GeoDAR: Georeferenced global dam and reservoir dataset for bridging attributes and geolocations

Dams and reservoirs are among the most widespread human-made infrastructure on Earth. Despite their societal and environmental significance, spatial inventories of dams and reservoirs, even for the large ones, are insufficient. A dilemma of the existing georeferenced dam datasets is the polarized focus on either dam quantity and spatial coverage (e.g., GOODD) or detailed attributes for limited dam quantity or regions (e.g., GRanD and national inventories). One of the most comprehensive datasets, the World Register of Dams (WRD) maintained by the International Commission on Large Dams (ICOLD), documents nearly 60,000 dams with an extensive suite of attributes. Unfortunately, WRD records are not georeferenced, limiting the benefits of their attributes for spatially explicit applications. To bridge the gap between attribute accessibility and spatial explicitness, we introduce the Georeferenced global Dam And Reservoir (GeoDAR) dataset, created by utilizing online geocoding API and multi-source inventories. We release GeoDAR in two successive versions (v1.0 and v1.1) at https://doi.org/10.6084/m9.figshare.13670527. GeoDAR v1.0 holds 21,051 dam points georeferenced from WRD, whereas v1.1 consists of a) 23,680 dam points after a careful harmonization between GeoDAR v1.0 and GRanD and b) 20,214 reservoir polygons retrieved from high-resolution water masks. Due to geocoding challenges, GeoDAR spatially resolved 40 % of the records in WRD which, however, comprise over 90 % of the total reservoir area, catchment area, and reservoir storage capacity. GeoDAR does not release the proprietary WRD attributes, but upon individual user requests we can assist in associating GeoDAR spatial features with the WRD attribute information that users have acquired from ICOLD. With a dam quantity triple that of GRanD, GeoDAR significantly enhances the spatial details of smaller but more widespread dams and reservoirs, and complements other existing global dam inventories. Along with its extended attribute accessibility, GeoDAR is expected to benefit a broad range of applications in hydrologic modelling, water resource management, ecosystem health, and energy planning.

Attribute accessibility, normative influence, and the effect of classical and country music on willingness to pay for social identity and utilitarian products

Previous studies indicate that background classical music is associated with customers in retail and leisure premises being prepared to pay more for various products and services. This online experiment tests whether these effects are due to music increasing the salience of valued product attributes (attribute accessibility hypothesis) or to a demand characteristic wherein music implies a norm to purchase expensive items (normative behavior hypothesis). A 3 (type of music—classical, country, no music, between subjects) × 2 (type of product—social identity or utilitarian, within subjects) × 2 (high vs. low incentive for accuracy, between subjects) mixed design was used in which participants stated the specific amount they would be prepared to pay for 30 products using free-choice format. Results showed a Music × Type of Product interaction, such that preparedness to spend was higher in the classical music condition but only in the case of social identity products. This is more consistent with the attribute accessibility hypothesis than the normative behavior hypothesis, and various commercial and practical consequences of these findings are discussed.