Spatial variability of saturated hydraulic conductivity and its links with other soil properties at the regional scale

Abstract

Saturated hydraulic conductivity (K) is a key property for evaluating soil water movement and quality. Most studies on spatial variability of K have been performed soil at a field or smaller scale. Therefore, the aim of this work was to assess (quantify) the spatial distribution of K at the larger regional scale in south-eastern Poland and its relationship with other soil properties, including intrinsic sand, silt, and clay contents, relatively stable organic carbon, cation exchange capacity (CEC) and temporally variable water content (WC), total porosity (FI), and dry bulk density (BD) in the surface layer (0–20 cm). The spatial relationships were assessed using a semivariogram and a cross-semivariogram. The studied region (140 km2) with predominantly permeable sandy soils with low fertility and productivity is located in the south-eastern part of Poland (Podlasie region). The mean sand and organic carbon contents are 74 and 0.86 and their ranges (in %) are 45–95 and 0.002–3.75, respectively. The number of individual samples varied from 216 to 228 (for K, WC, BD, FI) to 691 for the other soil properties. The best fitting models were adjusted to the empirical semivariogram (exponential) and the cross-semivariogram (exponential, Gaussian, or linear) used to draw maps with kriging. The results showed that, among the soil properties studied, K was most variable (coefficient of variation 77.3%) and significantly (p < 0.05) positively correlated with total porosity (r = 0.300) and negatively correlated with soil bulk density (r = – 0.283). The normal or close to the normal distribution was obtained by natural logarithmic and root square transformations. The mean K was 2.597 m day−1 and ranged from 0.01 up to 11.54 m day−1. The spatial autocorrelation (range) of K in the single (direct) semivariograms was 0.081° (8.1 km), while it favourably increased up to 0.149°–0.81° (14.9–81 km) in the cross-semivariograms using the OC contents, textural fractions, and CEC as auxiliary variables. The generated spatial maps allowed outlining two sub-areas with predominantly high K above 3.0 m day−1 in the northern sandier (sand content > 74%) and less silty (silt content < 22%) part and, with lower K in the southern part of the study region. Generally, the spatial distribution of the K values in the study region depended on the share of individual intrinsic textural fractions. On the other hand, the ranges of the spatial relationship between K and the intrinsic and relatively stable soil properties were much larger (from ~ 15 to 81 km) than between K and the temporally variable soil properties (0.3–0.9 km). This knowledge is supportive for making decisions related to land management aimed at alteration of hydraulic conductivity to improve soil water resources and crop productivity and reduce chemical leaching.

Linking the Pattern Structures to System Robustness Based on Dynamical Models and Statistical Method

“…Finally, through simulation, we obtain the best fitted semivariogram model and some important indicators, such as nugget C 0 , sill C 0 + C, range A, and the structural ratio C/(C 0 + C). Figure 1 shows the basic process of this method and the calculation formula of the semivariogram as follows [29]:…”

Identification of Infiltration Features and Hydraulic Properties of Soils Based on Crop Water Stress Derived from Remotely Sensed Data

“…The radial basis kernel (RBF) was used for the SVR model. The model was tuned with a variable insensitive-loss function epsilon in the range of 0 to 1.0 with step 0.1 and with the cost of constraints violation in the range 2 2 to 2 9 with step 2 n+1 , where n is an exponent from the previous calculation step. The gamma parameter was set as 1/number of values in the dataset.…”

“…The spatial heterogeneity of soil hydraulic properties directly affects crop yields via air-filled porosity, plant available water and penetration of plant roots [7]. Implementing soil heterogeneity into site-specific farming practices, increasing the efficiency of agricultural inputs, is a prerequisite for the use of precision agriculture methods [8,9]. The manifestation of soil heterogeneity is enhanced by plant water stress.…”

Quantifying Cereal Productivity on Sandy Soil in Response to Some Soil-Improving Cropping Systems

“…Sandy soils are characterized by low crop productivity. This is mostly attributed to a weakly developed aggregated structure [8], high saturated hydraulic conductivity and permeability and low water-retention capacity due to the high contribution of large pores between sand particles [9][10][11], low nutrient levels, and poor ability to store and exchange nutrients [1]. Furthermore, after rapid dewatering, the large pores become air-filled first and act as a barrier (discontinuity) to water flow through the smaller pores towards the plant roots in unsaturated soil conditions [12,13].…”