Modelling the temporal variation in snow-covered area derived from satellite images for simulating/forecasting of snowmelt runoff in Turkey

Download
index.pdf
2005-08-01
Tekeli, AE
Akyurek, Z
Sensoy, A
Sorman, AA
Sorman, U
Show full item record
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
180
views
0
downloads
Monitoring the change of snow-covered area (SCA) in a basin is vitally important for optimum operation of water resources, where the main contribution comes from snowmelt. A methodology for obtaining the depletion pattern of SCA, which is based on satellite image observations where mean daily air temperature is used, is applied for the 1997 water year and tested for the 1998 water year. The study is performed at the Upper Euphrates River basin in Turkey (10 216 km(2)). The major melting period in this basin starts in early April. The cumulated mean daily air temperature (CMAT) is correlated to the depletion of snow-covered area with the start of melting. The analysis revealed that SCA values obtained from NOAA-AVHRR satellite images are exponentially correlated to CMAT for the whole basin in a lumped manner, where R-2 values of 0.98 and 0.99 were obtained for the water years 1997 and 1998, respectively. The applied methodology enables the interpolation between the SCA observations and extrapolation. Such a procedure reduces the number of satellite images required for analysis and provides solution for the cloud-obscured images. Based on the image availability, the effect of the number of images on the quality of snowmelt runoff simulations is also discussed. In deriving the depletion curve for SCA, if the number of images is reduced, the timing of image analysis within the snowmelt period is found very important. Analysis of the timing of satellite images indicated that images from the early and middle parts of the melt period are more important.
Water Science and Technology
https://hdl.handle.net/11511/68099
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
Department of Civil Engineering, Article

Suggestions

Estimation of river flow by artificial neural networks and identification of input vectors susceptible to producing unreliable flow estimates
Kentel Erdoğan, Elçin (Elsevier BV, 2009-09-15)
Reliable river flow estimates are crucial for appropriate water resources planning and management. River flow forecasting can be conducted by conceptual or physical models, or data-driven black box models. Development of physically-based models requires an understanding of ail the physical processes which impact a natural process and the interactions among them. Since identification of the relationships among these physical processes is very difficult, data-driven approaches have recently been utilized in h...
Modeling biogeochemical processes in subterranean estuaries: Effect of flow dynamics and redox conditions on submarine groundwater discharge of nutrients
Spiteri, Claudette; Slomp, Caroline P.; Tuncay, Kağan; Meile, Christof (American Geophysical Union (AGU), 2008-02-22)
[1] A two-dimensional density-dependent reactive transport model, which couples groundwater flow and biogeochemical reactions, is used to investigate the fate of nutrients (NO(3)(-), NH(4)(+), and PO(4)) in idealized subterranean estuaries representing four end-members of oxic/anoxic aquifer and seawater redox conditions. Results from the simplified model representations show that the prevalent flow characteristics and redox conditions in the freshwater-seawater mixing zone determine the extent of nutrient ...
A process-based diagnostic approach to model evaluation: Application to the NWS distributed hydrologic model
Yılmaz, Koray Kamil; Wagener, Thorsten (American Geophysical Union (AGU), 2008-09-11)
Distributed hydrological models have the potential to provide improved streamflow forecasts along the entire channel network, while also simulating the spatial dynamics of evapotranspiration, soil moisture content, water quality, soil erosion, and land use change impacts. However, they are perceived as being difficult to parameterize and evaluate, thus translating into significant predictive uncertainty in the model results. Although a priori parameter estimates derived from observable watershed characteris...
Modelling and forecasting snowmelt runoff process using the HBV model in the eastern part of Turkey
ŞORMAN, ALİ ARDA; ŞENSOY ŞORMAN, AYNUR; Tekeli, A. E.; Sorman, A. Ue.; Akyürek, Sevda Zuhal (Wiley, 2009-03-30)
Snowmelt runoff in the mountainous eastern part of Turkey is of great importance as it constitutes 60-70% in volume of the total yearly runoff during spring and early summer months. Therefore, determining the amount and timing of snowmelt runoff especially in the Euphrates basin, where large clams are located, is ail important tusk in order to use the water resources of the country in an optimal manner.
The Auto-Tuned Land Data Assimilation System ( ATLAS)
Crow, W. T.; Yılmaz, Mustafa Tuğrul (American Geophysical Union (AGU), 2014-01-01)
Land data assimilation systems are commonly tasked with merging remotely sensed surface soil moisture retrievals with information derived from a soil water balance model driven by observed rainfall. The performance of such systems can be degraded by the incorrect specification of parameters describing modeling and observation errors. Here the Auto-Tuned Land Data Assimilation System (ATLAS) is introduced to simultaneously solve for all parameters required for the application of a simple land data assimilati...
Citation Formats
A. Tekeli, Z. Akyurek, A. Sensoy, A. Sorman, and U. Sorman, “Modelling the temporal variation in snow-covered area derived from satellite images for simulating/forecasting of snowmelt runoff in Turkey,” HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES, pp. 669–682, 2005, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/68099.
METU IIS - Integrated Information Service open@metu.edu.tr