Runoff formation in a small catchment at hillslope and catchment scales

Hrnčíř, Miroslav; Šanda, Martin; Kulasova, Alena; Cı́slerová, Milena

doi:10.1002/hyp.7614

Cited by 47 publications

(36 citation statements)

References 24 publications

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“…Annual precipitation in the area ranges between 930 and 1800 mm. The average air temperature in the headwater catchment is 4.7 • C (Hrnčíř et al, 2010). First hydrological data in the Uhlířská catchment were collected in 1982 and a monitoring and sampling network was subsequently developed, primarily aimed at studying extreme flood events as a consequence of deforestation.…”

Section: Czech Republicmentioning

confidence: 99%

A Tri-National program for estimating the link between snow resources and hydrological droughts

Zappa

Vitvar

Rücker³

et al. 2015

Proc. IAHS

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Abstract. To evaluate how summer low flows and droughts are affected by the winter snowpack, a Tri-National effort will analyse data from three catchments: Alpbach (Prealps, central Switzerland), Gudjaretis-Tskali (Little Caucasus, central Georgia), and Kamenice (Jizera Mountains, northern Czech Republic). Two GIS-based rainfall-runoff models will simulate over 10 years of runoff in streams based on rain and snowfall measurements, and further meteorological variables. The models use information on the geographical settings of the catchments together with knowledge of the hydrological processes of runoff generation from rainfall, looking particularly at the relationship between spring snowmelt and summer droughts. These processes include snow accumulation and melt, evapotranspiration, groundwater recharge in spring that contributes to (the) summer runoff, and will be studied by means of the environmental isotopes 18 O and 2 H. Knowledge about the isotopic composition of the different water sources will allow to identify the flow paths and estimate the residence time of snow meltwater in the subsurface and its contribution to the stream. The application of the models in different nested or neighbouring catchments will explore their potential for further development and allow a better early prediction of low-flow periods in various mountainous zones across Europe. The paper presents the planned activities including a first analysis of already available dataset of environmental isotopes, discharge, snow water equivalent and modelling experiments of the (already) available datasets.

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Section: Czech Republicmentioning

confidence: 99%

A Tri-National program for estimating the link between snow resources and hydrological droughts

Zappa

Vitvar

Rücker³

et al. 2015

Proc. IAHS

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“…is a region, where the long-term hydrological regime within the experimental catchments has been monitored by Czech Hydrometeorological Institute (Kulasová et al, 2005, CHMI, 1997. Detailed studies of water regime at selected locations were presented by Hrnčíř et al (2010), Vogel et al (2010), ), Remrová and Císlerová (2010 and Pavelková et al (2012).…”

Section: Study Sitementioning

confidence: 99%

Simulation of the influence of rainfall redistribution in spruce and beech forest on the leaching of Al and SO4 2- from forest soils

Nikodem

Kodešová²,

Bubeníčková³

2013

Journal of Hydrology and Hydromechanics

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Abstract:The aim of this study was to assess the impact of different vegetation on the distribution of rainfall (due to throughfall and stemflow), water regime, and Al and SO 4 2-leaching from forest soils. The water flow and Al and SO 4 2-transport were modeled using HYDRUS-1D. The study was performed at two elevation transects on the Paličník and Smědava Mountain in Jizera mountains. Podzols and Cambisols were prevailing soil units in this area. It was shown that the effect of the precipitation redistribution on water regime was considerable in the beech forest, while it was almost negligible in the spruce forest. Redistribution of precipitation under trees caused runoff (in one case), increased water discharge through the soil profile bottom, reduction of water storage in the soil, and thus reduction of root water uptake. Simulated Al leaching from the soil profile was determined mainly by the initial Al content in the soil profile bottom. Leaching of SO 4 2-was mainly determined by its initial content in the soil and to a lesser extent by redistributed precipitation and SO 4 2-deposition.

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“…Therefore we will use multiple linear regression models by using different response variables and predictor variables describing the runoff generation and among others the antecedent moisture conditions, respectively. Aware of the nonlinearity of hydrological processes and the threshold behavior of the rainfall-runoffrelationships the application of linear models to predict catchment's response is an auspicious approach to identify significant predictor variables (e.g., Graeff et al, 2012;Hrnčíř et al, 2010). Blume et al (2007) emphasize the surprisingly good results by using simple linear interrelationships to predict runoff coefficients, however, they point out that the derived model should not applied outside the range of the predictor variables.…”

Section: Introductionmentioning

confidence: 99%

The significance of soil moisture in forecasting characteristics of flood events. A statistical analysis in two nested catchments

Chifflard

Kranl

Strassen

et al. 2017

Journal of Hydrology and Hydromechanics

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Abstract:We examine the feasibility and added value of upscaling point data of soil moisture from a small-to a mesoscale catchment for the purpose of single-event flood prediction. We test the hypothesis that in a given catchment, the present soil moisture status is a key factor governing peak discharge, flow volume and flood duration. Multiple regression analyses of rainfall, pre-event discharge, single point soil moisture profiles from representative locations and peak discharge, discharge duration, discharge volume are discussed. The soil moisture profiles are selected along a convergent slope connected to the groundwater in flood plain within the small-scale catchment Husten (2.6 km²), which is a headwater catchment of the larger Hüppcherhammer catchment (47.2 km², Germany). Results show that the number of explanatory variables in the regression models is higher in summer (up to 8 variables) than in winter (up to 3 variables) and higher in the meso-scale catchment than in the small-scale catchment (up to 2 variables). Soil moisture data from selected key locations in the small catchment improves the quality of regression models established for the meso-scale catchment. For the different target variables peak discharge, discharge duration and discharge volume the adding of the soil moisture from the flood plain and the lower slope as explanatory variable improves the quality of the regression model by 15%, 20% and 10%, respectively, especially during the summer season. In the winter season the improvement is smaller (up to 6%) and the regression models mainly include rainfall characteristics as explanatory variables. The appearance of the soil moisture variables in the stepwise regression indicates their varying importance, depending on which characteristics of the discharge are focused on. Thus, we conclude that point data for soil moisture in functional landscape elements describe the catchments' initial conditions very well and may yield valuable information for flood prediction and warning systems.

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Runoff formation in a small catchment at hillslope and catchment scales

Cited by 47 publications

References 24 publications

A Tri-National program for estimating the link between snow resources and hydrological droughts

A Tri-National program for estimating the link between snow resources and hydrological droughts

Simulation of the influence of rainfall redistribution in spruce and beech forest on the leaching of Al and SO4 2- from forest soils

The significance of soil moisture in forecasting characteristics of flood events. A statistical analysis in two nested catchments

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