Soil loss tolerance in calcareous soils of a semiarid region: evaluation, prediction, and influential parameters

Abstract

Predicting soil loss tolerance (T‐value) as a first and crucial step in assessing soil erosion using pedotransfer functions (PTFs) could save time and cost. Therefore, this study aimed to evaluate T‐value and its influential parameters for calcareous soils of the Dorudzan Watershed, Fars Province, Iran, and to develop PTFs for its prediction using easily measureable soil properties. T‐value was determined in 60 soil profiles based on the soil thickness method. Various basic soil properties were used to develop five PTFs using stepwise multiple linear regression. T‐value varied from 3.5 to 22.5 with a mean value of 10.4 t ha−1 yr−1, which is approximately equal to the proposed value by US Department of Agriculture (11 t ha−1 yr−1). T‐value in Inceptisols located in the dam shore and agricultural lands was significantly higher than that of Entisols located in the forest and rangelands. Organic matter (OM) with a correlation coefficient of .77 with T‐value was the most influential variable in prediction of T‐value. The PTF 5, which used OM, soil aggregate stability, and permeability, with the highest R2 (0.72 and 0.79), the lowest mean error (−0.44 and 1.75 t ha−1 yr−1), the lowest root mean square error (2.98 and 2.75 t ha−1 yr−1) and the minimum Akaike information criterion (51.1 and 17.2) provided the best predictions for T‐value. However, when considering the acceptable indices and easier measureable soil properties (OM, soil erodibility, and pH) in PTF 3, we concluded that it was the best model to predict T‐value. Generally, the application of thickness method is recommended to determine T‐value in semiarid regions.

A Comparative Analysis of Soil Loss Tolerance and Productivity of the Olive Groves in the Protected Designation of Origin (PDO) Areas Norte Alentejano (Portugal) and Estepa (Andalusia, Spain)

“…In this sense, there are studies aimed at developing these indices from a methodological point of view, with the research of Li et al [26] and Duan et al [28] standing out, while other studies focus their applicability on how erosive processes affect the degradation of calcareous soil environments [58,63]. However, their use in agricultural environments and specifically in olive groves is novel, showing in general terms how erosive phenomena lead, in the long term, to the loss of fertility and soil horizons, minimising the sustainability of the crops [31,[78][79][80]. The present research consolidates, together with other similar studies, the necessary bases for the development of specific indices aimed at quantifying the estimation of the economic and environmental sustainability of these agricultural systems [40,[63][64][65].…”

“…In general terms, irrigation is considered an agricultural intensification measure that contributes to soil degradation, negatively affecting the long-term sustainability of agriculture [12,40]. However, in the study area, where a deficit/drip irrigation regime predominates in olive groves, the impacts derived from the addition of water to farms as a measure of intensification were minimised, improving water use efficiency and vegetative growth control [79][80][81]. Specifically, the addition of drip water in areas with water stress can nonetheless enhance the magnitude of soil erosion, driving the need for more efficient and integrated soil-water management practices [31,82].…”

“…This indicates a degree of sustainability even higher than that in the organic olive groves of the PDO Estepa, which are characterised by values of 140.89 t ha −1 year −1 . If soil loss tolerance is defined as the maximum annual soil degradation value permissible to guarantee the sustainability of an agricultural system over time [58,63,[78][79][80], the higher soil loss tolerance detected in the Portuguese integrated olive groves may be due to their shorter history, a fact that would explain that the soil degradation processes hampering the sustainability of these systems may have not yet appeared [3,4,13]. In addition, both the traditional and intensive olive groves in Portugal presented lower values of soil loss tolerance than the integrated and organic olive groves of the PDO Estepa, the intensive olive groves being those with the lowest results across the analysed timescale projections.…”

Improving Infiltration Prediction by Point-based PTFs for Some Soils in Southern of Iran

“…The moisture deficits in semi-arid regions, such as in Iran, cause the development of calcium carbonate (CaCO3) (Baumhardt and Lascano 1993). The presence of carbonates in soils display alkaline pH and an exchange complex dominated by Ca 2+ (Ostovari et al 2017;Ostovari et al 2020). In addition, carbonates can promote soil structure (Blume et al 2016).…”

Statistical Modeling for Spatial Groundwater Potential Map Based on GIS Technique

“…MLR can also determine the relative influence of one or more predictor variables and identify outliers or anomalies [6,10]. Geographic information systems (GIS) as a visual tool provides applicable methods for manipulating spatial data [11] because these tools have prepared a timeand cost-saving way for groundwater quality evaluation [12,13]. Hence, groundwater quality mapping integrated with statistical modeling has been widely used for carrying out successful groundwater protection and management programs [1][2][3].…”