Data on 33 Years of Erroneous Usage of Rainfall Erosivity Equations

One of the most critical concerns facing our planet is the impact of climate change on the environment. As such, it is essential to incorporate environmental education into soil erosion modeling, such as the Universal Soil Loss Equation (USLE) family of models. The rainfall erosivity factor (R) is a crucial parameter studied in these models, but it requires high-frequency precipitation data for accurate determination. However, in data-sparse regions, researchers have relied on empirical equations for decades to estimate the R factor. Unfortunately, one of these empirical equations, based on the Modified Fournier Index (MFI), has been widely misused, and the scientific community has not noticed the errors. The database presented here hold information on studies conducted since 1989 that employed incorrect equations to calculate rainfall erosivity (R). Due to the nature of the search criteria, it was impossible to directly query any literature database to locate articles containing the incorrect R equations. To locate these articles, we spent an extensive amount of time manually searching through scholarly sources such as Scopus, Google Scholar, and other Internet platforms using a combination of keywords such as “soil erosion”, “ecosystem service”, “erosivity”, “1.735”, “1.753”, “0.08188”, ”0.8188”, and their variations. Initially, the literature search was limited to English-language papers and later expanded to include Chinese publications to establish the origin of the R equation misuse. We collected 125 articles, and their details were carefully recorded in an entity-relationship-based Microsoft Access database. Using SQL (Structured Query Language) queries, we were able to analyze the occurrence of the errors and better understand why they persisted for over 33 years without detection. The relational database is an invaluable tool for conducting detailed analyses, and it can be easily updated to add new incorrect studies to the database. Based on the information from the collected papers, we published a paper in Earth-Science Reviews [1] titled “A systematic review of the incorrect use of an empirical equation for the estimation of the rainfall erosivity around the globe” (DOI: 10.1016/j.earscirev.2023.104339). We hope that by raising researchers’ awareness of the incorrect use of the R empirical equations, we can prevent similar errors from occurring in the future.

Aside from the Earth-Science Reviews article’s supplementary data, which was an unstructured Word document (https://doi.org/10.1016/j.earscirev.2023.104339), an entity-relationship model was implemented to structure the data for the analysis of the incorrect R equations. This analysis led to the development of the current database. The entity-relationship diagram, also known as an E-R diagram, is depicted in Figure 1, which explains the way in which all of the data in the database are linked to one another using the appropriate relations. The relational database, which was normalized to the third normal form, was implemented using Microsoft Access. SQL was used to implement common queries. To enhance the user experience, we also developed a custom-made greeting screen for the database’s users, as shown in Figure 2. On the greeting screen, there are four buttons that are linked to four different SQL queries. These buttons can be used to accomplish the following actions:

The following procedures were utilized in order to collect the articles that had incorrect R equations:

This database is valuable because it contains 125 studies spanning 33 years (from 1989) that have used incorrect R equations to calculate rainfall erosivity in soil erosion estimation. The fact that the error has been discovered for the first time has implications for the accuracy of these 125 studies. Simple search commands cannot reconstruct this database’s data. Only by manually examining publications in Scopus, Google Scholar, and other Internet sources and tracking citations was it possible to compile the data. The data were recorded in an easy-to-use Microsoft Access database to facilitate the addition of additional studies employing incorrect R equations.

Other researchers may benefit from this database by skipping the laborious and time-consuming steps involved in obtaining these data and transforming them into a relational database.

It is possible to make use of the database to extend the currently conducted analysis of incorrect R equations [1]. Newly discovered articles from the past may be added to the database in order to conduct an in-depth analysis of the error pattern and provide insight into ways to prevent this kind of error from arising in future publications on soil erosion.

No patents have resulted from the work reported in this manuscript.