Manifestation of spatial and temporal variability of soil hydraulic properties in the uncultivated Fluvisol and performance of hydrological model

Šípek, Václav; Jačka, Lukáš; Seyedsadr, Samar; Trakal, Lukáš

doi:10.1016/j.catena.2019.104119

Cited by 20 publications

(6 citation statements)

References 65 publications

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“…The prediction errors may be due to lateral flows entering as well as leaving the flow domain since the flow domain was not hydraulically isolated during data collection. Another source of prediction errors may be the spatial and temporal variability of the soil hydraulic properties (Schwen et al, 2011;Jirku et al, 2013;Šípek et al, 2019). The pore space in cultivated histosols may be dynamic due to fine particles migration which is almost a continuous phenomenon in Montérégie.…”

Section: Calibrated Model Hydraulic Parameters and Validation Resultsmentioning

confidence: 99%

Modeling Subsurface Drainage in Compacted Cultivated Histosols

et al. 2021

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Reclaiming histosols in Montéregie region, Québec, Canada, increases peat decomposition and compaction rate and decreases the effectiveness of subsurface drainage. The objective of this paper was to use HYDRUS-2D to model the behavior of subsurface drainage systems, in order to evaluate the compaction effect on drain depth and spacing, and to determine the compact layer thickness and saturated hydraulic conductivities (Ksat) resulting in an improvement of subsurface drainage]. The drainage model was calibrated [Nash-Sutcliffe efficiency coefficient (NSE) = 0.958, percent bias (PBIAS) = −0.57%] using Ksat, meteorological data, and matric potential (h) data measured on the project site from June 10 to July 19, 2017. The calibrated and validated model was used to analyze the variation of h values (Δh in cm d−1) as a function of drain spacing (2–7 m) and drain depth (1 and 1.2 m) and to identify the response surface of Δh to various compact layer thickness and Ksat combinations. The results showed that Δh was on average 58% greater below the compact layer than above it and that reducing drain spacing or increasing drain depth does not improve the drainage rate. The analysis of the compact layer thickness and Ksat effect on Δh showed that for a Δh of 40 cm d−1, Ksat actual values in the two uppermost layers should be multiplied by 50 for compact layer thickness varying from 12 to 35 cm. Water percolation in the soil is reduced by the compact layer. Soil management methods for improving Ksat should therefore be better than deepening the drains or and reducing the spacing.

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Section: Calibrated Model Hydraulic Parameters and Validation Resultsmentioning

confidence: 99%

Modeling Subsurface Drainage in Compacted Cultivated Histosols

et al. 2021

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“…SHPs are considered mostly constant in all hydrological modeling studies when predicting the flow behaviour of solutes and water in the soil–plant‐atmosphere system. However, due to the lack of hydrological and soil structural data, the efficient calibration and application of modelling tools are very difficult (Šípek et al, 2019). Further, a lack of adequate knowledge on the evolution of pore size distribution after tillage and soil pore space's temporal variation may lead to false predictions (Chandrasekhar et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Temporal variation of saturated and near‐saturated soil hydraulic conductivity and water‐conducting macroporosity in a maize‐wheat rotation under conventional and conservation tillage practices

et al. 2022

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Knowledge of temporal variation of soil hydraulic properties (SHPs) is crucial to understand soil physical behaviour under different tillage practices. The objective of this study was to assess the variation of saturated and near‐saturated soil hydraulic conductivity (NSHC) and water‐conducting macroporosity (Ɛ) under long‐term (09 years) tillage regimes viz. zero tillage (ZT), conventional tillage (CT), and minimum tillage (MT) in a rain‐fed maize‐wheat crop rotation (RMWC) in the North‐West Himalayas, India (NWHI). A hood infiltrometer (HI) was used to measure the steady‐state water flux (q) at 0, −10, and −30 mm pressure head (PH) after harvesting of maize and over two wheat cropping seasons for each treatment. The infiltration data were analyzed in terms of unsaturated hydraulic conductivity k(h), field saturated hydraulic conductivity (ks), water‐conducting macroporosity (Ɛ). The results showed that the seasonal effects on ks, k(h), and Ɛ values were significantly different (p ≤0.05) for tilled treatments (CT and MT). In contrast, no significant difference (p ≤0.05) was found for untilled treatment (ZT). Significantly higher (p ≤0.05) ks, k(h), and Ɛ values were observed in ZT than CT and MT, associated with higher SOC and lower ρb values. A multivariate analysis of variance of the ks showed a highly significant difference (p ≤0.01) with both time and tillage treatments. Overall, a significant improvement of hydraulic conductivity characteristics was observed during the wheat‐growing seasons compared with the maize harvest season. The temporal dynamics of SHPs under different tillage regimes indicate that ZT can be a suitable tillage practice for reducing runoff and soil loss in monsoon maize and winter wheat cropping system.

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“…Spatial and temporal variability refers to the phenomenon that variable value changes with the spatial position and time. A lot of variables in the field of ecology, geography, and agricultural science have spatial and temporal variability, for example, scholars around the world have conducted a lot of research on spatial and temporal variability of soil properties, such as soil water and soil hydraulic property and so on (Dari et al., 2019; Liu et al., 2018; Nie et al., 2014; Piotrowska‐Długosz et al., 2019; Robinet, et al., 2018; Šípek et al., 2019; Vidana Gamage et al., 2019; Zhao et al., 2017), and spatial and temporal variability of crop information also have carried out (Diacono et al., 2012; Eghball et al., 2003; Liu, Ren et al., 2016; Lu et al., 2014; Rüth & Lennartz, 2008; Usowicz & Lipiec, 2017; Xue et al., 2005). Since the 1990s, precision agriculture has become one of the most attractive frontier research fields; the quantitative characterization of spatial and temporal variability of crop information is an important research content of precision agriculture and is a foundation to realize the accurate management of soil and crop (Cai et al., 2009).…”

Section: Introductionmentioning

confidence: 99%

Spatial variability of maize leaf area and relationship with yield

Zhang

Liu

et al. 2022

Agronomy Journal

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Leaf area is an important factor affecting crop yield. However, leaf area has spatial variability and the relationship between leaf area and yield have scale dependence. For these reasons, we establish multifractal model of maize (Zea mays L.) leaf area and joint multifractal model of maize leaf area and yield. The experiment was carried at the Xiangyang base of Northeast Agricultural University. The size of experimental plot was 9,216 m2 which included 64 sampling points. The spatial and temporal variability of maize leaf area was studied with traditional statistics and multifractal methods, and the relationship between maize leaf area and yield at multiple scales was analyzed with the joint multifractal method. Multifractal theory can effectively characterize spatial and temporal variability of maize leaf area and multiscale relationship between leaf area and yield. Maize leaf area exhibited a moderate degree of variation which first decreased then increased with the change in the growth stage, and spatial variability at different growth stages was mainly caused by low leaf area values . At the observed scale, axis weight per ear, ear weight, and grain weight per ear were most significantly related to maize leaf area at the milk, filling, and jointing stages; at the multiscale level, axis weight per ear was most significantly related to maize leaf area at the tasseling, filling, milk, and jointing stages, and ear weight and grain weight per ear were most significantly related to maize leaf area at the tasseling, filling and ripening stages.

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Manifestation of spatial and temporal variability of soil hydraulic properties in the uncultivated Fluvisol and performance of hydrological model

Cited by 20 publications

References 65 publications

Modeling Subsurface Drainage in Compacted Cultivated Histosols

Modeling Subsurface Drainage in Compacted Cultivated Histosols

Temporal variation of saturated and near‐saturated soil hydraulic conductivity and water‐conducting macroporosity in a maize‐wheat rotation under conventional and conservation tillage practices

Spatial variability of maize leaf area and relationship with yield

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