Application of Agent-Based Modeling in Agricultural Productivity in Rural Area of Bahir Dar, Ethiopia
Round 1
Reviewer 1 Report
The authors present an ABM and crop productivity model in Ethiopia. The paper is of interest to the readership of the journal. I suggest acceptance in present form.
Author Response
Dear Reviewer,
Thank you very much for your time you gave us to review our manuscript. We really appreciate it.
Many thanks,
Authors
Reviewer 2 Report
The under review article presents the coupling of an agent-based model and a crop productivity model for studying farmers’ management decisions on maize productivity under different rainfall scenarios in Rim kebele, Amhara Region of Ethiopia.
In particular, this research work is identifying the main crop grown in the kebele, studying crop productivity of farmers under different rainfall conditions, assessing the impact of agents’ forecast adoption rates into kebele crop productivity and finally exploring ways to optimize forecast adoption. ABM was used to determine the adoption rates of farmers which were then used in the agriculture simulation model to understand crop responses to different farmer decisions. The effectiveness of this method is verified experimentally and the results indicate that the proposed model can meet the needs of agricultural production.
The methodology which is followed in the proposed approach is clearly defined and supported by adequate experiments permitting other researchers to reproduce certain aspects of their results. Additionally, the methodology analysis as well as the results are enriched with an efficient number of properly presented tables, figures and charts. Finally, the paper is well-structured and in general written in appropriate and understandable English language according to the standards of the Journal. However, some spell check might be needed.
Nevertheless, although the article is interesting in general, the authors should pay more attention in the Introduction section in order to substantiate and clarify the novelty of the proposed solution. Additionally at the end of the introduction section a paragraph is suggested to be added, including the structure of the remainder of the article.
Author Response
Dear Reviewer,
Thank you very much for your valuable feedback. We really appreciate your time you gave us to improve our manuscript. We have attained to your comments. We worked on the spell checks. We have improved our Introduction section with your comments and added some literatures to enhance the manuscript structure. We also restructured the abstract section.
Many thanks,
Authors
Reviewer 3 Report
General comments
This is an interesting study that can address climate change and sustainability challenges facing farmers in Ethiopia. However, it is not ready for publication due to the reasons listed below.
The abstract needs restructuring, a description of the methodology is provided between results. The description of the method in the abstract is thin and leaves out useful summary of the model, for instance the input data source, how the Agent Based Model (ABM) was coupled to the crop productivity model among others. It is also unclear what findings come from the model and which one come from the household survey, if any.
There is a lot of repetition in the paper particularly of statements discussing the utility of weather forecasts. The structure of the paper needs a lot of editing to ensure it is coherent and similar themes are discussed at the same place and not scattered throughout the paper.
The ABM and its link to the other models are poorly defined and needs sufficient details for readers to understand what was done. For instance, there is no description the variables used, at what time scale and space. Who are agents? How was agricultural productivity defined? For what crops? Over what time? Under what environmental conditions? What is the level of model uncertainty? Was there any validation done? Besides citing some published literature, the authors do not explicitly discuss how each step in the ABM was done and why it was done. Explicit details on the execution of the model would be useful for readers who do not have time to read the literature cited in this section.
Specific comments
- The abstract needs restructuring, a description of the methodology is provided between results. The description of the method in the abstract is thin and leaves out useful summary of the model, for instance the input data source, how the Agent Based Model (ABM) was coupled to the crop productivity model among others. It is also unclear what findings come from the model and which one come from the household survey, if any.
- The study area is sometimes referred as ‘Rim Kebele, other times it is called, the kebele or kebele. Choose one description to use throughout the manuscript. The spelling of kebele has capital K in some instances whereas in others, the k is not capitalised.
- Line 17 – what experiments were conducted and why?
- Line 30 – what resources need to be used effectively?
- Line 30-31- how does water and food security challenge management of crop productivity?
- Line 94-96 is unclear and needs rewriting.
- There is a lot of repetition in the narrative in Section 1.5, lines 87-112. Even though the sentences are different, most of them say the same thing. The paragraph needs tightening and rearranging the flow of the narrative.
- Line 116 – the sentence Another main reason of limited adoption….indicates there are several reasons for limited adoption of weather forecasts. What are these reasons?
- Line 124-125 – briefly give examples of some applications of ABMs in agricultural systems and how they addressed innovation diffusion.
- Line 138-154 – give examples of studies where DSSAT has been used and if it has been applied to Ethiopia or areas with similar agricultural environment.
- Section 2.1 the description of the study area is thin. Only the location has been described. Considering this is a manuscript on climate and involves farming, one would expect a description of biophysical and socio-economic factors in the study area. These need to be included.
- Section 2.2 – What kind of survey questions were asked? Who were the local experts asked these questions? What distinguishes local experts from local non-experts? Line 179 – what level of detail were the questions reviewed? How many local experts were surveyed and how many farmers were surveyed? How many surveys were done in each village and why? Line 178 what household data collection methods were used?
- Figure 2 – what is early rain, intermediate rain, late rain, dry and wet? Were these descriptions explained to the farmers/experts?
- Section 2.4 discusses results while the entire section 2 should be on ‘materials and methods’. This is confusing.
- Lines 218-220 – ‘We use agents’ adoption rates coupled with crop productivity model to assess the impact of farmers’ decisions on agricultural productivity (Figure 3).’ This is very general description of what was done. It would be useful to the readers if the authors can specify the variables used, at what time scale and space. Who are agents? How was agricultural productivity defined? For what crops? Over what time? Under what environmental conditions?
- Line 241-how far or near should a farmer be to be considered a neighbour?
- Line 245-248-what is the difference in the four extension agent workers? How does the ABM distinguish them?
- Lines 256-260 it is unclear how the LTA was calculated based on published literature and information from the surveys. How the calculation was done is important to allow the results to be reproduced by others.
- Line 261-262 – what is the size of the ‘predetermined radius’? How and why was it predetermined?
- Line 263 – how does the model differentiate treat the performance of farmers, friends and relatives?
- Lines 263-265-how is the effective communication between farmers and researchers modelled in the ABM?
- Lines 261-284 – so much information on the specific variables used in the model is missing. HOW the interactions between the variables were treated in the ABM is missing. This section is very descriptive and besides citing some published literature, the authors do not explicitly discuss how each step was done. Explicit details on the execution of the model would be useful for readers who do not have time to read the literature cited in this section.
- Line 270-271 – How does the model know the information has been delivered effectively? Was there an indicator for ‘effectiveness in information delivery’/’influence level’?
- Lines 286-288 – what was the timeframe for the Climagen SC data?
- Lines 300-301 – specify the rainfall range for early, normal and late.
- Lines 370-373 – information on these lines read like they should be in the material and methods section.
- Lines 418-420 –how can the challenges hindering farmers interactions be addressed to improve the maize production to the levels indicated in these lines? Have other studies assessed these challenges?
- Lines 491-495 – are there global or even African studies that have addressed ways of improving forecast accuracy and how it can influence crop production? What do the authors of this study propose to improve forecast accuracy?
- Definition of terms such as normal, early and late are not clear and abbreviations used in figure 2 are not explained.
Author Response
Dear Reviewer,
We are really thankful for your valuable feedback and comments to improve our manuscript. We have attained to your comments and it significantly improved our manuscript. We kindly attached our responses and improvement notes below.
We once again appreciate your time you gave us to improve our work.
Best Regards,
Authors
Author Response File: Author Response.docx
Round 2
Reviewer 3 Report
I thank the authors for the revising their paper, which has improved from the previous version.
However, most of the comments addressed in the cover letter were not included in the revised manuscript and the methodology still remains sketchy, and challenging to follow and replicate.
The questionnaire should be included in the manuscript as ‘supporting information’ so readers can refer to it and link it to the discussion and rationale of the paper.
The connection between different data streams/models/results need to be highlighted and discussed clearly.
Figure 2 caption still remains inadequately described and the use of different words to describe similar concepts is confusing.
Author Response
We really appreciate your feedback and time you gave us to improve our manuscript. Kindly attached the file to attain the feedback.
Author Response File: Author Response.docx