Spatial variability of soil hydraulic conductivity and runoff generation types in a small mountainous catchment

Yang, Yong; Chen, Rensheng; Song, Yunpeng; Han, Chuntan; Liu, Zhangwen; Liu, Junfeng

doi:10.1007/s11629-020-6258-1

Cited by 7 publications

(3 citation statements)

References 66 publications

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“…Variations in soil properties can significantly impact the hydrological processes by affecting water infiltration, storage, and flow. This can cause differences in the amount of water retained in the soil, leading to variable runoff generation at the hillslope [54,55]. Soil heterogeneity can result in differential water uptake, leading to variable soil water content and rates of rewetting.…”

Section: Discussionmentioning

confidence: 99%

Investigation of Hillslope Vineyard Soil Water Dynamics Using Field Measurements and Numerical Modeling

Krevh

Groh

Weihermüller

et al. 2023

Water

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Soil heterogeneities can impact hillslope hydropedological processes (e.g., portioning between infiltration and runoff), creating a need for in-depth knowledge of processes governing water dynamics and redistribution. The presented study was conducted at the SUPREHILL Critical Zone Observatory (CZO) (hillslope vineyard) in 2021. A combination of field investigation (soil sampling and monitoring campaign) and numerical modeling with hydrological simulator HYDRUS-1D was used to explore the water dynamics in conjunction with data from a sensor network (soil water content (SWC) and soil-water potential (SWP) sensors), along the hillslope (hilltop, backslope, and footslope). Soil hydraulic properties (SHP) were estimated based on (i) pedotransfer functions (PTFs), (ii) undisturbed soil cores, and (iii) sensor network data, and tested in HYDRUS. Additionally, a model ensemble mean from HYDRUS simulations was calculated with PTFs. The highest agreement of simulated with observed SWC for 40 cm soil depth was found with the combination of laboratory and field data, with the lowest average MAE, RMSE and MAPE (0.02, 0.02, and 5.34%, respectively), and highest average R2 (0.93), while at 80 cm soil depth, PTF model ensemble performed better (MAE = 0.03, RMSE = 0.03, MAPE = 7.55%, R2 = 0.81) than other datasets. Field observations indicated that heterogeneity and spatial variability regarding soil parameters were present at the site. Over the hillslope, SWC acted in a heterogeneous manner, which was most pronounced during soil rewetting. Model results suggested that the incorporation of field data expands model performance and that the PTF model ensemble is a feasible option in the absence of laboratory data.

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Section: Discussionmentioning

confidence: 99%

Investigation of Hillslope Vineyard Soil Water Dynamics Using Field Measurements and Numerical Modeling

Krevh

Groh

Weihermüller

et al. 2023

Water

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“…The highest lysimeter outflows were generally observed at the footslope, along with the lowest agreement with the model, suggesting the influence of downward moving water along the hillslope and high-volume rainfall on the vertical flux at the footslope. It is well documented that surface runoff generated on the hillslope can play a significant role in the overall distribution of infiltrated water [60]. Moreover, as rainwater moves downslope, it can encounter variations in soil properties that influence the amount of water retained in the soil, which can lead to variable runoff generation at the hillslope [61,62].…”

Section: Discussionmentioning

confidence: 99%

Investigating Near-Surface Hydrologic Connectivity in a Grass-Covered Inter-Row Area of a Hillslope Vineyard Using Field Monitoring and Numerical Simulations

Krevh

Filipović

Defterdarović

et al. 2023

Land

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The interplay of surface and shallow subsurface fluxes plays a critical role in controlling water movement in hillslope agroecosystems and impacting soil and plant health during prolonged dry periods, demonstrating a need for in-field monitoring. This study was conducted for two years (2021–2022) by combining field monitoring of the grass-covered inter-row area (passive wick lysimeter, surface runoff, and meteorological data), laboratory determination of soil hydraulic properties (SHPs), and numerical modeling with the aim to explore near-surface fluxes at the SUPREHILL Critical Zone Observatory (CZO) located on a hillslope vineyard. Additionally, sensitivity analysis for basic root water uptake (RWU) parameters was conducted. The model was evaluated (R2, RMSE, and NSE) with lysimeter (hillslope) and runoff (footslope) data, producing good agreement, but only after the inverse optimization of laboratory estimated hydraulic conductivity was conducted, demonstrating that adequate parameterization is required to capture the hydropedological response of erosion-affected soil systems. Results exhibit the dependence of runoff generation on hydraulic conductivity, rainfall, and soil moisture conditions. The data suggest different soil-rewetting scenarios based on temporal rainfall variability. Sensitivity analysis demonstrated that Leaf Area Index (LAI) was the most responsive parameter determining the RWU. The study offers an approach for the investigation of fluxes in the topsoil for similar sites and/or crops (and covers), presenting the methodology of self-constructed soil–water collection instruments.

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“…The Qilian Mountains (QLM), located on the northeast margin of the Tibetan Plateau (TP), serve as an important ecological security barrier for northwestern China and an important water source for the Heihe River basin (Sun and Liu, 2013;Yang et al, 2020). However, the ecological environment of the QLM has been impacted by human activities, including deforestation, overgrazing, overexploitation of water and energy resources (Yang et al, 2017;Wang X. et al, 2019;Zhou et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Bias correction of ERA-Interim reanalysis temperature for the Qilian Mountains of China

Zhao

Gao

et al. 2022

Front. Environ. Sci.

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Air temperature is the primary indicator of climate change. Reanalysis temperature products are important datasets for temperature estimates over high-elevation areas with few meteorological stations. However, they contain biases in observations, so a bias correction is required to enhance the accuracy of modeling predictions. In this study, we used the temperature lapse-rate method to correct ERA-Interim reanalysis-temperature data in the Qilian Mountains of China from 1979 to 2017. These temperature lapse rates were based on observations (ΓObs) and on model internal vertical lapse rates derived from different ERA-Interim pressure levels (ΓERA). The results showed that the temperature lapse rates in warm periods were larger than those in cold periods. Both the original and corrected ERA-Interim temperature can significantly capture the warming trend exhibited by observations. In general, the temperature lapse rate method was reliable for correcting ERA-interim reanalysis-temperature data. Although ΓObs performed best in bias correction, it depends heavily on the density of ground observation stations and is not appropriate for remote areas with a low data coverage. Correction methods based on ΓERA were shown to be reliable for bias correction, and will be especially applicable to mountainous areas with few observation stations. Our results contribute to the improvement of quality of data products and enhance the accuracy of modeling of climate change effects and risks to the environment and human health.

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Spatial variability of soil hydraulic conductivity and runoff generation types in a small mountainous catchment

Cited by 7 publications

References 66 publications

Investigation of Hillslope Vineyard Soil Water Dynamics Using Field Measurements and Numerical Modeling

Investigation of Hillslope Vineyard Soil Water Dynamics Using Field Measurements and Numerical Modeling

Investigating Near-Surface Hydrologic Connectivity in a Grass-Covered Inter-Row Area of a Hillslope Vineyard Using Field Monitoring and Numerical Simulations

Bias correction of ERA-Interim reanalysis temperature for the Qilian Mountains of China

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