Assessing the Impact of CFSR and Local Climate Datasets on Hydrological Modeling Performance in the Mountainous Black Sea Catchment

Gokhan Cuceloglu,Izzet Ozturk

doi:10.3390/w11112277

Gokhan Cuceloglu, Izzet Ozturk

Open Access

https://doi.org/10.3390/w11112277

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Journal: Water	Publication Date: Oct 30, 2019
Citations: 11	License type: CC BY 4.0

Affiliation: Istanbul Technical University

Abstract

Precise representation of precipitation input is one of the predominant factors affecting the simulation of hydrological processes in catchments. Choosing the representative climate datasets is crucial to obtain accurate model results, especially in mountainous regions. Hence, this study assesses the suitability of the Climate Forecasting System Reanalysis (CFSR) and local climate data to simulate the streamflow at multiple gauges in the data-scarce mountainous Black Sea catchment. Moreover, the applicability of using the elevations band in the model is also tested. The Soil and Water Assessment Tool (SWAT) is used as a hydrological simulator. Calibration and uncertainty analysis are performed by using SWAT-CUP with the Sequential Uncertainty Fitting (SUFI-2) algorithm based on monthly streamflow data at six different hydrometric stations located at different altitudes. The results reveal that the CFSR dataset provides quite reasonable agreements between the simulated and the observed streamflow at the gauge stations compared to the local dataset. However, SWAT simulations with both datasets result in poor performance for the upstream catchments of the study area. Considering orographic precipitation by applying elevation bands to the local climate dataset using CFSR data leads also to significant improvements to the model’s performance. Model results obtained with both climate datasets result in similar objective metrics, and larger uncertainty with a coefficient variation (CV) ranging from 73% to 107%. This paper mainly highlights that (i) global climate datasets (i.e., CFSR) can be a good alternative especially for data-scarce regions, (ii) elevation band application can improve the model performance for the catchments with high elevation gradients, and iii) CFSR data can be used to determine precipitation lapse rate in data scarce-regions.

Highlights

Hydrological models can be valuable tools to improve our understanding of environmental system behaviors and to solve long-term water resource management problems
These values were obtained by a weighted average of three local and six Climate Forecast System Reanalysis (CFSR) climate stations depending on the related subbasins through the closest station approach of the Soil and Water Assessment Tool (SWAT) model
One of the main objectives of this study was to evaluate the impacts of the two different climate datasets (CFSR and local observations) on hydrological modeling performance by using the SWAT

Summary

Introduction

Hydrological models can be valuable tools to improve our understanding of environmental system behaviors and to solve long-term water resource management problems. Distributed hydrological models mainly necessitate more data lumped models [7]. Distributed hydrological modeling requires representative spatial and temporal data to simulate the hydrologic behavior of the watersheds [8]. In developing countries/regions especially, and in mountainous areas, recorded spatial rainfall data is subject to larger uncertainties due to sparse networks of rain gauges [9]. The availability of representative climate data is crucial for accurate water resources modeling in mountain environments [10]. Background shows the topography of the Melen Watershed. 1. Land-use summary of theuse Melen Watershed. According to the Corine database, the land of the watershed is summarized in five classes (Table 1).

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Conclusion