Spatial and temporal occurrence of preferential flow in a forested headwater catchment

Wiekenkamp, Inge; Huisman, Johan Alexander; Bogena, Heye; Lin, Henry; Vereecken, Harry

doi:10.1016/j.jhydrol.2015.12.050

Cited by 146 publications

(136 citation statements)

References 35 publications

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“…Considering the measurement uncertainty of the installed SWC sensors (4-5 vol %; [37]) the RMSE of 3.4 to 5.3 vol % appear very low and are within the range of other HYDRUS-1D studies on the Wüstebach test site [50,53]. The varying soil hydraulic properties among plots and layers (Table 2) fit well to the observations of [36,38]. The low K s value in the riparian zone is plausible, because the soils in the valley bottom have a higher bulk density and a lower macro-porosity than the soils on the hillslopes [37,38].…”

Section: Soil Moisture Simulationssupporting

confidence: 76%

“…The varying soil hydraulic properties among plots and layers (Table 2) fit well to the observations of [36,38]. The low K s value in the riparian zone is plausible, because the soils in the valley bottom have a higher bulk density and a lower macro-porosity than the soils on the hillslopes [37,38].…”

Section: Soil Moisture Simulationssupporting

confidence: 68%

“…We manually optimized A qh and B qh with regard to the best fit (root-mean-square error) between measured and simulated soil moisture dynamics. Depending on the local site conditions [36,38] we discretized the HYDRUS-1D soil profiles into two (Riparian) and three (Slope) materials (one/two soil horizons plus an organic litter layer on top) (Figure 2). The hydraulic properties of the litter layer were parameterized according to [53].…”

Section: Estimating Root-zone Water Potentialmentioning

confidence: 99%

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Using Sap Flow Data to Parameterize the Feddes Water Stress Model for Norway Spruce

Rabbel

Bogena

Neuwirth³

et al. 2018

Water

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Abstract:Tree water use is a key variable in forest eco-hydrological studies and is often monitored by sap flow measurements. Upscaling these point measurements to the stand or catchment level, however, is still challenging. Due to the spatio-temporal heterogeneity of stand structure and soil water supply, extensive measuring campaigns are needed to determine stand water use from sap flow measurements alone. Therefore, many researchers apply water balance models to estimate stand transpiration. To account for the effects of limited soil water supply on stand transpiration, models commonly refer to plant water stress functions, which have rarely been parameterized for forest trees. The aim of this study was to parameterize the Feddes water stress model for Norway spruce (Picea abies [L.] Karst.). After successful calibration and validation of the soil hydrological model HYDRUS-1D, we combined root-zone water potential simulations with a new plant water stress factor derived from sap flow measurements at two plots of contrasting soil moisture regimes. By calibrating HYDRUS-1D against our sap flow data, we determined the critical limits of soil water supply. Drought stress reduced the transpiration activity of mature Norway spruce at root-zone pressure heads <−4100 cm, while aeration stress was not observed. Using the recalibrated Feddes parameters in HYDRUS-1D also improved our water balance simulations. We conclude that the consideration of sap flow information in soil hydrological modeling is a promising way towards more realistic water balance simulations in forest ecosystems.

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Section: Soil Moisture Simulationssupporting

confidence: 76%

Section: Soil Moisture Simulationssupporting

confidence: 68%

Section: Estimating Root-zone Water Potentialmentioning

confidence: 99%

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Using Sap Flow Data to Parameterize the Feddes Water Stress Model for Norway Spruce

Rabbel

Bogena

Neuwirth³

et al. 2018

Water

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“…The soil types can be subdivided into terrestrial soils (i.e., Cambisols, Planosols) and semi-terrestrial soils (i.e., Gleysols, Histosols) in the ripar- ian zone (Gottselig et al, 2017). The mean porosity of the soils varied from 20 to 81 % for groundwater influenced soils and from 60 to 78 % for the terrestrial soils with decreasing values with increasing depth (Wiekenkamp et al, 2016). In the riparian zone, the water table varied between 0.0 and 1.6 m, while it constantly remained below the soil-bedrock interface outside of the riparian zone .…”

Section: The Forested Wüstebach Catchment (Ger)mentioning

confidence: 99%

Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity

Schrön

Köhli

Scheiffele

et al. 2017

Hydrol. Earth Syst. Sci.

125

231

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Abstract. In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.

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“…However, the poor accuracy for surface soil moisture simulation may be caused by the unusual weather conditions in 2012. In addition, the uncertainties of input data and field measurements such as groundwater table [58], the possible preferential flow [59] and even the observation errors might also bring adverse influences on the accuracy of the simulations for all four stages. …”

Section: Performance Of the Wfsp Modelmentioning

confidence: 99%

Determination of Growth Stage-Specific Crop Coefficients (Kc) of Sunflowers (Helianthus annuus L.) under Salt Stress

Hong

Zeng

et al. 2017

Water

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Abstract:Crop coefficients (K c ) are important for the development of irrigation schedules, but few studies on K c focus on saline soils. To propose the growth-stage-specific K c values for sunflowers in saline soils, a two-year micro-plot experiment was conducted in Yichang Experimental Station, Hetao Irrigation District. Four salinity levels including non-salinized (EC e = 3.4-4.1 dS·m -1 ), low (EC e = 5.5-8.2 dS·m -1 ), moderate (EC e = 12.1-14.5 dS·m -1 ), and high (EC e = 18.3-18.5 dS·m -1 ) levels were arranged in 12 micro-plots. Based on the soil moisture observations, Vensim software was used to establish and develop a physically-based water flow in the soil-plant system (WFSP) model. Observations in 2012 were used to calibrate the WFSP model and acceptable accuracy was obtained, especially for soil moisture simulation below 5 cm (R 2 > 0.6). The locally-based K c values (LK c ) of sunflowers in saline soils were presented according to the WFSP calibration results. To be specific, LK c for initial stages (K c1 ) could be expressed as a function of soil salinity (R 2 = 0.86), while R 2 of LK c for rapid growth (K c2 ), middle (K c3 ), and mature (K c4 ) stages were 0.659, 1.156, and 0.324, respectively. The proposed LK c values were also evaluated by observations in 2013 and the R 2 for initial, rapid growth, middle, and mature stages were 0.66, 0.68, 0.56 and 0.58, respectively. It is expected that the LK c would be of great value in irrigation management and provide precise water application values for salt-affected regions.

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Spatial and temporal occurrence of preferential flow in a forested headwater catchment

Cited by 146 publications

References 35 publications

Using Sap Flow Data to Parameterize the Feddes Water Stress Model for Norway Spruce

Using Sap Flow Data to Parameterize the Feddes Water Stress Model for Norway Spruce

Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity

Determination of Growth Stage-Specific Crop Coefficients (Kc) of Sunflowers (Helianthus annuus L.) under Salt Stress

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