Abstract. 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.

Considering all the alterations on hydrology and water quality that urbanization process brings, permeable pavement (PP) is an alternative to traditional impermeable asphalt and concrete pavement. The goal of the PP and other low impact development devices is to increase infiltration and reduce peak runoff flows. These structures are barely used in Brazil aiming stormwater management, one of the big hydrological issues in cities throughout the country, with increasing urbanization rates. The main objective of this paper is the hydraulic characterization of a PP and the assessment of its hydrological efficiency from the point of view of the infiltration process. The study focuses on a pilot area in a parking lot in an urban area (Recife, Brazil). Soil elements filling the voids between concrete elements were sampled (particle size density, water contents) and tested with water infiltration experiments at several points of the 3 m × 1.5 m surface pilot area. Beerkan Estimation of Soil Transfer parameters algorithm was applied to the infiltration experiment data to obtain the hydraulic characteristics of the soil composing the PP surface layer, the concrete grid pavers (with internal voids filled with natural soil) permeability being neglected. Results show that the soil hydraulic characteristics vary spatially within the pilot area and that the soil samples have different hydraulic behaviours. The hydraulic characteristics derived from Beerkan Estimation of Soil Transfer parameters analysis were implemented into Hydrus code to simulate runoff, infiltration and water balance over a year. The numerical simulation showed the good potential of the PP for rainfall-runoff management, which demonstrates that PP can be used to retrofit existing parking infrastructure and to promote hydrological behaviour close to natural soils. Figure 6. Box-plots of the scale parameters, saturated hydraulic conductivity (K s in mm/s) and scale parameter for water pressure head (h g in mm) sorted by soil type for BEST Slope (BS), BEST Intercept (BI) and BEST Steady (BSst) 4249

Knowledge about soil moisture dynamics and their relation with rainfall, evapotranspiration, and soil physical properties is fundamental for understanding the hydrological processes in a region. Given the difficulties of measurement and the scarcity of surface soil moisture data in some places such as Northeast Brazil, modelling has become a robust tool to overcome such limitations. This study investigated the dynamics of soil water content in two plots in the Gameleira Experimental River Basin, Northeast Brazil. For this, Time Domain Reflectometry (TDR) probes and Hydrus-1D for modelling one-dimensional flow were used in two stages: with hydraulic parameters estimated with the Beerkan Estimation of Soil Transfer Parameters (BEST) method and optimized by inverse modelling. The results showed that the soil water content in the plots is strongly influenced by rainfall, with the greatest variability in the dry–wet–dry transition periods. The modelling results were considered satisfactory with the data estimated by the BEST method (Root Mean Square Errors, RMSE = 0.023 and 0.022 and coefficients of determination, R2 = 0.72 and 0.81) and after the optimization (RMSE = 0.012 and 0.020 and R2 = 0.83 and 0.72). The performance analysis of the simulations provided strong indications of the efficiency of parameters estimated by BEST to predict the soil moisture variability in the studied river basin without the need for calibration or complex numerical approaches.