Integrated Multi-parametric Analytic Hierarchy Process (AHP) and
Geographic Information System (GIS) based Spatial modelling for
Flood and Water logging Susceptibility Mapping: A case study of
English Bazar Municipality of Malda, West Bengal, India

Chattaraj, Diyali; Paul, Biswajit; Sarkar, Subir

doi:https://doi.org/10.5194/nhess-2020-399

Preprints

https://doi.org/10.5194/nhess-2020-399

Preprints

11 Jan 2021

| 11 Jan 2021

Status: this preprint was under review for the journal NHESS but the revision was not accepted.

Integrated Multi-parametric Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) based Spatial modelling for Flood and Water logging Susceptibility Mapping: A case study of English Bazar Municipality of Malda, West Bengal, India

Diyali Chattaraj, Biswajit Paul, and Subir Sarkar

Abstract. Waterlogging as a perennial problem is deep rooted on the urban fabrics of English Bazar Municipality. The present study pertains to vulnerability and risk assessment of flood and waterlogging susceptible areas in a micro or local scale, based on an integrated Analytic Hierarchy Process-Geographic information System (AHP-GIS) category model. For this purpose, a multi-criteria assessment of natural, quasi-natural and man-made factors have been performed. Criterion includes six parameters namely elevation, slope, soil, flow accumulation, land use land cover, density of digitized drain network which are responsible to initiate the waterlogged condition within municipality premises. The weights of all criterion are computed by pair wise comparison decision matrix (AHP). According to their weightage, information of different parameters are superimposed for a final weighted overlay analysis following a spatial modelling, under ArcGIS 10.5 platform to delineate the flood and water logging susceptible zones. The result obtained from this study indicate 11.45 %, 3.05 % and 85.49 % area of municipality corresponds with highly vulnerable, low and moderately vulnerable respectively. The major finding in the study reveals that unplanned urban expansion in the hazardous low-lying area by filling up of wetlands and depressions in association with inadequate drainage gravity provisions in the newly built-up wards (3, 23, 24 and 25) are noteworthy for resultant waterlogging condition. The present paper also aims to suggest long-term mitigation measures to be well integrated for arriving at a well drafted and implementable comprehensive drainage plan of English Bazar municipality.

Received: 07 Dec 2020 – Discussion started: 11 Jan 2021

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.

Download & links

Diyali Chattaraj, Biswajit Paul, and Subir Sarkar

Status: closed

RC1:
'Comment on nhess-2020-399', Anonymous Referee #1, 19 May 2021

The article “Integrated Multi-parametric Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) based Spatial modeling for Flood and Water logging Susceptibility Mapping: A case study of English Bazar Municipality of Malda, West Bengal, India” makes an important contribution to the mapping of vulnerability in the face of fluvial seasonality. The methodology can even be applied in other locations, based on the availability of geographic and physical data.

It would be interesting to present population data from the city of Malda in the introduction

In the introduction it was necessary to comment on why the city of Malda was chosen, what are its specificities? What activities would be impaired in flood situations?

All maps need to be presented with better resolution. In figure 1 on the Malda map (zoom 2) put the name of the Ganges River.

It would be interesting to show the percentage of each land use area in relation to its vulnerability (low, moderate and high). Example: x% of the urban area is considered to be of medium vulnerability. In addition, indicate the reason for each class to have a specific vulnerability index. For example, the percentage of urban area in average vulnerability occurs due to factors such as ...

It would be interesting to present a flood map for monsoon seasons, showing the influence of the rain seasonality in the region. Those at least cite how monsoons could exacerbate vulnerability rates.

There was a lack of contextualization about how this methodology (AHP) comes from other areas and the importance of consulting specialists. It was not clear how you determined the weight for each parameter. Make this clearer in the methodology and discussion.

In your discussion, it would be interesting to show how climate change can aggravate your predictions, increasing the frequency and magnitude of rainfall.

Thank you for the invitation as a reviewer. The AHP method is very useful in several situations, mainly in association with GIS and geographic data.

Citation: https://doi.org/10.5194/nhess-2020-399-RC1
- AC1:
  'Reply on RC1_Author comment', Diyali Chattaraj, 30 May 2021
  The population data of Malda district as per the 2011 census will be incorporated in the introduction part. The ward wise population, especially those wards which have newly been formed in order to accommodate the growing population in the study area has already been discussed under section 4.
  
  The authors have chosen the city of Malda as a study area because of two reasons:
  
  The district of Malda is a home to 4.1 per cent of the total state (West Bengal) population and comprises a unique location as it shares the district boundary in north, north-east and south (North and South Dinajpur and Murshidabad); state boundary in the west and north-west (Jharkhand and Bihar) and international boundary in the entire south-east (Bangladesh). English Bazar Municipality (study area) is the one of the oldest municipalities in India as well as the most fastest growing metropolitan area. With the passing of time, the municipality experiences massive refugee influx from the neighbouring districts, states and country.
  
  To cope with the growing population during the post-independent period, unplanned extension of built-up areas and metalled roads with no or little provisions for drainage in and around the municipality, has converted many low-lying areas, wetland, and arable land into residential area along Mahananda levee. As a consequence, water-logging is a perennial problem and is set persist throughout the rainy season on the urban fabrics of English Bazar Municipality.
  
  The present study enquires the causes of water-logging and pertains to identify and mapping of the water logging vulnerability and risk zones within English Bazar Municipality premises.
  All the maps, presented in the paper are extracted at 600-dpi resolution. It will be enlarged and rearranged, so that the components are vividly noticeable. Moreover, all the maps, diagrams and tables will be sent to the handling editor of this journal as supplement files for better understanding.
  
  In figure 1 on Malda map (zoom 2), the name of River Ganges will be written.
  The land use land cover map in the raster image will be converted into vector format in order to show the percentage of each land use in relation to its vulnerability, i.e., highly susceptible, moderate and low susceptible to water-logging along with the interpretation and associated attributing factors. Moreover, municipal ward wise area irrespective of all the land use category in relation to its vulnerability (low, moderate and high) can also be displayed.
  
  The authors have tried earlier to present a water-logged map in respect to normalized difference water index (NDWI) for the monsoon season to show the rainy seasonality in the municipal region, but are unable to extract cloud free satellite image during June to September in 2018.
  
  Some more literatures will be reviewed as well as cited by the authors in the present work to know how monsoon could exacerbate the rate of vulnerability.
  The background of applying the AHP integrated with the GIS will be much strengthened with the help of more literature reviews. Further, to determine the objective and formulate the decision-making process, number of experts comprising hydrologists, engineers, municipal authority were asked during the study to give their assessment and judgement regarding the variables related to water-logging along with their significance in terms of weight. Therefore, the importance of consulting specialists will be mentioned in the present work.
  
  It would really be interesting to show the relationship between the climate change in the form of frequency and magnitude of rainfall and water-logging situation in the municipality, but there are two limitations:
  
  Monthly rainfall data for this micro region (13.25 km²) is not provided by the Indian Meteorological Department (IMD) which is considered one of the most authentic weather report organization in India.
  
  It would have been much lengthy paper to apply the statistical methods (linear regression etc.) to show the relation between climate change in terms of average annual rainfall and intensity of water-logging.
  
  Citation: https://doi.org/10.5194/nhess-2020-399-AC1
RC2:
'Comment on nhess-2020-399', Anonymous Referee #2, 20 May 2021
This paper explores the application of AHP to map waterlogging in a small region in West Bengal. This is a fairly routine work of local interest, and I did not find much except for the standard GIS-based analysis. There is absolutely nothing for an international audience here. The fundamental problem here is that there is very little in terms of process interpretations or the causal factors and some possible mitigation measures. After showing the results, the paper literally crashes and does not offer much in terms of analysis and discussion. For producing a quality work in such a small area, you need a much higher resolution of data which is not available on satellite platform. The only way to get this is to use drone surveys or an extensive ground based mapping.

In the interest of the authors to improve this work, I offer the following comments and suggestions:

Please consider enlarging the study area to understand the regional and local controls of waterlogging better. The primary reason for waterlogging is drainage congestion and this particularly important in urban areas because of unplanned development – a point that has been highlighted by the author but is not substantiated by data.

In this context, one of the most important data that is missing is the road network and its intersection with drainage/drain lines.

The objectives and scope of this study look diffused. The authors sometimes use waterlogging mapping but several places use waterlogging and flood risk zones. Please note that this study contributes nothing to flood risk zoning.

Most of the maps are very poor and not legible. It would be useful to show a satellite image of the study area as the first figure.

Two flow charts for the methodology are not needed – should be merged into one.

Table 1 is not required – most of the information is already there in the main text.

It would be useful to show the 5 zones mentioned in the text in the elevation map (Fig. 5). Otherwise, it is hard to match the text and figure.

Slope data does not seem to be useful as there is very little variation. It may be useful to redesign this by using a finer interval if the original data permits.

Similarly, the flow accumulation also does not show anything – more than 98% of the area falls in just one class. Again, it needs a finer resolution to make this data useful.

The LULC data analysis is interesting but does not connect to the main objective of the paper. How is the LULC change data used in the spatial analysis? Also, there are some issues with the correspondence of different data sets. For example, Figure 10 shows that the newly built areas are in the western part but a quick look at the LULC maps of 1990 and 2018 shows that most of the expansion has happened in the eastern part. Am I missing something?

Also, taking cues from the LULC change and some explanation offered in the text, I am fairly convinced that it is the drainage congestion that might have led to waterlogging rather than the LULC change itself. So, you need to find some ways to quantify this.

Taking the above argument further, the weightage scheme should also be relooked. If LULC has not played an important role, then you should bring this factor down and perhaps bring drain density up. Also, the flow accumulation factor is not an independent factor – it is a function of the slope. A mentioned earlier, road network should also be brought in this scheme, this is absolutely critical.

Section 7 on discussion should have been a major section of this paper but this hardly developed.

The authors talk about field evidence in the end but I did not find anything on this. The conclusion also talks about providing ‘essential information' for local government and again there is nothing on this.
Citation: https://doi.org/10.5194/nhess-2020-399-RC2
- AC2:
  'Reply on RC2_Author Comment', Diyali Chattaraj, 04 Jun 2021
  The enlargement of the study area definitely will provide better understanding about regional control of waterlogging. But our objective is confined to a micro/ward level analysis which provides vivid insights about waterlogging susceptibility at grass root level. Your valuable suggestion will be considered in future works.
  
  Road network plays a very important role in waterlogging especially in this municipality. The authors have considered road network as built-up, in land-use and land-cover map as well as considered in the overlay For this study area, drain network and road network run almost parallel to each other and their spatial distribution is also similar, that is why, the authors have not considered road network as a separate criterion.
  
  The study is solely dealing with waterlogging susceptibility mapping with the help of some parameters. Thus, to make the manuscript much simpler the words related to flood will be omitted.
  
  As the authors have already mentioned in AC1, all the maps presented in the paper (has been extracted with 600 dpi resolution) will be enlarged and rearranged so that all the components of map could be noticeable. A satellite view (FCC) of the study arch will be incorporated in the location map (Fig. 1).
  
  Figure 2 and 3 will be merged with a precise workflow of methodology as per your suggestion in the final manuscript.
  
  Tables generally provide a visual grouping of information and make the information more noticeable. That is why Table 1 has been included in the text. If it is not needed than it can be eliminated.
  
  5 elevation zones, which have already been mentioned in the text, will be incorporated and displayed in the elevation map (Fig. 4) as well.
  
  The slope map has been prepared from a contour map collected from the municipality. The accuracy of that contour map is considered 5 millimeters in order to get a clear idea about the micro-topographic forms of this region. The variation of the slope map is very less as the study area belongs to flat topography having only about 13 sq. km. of areal extent. The authors have already experimented with finer class intervals and did not find any differences in the final result.
  
  The situation is also similar in case of flow accumulation These two maps have been included in criteria according to experts’ views (hydrologists and engineers) and various literatures dealing with the waterlogging susceptibility mapping.
  
  In consultation with the experts to formulate the decision-making process, six parameters namely; elevation, slope, rainfall, soil, flow accumulation, land-use / land-cover (LULC), and drain density are considered responsible for the initiation of waterlogged condition in English bazar municipality. The criteria weight (weightage scheme) has been developed accordingly as per experts’ views and based on the previous literatures. If required, some more literatures will positively be reviewed for further understanding.
  
  Land use land cover is considered one of the most important parameters of water-logging within municipality premises. The LULC undergoes unplanned construction on the low-lying wetlands (located at the west) along with dramatic transformation of the natural and manmade sewerage system without paying any attention to the normal and storm water disposal waterways have led to drainage congestion and water-logging (Fig. 13). Further, absence of planned and adequate drainage system in the newly built-up extension (discussed later) has led the perennial problem of water-logging to be deep rooted in the urban fabrics of this municipality (less dense the drain network (Fig. 11a & b) emanates the capacity of an area to be more waterlogged (Fig. 13). You have also highlighted the importance of road network, which is included in land-use and land-cover map to determine the criteria weight. The temporal change of land-use and land-cover has not been considered in the overlay analysis. Only the land-use and land-cover of 2018 has been taken into consideration. Moreover, two time series satellite data (1990 and 2018) (Fig. 8a & b) have been used to identify and quantify (Fig. 9) the LULC change within municipality over last 30 years.
  
  The English Bazar municipality experiences a unique urban growth pattern. The LULC map of 2018 (Fig. 8b) shows urban infill, which has taken place in the eastern part that you have identified. If you have a look on the multi-date LULC map (Fig. 8a & b), rapid urban expansion has been developed in the western part which is attributed to huge in-migration since 1970 during the liberation war of Bangladesh. Rapid population growth, unplanned low-land filling eventually leads to number of localities to be emerged in the western part of municipality as newly built-up area (Fig. 10), which is further documented in table 4.
  
  As per the manuscript, result and discussion have been mentioned under different sections, but the results with the necessary discussions go simultaneously from section 4. Therefore, the section wise sub-headings can be rearranged for clear-cut understanding. Moreover, section 7 exclusively deals with several mitigating measures, suggested by the authors and stakeholders, applicable to this micro-region.
  
  The authors belong to English Bazar municipality, Malda town and experience the problem of drainage congestion and water-logging after every medium and heavy shower. However, some plates covering several waterlogged pockets within municipal wards, captured by the authors, will be sent as field evidence through supplement file, which may help to understand the severity.
  
  Citation: https://doi.org/10.5194/nhess-2020-399-AC2
RC3:
'Comment on nhess-2020-399', Anonymous Referee #3, 20 May 2021
This manuscript is a case study of using an integrated AHP-GIS approach to the English Bazar Municipality in West Bengal, India.

Overall—this case study, if significantly revised to put it into the context of the broader literature and to carefully consider how uncertainty in the data (including years of input for different data values) than it might become useful for the broader community. But, as it now stands, it is a case study without a lot of relevance outside of the region that it has been done, either for broader learnings of the methodology benchmarked in this region, or comparison of this method with other regions, or comparison of this methodology with other methodologies. Without this, it is difficult to see how it might be useable, used, and useful for other colleagues. What should they make of it, as it seems like a lot of variables, with a result that has little understanding if it is meaningful. If some of this can be adjusted in a major revision, this would make a useful case study contribution to NHESS. My comments are as follows:

The manuscript is very much a case study, and it is difficult to see how someone else should apply the study to their region, or what has been learned that is new. If the element of what is being done to either confront this method with this case study and benchmark results (and thus be useful to others) or to put this methodology in the context of other studies (and thus be useful to others), this would be fine. I suggest then the authors consider carefully how they are constructing their argument. One way is to introduce a section at the beginning that is a background which includes:

Waterlogging analytic approaches currently being used.

A critical review (even brief, of a dozen studies) of where AHP-GIS has been used in similar situations (not necessarily in India, this could be worldwide).

A critical presentation of variables that have been used to with regards to influence waterlogging (from the literature).

From this background, then you can state you will go into a specific case study.

Then in the discussion, it is important to come back to the bigger picture, as to what has been learned from this methodology to make this ‘more’ than just a case study, such that the case study is in the context of the wider literature.

Uncertainty. Although you discuss accuracy in places of input data, when I get to Figure 15, I don’t have a good understanding of how much the accuracy is influencing the final flood susceptibility map, nor how much the influence of the equations and parameters is influencing it. So if one of my input variables changed ‘a bit’ how much would this change? I believe much more needs to be done with discussing the influence of the accuracy (e.g., of data, and inputs) and the method used, on the results.

The method and the equations quoted seem to be from the 1980s. How has this methodology progressed beyond the 1980s?

Other:

Please go through and check all items for typos (e.g., line 126 Ci is CI,

Line 69: [Minor, my preference] Human-made not ‘mand-made’

Avoid acronyms in figure captions.

Figure captions. Please make these more self-standing (e.g., so one does not need to go to the text to figure them out, and including and sources of data used for the figure).

Figures: Please ensure all acronyms used in the figure are defined in the figure caption. Otherwise it makes the figures really hard to read. Figure 3: NBSS, LUP, LULC, TIN, DEM, are all used.

For equations, it seems odd to use words instead of variables. For example dist_i would be much better as d_i (d subscript i), radius would be much better as r. Having owrds just makes these difficult to read. Density could be ro.

Because of the importance of the variables, please create a table of variables, which is introduced towards the beginning, including units.

For data such as the soil map, how will the influence of when it has been collected influence the results? How much will it have changed over time. Can you do the same for ALL input, discussing carefully the year of collection of the data and how it might have changed.

Accuracy of your reporting of data in places seems a bit optimistic. For example, Table 2, you report to the nearest 0.01 mm. That seems a bit over-optimistic for the data you are working with.

Because of the importance of rainfall, I’d like to better understand its variation over the last 36 years, and within a year.

For your reporting of metres, this should be m, and it should be m above sea level (asl) as just stating ‘m’ is sort of meaningless without a reference point.

For the slope map, please clarify what the resolution of the grid that is used to construct it.

Line 188. Do you mean Table 7? This is many pages later. Please put ‘cells’ after 4139 for clarity, and check everywhere for units after numbers.

Figures everywhere, hard to see because of their size, so will need a careful look at these.

Please do look at the formatting guidelines for NHESS papers at https://www.natural-hazards-and-earth-system-sciences.net/submission.html.
Citation: https://doi.org/10.5194/nhess-2020-399-RC3
- AC3:
  'Reply on RC3_Author Comment', Diyali Chattaraj, 08 Jun 2021
  This manuscript is very much a case study of English Bazar municipality, Malda district which has grown with land availability not keeping pace with rapid population growth during last few decades. As a consequence, perennial problem of water-logging and drainage congestion in several pockets has been deep rooted on its urban fabrics after every medium to heavy shower. The present study aims to apply an integrated Analytic Hierarchy Process (AHP) in order to highlight the leading factors of water-logging and to delineate the susceptible zones on the GIS platform.
  
  The manuscript comprises a section at the beginning including the steps, through which the entire work has been formulated. In the introduction part, the problem of study has already been mentioned, along with the applied methodology, which is supported with several literatures on India and other developing nations. Moreover, a background containing several current literatures on the water-logging analytic approaches in association with brief reviews on integrated AHP-GIS throughout the World can also be incorporated, after which the specific case study proceeds.
  
  The input variables (as water-logging causative factors) are already mentioned in text form as well as presented in the workflow of methodology.
  
  The method and equations of AHP is quoted from 1980 by Thomas L. Saaty. The present work has also reviewed further progression of AHP as a method and its application (1986) by Fatemeh Zahedi; the axiomatic treatment of priority setting in Analytic Hierarchy Process (1986); a method of measurement with ratio scales (1987); an exposition of AHP in reply to remarks on the Analytic Hierarchy Process (1990); as a multicriteria decision making approach with factors in hierarchic structure (1990); (2008) by Thomas L. Saaty.
  
  The present work has gone through carefully and all the necessary corrections regarding the typos, minor corrections, avoiding acronyms in figure, figure captions and sources, use of variables in the equations will be made. Further, the authors ensure that all the acronyms, used in the figure are defined in the text and figure caption.
  
  The authors will make the figures more self-standing in order to easily figure them out.
  
  Sources are mentioned in all the figures, that may be enlarged for better understanding.
  
  The input variables are displayed in the workflow (in chart format) of methodology including units, that is why these are not mentioned in another table to avoid repetition.
  
  As the authors have already mentioned in AC1, monthly rainfall data for this micro region (13 km²) is not provided by the Indian Meteorological Department (IMD) which is considered one of the most authentic weather report organization in India. Further, the variation of rainfall over 36 years (1976-2012) can be displayed through a line diagram to better understand.
  
  m (meter) above sea level (msl) will be replaced in the manuscript.
  
  For all the six thematic input layers, the grid resolution is mentioned below:
  
  Elevation – 27.77 m
  
  Slope – 27.77 m
  
  Flow accumulation – 27.77 m
  
  Soil – 16.00 m
  
  Land use land cover – 10.00 m
  
  Drain density – 16.00 m
  
  The cell number along with the table (already in text) will be mentioned within manuscript wherever required.
  
  All the units (m (msl) for elevation, slope; pixels for flow accumulation; km/km² for drain density) are mentioned both in the text and figure and once again will be checked.
  
  As mentioned in AC1, all the maps, presented in the manuscript are extracted at 600-dpi resolution. It will be enlarged and rearranged, so that the components are vividly noticeable. Moreover, all the maps, diagrams and tables will be sent to the handling editor of this journal as supplement files to better understand.
  
  The formatting guideline for NHESS papers are thoroughly followed while preparing as well as arranging the manuscript for the submission, once again it will be verified by the authors.
  
  The soil map (Fig. 07) has been collected from National Bureau of Soil Survey and Land Use Planning (NBSS & LUP) in 2004 comprises of 3 types: a) Typic ustifluvents (low infiltrated); b) Typic ustorchrepts (moderately infiltrated) and c) Fluventic ustochrepts (highly infiltrated) within the municipality. These three soil types have not been changed in such a short time duration. And as per the water retention magnitude, Typic ustorchrepts records maximum flow accumulation (Fig. 06) and is found most susceptible to water logging as well (Fig. 13).
  
  You have pointed out that how much a ‘bit change’ in the input variable will influence the final water-logging susceptibility map. This unique study positively could have been made. In that case, it would have been much lengthy and entirely methodology-oriented paper. Rather the authors aimed to do a case study of the current urban water-logging problem in one of the oldest and fastest growing metropolitan area in India. In this regard, the authors will certainly consider your valuable suggestions for future study.
  
  Citation: https://doi.org/10.5194/nhess-2020-399-AC3

Status: closed

RC1:
'Comment on nhess-2020-399', Anonymous Referee #1, 19 May 2021

The article “Integrated Multi-parametric Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) based Spatial modeling for Flood and Water logging Susceptibility Mapping: A case study of English Bazar Municipality of Malda, West Bengal, India” makes an important contribution to the mapping of vulnerability in the face of fluvial seasonality. The methodology can even be applied in other locations, based on the availability of geographic and physical data.

It would be interesting to present population data from the city of Malda in the introduction

In the introduction it was necessary to comment on why the city of Malda was chosen, what are its specificities? What activities would be impaired in flood situations?

All maps need to be presented with better resolution. In figure 1 on the Malda map (zoom 2) put the name of the Ganges River.

It would be interesting to show the percentage of each land use area in relation to its vulnerability (low, moderate and high). Example: x% of the urban area is considered to be of medium vulnerability. In addition, indicate the reason for each class to have a specific vulnerability index. For example, the percentage of urban area in average vulnerability occurs due to factors such as ...

It would be interesting to present a flood map for monsoon seasons, showing the influence of the rain seasonality in the region. Those at least cite how monsoons could exacerbate vulnerability rates.

There was a lack of contextualization about how this methodology (AHP) comes from other areas and the importance of consulting specialists. It was not clear how you determined the weight for each parameter. Make this clearer in the methodology and discussion.

In your discussion, it would be interesting to show how climate change can aggravate your predictions, increasing the frequency and magnitude of rainfall.

Thank you for the invitation as a reviewer. The AHP method is very useful in several situations, mainly in association with GIS and geographic data.

Citation: https://doi.org/10.5194/nhess-2020-399-RC1
- AC1:
  'Reply on RC1_Author comment', Diyali Chattaraj, 30 May 2021
  The population data of Malda district as per the 2011 census will be incorporated in the introduction part. The ward wise population, especially those wards which have newly been formed in order to accommodate the growing population in the study area has already been discussed under section 4.
  
  The authors have chosen the city of Malda as a study area because of two reasons:
  
  The district of Malda is a home to 4.1 per cent of the total state (West Bengal) population and comprises a unique location as it shares the district boundary in north, north-east and south (North and South Dinajpur and Murshidabad); state boundary in the west and north-west (Jharkhand and Bihar) and international boundary in the entire south-east (Bangladesh). English Bazar Municipality (study area) is the one of the oldest municipalities in India as well as the most fastest growing metropolitan area. With the passing of time, the municipality experiences massive refugee influx from the neighbouring districts, states and country.
  
  To cope with the growing population during the post-independent period, unplanned extension of built-up areas and metalled roads with no or little provisions for drainage in and around the municipality, has converted many low-lying areas, wetland, and arable land into residential area along Mahananda levee. As a consequence, water-logging is a perennial problem and is set persist throughout the rainy season on the urban fabrics of English Bazar Municipality.
  
  The present study enquires the causes of water-logging and pertains to identify and mapping of the water logging vulnerability and risk zones within English Bazar Municipality premises.
  All the maps, presented in the paper are extracted at 600-dpi resolution. It will be enlarged and rearranged, so that the components are vividly noticeable. Moreover, all the maps, diagrams and tables will be sent to the handling editor of this journal as supplement files for better understanding.
  
  In figure 1 on Malda map (zoom 2), the name of River Ganges will be written.
  The land use land cover map in the raster image will be converted into vector format in order to show the percentage of each land use in relation to its vulnerability, i.e., highly susceptible, moderate and low susceptible to water-logging along with the interpretation and associated attributing factors. Moreover, municipal ward wise area irrespective of all the land use category in relation to its vulnerability (low, moderate and high) can also be displayed.
  
  The authors have tried earlier to present a water-logged map in respect to normalized difference water index (NDWI) for the monsoon season to show the rainy seasonality in the municipal region, but are unable to extract cloud free satellite image during June to September in 2018.
  
  Some more literatures will be reviewed as well as cited by the authors in the present work to know how monsoon could exacerbate the rate of vulnerability.
  The background of applying the AHP integrated with the GIS will be much strengthened with the help of more literature reviews. Further, to determine the objective and formulate the decision-making process, number of experts comprising hydrologists, engineers, municipal authority were asked during the study to give their assessment and judgement regarding the variables related to water-logging along with their significance in terms of weight. Therefore, the importance of consulting specialists will be mentioned in the present work.
  
  It would really be interesting to show the relationship between the climate change in the form of frequency and magnitude of rainfall and water-logging situation in the municipality, but there are two limitations:
  
  Monthly rainfall data for this micro region (13.25 km²) is not provided by the Indian Meteorological Department (IMD) which is considered one of the most authentic weather report organization in India.
  
  It would have been much lengthy paper to apply the statistical methods (linear regression etc.) to show the relation between climate change in terms of average annual rainfall and intensity of water-logging.
  
  Citation: https://doi.org/10.5194/nhess-2020-399-AC1
RC2:
'Comment on nhess-2020-399', Anonymous Referee #2, 20 May 2021
This paper explores the application of AHP to map waterlogging in a small region in West Bengal. This is a fairly routine work of local interest, and I did not find much except for the standard GIS-based analysis. There is absolutely nothing for an international audience here. The fundamental problem here is that there is very little in terms of process interpretations or the causal factors and some possible mitigation measures. After showing the results, the paper literally crashes and does not offer much in terms of analysis and discussion. For producing a quality work in such a small area, you need a much higher resolution of data which is not available on satellite platform. The only way to get this is to use drone surveys or an extensive ground based mapping.

In the interest of the authors to improve this work, I offer the following comments and suggestions:

Please consider enlarging the study area to understand the regional and local controls of waterlogging better. The primary reason for waterlogging is drainage congestion and this particularly important in urban areas because of unplanned development – a point that has been highlighted by the author but is not substantiated by data.

In this context, one of the most important data that is missing is the road network and its intersection with drainage/drain lines.

The objectives and scope of this study look diffused. The authors sometimes use waterlogging mapping but several places use waterlogging and flood risk zones. Please note that this study contributes nothing to flood risk zoning.

Most of the maps are very poor and not legible. It would be useful to show a satellite image of the study area as the first figure.

Two flow charts for the methodology are not needed – should be merged into one.

Table 1 is not required – most of the information is already there in the main text.

It would be useful to show the 5 zones mentioned in the text in the elevation map (Fig. 5). Otherwise, it is hard to match the text and figure.

Slope data does not seem to be useful as there is very little variation. It may be useful to redesign this by using a finer interval if the original data permits.

Similarly, the flow accumulation also does not show anything – more than 98% of the area falls in just one class. Again, it needs a finer resolution to make this data useful.

The LULC data analysis is interesting but does not connect to the main objective of the paper. How is the LULC change data used in the spatial analysis? Also, there are some issues with the correspondence of different data sets. For example, Figure 10 shows that the newly built areas are in the western part but a quick look at the LULC maps of 1990 and 2018 shows that most of the expansion has happened in the eastern part. Am I missing something?

Also, taking cues from the LULC change and some explanation offered in the text, I am fairly convinced that it is the drainage congestion that might have led to waterlogging rather than the LULC change itself. So, you need to find some ways to quantify this.

Taking the above argument further, the weightage scheme should also be relooked. If LULC has not played an important role, then you should bring this factor down and perhaps bring drain density up. Also, the flow accumulation factor is not an independent factor – it is a function of the slope. A mentioned earlier, road network should also be brought in this scheme, this is absolutely critical.

Section 7 on discussion should have been a major section of this paper but this hardly developed.

The authors talk about field evidence in the end but I did not find anything on this. The conclusion also talks about providing ‘essential information' for local government and again there is nothing on this.
Citation: https://doi.org/10.5194/nhess-2020-399-RC2
- AC2:
  'Reply on RC2_Author Comment', Diyali Chattaraj, 04 Jun 2021
  The enlargement of the study area definitely will provide better understanding about regional control of waterlogging. But our objective is confined to a micro/ward level analysis which provides vivid insights about waterlogging susceptibility at grass root level. Your valuable suggestion will be considered in future works.
  
  Road network plays a very important role in waterlogging especially in this municipality. The authors have considered road network as built-up, in land-use and land-cover map as well as considered in the overlay For this study area, drain network and road network run almost parallel to each other and their spatial distribution is also similar, that is why, the authors have not considered road network as a separate criterion.
  
  The study is solely dealing with waterlogging susceptibility mapping with the help of some parameters. Thus, to make the manuscript much simpler the words related to flood will be omitted.
  
  As the authors have already mentioned in AC1, all the maps presented in the paper (has been extracted with 600 dpi resolution) will be enlarged and rearranged so that all the components of map could be noticeable. A satellite view (FCC) of the study arch will be incorporated in the location map (Fig. 1).
  
  Figure 2 and 3 will be merged with a precise workflow of methodology as per your suggestion in the final manuscript.
  
  Tables generally provide a visual grouping of information and make the information more noticeable. That is why Table 1 has been included in the text. If it is not needed than it can be eliminated.
  
  5 elevation zones, which have already been mentioned in the text, will be incorporated and displayed in the elevation map (Fig. 4) as well.
  
  The slope map has been prepared from a contour map collected from the municipality. The accuracy of that contour map is considered 5 millimeters in order to get a clear idea about the micro-topographic forms of this region. The variation of the slope map is very less as the study area belongs to flat topography having only about 13 sq. km. of areal extent. The authors have already experimented with finer class intervals and did not find any differences in the final result.
  
  The situation is also similar in case of flow accumulation These two maps have been included in criteria according to experts’ views (hydrologists and engineers) and various literatures dealing with the waterlogging susceptibility mapping.
  
  In consultation with the experts to formulate the decision-making process, six parameters namely; elevation, slope, rainfall, soil, flow accumulation, land-use / land-cover (LULC), and drain density are considered responsible for the initiation of waterlogged condition in English bazar municipality. The criteria weight (weightage scheme) has been developed accordingly as per experts’ views and based on the previous literatures. If required, some more literatures will positively be reviewed for further understanding.
  
  Land use land cover is considered one of the most important parameters of water-logging within municipality premises. The LULC undergoes unplanned construction on the low-lying wetlands (located at the west) along with dramatic transformation of the natural and manmade sewerage system without paying any attention to the normal and storm water disposal waterways have led to drainage congestion and water-logging (Fig. 13). Further, absence of planned and adequate drainage system in the newly built-up extension (discussed later) has led the perennial problem of water-logging to be deep rooted in the urban fabrics of this municipality (less dense the drain network (Fig. 11a & b) emanates the capacity of an area to be more waterlogged (Fig. 13). You have also highlighted the importance of road network, which is included in land-use and land-cover map to determine the criteria weight. The temporal change of land-use and land-cover has not been considered in the overlay analysis. Only the land-use and land-cover of 2018 has been taken into consideration. Moreover, two time series satellite data (1990 and 2018) (Fig. 8a & b) have been used to identify and quantify (Fig. 9) the LULC change within municipality over last 30 years.
  
  The English Bazar municipality experiences a unique urban growth pattern. The LULC map of 2018 (Fig. 8b) shows urban infill, which has taken place in the eastern part that you have identified. If you have a look on the multi-date LULC map (Fig. 8a & b), rapid urban expansion has been developed in the western part which is attributed to huge in-migration since 1970 during the liberation war of Bangladesh. Rapid population growth, unplanned low-land filling eventually leads to number of localities to be emerged in the western part of municipality as newly built-up area (Fig. 10), which is further documented in table 4.
  
  As per the manuscript, result and discussion have been mentioned under different sections, but the results with the necessary discussions go simultaneously from section 4. Therefore, the section wise sub-headings can be rearranged for clear-cut understanding. Moreover, section 7 exclusively deals with several mitigating measures, suggested by the authors and stakeholders, applicable to this micro-region.
  
  The authors belong to English Bazar municipality, Malda town and experience the problem of drainage congestion and water-logging after every medium and heavy shower. However, some plates covering several waterlogged pockets within municipal wards, captured by the authors, will be sent as field evidence through supplement file, which may help to understand the severity.
  
  Citation: https://doi.org/10.5194/nhess-2020-399-AC2
RC3:
'Comment on nhess-2020-399', Anonymous Referee #3, 20 May 2021
This manuscript is a case study of using an integrated AHP-GIS approach to the English Bazar Municipality in West Bengal, India.

Overall—this case study, if significantly revised to put it into the context of the broader literature and to carefully consider how uncertainty in the data (including years of input for different data values) than it might become useful for the broader community. But, as it now stands, it is a case study without a lot of relevance outside of the region that it has been done, either for broader learnings of the methodology benchmarked in this region, or comparison of this method with other regions, or comparison of this methodology with other methodologies. Without this, it is difficult to see how it might be useable, used, and useful for other colleagues. What should they make of it, as it seems like a lot of variables, with a result that has little understanding if it is meaningful. If some of this can be adjusted in a major revision, this would make a useful case study contribution to NHESS. My comments are as follows:

The manuscript is very much a case study, and it is difficult to see how someone else should apply the study to their region, or what has been learned that is new. If the element of what is being done to either confront this method with this case study and benchmark results (and thus be useful to others) or to put this methodology in the context of other studies (and thus be useful to others), this would be fine. I suggest then the authors consider carefully how they are constructing their argument. One way is to introduce a section at the beginning that is a background which includes:

Waterlogging analytic approaches currently being used.

A critical review (even brief, of a dozen studies) of where AHP-GIS has been used in similar situations (not necessarily in India, this could be worldwide).

A critical presentation of variables that have been used to with regards to influence waterlogging (from the literature).

From this background, then you can state you will go into a specific case study.

Then in the discussion, it is important to come back to the bigger picture, as to what has been learned from this methodology to make this ‘more’ than just a case study, such that the case study is in the context of the wider literature.

Uncertainty. Although you discuss accuracy in places of input data, when I get to Figure 15, I don’t have a good understanding of how much the accuracy is influencing the final flood susceptibility map, nor how much the influence of the equations and parameters is influencing it. So if one of my input variables changed ‘a bit’ how much would this change? I believe much more needs to be done with discussing the influence of the accuracy (e.g., of data, and inputs) and the method used, on the results.

The method and the equations quoted seem to be from the 1980s. How has this methodology progressed beyond the 1980s?

Other:

Please go through and check all items for typos (e.g., line 126 Ci is CI,

Line 69: [Minor, my preference] Human-made not ‘mand-made’

Avoid acronyms in figure captions.

Figure captions. Please make these more self-standing (e.g., so one does not need to go to the text to figure them out, and including and sources of data used for the figure).

Figures: Please ensure all acronyms used in the figure are defined in the figure caption. Otherwise it makes the figures really hard to read. Figure 3: NBSS, LUP, LULC, TIN, DEM, are all used.

For equations, it seems odd to use words instead of variables. For example dist_i would be much better as d_i (d subscript i), radius would be much better as r. Having owrds just makes these difficult to read. Density could be ro.

Because of the importance of the variables, please create a table of variables, which is introduced towards the beginning, including units.

For data such as the soil map, how will the influence of when it has been collected influence the results? How much will it have changed over time. Can you do the same for ALL input, discussing carefully the year of collection of the data and how it might have changed.

Accuracy of your reporting of data in places seems a bit optimistic. For example, Table 2, you report to the nearest 0.01 mm. That seems a bit over-optimistic for the data you are working with.

Because of the importance of rainfall, I’d like to better understand its variation over the last 36 years, and within a year.

For your reporting of metres, this should be m, and it should be m above sea level (asl) as just stating ‘m’ is sort of meaningless without a reference point.

For the slope map, please clarify what the resolution of the grid that is used to construct it.

Line 188. Do you mean Table 7? This is many pages later. Please put ‘cells’ after 4139 for clarity, and check everywhere for units after numbers.

Figures everywhere, hard to see because of their size, so will need a careful look at these.

Please do look at the formatting guidelines for NHESS papers at https://www.natural-hazards-and-earth-system-sciences.net/submission.html.
Citation: https://doi.org/10.5194/nhess-2020-399-RC3
- AC3:
  'Reply on RC3_Author Comment', Diyali Chattaraj, 08 Jun 2021
  This manuscript is very much a case study of English Bazar municipality, Malda district which has grown with land availability not keeping pace with rapid population growth during last few decades. As a consequence, perennial problem of water-logging and drainage congestion in several pockets has been deep rooted on its urban fabrics after every medium to heavy shower. The present study aims to apply an integrated Analytic Hierarchy Process (AHP) in order to highlight the leading factors of water-logging and to delineate the susceptible zones on the GIS platform.
  
  The manuscript comprises a section at the beginning including the steps, through which the entire work has been formulated. In the introduction part, the problem of study has already been mentioned, along with the applied methodology, which is supported with several literatures on India and other developing nations. Moreover, a background containing several current literatures on the water-logging analytic approaches in association with brief reviews on integrated AHP-GIS throughout the World can also be incorporated, after which the specific case study proceeds.
  
  The input variables (as water-logging causative factors) are already mentioned in text form as well as presented in the workflow of methodology.
  
  The method and equations of AHP is quoted from 1980 by Thomas L. Saaty. The present work has also reviewed further progression of AHP as a method and its application (1986) by Fatemeh Zahedi; the axiomatic treatment of priority setting in Analytic Hierarchy Process (1986); a method of measurement with ratio scales (1987); an exposition of AHP in reply to remarks on the Analytic Hierarchy Process (1990); as a multicriteria decision making approach with factors in hierarchic structure (1990); (2008) by Thomas L. Saaty.
  
  The present work has gone through carefully and all the necessary corrections regarding the typos, minor corrections, avoiding acronyms in figure, figure captions and sources, use of variables in the equations will be made. Further, the authors ensure that all the acronyms, used in the figure are defined in the text and figure caption.
  
  The authors will make the figures more self-standing in order to easily figure them out.
  
  Sources are mentioned in all the figures, that may be enlarged for better understanding.
  
  The input variables are displayed in the workflow (in chart format) of methodology including units, that is why these are not mentioned in another table to avoid repetition.
  
  As the authors have already mentioned in AC1, monthly rainfall data for this micro region (13 km²) is not provided by the Indian Meteorological Department (IMD) which is considered one of the most authentic weather report organization in India. Further, the variation of rainfall over 36 years (1976-2012) can be displayed through a line diagram to better understand.
  
  m (meter) above sea level (msl) will be replaced in the manuscript.
  
  For all the six thematic input layers, the grid resolution is mentioned below:
  
  Elevation – 27.77 m
  
  Slope – 27.77 m
  
  Flow accumulation – 27.77 m
  
  Soil – 16.00 m
  
  Land use land cover – 10.00 m
  
  Drain density – 16.00 m
  
  The cell number along with the table (already in text) will be mentioned within manuscript wherever required.
  
  All the units (m (msl) for elevation, slope; pixels for flow accumulation; km/km² for drain density) are mentioned both in the text and figure and once again will be checked.
  
  As mentioned in AC1, all the maps, presented in the manuscript are extracted at 600-dpi resolution. It will be enlarged and rearranged, so that the components are vividly noticeable. Moreover, all the maps, diagrams and tables will be sent to the handling editor of this journal as supplement files to better understand.
  
  The formatting guideline for NHESS papers are thoroughly followed while preparing as well as arranging the manuscript for the submission, once again it will be verified by the authors.
  
  The soil map (Fig. 07) has been collected from National Bureau of Soil Survey and Land Use Planning (NBSS & LUP) in 2004 comprises of 3 types: a) Typic ustifluvents (low infiltrated); b) Typic ustorchrepts (moderately infiltrated) and c) Fluventic ustochrepts (highly infiltrated) within the municipality. These three soil types have not been changed in such a short time duration. And as per the water retention magnitude, Typic ustorchrepts records maximum flow accumulation (Fig. 06) and is found most susceptible to water logging as well (Fig. 13).
  
  You have pointed out that how much a ‘bit change’ in the input variable will influence the final water-logging susceptibility map. This unique study positively could have been made. In that case, it would have been much lengthy and entirely methodology-oriented paper. Rather the authors aimed to do a case study of the current urban water-logging problem in one of the oldest and fastest growing metropolitan area in India. In this regard, the authors will certainly consider your valuable suggestions for future study.
  
  Citation: https://doi.org/10.5194/nhess-2020-399-AC3

Diyali Chattaraj, Biswajit Paul, and Subir Sarkar

Viewed

Total article views: 2,111 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
1,103	956	52	2,111	41	52

HTML: 1,103
PDF: 956
XML: 52
Total: 2,111
BibTeX: 41
EndNote: 52

Views and downloads (calculated since 11 Jan 2021)

Month	HTML	PDF	XML	Total
Jan 2021	158	36	3	197
Feb 2021	33	13	0	46
Mar 2021	28	9	0	37
Apr 2021	15	12	1	28
May 2021	71	29	10	110
Jun 2021	38	22	2	62
Jul 2021	17	12	0	29
Aug 2021	7	8	0	15
Sep 2021	23	29	0	52
Oct 2021	24	136	0	160
Nov 2021	12	84	0	96
Dec 2021	14	23	0	37
Jan 2022	14	27	0	41
Feb 2022	8	9	0	17
Mar 2022	11	27	1	39
Apr 2022	25	22	1	48
May 2022	12	14	1	27
Jun 2022	10	16	2	28
Jul 2022	8	14	0	22
Aug 2022	23	22	1	46
Sep 2022	13	11	1	25
Oct 2022	14	10	1	25
Nov 2022	17	13	0	30
Dec 2022	10	8	0	18
Jan 2023	22	33	0	55
Feb 2023	13	20	1	34
Mar 2023	18	7	0	25
Apr 2023	13	15	0	28
May 2023	19	16	1	36
Jun 2023	13	20	0	33
Jul 2023	23	22	2	47
Aug 2023	10	15	2	27
Sep 2023	30	14	0	44
Oct 2023	41	15	1	57
Nov 2023	18	10	0	28
Dec 2023	23	10	0	33
Jan 2024	33	10	0	43
Feb 2024	22	25	2	49
Mar 2024	20	27	2	49
Apr 2024	27	17	7	51
May 2024	27	10	2	39
Jun 2024	34	7	4	45
Jul 2024	24	10	1	35
Aug 2024	14	11	3	28
Sep 2024	21	9	0	30
Oct 2024	14	11	0	25
Nov 2024	12	9	0	21
Dec 2024	7	7	0	14

Cumulative views and downloads (calculated since 11 Jan 2021)

Month	HTML	PDF	XML	Total
Jan 2021	158	36	3	197
Feb 2021	33	13	0	46
Mar 2021	28	9	0	37
Apr 2021	15	12	1	28
May 2021	71	29	10	110
Jun 2021	38	22	2	62
Jul 2021	17	12	0	29
Aug 2021	7	8	0	15
Sep 2021	23	29	0	52
Oct 2021	24	136	0	160
Nov 2021	12	84	0	96
Dec 2021	14	23	0	37
Jan 2022	14	27	0	41
Feb 2022	8	9	0	17
Mar 2022	11	27	1	39
Apr 2022	25	22	1	48
May 2022	12	14	1	27
Jun 2022	10	16	2	28
Jul 2022	8	14	0	22
Aug 2022	23	22	1	46
Sep 2022	13	11	1	25
Oct 2022	14	10	1	25
Nov 2022	17	13	0	30
Dec 2022	10	8	0	18
Jan 2023	22	33	0	55
Feb 2023	13	20	1	34
Mar 2023	18	7	0	25
Apr 2023	13	15	0	28
May 2023	19	16	1	36
Jun 2023	13	20	0	33
Jul 2023	23	22	2	47
Aug 2023	10	15	2	27
Sep 2023	30	14	0	44
Oct 2023	41	15	1	57
Nov 2023	18	10	0	28
Dec 2023	23	10	0	33
Jan 2024	33	10	0	43
Feb 2024	22	25	2	49
Mar 2024	20	27	2	49
Apr 2024	27	17	7	51
May 2024	27	10	2	39
Jun 2024	34	7	4	45
Jul 2024	24	10	1	35
Aug 2024	14	11	3	28
Sep 2024	21	9	0	30
Oct 2024	14	11	0	25
Nov 2024	12	9	0	21
Dec 2024	7	7	0	14

Viewed (geographical distribution)

Total article views: 1,956 (including HTML, PDF, and XML) Thereof 1,954 with geography defined and 2 with unknown origin.

Country	#	Views	%

Cited

Latest update: 13 Dec 2024

Short summary

The present study pertains to identify and mapping of the water-logging susceptible zones in a municipality which has become a perennial deep rooted problem on the urban fabrics. By considering multi-criteria assessment of six natural and man-made factors the result reveals that 11.45 %, 3.05 % and 85.49 % area corresponds with highly vulnerable, low and moderately vulnerable respectively, is attributed to unplanned urban expansion in the hazardous low-lying area with inadequate drainage problem.


Total:	0
HTML:	0
PDF:	0
XML:	0

Integrated Multi-parametric Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) based Spatial modelling for Flood and Water logging Susceptibility Mapping: A case study of English Bazar Municipality of Malda, West Bengal, India

Viewed

Viewed (geographical distribution)

Cited

8 citations as recorded by crossref.