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The curation of hydrologic data includes quality control, documentation, database development, and provisions for public access. This article describes the development of new quality control procedures for experimental watersheds like the Walnut Gulch Experimental Watersheds (WGEW). WGEW is a 149 km2 watershed outdoor hydrologic laboratory equipped with a dense network of hydro-climatic instruments since the 1950s. To improve data accuracy from the constantly growing instrumentation networks in numerous experimental watersheds, we developed five new QAQC tools based on fundamental hydrologic principles. The tools include visual analysis of interpolated rainfall maps and evaluating temporal, spatial, and quantitative relationships between paired rainfall-runoff events, including runoff lag time, runoff coefficients, multiple regression, and association methods. The methods identified questionable rainfall and runoff observations in the WGEW database that were not usually captured by the existing QAQC procedures. The new tools were evaluated and confirmed using existing metadata, paper charts, and graphical visualization tools. It was found that 13% of the days (n = 780) with rainfall and 7% of the runoff events sampled had errors. Omitting these events improved the quality and reliability of the WGEW dataset for hydrologic modeling and analyses. This indicated the effectiveness of application of conventional hydrologic relations to improve the QAQC strategy for experimental watershed datasets.

The suggested method concerns detailed quantitative rebuilding of textural characteristics of the subsoil in plain areas. The key point of the proposed approach relates to the organisation, georeferencing and code translation of stratigraphic data pertaining to water wells present in the study area. Stratigraphic data is stored and codified in a specific hydraulic database, TANGRAM, in order to assign percentage values for each textural class (gravel, sand, clay) to each well level. This data is then extracted and processed using three dimensional modelling software, GOCAD. Spatial data of the study area (topographic surface and aquifer bottom) is processed using an external GIS or directly on the GOCAD, to build a 3D grid between the two surfaces resulting in proportionally shaped cell thickness values. Gravel, sand and clay (textural class) percentages are assigned to each cell located in association with each georeferenced well using the "Discrete Smooth Interpolator" (DSI Mallet 1992) or geostatistic techniques. Values are interpolated in every dimensional cell of the grid to provide the 3D reconstruction of subsoil textural distribution. Processing can refer to either shallow or deep aquifers. An example of this method was used in the plain area in Alessandria (Piemonte, North-west Italy) and is illustrated in this paper and the relative codified stratigraphic files of the wells have already been completed. 3D rebuilding of subsoil textural distribution can be used as an input data starting point for many hydrogeological applications, such as mass-balance evaluation of a hydrogeological system, groundwater flow and pollutant transport models.