18 O values indicated that stored water sources from permafrost, snow, and glacier melt-water, were comparavely important contributors to the river-runoff. For river staons where CC-RCWIP predicted δ 18 O values that were more negave than observed, the results reveal important evaporaon processes. -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 1 2 3 4 5 6 7 8 9 10 11 12 Monthly mean average δ 18 O VSMOW (‰) Month Vienna Danube River (43 years) Precipitaon (51 years) Fig. 4. Isotopic composion of precipitaon and Danube River water in Vienna. This figure compares the monthly mean average of the stable oxygen isotope composion (δ 18 O) of Danube River water (red) and precipitaon (blue) in Vienna. The difference between both can be explained by the mixing of (1) river baseflow (well mixed summer and winter precipitaon) and (2) snow melt (delayed run-off of winter precipitaon). Data are taken from Seibersdorf research: IAEA/ZAMG. 1 2 3 4 5 6 7 8 9 10 11 12 Month -3 -2 -1 0 1 Predicted variation Zambezi River, Tete, Mozambique 1 2 3 4 5 6 7 8 9 10 11 12 Month -1.2 -0.8 -0.4 0 0.4 0.8 1.2 Predicted variation model 1 Predicted variation model 2 Waikato River, Hamilton, New Zealand 1 2 3 4 5 6 7 8 9 10 11 12 -2 -1 0 1 Predicted variation Torne River, Jukkarsjärvi, Sweden 1 2 3 4 5 6 7 8 9 10 11 12 -1.5 -1 -0.5 0 0.5 1 Predicted variation Euphrates River, Jarablous, Syrian Arab Republic δ 18 O seasonal offset (‰) Month Month Fig. 5. Isotopic composion in impacted river systems. The figure shows four examples of reservoir influenced river systems and underlines the difference between the expected (Halder et al., 2014) and measured isotopic composion. For example, the freezing of upstream surface water, which changes the river runoff components in winter (Torne River downstream of Lake Torneträsk, Sweden, Burgman et al., 1981); the averaging of different water sources due to cumulave dam systems (e.g. Euphrates River, Syrian Arab Republic, Kaan, 2012 and Waikato River, New Zealand, Mook, 1982), mixing of evaporated water and reverse seasonal flow from the oulow of regulated reservoirs having long water residence mes (e.g. Zambezi River downstream of Cahora Bassa Dam, Mozambique, Talma et al., 2012).

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Page 1: THE GLOBAL NETWORK OF ISOTOPES IN RIVERS …...THE GLOBAL NETWORK OF ISOTOPES IN RIVERS (GNIR) INTEGRATION OF WATER STABLE ISOTOPES IN RIVERINE RESEARCH AND MANAGEMENT J. Halder, S

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THE GLOBAL NETWORK OF ISOTOPES IN RIVERS (GNIR)

INTEGRATION OF WATER STABLE ISOTOPES IN RIVERINE RESEARCH AND MANAGEMENTJ. Halder, S. Terzer, L.I. Wassenaar, L.J. Araguás-Araguás, P.K. Aggarwal

Isotope Hydrology Section, International Atomic Energy Agency, Vienna, Austria, [email protected]

The Global Network of Isotopes in Rivers (GNIR) is a global environmental observation programme, which serves as an essential world-wide repository for riverine isotope data and facilitates public dissemination of contributed riverine isotopic data. GNIR is a complimentary programme to the IAEA’s well-established Global Network of Isotopes in Precipitation (GNIP).

What is the aim of GNIR? z Collect and disseminate time-series and synoptic collections of riverine isotope data from

the world’s rivers (Fig. 1);

z It relies upon voluntary partnerships with institutions and researchers for riverine sample collections and isotopic analyses (Fig. 2);

z GNIR is publicly accessible through the Water Isotope System for Data Analysis, Visualization and Electronic Retrieval (WISER) interface at https://nucleus.iaea.org/wiser.

What can river isotope observation tell us? z The stable isotope ratios of the water molecule (18O/16O, 2H/1H) are powerful recorders of

river recharge sources (direct precipitation, runoff, soil water, groundwater, lakes, snow, and ice) (Fig. 3);

z Long-term patterns of isotopes in rivers generally correlate with that of local precipitation but can also deviate significantly, indicating important hydrological processes (e.g. water sources mixing, evaporation) in the catchment (Figs 3 and 4);

z Variations of the isotopic composition over time can trace changes in hydrological processes, but also human and environmental impacts occurring between rainfall input and river discharge (Fig. 5).

Get involved in GNIRAt the IAEA, we are happy to receive archived, published data, and new proposals for GNIR stations. To propose a new GNIR station, please contact the GNIR team ([email protected]). The IAEA may provide support to GNIR stations by providing bottles or by analysing water stable isotopes at the Isotope Hydrology Laboratory in Vienna.

BibliographyBURGMAN, J.O., ERIKSSON, E., WESTMAN, F., Oxygen-18 variation in river waters in Sweden, unpublished report, Uppsala University (1981).HALDER, J., TERZER, S., WASSENAAR, L.I., ARAGUÁS-ARAGUÁS, L.J., AGGARWAL, P.K., The Global Network of Isotopes in Rivers (GNIR): Integration of water isotopes in watershed observation and riverine research, Hydrol. Earth Syst. Sci. (2014).KATTAN, Z., “Chemical and isotopic compositions of the Euphrates River water, Syria”, iMonitoring isotopes in rivers: Creation of the Global Network of Isotopes in Rivers (GNIR), IAEA-TECDOC-1673, Vienna (2012).

MOOK, W.G., The oxygen-18 content of rivers, Mitt. Geol.-Paläont. Inst. Univ. Hamburg, SCOPE/UNEP Sonderband 52 (1982) 565–570.TALMA, S., LORENTZ, S., WOODBORNE, S., “South African contribution to the rivers CRP“, Monitoring isotopes in rivers: Creation of the Global Network of Isotopes in Rivers (GNIR), IAEA-TECDOC-1673, Vienna (2012).TERZER, S., WASSENAAR, L.I., ARAGUAS-ARAGUAS, L.J., AGGARWAL, P.K., Global isoscapes for δ18O and δ2H in precipitation: improved prediction using regionalized climatic regression models, Hydrol. Earth Syst. Sci. 17 (2013) 4713–4728.

Fig. 1. GNIR Stations.The figure shows the 2730 GNIR sampling sites for water stable isotopes from 56 countries, covering all continents. The GNIR database covers rivers of all lengths and sizes, including lakes and reservoirs falling within the course of rivers. Sampling sites are either a part of synoptic, longitudinal, or time-series studies.

Fig. 2. GNIR sampling.Water samples are usually taken monthly as grab samples. Fig. 2 shows GNIR sampling in the Red River Delta, Viet Nam (Photo: Trinh Anh Duc).

-22 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2

CC-RCWIP average δ18OP (‰)

-22

-20

-18

-16

-14

-12

-10

-8

-6

-4

-2

0

GN

IR a

vera

ge δ

18O

R (‰)

R2 = 0.88

Lena River

Indus andGila River

Rivers Western & South Africaand arid USA

Yellowstone River

St. Lawrence andSkellefte River

Evaporation

Snow, ice, permafrost

Fig. 3. Comparison of measured and modelled catchment isotope data.This figure depicted the comparison between the predicted amount-weighted upstream catchment precipitation (δ18OP ) against measured (un-weighted) isotopic composition at the GNIR river observation stations (δ18OR ). The application of the CC-RCWIP model is described in detail in Terzer et al. (2013) and Halder et al. (2014). GNIR stations for which the CC-RCWIP predicted overly positive δ18O values indicated that stored water sources from permafrost, snow, and glacier melt-water, were comparatively important contributors to the river-runoff. For river stations where CC-RCWIP predicted δ18O values that were more negative than observed, the results reveal important evaporation processes.

-14

-13

-12

-11

-10

-9

-8

-7

-6

-5

1 2 3 4 5 6 7 8 9 10 11 12

Mon

thly

mea

n av

erag

e δ18

O V

SMO

W (‰

)

Month

ViennaDanube River (43 years)Precipitation (51 years)

Fig. 4. Isotopic composition of precipitation and Danube River water in Vienna.This figure compares the monthly mean average of the stable oxygen isotope composition (δ18O) of Danube River water (red) and precipitation (blue) in Vienna. The difference between both can be explained by the mixing of (1) river baseflow (well mixed summer and winter precipitation) and (2) snow melt (delayed run-off of winter precipitation). Data are taken from Seibersdorf research: IAEA/ZAMG.

1 2 3 4 5 6 7 8 9 10 11 12Month

-3

-2

-1

0

1

Predicted variationZambezi River, Tete, Mozambique

1 2 3 4 5 6 7 8 9 10 11 12

Month

-1.2

-0.8

-0.4

0

0.4

0.8

1.2 Predicted variation model 1Predicted variation model 2Waikato River, Hamilton, New Zealand

1 2 3 4 5 6 7 8 9 10 11 12-2

-1

0

1

Predicted variationTorne River, Jukkarsjärvi, Sweden

1 2 3 4 5 6 7 8 9 10 11 12-1.5

-1

-0.5

0

0.5

1

Predicted variationEuphrates River, Jarablous, Syrian Arab Republic δ18

O se

ason

al o

ffset

(‰)

Month Month

Fig. 5. Isotopic composition in impacted river systems.The figure shows four examples of reservoir influenced river systems and underlines the difference between the expected (Halder et al., 2014) and measured isotopic composition. For example, the freezing of upstream surface water, which changes the river runoff components in winter (Torne River downstream of Lake Torneträsk, Sweden, Burgman et al., 1981); the averaging of different water sources due to cumulative dam systems (e.g. Euphrates River, Syrian Arab Republic, Kattan, 2012 and Waikato River, New Zealand, Mook, 1982), mixing of evaporated water and reverse seasonal flow from the outflow of regulated reservoirs having long water residence times (e.g. Zambezi River downstream of Cahora Bassa Dam, Mozambique, Talma et al., 2012).