Development and analysis of the Soil Water Infiltration Global database.

In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (~76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76% of the experimental sites with agricultural land use as the dominant type (~40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it

Assessing the accuracy of TDR-based water leak detection system

The use of TDR system to detect leakage locations in underground pipes has been developed in recent years. In this system, a bi-wire is installed in parallel with the underground pipes and is considered as a TDR sensor. This approach greatly covers the limitations arisen with using the traditional method of acoustic leak positioning. TDR based leak detection method is relatively accurate when the TDR sensor is in contact with water in just one point. Researchers have been working to improve the accuracy of this method in recent years.In this study, the ability of TDR method was evaluated in terms of the appearance of multi leakage points simultaneously. For this purpose, several laboratory tests were conducted. In these tests in order to simulate leakage points, the TDR sensor was put in contact with water at some points, then the number and the dimension of the simulated leakage points were gradually increased. The results showed that with the increase in the number and dimension of the leakage points, the error rate of the TDR-based water leak detection system increases.The authors tried, according to the results obtained from the laboratory tests, to develop a method to improve the accuracy of the TDR-based leak detection systems. To do that, they defined a few reference points on the TDR sensor. These points were created via increasing the distance between two conductors of TDR sensor and were easily identifiable in the TDR waveform. The tests were repeated again using the TDR sensor having reference points. In order to calculate the exact distance of the leakage point, the authors developed an equation in accordance to the reference points. A comparison between the results obtained from both tests (with and without reference points) showed that using the method and equation developed by the authors can significantly improve the accuracy of positioning the leakage points. Keywords: Multiple leakage points, TDR, Reference point

Influence of Different Slope Aspects on Some Soil Properties and Forest Soils Evolution (Case Study: Rostam Abad Region, Guilan Province)

Introduction: Spatial variation of soil properties is significantly influenced by numerous environmental factors such as landscape features, including position, topography, slope gradient and aspect, parent material, climate and vegetation. Soil properties vary spatially in south- and north-facing hill slopes. This factor (different slope aspects) can affect the distribution of soil organic matter, the presence or absence of a layer, pH, nutrient levels, soil mineralogical and micromorphological properties. Topographic factors such as the orientation of the hill slope and the steepness of the slope affect microclimate, vegetation establishment, water movement and erosion. Aspect and slope control the movement of water and materials in a hill slope and contribute to differences in soil properties. Temperature, precipitation and climate vary with elevation and influence pedogenic processes. Accelerated rates of weathering and soil development were found to occur in soils on south-facing slopes. Slopes with a south aspect are dominated by stone and bare soil patches, while slopes with a north aspect are dominated by biotic components. Northern slopes have higher productivity and species diversity compared to Southern slopes. Slope aspect has a significant effect on the composition, species richness, structure and density of plant communities, differed significantly between North- and South- facing slopes. Materials and Methods: In the present study, the effects of two slope aspects on some soil properties and soil evolution was investigated in Northern Rostam Abad region in the Guilan Province. Five profiles in Southern hill slope(South-facing hill slopes) and five profiles in Northern hill slopes(North-facing hill slopes) with 40% slope and same parent material (basaltic andesite) and same plant cover were dug. The elevation of two slope aspects was 240 meters from the sea level. Average annual temperatures and precipitation are16 degrees centigrade and 1359 mm, respectively. Thus, the soil moisture and temperature regimes are udic and thermic, respectively. The physical and chemical analysis were carried out on soil samples including particle size distribution, bulk density, pH, organic carbon, total nitrogen, available phosphor and cation exchange capacity. This study was done in a completely randomized design several observational with five replications. The total of 34 soil samples were collected in the two slope aspect of the profile and all samples were tested and statistical analyzed. For the micromorphological study, thin sections were prepared from undisturbed samples. The samples were impregnated with polyester resin and later sectioned. The thin sections were prepared and analyzed in petrographic microscope equipped with polarized light. Results and Discussion: The results of multivariable analysis of variance (MANOVA) and Hotteling's T2 showed that there is significant different in soil properties between two hill slopes(p≤0.01). Also, the results of t-test showed the values of pH, content of sand, sand to clay ratio and available phosphorous significantly was higher in Southern hill slope in comparison with Northern hill slope(p≤0.01). Whereas, clay content and cation exchange capacity significantly were higher in Northern hill slope in comparison with Southern hill slope(p≤0.05). Also observed micromorphological studies showed biological activity was stronger in Northern hill slope in comparison with Southern hill slope. Properties observed in thin sections of Northern slope aspect include fungal hyphae, spherical and ellipsoid excrement of microorganisms in root residual (related to oribatid mites) which indicated stronger biology in Northern slope aspect soils as compare to Southern slope aspect soils. Also, more accumulates* of clay inside voids, nodules, fragmented of coating of well-oriented, micro laminated, reddish-brown clay, chamber voids in Northern slope soils toward Southern slope soils were observed. B-fabricobserved in Northern hill slope soils is stipple speckled in surface horizons and in subsurface horizons is grano-striated and stipple speckled and b-fabric observed in Southern hill slopes soils in surface horizons and subsurface horizons is stipple speckled. Conclusion: Higher content of clay, Cation exchange capacity, Accumulation of clay in pores, Fragments of clay coating (papule), chamber pores, Fe/Mn oxide nodule and micro-laminations in Northern hill slope and higher values of pH, higher content of sand, sand to clay ratio and available phosphorous, lithorelict in Southern hill slope showed that weathering was higher in Northern hill slope in comparison with Southern hill slope. Generally, Southern hill slope had less developed soils (Entisols and Udorthents great group) and Northern hill slope had high developed soils (Alfisols and Hapludalfs great group)

Assessing soil organic carbon stocks under land-use change scenarios using random forest models

Identifying changes in soil organic carbon stocks (SOCS) is essential for determining appropriate ways to deal with land degradation, for understanding soil and crop management and for gathering useful information for a range of environmental studies. The aim of this study was to predict SOCS and compare under current and potential future land uses. Soil organic carbon (SOC) and bulk density were measured at 137 locations across the Marivan, Kurdistan Province, Iran, and soil SOCS was computed. Auxiliary data including, terrain attributes and Landsat 8 ETM+ data were acquired. Random forest (RF) models were used to relate the SOCS to the auxiliary data. Results suggested that the mean SOCS in the topsoil and subsurface in croplands were lower than in forestland and wetland, although not significantly so. In the area, approximately 18.48% of forestland and 17.39% of wetland has been brought into cultivation. The authors estimate that this has led to a loss of SOCS from forestland topsoil of 22,860 Mg C, and from subsurface of 15,685 Mg C. The SOCS loss from wetland topsoil and subsurface were not as great, at 4193 and 2680 Mg C, respectively, but this was due to the area not being as large

Towards robust smart data-driven soil erodibility index prediction under different scenarios

Soil erosion is a major cause of damage to agricultural lands in many parts of the world and is of particular concern in semiarid parts of Iran. We use five machine learning techniques—Random Forest (RF), M5P, Reduced Error Pruning Tree (REPTree), Gaussian Processes (GP), and Pace Regression (PR)—under two scenarios to predict soil erodibility in the Dehgolan region, Kurdistan Province, Iran. Our models are based on a variety of soil properties, including soil texture, structure, permeability, bulk density, aggregates, organic matter, and chemical constituents. We checked the validity of the models with statistical metrics, including the coefficient of determination (R2), mean absolute error (MAE), root mean squared error (RMSE), T-tests, Taylor diagrams, and box plots. All five algorithms show a positive correlation between the soil erodibility factor (K) and silt, sand, fine sand, bulk density, and infiltration. The GP model has the highest prediction accuracy (R2 = 0.843, MAE = 0.0044, RMSE = 0.0050). It outperformed the RF (R2 = 0.812, MAE = 0.0050, RMSE = 0.0061), PR, (R2 = 0.794, MAE = 0.0037, RMSE = 0.0052), M5P (R2 = 0.781, MAE = 0.0043, RMSE = 0.0053), and REPTree (R2 = 0.752, MAE = 0.0045, RMSE = 0.0056) algorithms and thus is a useful complement to studies aimed at predicting soil erodibility in areas with similar climate and soil characteristics