scholarly journals Spatio-temporal Analysis of Hydrological Drought at Catchment Scale Using a Spatially-distributed Hydrological Model

2016 ◽  
Vol 154 ◽  
pp. 738-744 ◽  
Author(s):  
Vitali Diaz Mercado ◽  
Gerald Corzo Perez ◽  
Dimitri Solomatine ◽  
Henny A.J. van Lanen
2017 ◽  
Author(s):  
Gorka Mendiguren ◽  
Julian Koch ◽  
Simon Stisen

Abstract. Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two source energy balance model (TSEB) driven mainly by satellite remote sensing data. The main hypothesis of the study is that while both approaches are essentially estimates, the spatial patterns of the remote sensing based approach are explicitly driven by observed land surface temperature and therefore represent the most direct spatial pattern information of ET; enabling its use for distributed hydrological model evaluation. Ideally the hydrological model simulation and remote sensing based approach should present similar spatial patterns and driving mechanism of ET. However, the spatial comparison showed that the differences are significant and indicating insufficient spatial pattern performance of the hydrological model. The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in 6 domains that are calibrated independently from each other, as it is often the case for large scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of Leaf Area Index (LAI), root depth (RD) and Crop coefficient (Kc) for each land cover type. This zonal approach of model parametrization ignores the spatio-temporal complexity of the natural system. To overcome this limitation, the study features a modified version of the DK-Model in which LAI, RD, and KC are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatio-temporal variability and spatial consistency between the 6 domains. The effects of these changes are analyzed by using the empirical orthogonal functions (EOF) analysis to evaluate spatial patterns. The EOF-analysis shows that including remote sensing derived LAI, RD and KC in the distributed hydrological model adds spatial features found in the spatial pattern of remote sensing based ET.


2015 ◽  
Vol 7 (2) ◽  
pp. 73-77 ◽  
Author(s):  
MN Uddin ◽  
MSA Mondal ◽  
NMR Nasher

The analysis of annual mean maximum and annual mean minimum temperature data are studied in GIS environment, obtained from 34 meteorological stations scattered throughout the Bangladesh from 1948 to 2013. IDW method was used for the spatial distribution of temperature over the study area, using ArcGIS 10.2 software. Possible trends in the spatially distributed temperature data were examined, using the non-parametric Mann-Kendall method with statistical significance, and the magnitudes of available trends were determined using Sen’s method in ArcMap depiction. The findings of the study show positive trends in annual mean maximum temperatures with 90%, 95%, 99% and 99.9% significance levels.DOI: http://dx.doi.org/10.3329/jesnr.v7i2.22210 J. Environ. Sci. & Natural Resources, 7(2): 73-77 2014


2016 ◽  
Vol 64 (4) ◽  
pp. 304-315 ◽  
Author(s):  
Kamila Hlavčová ◽  
Silvia Kohnová ◽  
Marco Borga ◽  
Oliver Horvát ◽  
Pavel Šťastný ◽  
...  

Abstract This work examines the main features of the flash flood regime in Central Europe as revealed by an analysis of flash floods that have occurred in Slovakia. The work is organized into the following two parts: The first part focuses on estimating the rainfall-runoff relationships for 3 major flash flood events, which were among the most severe events since 1998 and caused a loss of lives and a large amount of damage. The selected flash floods occurred on the 20th of July, 1998, in the Malá Svinka and Dubovický Creek basins; the 24th of July, 2001, at Štrbský Creek; and the 19th of June, 2004, at Turniansky Creek. The analysis aims to assess the flash flood peaks and rainfall-runoff properties by combining post-flood surveys and the application of hydrological and hydraulic post-event analyses. Next, a spatially-distributed hydrological model based on the availability of the raster information of the landscape’s topography, soil and vegetation properties, and rainfall data was used to simulate the runoff. The results from the application of the distributed hydrological model were used to analyse the consistency of the surveyed peak discharges with respect to the estimated rainfall properties and drainage basins. In the second part these data were combined with observations from flash flood events which were observed during the last 100 years and are focused on an analysis of the relationship between the flood peaks and the catchment area. The envelope curve was shown to exhibit a more pronounced decrease with the catchment size with respect to other flash flood relationships found in the Mediterranean region. The differences between the two relationships mainly reflect changes in the coverage of the storm sizes and hydrological characteristics between the two regions.


2009 ◽  
Vol 13 (10) ◽  
pp. 1867-1885 ◽  
Author(s):  
Y. van der Velde ◽  
G. H. de Rooij ◽  
P. J. J. F. Torfs

Abstract. Freely discharging lowland catchments are characterized by a strongly seasonal contracting and expanding system of discharging streams and ditches. Due to this rapidly changing active channel network, discharge and solute transport cannot be modeled by a single characteristic travel path, travel time distribution, unit hydrograph, or linear reservoir. We propose a systematic spatial averaging approach to derive catchment-scale storage and discharge from point-scale water balances. The effects of spatial heterogeneity in soil properties, vegetation, and drainage network are lumped and described by a relation between groundwater storage and the spatial probability distribution of groundwater depths with measurable parameters. The model describes how, in lowland catchments, the catchment-scale flux from groundwater to surface water via various flow routes is affected by a changing active channel network, the unsaturated zone and surface ponding. We used observations of groundwater levels and catchment discharge of a 6.6 km2 Dutch watershed in combination with a high-resolution spatially distributed hydrological model to test the model approach. Good results were obtained when modeling hourly discharges for a period of eight years. The validity of the underlying assumptions still needs to be tested under different conditions and for catchments of various sizes. Nevertheless, at this stage the model can already improve monitoring efficiency of groundwater-surface water interactions.


2009 ◽  
Vol 13 (7) ◽  
pp. 1019-1029 ◽  
Author(s):  
B. Pallard ◽  
A. Castellarin ◽  
A. Montanari

Abstract. We investigate the links between the drainage density of a river basin and selected flood statistics, namely, mean, standard deviation, coefficient of variation and coefficient of skewness of annual maximum series of peak flows. The investigation is carried out through a three-stage analysis. First, a numerical simulation is performed by using a spatially distributed hydrological model in order to highlight how flood statistics change with varying drainage density. Second, a conceptual hydrological model is used in order to analytically derive the dependence of flood statistics on drainage density. Third, real world data from 44 watersheds located in northern Italy were analysed. The three-level analysis seems to suggest that a critical value of the drainage density exists for which a minimum is attained in both the coefficient of variation and the absolute value of the skewness coefficient. Such minima in the flood statistics correspond to a minimum of the flood quantile for a given exceedance probability (i.e., recurrence interval). Therefore, the results of this study may provide useful indications for flood risk assessment in ungauged basins.


2010 ◽  
Vol 4 (Special Issue 2) ◽  
pp. S111-S122
Author(s):  
R. Košková ◽  
S. Němečková

The application of the distributed hydrological model brings the benefits of assessment of the spatially distributed quantities which are hard to measure in the field over a larger area, e.g. evapotranspiration. The Malše River basin has been chosen for the evaluation of evapotranspiration simulation by the distributed hydrological model, SWIM (Soil and Water Integrated Model). The primary interest in this analysis was to assess the ability of the hydrological model to simulate the actual evapotranspiration on larger scales and to evaluate its dependence on the landscape characteristics such as the vegetation cover, soil type, and average precipitation amount during the simulation. Annual actual evapotranspiration in each hydrotope was evaluated in the simulation period of 1985–1998. Because of the lack of the data observed (evapotranspiration), the model was calibrated on the discharge time series. The credibility was quantified using Nash Sutcliffe efficiency which was more than 0.7. The main trends of the simulated actual evapotranspiration were evaluated and assessed as satisfactory. The differences in the soil types did not seem significant for the evapotranspiration variation, the monthly average values among soil types differing by ± 10% except histosol. On the other hand the differences in the land-use categories strongly influenced the amount of evapotranspiration (–30; +50%). It appears that the model SWIM overestimates the actual evapotranspiration in the spring and, on the other hand, underestimates that in the autumn according to the comparison with the only data available in the entire Climate Atlas of the Czech Republic.


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