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.

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Abstract. In this paper, we present and analyze a global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database, for the first time. 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 USA. In addition to its global spatial coverage, the collected infiltration curves cover a time span of research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use were gathered along with the infiltration data, which makes the database valuable for the development of pedo-transfer functions 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 the land use is available for 76 % of 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 use by public domain only and can be copied freely by referencing it. Supplementary data are available at doi:10.1594/PANGAEA.885492. Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend/update the SWIG by uploading new data to it.

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Restoration ecology that maximizes ecosystem services (ES) requires planning at large spatial scales, which are often the most meaningful for ecosystem functioning and ES supply. As economic resources to undertake ecological restoration at large scales are scarce, prioritizing sites to enhance multiple ES supply is critical. We present the Relative Aggregated Value of Ecosystem Services (RAVES) index, to prioritize sites for ecological restoration based on the assessment of multiple ES. We tested the spatial heterogeneity of ES to identify the relevant scale to managing ES and to apply the RAVES index using a local case study. We also used the RAVES index to compare three alternative restoration scenarios to enhance ES based on the availability of socio‐economic resources. The highest RAVES values were found in areas with natural vegetation and in gorges with riparian forests. The lowest values were found in crop fields, steep slopes and river stretches without riparian forest. The multiscale spatial analysis indicated that most ES showed significant heterogeneity at multiple spatial scales, especially at broad (20–30 km) and very broad (40–50 km) scales. For spatial scales smaller than 2 km, only biological control showed significant heterogeneity. The optimal socio‐economic conditions to enhance ES supply were met when both private and public land, together with economic funds, were available to implement ecological restoration. As most areas with low RAVES were in private lands, even with limited funds restoration of private lands would result in a large increase in RAVES. Synthesis and applications. The Relative Aggregated Value of Ecosystem Services (RAVES) index is a practical tool to hierarchically prioritize sites for ecological restoration across large spatial scales. The RAVES index integrates both ecological information and societal values by weighting ecosystem services (ES) via a multicriteria analysis and can be used in scenario analysis to identify optimal management scenarios. We highlight the importance of analysing the spatial heterogeneity of ES to identify the most relevant scale to applying the RAVES index and to managing ES via ecological restoration.

Please cite this article in press as: Comín, F.A., et al., A protocol to prioritize wetland restoration and creation for water quality improvement in agricultural watersheds. Ecol. Eng. (2013), http://dx.doi.org/10.1016/j.ecoleng.2013.04.059 ARTICLE IN PRESSG Model ECOENG 2560 1-9 Ecological Engineering xxx (2013) xxx-xxx Contents lists available at SciVerse ScienceDirectEcological Engineering j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / e c o l e n g A protocol to prioritize wetland restoration and creation for water quality improvement in agricultural watersheds With adequate planning, wetland restoration and creation can be useful tools for improving the water quality of natural ecosystems in agricultural territories. Here, a protocol for selecting wetland-restoration sites at the watershed scale is proposed as part of a demonstration project (EU Life CREAMAgua) for improving wastewater from irrigated agricultural land discharging into the Flumen River (Ebro River Valley, NE Spain). This watershed is semiarid, and 70% of its 1430-km 2 area is used for irrigated agriculture. A preliminary study of the physical and chemical characteristics of the Flumen River and its watershed identified nitrates as the key water-quality characteristic in terms of data variability. The protocol consisted of five steps that encompassed scientific-technical, social and economic criteria. The first step was to select all of the sites in the watershed that had the hydrogeomorphic characteristics of a wetland. The second step was to estimate the levels of nitrate discharge through all of the tributaries discharging to the river and to select the sub-watersheds that contributed the most nitrates. The program SWAT (Soil and Water Assessment Tool), which considers the biophysical characteristics and land uses of the watershed, including farming practices, was utilized in these first two steps. In the third step, a first-order arearemoval model was used to rank wetlands for nitrate removal. The wetland sites that were estimated to be most efficient for nitrate removal were selected. These wetland sites were located in the agricultural zone within the watershed, where fertilizers and irrigation are intensively used. In the next step, the previously selected sites were considered based on a social-availability criterion (the potential to obtain at no cost the land required to restore or create wetlands at those sites). Finally, the concordance between site availability and funding was used to sequentially select 15 sites (135 ha) that would be cost-effective for the Flumen River watershed project, which provided a case study. This protocol is compared to previously published protocols with the same purpose, and the applications of this procedure are discussed in terms of up-scaling and integrating experience in land-use and agricultural policies.

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