STREAMFLOW MAP OF THE EASTERN BLACK SEA REGION, TURKEY

Document Type : Article

Authors

1 Ege University, Civil Engineering Department , Bornova, Izmir, 35100 Turkey

2 Istanbul Technical University, Civil Engineering Faculty , Hydraulics Laboratory, Maslak, Istanbul, 34469 Turkey

Abstract

The purpose of this study is to generate a streamflow map for the coastal part of the Eastern Black Sea Region which is located in the north east of Turkey. The topographic structure of the region is an obstacle in terms of the number of observation gauges. In order to determine spatial variation of flow and to estimate flow on any ungauged points in the region, interpolation between gauged and ungauged points is applicable. For this purpose, any hydrological models which depend on a large number of meteorological dataset can be used. Instead, in this study, ordinary and universal kriging as geostatistical interpolation methods are used to interpolate mean annual flow depth over the study area, thus, flow values on ungauged points can be easily estimated. Kriging methods are compared to simple regression based on the relationship between flow data and basin area. Calibration results of observed and estimated flow depths for ordinary and universal kriging methods are satisfactory, the determination coefficients are found to be 0.84 and 0.87, respectively.  Besides, the validation results show that the performance of kriging methods is superior compared to the regression model.

Keywords

Main Subjects


References

1. Milly, P.C.D. and Dunne, K.A. \Macroscale water

uxes: 1. Quantifying errors in the estimation of basin
mean precipitation", Water Resour. Res., 38(10), pp.
1-14 (2002).
2. Huang, W.C. and Yang, F.T. \Stream
ow estimation
using Kriging", Water Resour. Res., 34(6), pp. 1599-
1608 (1998).
3. Rochelle, B.P., Stevens Jr., D.L., and Church, M.R.
\Uncertainty analysis of runo estimates from a runo
contour map", Water Resour. Bull., 25, pp. 491-498
(1989).
4. Krug, W.R., Gebert, W.A., Graczyk, D.J., Stevens,
D.L., Rochelle, B.P., and Church, M.R. \Map of
mean annual runo for the northeastern, southeastern,
and mid-Atlantic United States Water Years 1951-80",
U.S. Geological SurveyWater Resources Investigations
Report, Madison, WI (1990).
5. Bishop, G.D. and Church, M.R. \Automated approaches
for regional runo mapping in the northeastern
United States", J. Hydrol., 138, pp. 361-383
(1992).
6. Merz, R. and Bloschl, G. \Flood frequency regionalisation
{ spatial proximity vs. catchment attributes",
J. Hydrol., 302, pp. 283-306 (2005).
7. Arnell, N.W. \Grid mapping of river discharge", J.
Hydrol., 167, pp. 39-56 (1995).
8. Gottschalk, L. \Correlation and covariance of runo ",
Stoch. Hydrol. Hydraulics., 7(2), pp. 85-101 (1993).
9. Gottschalk, L. \Interpolation of runo applying objective
methods", Stoch. Hydrol. Hydraulics., 7(4), pp.
269-281 (1993).
10. Sauquet, E., Gottschalk, L., and Leblois, E. \Mapping
average annual runo : A hierarchical approach applying
a stochastic interpolation scheme", Hydrol. Sci. J.,
45, pp. 799-816 (2000).
11. Sauquet, E. \Mapping mean annual river discharges:
Geostatistical developments for incorporating river
network dependencies", J. Hydrol., 331, pp. 300-314
(2006).
12. Sauquet, E., Gottschalk, L., and Krasovskaia, I. \Estimating
mean monthly runo at ungauged locations:
An application to France", Hydrol. Res., 39(5-6), pp.
403-423 (2008).
13. Skoien, J.O., Merz, R., and Bloschl, G. \Top-kriging {
geostatistics on stream networks", Hydrol. Earth Syst.
Sci., 10, pp. 277-287 (2006).
14. Laaha, G., Skoien, J.O., and Bloschl, G. \Spatial
prediction on river networks: Comparison of topkriging
with regional regression", Hydrol. Process., 28,
pp. 315-324 (2014).
15. Arch eld, S.A., Pugliese, A., Castellarin, A., Skien,
J.O. and Kiang, J.E. \Topological and canonical kriging
for design
ood prediction in ungauged catchments:
an improvement over a traditional regional regression
approach?", Hydrol. Earth Syst. Sci., 17, pp. 1575-
1588 (2013).
16. Pugliesse, A., Farmer, W.H., Castellarin, A., Arch-
eld, S.A., and Vogel, R.M. \Regional
ow duration
curves: Geostatistical techniques versus multivariate
regression", Adv. Water Resour., 96, pp. 11-22 (2016).
17. Yan, Z., Xia, J., and Gottschalk, L. \Mapping runo
based on hydro-stochastic approach for the Huaihe
River Basin, China", J. Geogr. Sci., 21(3), pp. 441-
457 (2011).
18. Kaygusuz, K. and Sari, A. \Renewable energy potential
and utilization in Turkey", Energ. Convers.
Manag, 44, pp. 459-478 (2003).
19. Eris, E. \Determination of spatial distribution of
precipitation on poorly gauged coastal regions", PhD
Thesis, Istanbul Technical University, Institute of
Science and Technology (2011).
20. Eris, E. and Agiralioglu, N. \Homogeneity and trend
analysis of hydrometeorological data of the eastern
black sea region, Turkey", JWARP, 4, pp. 99-105
(2012).
21. Sima, S. and Tajrishy, M. \Developing water quality
maps of a hyper-saline lake using spatial interpolation
methods", Sci. Iran., 22(1), pp. 30-46 (2015).
22. Isaaks, E.H. and Srivastava, R.M., Applied Geostatistics,
Oxford University Press, NY (1989).
23. Goovaerts, P., Geostatistics for Natural Resources
Evaluation, Oxford University Press, NY (1997).
24. Journel, A.G. and Huijbregts, Ch.J., Mining Geostatistics,
The Blackburn Press, NJ (2003).
25. Goovaerts, P. \Geostatistical approaches for incorporating
elevation into the spatial interpolation of
rainfall", J. Hydrol., 228, pp. 113{129 (2000).
26. Gyalistras, D. \Development and validation of a high
resolution monthly gridded temperature and precipitation
data set for Switzerland (1951{2000)", Clim. Res.,
25, pp. 55-83 (2003).
27. Vicente-Serrano, S.M., Saz-Sanchez, M.A. and
Cuadrat, J.M. \Comparative analysis of interpolation
methods in the Middle Ebro Valley (Spain): Application
to annual precipitation and temperature", Clim.
Res., 24, pp. 161-180 (2003).
28. Eris, E. and Agralioglu, N. \E ect of coastline con guration
on precipitation distribution in coastal zones",
Hydrol. Process., 23(25), pp. 3610-3618 (2009).
29. Vogel, R.M., Wilson, I. and Daly, C. \Regional regression
models of annual stream
ow for the United
States", J. Irrig. Drain. Eng., 125(3), pp. 148-157
(1999).
1056 E. Eris and N. Agiralioglu/Scientia Iranica, Transactions A: Civil Engineering 25 (2018) 1048{1056
30. Helsel, D.R. and Hirsch, R.M., Statistical Methods
in Water Resources Techniques of Water Resources
Investigations, Book 4, chapter A3. U.S. Geological
Survey (2002).