Integrating Hourly Scale Hydrological Modeling and Remote Sensing Data for Flood Simulation and Hydrological Analysis in a Coastal Watershed
Round 1
Reviewer 1 Report
The author's work (Integrating Hourly-Scale Hydrological Modeling and Remote Sensing Data for Flood Simulation and Hydrological Analysis in a Coastal Watershed) generally represents a good contribution to the field of study. Nevertheless, specific corrections and clarifications must be addressed before the manuscript can be deemed suitable for publication. Certain sections would benefit from additional information or data to support the author's claims and strengthen the research findings. There are areas where further clarification is needed to enhance the reader's understanding.
Below are my comments and questions. I'm looking forward to receiving your clarifications and explanations, which I suggest you incorporate into the relevant sections of your manuscript.
1. How does the study address hourly simulations' limited scope and usage history with the SWAT model?
2. Could you discuss potential real-world applications or decision-making scenarios where the findings and insights from this study could be applied?
3. What key features make the SWAT model versatile in simulating various temporal scales?
4. Could you provide additional context on the source of the statistics regarding the global frequency of natural disasters?
5. Could you elaborate on the technical aspects that enable the hourly scale to capture flow variability with "high-resolution time intervals"? How does this feature contribute to improved simulation of watershed floods?
6. How does this study aim to contribute to the understanding of hourly scale simulations of the SWAT model? What specific objectives does the study have regarding shedding light on strengths, shortcomings, and parameterization processes?
7. What are some of the key characteristics of the Ashida River that make it significant for the study? How does its course through Fukuyama City contribute to the overall hydrological dynamics of the area?
8. Could you elaborate on the significance of the average annual precipitation of around 1814 mm? How does this precipitation level contribute to the study area's overall hydrological dynamics?
9. Could you elaborate on the topographical variations within the study area, ranging from elevated terrain to lower terrain? How do these topographical features contribute to the distribution of water and runoff patterns?
10. What factors influenced the selection of the Fuzhong Station and the Shanshou Station as hydrographic monitoring points? Are these points representative of specific hydrological characteristics within the watershed?
11. How strategically positioned are these hydrographic stations within the overall flow pathways of the Ashida River? How do their locations contribute to capturing the river's behavior as it traverses through the study area?
12. Could you provide additional insight into the role of each of the key datasets, such as DEM, soil, land use, and meteorological data, in shaping the foundation of the SWAT model? How do these datasets collectively contribute to constructing the model's database?
13. Could you explain the transition from the SWAT/GRASS interface to the AVSWAT and ArcSWAT interfaces? How have these interface developments impacted the model's accessibility and ease of use?
14. While originally designed to assess hydrological, sediment, and water quality conditions, how has the SWAT model's focus shifted to predominantly serve hydrology, sedimentation, crop growth, nutrient cycling, and pest hazards? Can you provide examples of its utility in these areas?
15. How was the watershed extraction function within ArcSWAT 2012 used to define sub-basins and establish river networks? Were there specific criteria or considerations that guided the delineation process?
16. Were there any particular advantages to employing hourly data intervals as opposed to other temporal scales, considering the study's objectives?
17. What were the adjustments required for relevant basin parameters when incorporating the hourly simulation plug-in? How did these adjustments impact the model's behavior at the hourly scale compared to other temporal resolutions?
18. In the text, it's mentioned that parameter sensitivity analysis serves a dual purpose of refining parameter selection and enhancing comprehension of their roles in watershed simulation. Could you elaborate on how this analysis contributes to a better understanding of the individual impacts of these parameters on the simulation outcomes?
19. The text describes that the T-stat and P-value are utilized as metrics for assessing the sensitivity of model parameters. Could you explain how these two metrics work in conjunction to determine the sensitivity of a parameter? What is the significance of both the T-stat's absolute value and the P-value in this context?
20. When discussing the sensitivity ranking of parameters in Table 2, could you provide more information about the methodology used to rank these parameters during the calibration period? How were the fitted values derived and what role do they play in understanding parameter sensitivity?
21. In the text, it's suggested that greater parameter sensitivity is indicated by a larger absolute value of the T-stat and a smaller P-value approaching zero. Could you clarify the rationale behind this assertion? Why are these specific conditions considered indicative of higher sensitivity?
22. Could you detail the implications of the sensitivity ranking of parameters during the calibration period? How do these rankings influence the subsequent steps in the modeling process, such as fine-tuning sensitive parameters to align simulated values with observed counterparts?
23. Given the extensive array of model parameter attributes in SWAT-CUP, how were potential interactions or dependencies between different parameter types considered during the sensitivity analysis? Were there any instances where the sensitivity of one parameter type influenced the sensitivity of another?
24. While T-stat and P-value offer quantitative insights into parameter sensitivity, are there any qualitative factors that were taken into account during the analysis? For instance, did expert judgment or domain knowledge play a role in interpreting the sensitivity rankings and guiding parameter adjustments?
25. The text mentions sensitivity analysis during the calibration period. Were there any efforts to assess parameter sensitivity across different time periods or under varying conditions? If so, could you provide a brief overview of the outcomes and any trends observed?
26. Can you expand on how the insights gained from parameter sensitivity analysis, as presented in Table 2, contribute to the broader goal of improving the overall accuracy and reliability of watershed simulations? How have these insights led to practical improvements or adjustments in modeling practices?
27. The text mentions that variations in hydrological components generally follow the oscillations in precipitation. Could you elaborate on whether these hydrological components respond similarly to both increases and decreases in precipitation? Are there instances where their responses deviate from this pattern?
28. The text discusses temporal disparities between groundwater changes and shifts in surface runoff and lateral flow recharge to runoff. Could you clarify the reasons behind this temporal lag in groundwater changes? What factors might contribute to groundwater responding differently compared to other hydrological components?
29. In the example provided for November, where groundwater recharge to runoff registers higher than the precipitation, could you explain the mechanisms or factors that lead to this phenomenon? How does the hydrological system manage to generate more groundwater recharge despite lower precipitation?
30. The contrast in lateral flow and groundwater recharge between June and September is highlighted as being influenced by summer precipitation stored in different reservoirs. Could you provide more insights into how the aquifers, soil, and vegetation store and release precipitation to create this observed difference in recharge values?
31. The cumulative basin-wide contributions from surface runoff, lateral flow to recharge, and groundwater to recharge are given as percentages of the total precipitation. Could you provide some context on these percentages? How do these contributions collectively influence the water balance of the basin?
32. The text mentions the annual basin-wide evapotranspiration value. Could you elaborate on how evapotranspiration fits into the overall hydrological dynamics of the basin? What factors impact the evapotranspiration rate and its relevance in the context of the study?
A number of English corrections need to be considered by the authors to improve the quality of the paper.
In abstract
Original: "Hydrological modeling at the hourly scale is of paramount importance for flood-related research..."
Suggestion: "Hourly-scale hydrological modeling holds pivotal significance for flood-related research..."
Original: "The study reveals that hourly simulation effectively captures flood trends across various time intervals and precisely reproduces both baseflow and flood peaks within the range of 0 to 200 m3/s."
Suggestion: "The study highlights the hourly simulation's proficiency in capturing diverse flood trends across multiple time intervals, while also accurately replicating baseflow and flood peaks within the 0 to 200 m3/s range."
Original: "...revealing the control effects of different parameters on simulated runoff, such as the impact of BFLO_DIST on baseflow simulation in hourly mode."
Suggestion: "...revealing how distinct parameters influence simulated runoff. For instance, it outlines how BFLO_DIST significantly affects baseflow simulation when operating in hourly mode."
Original: "Furthermore, empirical summaries were created for the parameterization process..."
Suggestion: "Moreover, empirical summaries have been generated to outline the parameterization process..."
Original: "While the hourly simulation of the SWAT (Soil and Water Assessment Tool) model has been applied in a few watersheds, the relatively short history and limited scope of its usage still constrain a comprehensive understanding of its potential."
Suggestion: "Although the SWAT model's hourly simulation has found application in a few watersheds, the relatively short usage history and limited scope inhibit a comprehensive grasp of its potential."
In introduction
Original: "Flooding stands out as a significant natural calamity that poses a grave threat to human society and has seriously impacted the safety of lives and property."
Suggestion: "The occurrence of flooding stands as a substantial natural catastrophe, posing a severe peril to human communities and profoundly affecting both lives and property safety."
Original: "In tandem with the escalating global temperatures observed in recent decades, the incidence of anomalous climatic events has surged, encompassing floods triggered by unprecedented rainstorms."
Suggestion: "Concurrently, as global temperatures continue to rise in recent decades, an upsurge in anomalous climatic events, including floods triggered by unprecedented rainstorms, has been observed."
Original: "Statistics reveal that the global frequency of natural disasters surged to 14,851 between 1900 and 2018, with floods constituting the predominant share at 33%."
Suggestion: "Data illustrates a surge in the worldwide occurrence of natural disasters, reaching 14,851 between 1900 and 2018, with floods constituting the majority share at 33%."
Original: "Singh et al. effectively employed the SWAT model to simulate runoff at both daily and monthly scales for the Tungabhadra watershed, showcasing a strong correlation between observed and simulated values."
Suggestion: "Singh and colleagues adeptly utilized the SWAT model to replicate runoff at both daily and monthly scales for the Tungabhadra watershed, illuminating a robust correlation between observed and simulated values."
Original: "However, the heightened temporal granularity inherent in hourly simulations can lead to a relatively diminished accuracy in comparison to daily simulations."
Suggestion: "Nonetheless, the heightened temporal granularity intrinsic to hourly simulations might lead to a relatively reduced accuracy when contrasted with daily simulations."
Original: "Delving into hourly-scale simulation results, Bauwe et al. employed the SWAT model's Green-Ampt method to explore the influence of hourly precipitation resolution on both model performance and hydrological elements."
Suggestion: "In-depth analysis of hourly-scale simulation outcomes by Bauwe and colleagues involved the application of the SWAT model's Green-Ampt methodology to scrutinize the impact of hourly precipitation resolution on model performance and hydrological attributes."
Original: "Additionally, Campbell et al. utilized the SWAT model at an hourly scale within the Pawtuxet watershed, though the NSE results fell short of expectations during both calibration and validation periods."
Suggestion: "Furthermore, Campbell and co-authors harnessed the SWAT model at an hourly scale for the Pawtuxet watershed. However, the NSE results, falling below anticipated levels, underscored important insights for both calibration and validation phases."
Original: "The SWAT model's hourly simulation module was introduced as a novel addition by Jeong et al. in 2010 [10]."
Suggestion: "Jeong and colleagues introduced the innovative hourly simulation module of the SWAT model in 2010 [10]."
Original: "In contrast to the daily scale, the hourly scale offers the capacity to capture flow variability with high-resolution time intervals, which holds significant importance for simulating watershed floods."
Suggestion: "Differing from the daily scale, the hourly scale excels in capturing flow variability through high-resolution time intervals. This capability is of paramount importance when modeling watershed floods."
Original: "Due to its relatively recent development, limited established simulation practices, and heightened uncertainties, the utilization of the SWAT model at hourly scales for watershed studies has been comparatively infrequent."
Suggestion: "Given its relatively recent inception, scarcity of established simulation methodologies, and increased uncertainties, the application of the SWAT model at hourly scales for watershed studies remains less prevalent."
Original: "In one of the few published investigations, Yang et al. conducted a comparative analysis between hourly-scale and daily-scale flow simulations..."
Suggestion: "In an example among the limited published investigations, Yang and co-authors performed a comparative analysis, contrasting flow simulations between hourly and daily scales..."
Original: "The daily scale's inability to accurately represent the finer temporal intricacies of river flow and material output prompted Shannak to further substantiate the predictive prowess of the hourly scale model..."
Suggestion: "Recognizing the daily scale's limitations in capturing intricate temporal nuances of river flow and material dynamics, Shannak extended efforts to reinforce the predictive capabilities of the hourly scale model..."
Original: "Additionally, Boithias et al. applied the hourly module for flow prediction in coastal watersheds, albeit with hourly-simulated R2 and NSE values for overall flow simulations across various stations exhibiting inferior performance compared to daily scale simulations."
Suggestion: "Furthermore, Boithias and collaborators employed the hourly module for predicting flow in coastal watersheds. However, hourly-simulated R2 and NSE values showcased subpar performance across various stations in contrast to daily scale simulations."
Original: "Consequently, this study embarks on dissecting the inherent strengths and shortcomings within hourly scale simulations of the SWAT model..."
Suggestion: "As a result, the present study aims to meticulously examine the inherent advantages and limitations within hourly scale simulations of the SWAT model..."
Original: "Furthermore, it delves into the intra-annual dynamics of hydrological components within the basin, thereby offering novel perspectives for the analysis of basin water volume."
Suggestion: "Additionally, it delves into the nuanced intra-annual variations of hydrological components within the basin, presenting fresh insights into the analysis of basin water volume."
Study sites and materials
Original: "Nestled within the subtropical monsoon zone..."
Suggestion: "Situated in the subtropical monsoon zone..."
Original: "...witnesses an average annual precipitation of around 1814 mm."
Suggestion: "...experiences an average annual precipitation of approximately 1814 mm."
Original: "The total population of Fukuyama City is estimated to be around 460,000 residents."
Suggestion: "Fukuyama City has an estimated population of approximately 460,000 residents."
Original: "Topographically, the region showcases elevated terrain in its western and northern sectors, gradually transitioning into lower terrain towards the east and south."
Suggestion: "Topographically, the area features elevated terrain in the west and north, gradually giving way to lower terrain in the east and south."
Original: "...strategically positioned before the Ashida River's entry into the city..."
Suggestion: "...strategically located upstream of the Ashida River's entry into the city..."
Original: "The study incorporates two strategically chosen hydrographic stations..."
Suggestion: "The study includes two carefully selected hydrographic stations..."
Original: "...the Shanshou Station, strategically located before the river's confluence with the sea."
Suggestion: "...the Shanshou Station, strategically positioned prior to the river's merging point with the sea."
Original: "The construction of the SWAT model database is reliant on several key datasets..."
Suggestion: "Building the SWAT model database hinges on pivotal datasets..."
Original: "The DEM data for the study area were sourced from the U.S. Geological Survey website, boasting a spatial resolution of 30 m."
Suggestion: "The study area's DEM data were sourced from the U.S. Geological Survey website, featuring an impressive spatial resolution of 30 m."
Original: "Meanwhile, soil data and land use data were procured from the Japan Land Resources Agency's website, featuring scales of 1:1 million and 1:25,000, respectively."
Suggestion: "In addition, soil and land use data were obtained from the Japan Land Resources Agency's website, with scales of 1:1 million and 1:25,000, respectively."
Original: "Meteorological data were garnered from the Japan Meteorological Agency's website."
Suggestion: "Meteorological data were collected from the Japan Meteorological Agency's website, a trusted source."
Original: "Precipitation data was collected at hourly intervals in alignment with the SWAT model's hourly simulation requisites."
Suggestion: "Precipitation data was gathered at hourly intervals to align with the SWAT model's hourly simulation requirements."
Original: "In parallel, other meteorological parameters such as temperature, solar radiation, relative humidity, and wind speed were amassed at daily intervals."
Suggestion: "Simultaneously, additional meteorological parameters—temperature, solar radiation, relative humidity, and wind speed—were collected on a daily basis."
Original: "Hourly flow data are monitored and officially published by hydrological stations in Japan."
Suggestion: "Hydrological stations in Japan diligently monitor and officially release hourly flow data."
Original: "Comprehensive details of the data utilized are delineated in Table 1."
Suggestion: "Table 1 provides a comprehensive breakdown of the utilized data, including intricate details."
Methodology
Original: "The SWAT model, originating from the US Department of Agriculture in 1995, was built upon the foundation of the SWRRB (Simulator for Water Resources in Rural Basins) model..."
Suggestion: "The SWAT model, developed by the US Department of Agriculture in 1995, was constructed on the basis of the SWRRB (Simulator for Water Resources in Rural Basins) model..."
Original: "Over the span of nearly three decades of development, eight distinct versions 116 of the model have been unveiled..."
Suggestion: "During nearly three decades of development, eight distinct versions of the model have been introduced..."
Original: "What initially began as the SWAT/GRASS interface has since evolved into the AVSWAT and ArcSWAT interfaces..."
Suggestion: "Originating as the SWAT/GRASS interface, it has evolved into the AVSWAT and ArcSWAT interfaces..."
Original: "Originally conceived to assess hydrological, sediment, and water quality conditions within watersheds, the SWAT model has predominantly found utility in hydrology, sedimentation, crop growth, nutrient cycling, and pest hazards..."
Suggestion: "Initially designed for evaluating hydrological, sediment, and water quality conditions in watersheds, the SWAT model is now primarily employed for hydrology, sedimentation, crop growth, nutrient cycling, and managing pest hazards..."
Original: "Its computational framework has undergone continual enhancement and refinement since 1995, steadily broadening its range of applications due to the potent computational capabilities and robust physical mechanisms inherent to the SWAT model."
Suggestion: "Its computational framework has been continuously enhanced and refined since 1995, progressively expanding its applicability due to the model's powerful computational capabilities and robust physical mechanisms."
Original: "As a result, it has emerged as a crucial underpinning for the formulation of strategies and policies in water resources management..."
Suggestion: "Consequently, it has become a pivotal foundation for developing strategies and policies in managing water resources..."
Original: "Based on a statistical study on hydrological modeling published in 2015 [20], approximately 46% of hydrological modeling studies utilized the SWAT model, highlighting its current status as one of the most extensively employed hydrological models."
Suggestion: "According to a 2015 statistical study on hydrological modeling [20], the SWAT model was employed in about 46% of such studies, indicating its position as one of the most widely used hydrological models."
Original: "Within the temporal scope of the model, the hourly simulation module of the SWAT model stands as a recent addition. However, it demands more precise meteorological input data, real measurements, and a higher level of complexity compared to the daily scale simulation [21]."
Suggestion: "In the model's temporal scope, the recent inclusion of the SWAT model's hourly simulation module introduces greater complexity. However, it necessitates heightened precision in meteorological input data, real measurements, and a higher level of intricacy compared to daily scale simulations [21]."
In Parameter sensitivity
Original: SWAT-CUP encompasses a diverse array of model parameter attributes, spanning groundwater characteristics, soil properties, vegetation attributes, hydrologic response unit factors, management settings, and channel attributes.
Suggestion: SWAT-CUP covers a wide range of model parameter attributes, including groundwater characteristics, soil properties, vegetation attributes, hydrologic response unit factors, management settings, and channel attributes.
Original: Such an analysis serves a dual purpose: it not only refines the parameter selection process but also enhances comprehension regarding the roles these parameters play in watershed simulation.
Suggestion: This analysis serves a dual purpose: refining not only the parameter selection process but also enhancing comprehension of the roles these parameters play in watershed simulation.
Original: The statistical data presented in Table 2 outlines the sensitivity ranking of the parameters during the calibration period and their corresponding fitted values.
Suggestion: The statistical data presented in Table 2 outlines the sensitivity ranking of parameters during the calibration period, along with their corresponding fitted values.
Original: A widely held perspective is that a parameter exhibits greater sensitivity if its T-stat's absolute value is larger and its P-value approaches zero.
Suggestion: A widely held perspective is that a parameter exhibits greater sensitivity when its T-stat's absolute value is larger and its P-value approaches zero.
Original: Conversely, parameters are considered less sensitive if their T-stat's absolute value is smaller and their P-value is larger.
Suggestion: In contrast, parameters are considered less sensitive if their T-stat's absolute value is smaller and their P-value is larger.
Author Response
Please see the attachment.
Author Response File: 
Author Response.docx
Reviewer 2 Report
1. Could you clarify the term "T-stat"? It seems that you intend to discuss the concept of a T-test, which is commonly employed in statistical analysis.
2. You've indicated that a parameter's sensitivity increases when the absolute value of its T-test is larger and its P-value approaches zero. Could you provide the sensitivity values you computed for the T-test? What formula did you use to calculate this sensitivity?
3. What specific type of T-test did you use for your statistical evaluation? As there are various types of T-tests, such as independent samples, paired samples, one-sample, and T-tests with unequal sample sizes, could you elaborate on the purpose behind showcasing the properties of your input parameter?
4. I understand that your intention might be to highlight greater sensitivity with a larger number of input parameters. However, if my interpretation is accurate, you have ten parameters that exhibit statistically significant p-values (*) well below 0.10. This result lacks meaningful significance, even considering my own modeling experience. In typical research, a p-value threshold of 0.05 (**) is often used as a baseline for assessment, with 0.01 and 0.001 serving as supplementary indicators.
5. Consider the process outlined below, or alternative approaches, to investigate sensitivity and uncertainty in numerical modeling: (1) Analyze the statistical characteristics of all input parameters, (2) Explore the statistical distribution of these parameters, (3) Examine the distribution properties of your data, and subsequently employ techniques like Monte Carlo simulations, Latin Hypercube sampling, or other suitable methods.
6. Your regression analysis lacks statistical validation for the regression model and estimated coefficients, despite the presence of the R-squared value.
7. Based on the assessment of points 1 through 6, there appears to be a deficiency in clearly defining the structure of the input data used for the modeling process. This raises questions about the reliability of the results obtained.
8. Considering the outcomes, could you elaborate on the primary issue you intend to highlight for the government's hydrological management department?
Author Response
Please see the attachment
Author Response File: Author Response.docx
Round 2
Reviewer 2 Report
Review comments have provided to Editors.
