## 3 Methodology
\begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{2}{c}{**Research Question**} & **Inspiration** & **Technique** \\ \hline RQ1 & What are the publication trends in groundwater level changes using ML and MM approaches? & To categorize studies and evaluate their foci, dominant venues, and contributions. Trends can be examined throughout time depending on the quantity of studies. These data will show the scientific community where there are gaps in the domain. \\  & & To identify the several ML and MM techniques that are currently being utilized to predict groundwater level changes. This will reveal which method is the most popular. It will also reveal why it is the most popular option. Researchers will be able to see the potentials and/or lack of concentration in various ML and MM methodologies based on this information. \\  & & To determine the present impact of ML and MM approaches on groundwater level changes, as well as to study and categorize existing ML and MM approaches for groundwater level changes based on the specific challenges they attempt to solve. \\ RQ4 & What will be the research focus in the future? & To determine the present impact of ML and MM approaches on groundwater level changes, as well as to study and categorize existing ML and MM approaches for groundwater level changes based on the specific challenges they attempt to solve. \\  & & This topic aims to suggest future ambitions for researchers and practitioners in using ML and MM methodologies to predict groundwater level changes. \\  & & It provides newbie researchers with information on current subjects of interest in the domain. \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Review interrogations and motivation. Other publications were found through a search on Google Scholar and Google, based on our study's topic and objectives. From Scopus, Google Scholar, and Google search, there were a substantial number of duplicate articles. The problem of duplication was solved using [PERSON]'s automatic duplicate elimination procedure. We examined if the title, keywords, and DOI of the records in the CSV file were the same, and eliminated the duplicates accordingly to ensure the process's credibility. After removing duplicates, the screening procedure began with 410 records, which included the inclusion and exclusion criteria. Two reviewers worked simultaneously and independently to qualify the titles of articles that would be kept or eliminated. In some cases, the reviewers submitted article titles for consideration to third-party reviewers who are experts in the field. The agreement was the final judgment if both critics agreed to maintain or remove a certain record. In the end, 290 reports were assessed for eligibility (Figure 3). The papers were randomly assigned to five reviewers from two different higher education institutions. Each reviewer evaluated the allocated records to see if they fulfilled the exclusion and inclusion criteria. The exclusion and inclusion criteria were used to keep or remove papers that were more relevant to our topic. For this study, a report may have been removed (a) or met (b) the criteria on:  
* Exclusion criteria: Our research disqualifies any report that meets the following criteria:
* There were no full texts available. As a result, 98 reports were deemed unfit;
* Titles were not in the scope of our study. As a result, 54 reports were discarded;
* Original research was not presented in the abstracts. As a result, 30 reports were deleted;
* The articles were written in non-English language. As a result, 13 reports were removed. Figure 3: The PRISMA diagram for inclusion and exclusion criteria of literature. * means all the records were from Scopus, whiles ** means the records were discarded in its entirety. * Inclusion criteria: Reports that matched the following criteria were included in our research:
* The articles are published in English, and the abstracts contain original research on the topics;
* Articles in our scope introduce machine learning and mathematical model techniques.