Interview with Dr. Godson Ebenezer Adjovu—Winner of the Hydrology Best Paper Award

The Hydrology Best Paper Award is presented annually to recognize publications of outstanding quality, scientific significance, and broad impact. All papers published in Hydrology (ISSN: 2306-5338) in 2023 were eligible for consideration. Following a comprehensive evaluation of originality, scientific relevance, citation performance, and download metrics, the winning paper was selected. For more information about the award, please visit https://www.mdpi.com/journal/hydrology/awards/3765.

We are honored to have this conversation with Dr. Godson Ebenezer Adjovu, the first author of the winning paper:
“Spatiotemporal Variability in Total Dissolved Solids and Total Suspended Solids along the Colorado River”
by Godson Ebenezer Adjovu, Haroon Stephen and Sajjad Ahmad
Hydrology 2023, 10(6), 125; https://doi.org/10.3390/hydrology10060125

The following is an interview with Dr. Godson Ebenezer Adjovu:

1. Could you please give us a brief introduction of yourself (including your research field and research findings)?
I am Godson Ebenezer Adjovu. I earned my PhD in civil and environmental engineering from the University of Nevada, Las Vegas where my research focused on water quality monitoring using remote sensing and machine learning applications.
My research led to the development of machine learning models for the estimation of water quality parameters, mainly total dissolved solids (TDS) and total suspended sediments or solids (TSS), in the Colorado River Basin. The research was focused on the river system and Lake Mead located in the Colorado River Basin.
The use of gradient boosting, which is an ensemble machine learning model, was found to be optimal for the future estimation of TDS in Lake Mead using Sentinel-2 images.
The study proposed the utilization of eXtreme Gradient Boosting (XGBoost) for the estimation of TDS for the river system using images from both sensors used (i.e. Sentinel 2 and Landsat 8 OLI).The Adaptive Boosting (AdaBoost) and the Random Forest (RF) models were found to be optimal for TSS estimations for river system using Sentinel-2 MSI and Landsat 8 OLI images.
The findings from my research provide key stakeholders, water resource managers, and researchers with a perspective on the spatiotemporal dynamics of water quality parameters in water bodies as well as a cost-effective tool for deriving these water quality parameters in the basin which will go a long way in helping to improve the effective monitoring efforts of the fast-depleting water resources.

2. Could you briefly summarize the main findings or contributions of your award-winning paper?
The award-winning paper, as you mentioned earlier, is titled “Spatiotemporal Variability in Total Dissolved Solids and Total Suspended Solids along the Colorado River”.
The objective of this paper was to is to analyze the spatiotemporal variations in WQPs, specifically TDS and TSS concentrations along the Colorado River.
In this paper, we hypothesized that there is a significant variation in TDS and TSS concentrations along the Colorado River and that the reservoir storage influences the concentrations of these WQPs.
So, the Colorado River Basin, just to give a little bit of background, is a river system that encompasses seven states in the United States, which are subdivided into the Upper Colorado River Basin (UCRB) and the Lower Colorado River Basin (LCRB). The UCRB includes states such as Utah, Colorado, New Mexico, and Wyoming, and the LCRB includes Arizona, Nevada, and California. All these states depend on the river for water.
We found that the activities in these two basins are distinctive and may be a factor in these variations.
While the UCRB is characterized by mountainous terrain producing large amounts of snow melting and an increase in agriculture, mining, and energy development activities, the LCRB is made of several large reservoirs including Lake Mead and Lake Powell with huge storage which have the potential to effectively dilute the effects of dissolved salts.
These reservoirs, however, experienced large evaporations during the summertime which plays significant impacts on their TDS level. The byproducts of agriculture and mining practices such as sediments and fertilizers are transported and deposited in the river during rainfall and snowmelt, increasing the level of TSSs particularly in the UCRB.
Additionally, TSSs in the river basin are increased by natural erosion from neighboring watersheds which are aided by slope steepness and the land use land cover (LULC) of the region as well as channel and streambank erosion of the river basin.
Results from the significance test show there are statistically significant differences in TDSs and TSSs from month to month, season to season, and year to year. We suspect that these significant variations are largely due to the prolong drought in the basin leading to seasonal rises in consumptive use as well as agriculture practices, snowmelt runoff, and evaporation rates exacerbated by increased temperature in the summer months.
Additional research will need to be conducted to quantify the effect of flowrates, precipitation, LULC, channel modifications, and evaporation on the overall changes in TDS and TSS concentration in the river system.
So, basically, this was what the award-winning paper was about.

3. What was the biggest challenge you encountered during the research process? How did you overcome it?
Considering this research relies on data, the main issue has to do with data availability. The water quality data we used are freely available and span a period of 20 years. So, there was some gap in the data. We found some missing data that we had to overcome using data cleaning processes including imputation methods like interpolation processes.
Also, the presence of some missing data did not in any way affect the overall output of the study because the data, as I mentioned, cover a period of 20 years. This long-time span helps reduce potential biases that might have been introduced by conditions, such as drought, local events, and climatic variations.

4. How does it feel to receive the Best Paper Award? What does this recognition mean to you?
I’m extremely excited to receive this award, and I’m privileged to have been selected among several authors who have published this journal to receive this award. It is a very important recognition for me and for the team. This award means a whole lot to me, knowing that our efforts have been recognized, and it will definitely serve as great motivation for future pursuits and for contributing to the body of knowledge in advancing science.

5. What attracted you to submit your paper to Hydrology? What benefits do you believe authors gain from publishing in this journal?
We submitted to Hydrology largely due to its aim of being a focal point for addressing issues in integrated water management and its overall impact on the research community. Publishing in Hydrology offers authors the opportunity to have their work reach a greater audience and to make the desired impact with the needed credibility, due to the journal’s critical and robust peer-review process.

6. Which research topics do you think will be of particular interest to the research community in the coming years?
I am of the view that research in the development of advanced AI technology in water quality monitoring and resources management will be of great importance in future. That is developing technologies that can be able to quickly produce, estimate, or predict water quality information in real time to aid in decision-making.
Advanced technologies that can aid this include deep learning and data mining. Leveraging deep learning and data mining will be of great importance and will be something research community will be interested in.

7. Before we close, is there anything else you’d like to share—perhaps thoughts on how journals like Hydrology can better support researchers, or reflections that haven’t come up yet?
Thank you so much again for the opportunity. It is a great honor to be selected for this award, and there are few things I would like to share. Among these is the need for journals to initiate and improve incentive rewards such as this (Best Paper Award).
Generally, replicating this and having more of such initiatives will help motivate authors. Developing author engagement, I believe having dedicated sections with authors through features and engagements, either via social media or interviews, will be a motivating factor in encouraging more authors to conduct research.
I also believe that providing clearer and more streamlined guidance throughout the publication process would be very helpful. Last but not least, I believe that improving the peer-review process is of great importance to the research community, because research should be treated as a meaningful opportunity. Producing high-quality research requires experts who can conduct critical and thorough peer review. My suggestion is to involve more experts who are knowledgeable in particular fields in the peer-review process. Having such reviewers evaluate papers would have a significant impact and would greatly benefit the research community.