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Peer-Review Record

Drought Risk under Climate and Land Use Changes: Implication to Water Resource Availability at Catchment Scale

Water 2019, 11(9), 1790; https://doi.org/10.3390/w11091790
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Water 2019, 11(9), 1790; https://doi.org/10.3390/w11091790
Received: 10 July 2019 / Revised: 22 August 2019 / Accepted: 24 August 2019 / Published: 28 August 2019
(This article belongs to the Section Hydrology)

Round 1

Reviewer 1 Report

General comments

The manuscript “Drought risk under climate and land use changes: Implication to water resources availability at catchment scale” presents a study on potential climate and land use change impacts on water resources, focusing on drought conditions. The location of the study is at Frome river basin (UK), using data and simulated climate change projections from several sources. A hydrological model and various indices were used to perform the presented analysis.

The topic of the paper is timely and interesting. Although the study focuses only on one small catchment, insights regarding current and future conditions of water resources in the region could be derived. However, the paper has structural weaknesses, while parts of the methodological approach are poorly described / supported and contain rather critical conceptual flaws (see specific comments).

Overall, the paper includes interesting features, though there should be corrections and improvements; the introductory and methodological sections must be revised and enhanced, while parts of the analysis should be reconsidered.


Specific comments

[Section 1] The introductory section mainly presents an overview of drought events and potential impacts in the UK. However, the included references are rather old, while no overview of recent literature on the topic/approach under study is presented. It is recommended to enhance this section with more up-to-date references, including recent research on drought analysis under climate change, that use similar approaches to the present study (i.e. hydrological modelling for assessing drought / climate change impacts on streamflow and/or groundwater).

[Section 2] It is recommended to use more clear titles describing the content of this section. Indicatively, the section title could be “2. Material and methods", subdivided to “2.1 Study area and data”, “2.2 DiCaSM model ….”, etc. It is also important to include an overview of the methodological approach (a flow chart could be also helpful), due to the fact that the components of the analysis and the steps followed may create confusion to the reader. 

[Section 2.1] The part of this section referring to data could be placed in another sub-section, e.g. “Study area and data” (see comment above). Additionally, more specific information on the acquired data would be useful. For example, regarding the “historic continuous climatic variables data” (line 98), what type of data is included, in what time step and for which stations (or, if they are modelled data, in what resolution/grid size)? Where is the location of streamflow gauging station? What type of data is included in the “river and water bodies data” (line 102)? It would be also useful to include the locations of the gauging stations in the map of the study area (e.g. Fig. 2).

[Section 2.1] It is recommended to add here (instead of the results section) further information on the utilised model, such as the number of the calibration parameters and their significance. Also, to avoid confusion to the reader, please use unique symbols for representing same parameters in Eqs. 1 and 2 (e.g., use either Oi or yo).

[Section 2.2] The percentages presented in Table 1 are important in understanding possible seasonal variations, however it would be useful to present also the annual change percentage for each scenario / time period, because even a small change (%) during winter may have significant impact on annual rainfall.

[Section 2.3] The use of RDI in identifying drought conditions compared to SPI, especially under climate change scenarios, is a sound approach based on previous studies on the topic. However, apart from RDI, the ‘adjusted RDI’ is introduced here (using net rainfall and actual evapotranspiration), without providing any detail on its rationale or any other justification for the purpose of its use. Although its approach may have some similarity to the ‘Effective RDI’ (https://doi.org/10.1007/s40710-017-0219-x), the use of actual evapotranspiration has several conceptual drawbacks (already analysed in previous studies). The main problem lies on the fact that actual evapotranspiration (in contrast to potential evapotranspiration) is limited by rainfall amount and acts as a dependant variable, therefore the ratio of (net) rainfall to actual evapotranspiration cannot reliably represent drought conditions (see also comment #10). If the authors choose to include this adjustment for demonstration/comparison purposes, this should be clearly stated, including also its sufficient description, justification and support by relevant literature. In any case, the final evaluation of drought conditions for climate change scenarios must be principally performed using the original index (see also comment #12). 

[Section 2.3] Further explanation / description should be included regarding SMD and WI indices, along with some basic references.

[Section 3.1] The calibration period must be clarified; is it 2000-2001 (line 214, Fig. 4 caption) or 2012 (Fig. 4a, Table 2)? In any case, it seems that only one year was used for model calibration. A typical approach for model calibration would be to use a period of years that also include extreme conditions. Considering that apart from simulating historical streamflow the model is also used under climate change scenarios, the aforementioned approach would reduce the involved uncertainties. Please elaborate on the matter.

[Section 3.2.1] The time scale used for SPI calculation is not clarified (only in Fig. 7 it is mentioned that 6-month SPI is presented). The selection of the appropriate time scale is important for identifying different types of drought; some justification on the selection of the time scale must be included (see also next comment).

[Section 3.2.2] Similarly to the above comment, the selection of the time scale should be explained. Also, it seems that different time scale is used for RDI and SPI, please explain. Regarding the use of the Adjusted RDI, it is clear that its results are quite different from the results of the original index, while in many cases they fall in different drought categories. The differences are more evident in dry years and may lead to misleading interpretation of drought conditions. Taking into account the conceptual issues (comment #6), the use of the Adjusted RDI must be reconsidered.

[Sections 3.3.1 – 3.3.2] Similarly to comment #5, it would be useful to present also the annual percentage in Figs. 10 and 11. 

[Section 3.3.3.2] According to comment #6, the use of Adjusted RDI must be reconsidered, using RDI for the evaluation of drought conditions.

[Sections 4 – 5] The discussion and the conclusions must be revised according to the previous comments.


Minor issues

Please improve the resolution of Fig. 2 and 3, it is difficult to read some parts of these figures.

The caption of Fig. 4 does not represent accurately the contents of the figure; please revise.

[line 262] Please revise the phrase ‘extremely severe’.

[lines 487-490] The repetition of drought severity levels is not necessary here.

Please edit the text according to the style of the journal (sub-sections levels, numbered references, capitalization, etc.).

Author Response

Reviewer 1

Comment

Reply to the comment

[Section 1] The introductory section mainly presents an overview of drought events and potential impacts in the UK. However, the included references are rather old, while no overview of recent literature on the topic/approach under study is presented. It is recommended to enhance this section with more up-to-date references, including recent research on drought analysis under climate change, that use similar approaches to the present study (i.e. hydrological modelling for assessing drought / climate change impacts on streamflow and/or groundwater).

Added

Changes in the land surface hydrology are attributed to the multiple effects of the changes in climate, vegetation, and soil [1]. Therefore, it is important to understand the combined impact of climate and land use changes on water resources availability. Drought has  significant economic, social and ecological impacts, However, there is no universal consensus about the definition of drought [2]. Commonly, drought occurs due to an extended period receiving below average rainfall This is considered a meteorological drought, which progresses into agricultural, hydrological, and the socio-economic drought [3]. The general perception is that the UK is not a drought-prone country, however in the UK has experienced frequent occurrence of drought events such as those of  the 1970s, 1980s and in the 1990s, where summer drought events were the outcome of the increased variability in climate  [4]. These events were followed by another severe drought event that occurred in 1995, mainly affecting the north and western parts of the country [5].

[Section 2] It is recommended to use more clear titles describing the content of this section. Indicatively, the section title could be “2. Material and methods", subdivided to “2.1 Study area and data”, “2.2 DiCaSM model ….”, etc. It is also important to include an overview of the methodological approach (a flow chart could be also helpful), due to the fact that the components of the analysis and the steps followed may create confusion to the reader. 

Moved

Section 2.1] The part of this section referring to data could be placed in another sub-section, e.g. “Study area and data” (see comment above). Additionally, more specific information on the acquired data would be useful. For example, regarding the “historic continuous climatic variables data” (line 98), what type of data is included, in what time step and for which stations (or, if they are modelled data, in what resolution/grid size)? Where is the location of streamflow gauging station? What type of data is included in the “river and water bodies data” (line 102)? It would be also useful to include the locations of the gauging stations in the map of the study area (e.g. Fig. 2).

Described and new figure of schematic representation added

Figure 4: Frome catchment modelling work schematic representation

Quality of the figures 1 and 2 improved

[[Section 2.1] It is recommended to add here (instead of the results section) further information on the utilised model, such as the number of the calibration parameters and their significance. Also, to avoid confusion to the reader, please use unique symbols for representing same parameters in Eqs. 1 and 2 (e.g., use either Oi or yo).

The section added in the methodology section

In the DiCaSM model, the streamflow significantly depends on five key parameters: the percentage of surface runoff routed to stream, catchment storage/time lag coefficient, exponent function describing the peak flows, stream storage/time lag coefficient, and the stream bed infiltration//leakage. At the start of the model calibration process, the model was run by changing all the five key parameters using different time periods’ data and the best time period was selected for the possible use for the model calibration. This was followed by the optimization process based on a simple iteration algorithm in which each of the five parameters were assigned a realistic range. Each range was divided into smaller steps and the number of total iterations is the product of multiplication of the steps of the five key parameters. The number of iterations for each parameter was assigned according to the parameter sensitivity, i.e. a higher number of iterations were assigned to parameters which showed more sensitivity to the streamflow. The model calculates the Nash-Sutcliffe Efficiency value, NSE for each iteration based on the least square of the difference between the simulated and observed streamflow values. The model optimisation process helps in finding a good set of parameters that produces a good model efficiency value.

[Section 2.2] The percentages presented in Table 1 are important in understanding possible seasonal variations, however it would be useful to present also the annual change percentage for each scenario / time period, because even a small change (%) during winter may have significant impact on annual rainfall.

A new column of annual change added

[Section 2.3] The use of RDI in identifying drought conditions compared to SPI, especially under climate change scenarios, is a sound approach based on previous studies on the topic. However, apart from RDI, the ‘adjusted RDI’ is introduced here (using net rainfall and actual evapotranspiration), without providing any detail on its rationale or any other justification for the purpose of its use. Although its approach may have some similarity to the ‘Effective RDI’ (https://doi.org/10.1007/s40710-017-0219-x), the use of actual evapotranspiration has several conceptual drawbacks (already analysed in previous studies). The main problem lies on the fact that actual evapotranspiration (in contrast to potential evapotranspiration) is limited by rainfall amount and acts as a dependant variable, therefore the ratio of (net) rainfall to actual evapotranspiration cannot reliably represent drought conditions (see also comment #10). If the authors choose to include this adjustment for demonstration/comparison purposes, this should be clearly stated, including also its sufficient description, justification and support by relevant literature. In any case, the final evaluation of drought conditions for climate change scenarios must be principally performed using the original index (see also comment #12). 

Described and a new paragraph added

In order to accurately quantify the RDI, one could use actual values instead of potential values. Total rainfall does not represent the actual rainfall that is ready for infiltration and surface runoff as some of the total rainfall gets intercepted by land cover and evaporates back to the atmosphere and in case of trees, the intercepted amount is significant. Therefore, if the amount of rainfall intercepted, by the canopy, is not considered, there would be overestimated of the amount of rain available for infiltration and runoff and subsequently overestimate of the fluxes (streamflow, groundwater recharge, transpiration, bare soil evaporation, etc.). Potential evapotranspiration represents the atmospheric demand for water and reflects the potential ability of soil and plant to transport water from the soil to the atmosphere. A plant can only transpire at the potential level and soil can only evaporate at the potential level if soil moisture at maximum holding capacity. During drought events, soil moisture falls well below maximum holding capacity and neither the plant nor the soil can transport water to the atmosphere at potential level, therefore it makes sense to use net rainfall and actual evapotranspiration (plant transpiration and bare soil evaporation) in calculating the RDI. If soil moisture is at maximum holding capacity, actual evapotranspiration will be equal to potential evapotranspiration

In order to accurately quantify the RDI, one could use actual values instead of potential values. Total rainfall does not represent the actual rainfall that is ready for infiltration and surface runoff as some of the total rainfall gets intercepted by land cover and evaporates back to the atmosphere and in case of trees, the intercepted amount is significant. Therefore, if the amount of rainfall intercepted, by canopy, is not considered, there would be overestimate of the amount of rain available for infiltration and runoff and subsequently overestimate of  the fluxes (stream flow, groundwater recharge, transpiration, bare soil evaporation, etc.). Potential evapotranspiration represents the atmospheric demand for water and reflects the potential ability of soil and plant to transport water from soil to the atmosphere. Plant can only transpire at potential level and soil can only evaporates at potential level if soil moisture at maximum holding capacity.  During drought events, soil moisture falls well below maximum holding capacity and neither the plant nor the soil can transport water to the atmosphere at potential level,   therefore it makes sense to use net rainfall and actual evapotranspiration (plant transpiration and bare soil evaporation) in calculating the RDI. If soil moisture is at maximum holding capacity, actual evapotranspiration will be equal to potential evapotranspiration. 

 

[Section 2.3] Further explanation / description should be included regarding SMD and WI indices, along with some basic references.

Added

Two other drought indices were considered: the soil moisture deficit (SMD) and wetness index (WI) of the root-zone. The SMD is the difference between current soil moisture and the maximum water holding capacity of the soil known as “Field Capacity. The, WI is the scaled soil moisture: 1 means, soil water content at maximum value, 0: means the soil water content at its minimum value. The WI accounts for the spatial variability of soil types, elevation, and vegetation cover across the catchment

[Section 3.1] The calibration period must be clarified; is it 2000-2001 (line 214, Fig. 4 caption) or 2012 (Fig. 4a, Table 2)? In any case, it seems that only one year was used for model calibration. A typical approach for model calibration would be to use a period of years that also include extreme conditions. Considering that apart from simulating historical streamflow the model is also used under climate change scenarios, the aforementioned approach would reduce the involved uncertainties. Please elaborate on the matter.

Revised

Results of the model calibration for the period 2001-2012 are shown in Figure 5, which illustrates that the model performance was very satisfactory during the model calibration period and the model responded well to the rainfall events. The figure shows that the simulated values are a mirror image to the observed values. During the model calibration stage model efficiency measured using the NSE, efficiency was over 85% and the percentage error was less than 1%.

[Section 3.2.1] The time scale used for SPI calculation is not clarified (only in Fig. 7 it is mentioned that 6-month SPI is presented). The selection of the appropriate time scale is important for identifying different types of drought; some justification on the selection of the time scale must be included (see also next comment).

Added

[Section 3.2.2] Similarly to the above comment, the selection of the time scale should be explained. Also, it seems that different time scale is used for RDI and SPI, please explain. Regarding the use of the Adjusted RDI, it is clear that its results are quite different from the results of the original index, while in many cases they fall in different drought categories. The differences are more evident in dry years and may lead to misleading interpretation of drought conditions. Taking into account the conceptual issues (comment #6), the use of the Adjusted RDI must be reconsidered

Explained and new paragraph added in section 2.5 (see track changes documents).

[Sections 3.3.1 – 3.3.2] Similarly to comment #5, it would be useful to present also the annual percentage in Figs. 10 and 11. 

Added and figures revised

  [Section 3.3.3.2] According to comment #6, the use of Adjusted RDI must be reconsidered, using RDI for the evaluation of drought conditions.

 

[Sections 4 – 5] The discussion and the conclusions must be revised according to the previous comments.

Revised (see track changes)

 

Minor issues

Please improve the resolution of Fig. 2 and 3, it is difficult to read some parts of these figures.

The caption of Fig. 4 does not represent accurately the contents of the figure; please revise.

[line 262] Please revise the phrase ‘extremely severe’.

[lines 487-490] The repetition of drought severity levels is not necessary here.

Please edit the text according to the style of the journal (sub-sections levels, numbered references, capitalization, etc.).

 

 

Quality of both figures improved. Caption for the figure 4old (new figure 5) changed,

 

 

 

 

 

This is well-used terminology

 

 

 

All changed (References are numbered now).

 

Author Response File: Author Response.docx

Reviewer 2 Report

The paper presents a study on the impact of drought on water resources at a catchment scale under climate and land use changes. The results of the study can help in the planning and management of water resources in the study area.

The paper is organized in five main sections but the subsection descriptions need more clarifications. Please, follow the specific comments and suggestions below.

Line 61:  2. Data, the catchment and methodology

Comment: Your subsections order does not follow the order you’ve mentioned in the section’s title. Therefore, I would suggest you to harmonized the section and subsections titles in a logical order which might be “2.1 Catchment description, 2.2 Data and 2.3 Methodology”

Line 79:  The DiCaSM model and model efficiency measuresThis could be either a subsection of Methodology or a stand-alone subsection

Lines 112-113:” The model calibration was carried out over two years and the validation period varied from a number of years to the entire available record.” – Could you be more specific indicating the specific years for calibration and validation?

Lines 114: “simulated and observed flow data were compared using a number of indices,..”

Before comparing the indices, it would be interesting to show a comparison between the simulated and observed data used to calculate the indices. Please, define all the indices you have analyzed.

Lines 129-134: “..the UK Climate Change Scenarios (UKCP09) which provide projections for the changes in the amount and seasonal variation of precipitation, temperature and other climatic variables…” – Please provide a reference for the UKCP09 and, eventual, a short description of it.

Lines 134-135: “..UKCP09 climate change projections are provided for seven overlapping time periods and for three greenhouse gas emission scenarios, low, medium and high relative to the baseline time period,…” – Please, provide more details on time horizon, emission, scenarios, and base line period.

– What stands for low, medium and high emission scenarios??-

Line 158 – Which is the UK base line period?

Lines 166-197: Drought indices – Please, define all the drought indices you’ve calculated and then analyzed in section 3 Results.

Figure 1 – Please, improve the resolution because as it is, it is not readable

Figure 2 – the text in the bottom is not readable; please, improve the resolution

Lines 214-218: ..” Results of the model calibration for the period 2000‐2001 are shown in Figure 4, which illustrates that the model performance was very satisfactory during the model calibration period and the model responded well to the rainfall events. The figure shows that the simulated values are mirror image to the observed values.” – Figure 4 confused me: The figure caption says “Model calibration of stream flow during the 2000‐2001 period”, The upper graph shows the Frome model calibration for 2012, and the bottom graph shows the Frome model validation for 1971-1980. – Could you please, clarify the text where it is the case?

Lines 224-225 ” .. the model performed very well as the NSE Efficiency was above 80% and the percentage error between the observed and modelled flow was less 5%.” – Where can we see that?

Line 247: Figure 6 Relationship between the observed and simulated daily flow of the River Frome in Bristol

– Could you, please, explain in the text the reason why you have selected the examples presented in Fig 6? On the upper row you have simulated flow of 2012 next to the observed flow of 2001-212, in the middle observed flow of 1991-2000 vs observed flow of 1981-1990 and in the bottom observed flow of 1971-1980 vs 1962-2012.

Line 248  Table 2:  – Please, comment in the text the results presented in Table 2.

Lines 254-256: instead of the description provided in the text you may better present the scale values of the SPI in a table.

Lines 262-274: Please, specify in the text the time lag (6-month?) that you have used in your study for the SPI.

Lines 278-294: - It seems from the Figure 8 that the RDI is calculated at annual time scale. Please, specify that in the text. Also, it is important to know whether the classification of drought upon the RDI values is the same as that for the SPI.

Lines 372-394: The indices presented in this subsection should have been described in the Methodology section. Also, you should also explain the reason why all these indices are important and necessary to identify the major drought episodes during the observation period?

Lines 399-403: “The streamflow projections under both the simplified change factors provided by the joint probability and the weather generator data suggest that the stream flow is likely to be reduced under all emission scenarios ....”  - This sentence is unclear. What are the “simplified change factors”?

The discussion in this subsection should be carefully reconsidered, for the sake of clarity.

Line 458 3.3.3 Drought indices – This subsection refers to the projected drought indices

Line 462 “The use of the daily projected data of the weather generator with the DiCaSM model …”

– You should explained how have you calculated the projected changes for the 30-year periods from the daily projected data.

The scenarios corresponding to low, medium and high emissions should be describes in the section 2

Lines 487-490 – The scale values of RDI can be better presented in a table in the corresponding subsection of section 2 where the definition of RDI is described.

Figure 13 – Please, explain how have you defined a drought event represented here.

Section 4 Discussion – I would suggest the discussion be more focused on the physical arguments involved in the use of as many drought indices.

The discussion of the results obtained in comparison with other similar studies is welcome.

Lines 589-590: Could you, please provide more comments on the results obtained from “weather generator and joint probability data”. Is any preference in using one or the other data ?

Section 5. Conclusions

This section should be better organized as such to present clear conclusions of the results on the observed and projected drought impact on water resources at the selected catchment scale.

 

Author Response

Reviewer 2

Comment

Reply to the comment

 

 

Figure 1

Changed according to both reviewers’ suggestions. Gauging station location added in the figure

Comment: Your subsections order does not follow the order you’ve mentioned in the section’s title. Therefore, I would suggest you to harmonized the section and subsections titles in a logical order which might be “2.1 Catchment description, 2.2 Data and 2.3 Methodology”

Changed.

Line 79:  The DiCaSM model and model efficiency measuresThis could be either a subsection of Methodology or a stand-alone subsection

Changed (see reply to reviewer 1 comments)

Lines 112-113:” The model calibration was carried out over two years and the validation period varied from a number of years to the entire available record.” – Could you be more specific indicating the specific years for calibration and validation?

Changed (see reply to reviewer 1 comments)

Lines 114: “simulated and observed flow data were compared using a number of indices,..”

Before comparing the indices, it would be interesting to show a comparison between the simulated and observed data used to calculate the indices. Please, define all the indices you have analyzed.

The order changed

Lines 129-134: “..the UK Climate Change Scenarios (UKCP09) which provide projections for the changes in the amount and seasonal variation of precipitation, temperature and other climatic variables…” – Please provide a reference for the UKCP09 and, eventual, a short description of it. Lines 134-135: “..UKCP09 climate change projections are provided for seven overlapping time periods and for three greenhouse gas emission scenarios, low, medium and high relative to the baseline time period,…” – Please, provide more details on time horizon, emission, scenarios, and base line period.

– What stands for low, medium and high emission scenarios??-

 

 

Added

These probabilistic climate predictions are based on families of runs of the Met Office Hadley Centre climate models HadCM3, HadRM3 and HadSM3, combined with other climate models from different climate centres contributing to IPCC AR4 and CMIP3. The changes in global temperature are taken from three emissions scenarios: low (IPCC SRES: B1), medium (IPCC SRES: A1B), and high (IPCC SRES: A1F1), and each scenario provides estimates over seven 30-years overlapping time periods, wherein this study three time periods (2020, the 2050s and 2080s) were selected (Table 1).

 

Other changes

Changed to the baseline period (1961-1990)

Changed (see track changes manuscript and the revised calibration period figure in

Line 158 – Which is the UK base line period?

Lines 166-197: Drought indices – Please, define all the drought indices you’ve calculated and then analyzed in section 3

Added

 

Defined

Figure 1 – Please, improve the resolution because as it is, it is not readable

Figure 2 – the text in the bottom is not readable; please, improve the resolution

Lines 214-218: ..” Results of the model calibration for the period 2000‐2001 are shown in Figure 4, which illustrates that the model performance was very satisfactory during the model calibration period and the model responded well to the rainfall events. The figure shows that the simulated values are mirror image to the observed values.” – Figure 4 confused me: The figure caption says “Model calibration of stream flow during the 2000‐2001 period”, The upper graph shows the Frome model calibration for 2012, and the bottom graph shows the Frome model validation for 1971-1980. – Could you please, clarify the text where it is the case?

Changed and quality improved

 

Changed and quality improved

 

 

Figure changed and result revised

Lines 224-225 ” .. the model performed very well as the NSE Efficiency was above 80% and the percentage error between the observed and modelled flow was less 5%.” – Where can we see that?

Line 247: Figure 6 Relationship between the observed and simulated daily flow of the River Frome in Bristol

– Could you, please, explain in the text the reason why you have selected the examples presented in Fig 6? On the upper row you have simulated flow of 2012 next to the observed flow of 2001-212, in the middle observed flow of 1991-2000 vs observed flow of 1981-1990 and in the bottom observed flow of 1971-1980 vs 1962-2012.

 

Table 2 updated and revised

 

 

 

 

 

 

 

Explained, to find the model performance during the dry and wet events

Line 248  Table 2:  – Please, comment in the text the results presented in Table 2.

Lines 254-256: instead of the description provided in the text you may better present the scale values of the SPI in a table.

Lines 262-274: Please, specify in the text the time lag (6-month?) that you have used in your study for the SPI.

Lines 278-294: - It seems from the Figure 8 that the RDI is calculated at annual time scale. Please, specify that in the text. Also, it is important to know whether the classification of drought upon the RDI values is the same as that for the SPI.

 

 

 

It's easy to explain using figures, there is no point in having another table with two columns

 

Explained

 

Yes, RDI was calculated on an annual scale, the resulted are shown with the comparison of two.

Lines 372-394: The indices presented in this subsection should have been described in the Methodology section. Also, you should also explain the reason why all these indices are important and necessary to identify the major drought episodes during the observation period?

It has been explained in the text

Lines 399-403: “The streamflow projections under both the simplified change factors provided by the joint probability and the weather generator data suggest that the stream flow is likely to be reduced under all emission scenarios ....”  - This sentence is unclear. What are the “simplified change factors”?

The discussion in this subsection should be carefully reconsidered, for the sake of clarity

Described

Line 458 3.3.3 Drought indices – This subsection refers to the projected drought indices

Line 462 “The use of the daily projected data of the weather generator with the DiCaSM model …”

– You should explained how have you calculated the projected changes for the 30-year periods from the daily projected data.

The scenarios corresponding to low, medium and high emissions should be describes in the section 2

Explained

Lines 487-490 – The scale values of RDI can be better presented in a table in the corresponding subsection of section 2 where the definition of RDI is described.

We tried to show them in the table, with a small range of values it's not well explanatory, however, in the figures, one can clearly see the difference between the different drought severity levels under different climate change scenarios and the time periods.

Section 4 Discussion – I would suggest the discussion be more focused on the physical arguments involved in the use of as many drought indices.The discussion of the results obtained in comparison with other similar studies is welcome.

Lines 589-590: Could you, please provide more comments on the results obtained from “weather generator and joint probability data”. Is any preference in using one or the other data

Restructured and drought Indices received more attention, followed by climate change impact on water resources followed by land-use change impact on water resources.

 

 

 

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The revised version of the manuscript is improved addressing many of the comments and suggestions.

A main issue that has not been sufficiently dealt with is the utilised adjustment of RDI index, that should be further revised and discussed to avoid misinterpretation of the results:

The use of the net or effective precipitation instead of the total precipitation in RDI formulation is a rational approach that has been already discussed in the literature (e.g. see https://doi.org/10.1016/j.proeng.2016.11.072). However, the use of evapotranspiration in RDI (and similar drought indices such as SPEI) intends to represent the evaporative atmospheric demand (e.g. see https://doi.org/10.1007/s11269-006-9105-4), in contrast to other drought indices (such as PDSI) that practically incorporate water balance procedures. Therefore, the use of actual instead of potential evapotranspiration may have weaknesses and limitations, related to the soil/plant/atmosphere interaction and the direct dependence of actual evapotranspiration to precipitation (e.g. see https://doi.org/10.1002/joc.3887).

In order to evaluate efficiently the proposed adjustment of RDI, the above issues should be taken into account and included with proper justification / literature support in section 2.5, while the corresponding discussion in section 3.2.2 must be also enhanced.

 

Minor issues

- Please correct the calibration period in the caption of Fig. 5

- [line 415] The phase «‘extremely severe’ drought level» is not well used terminology; according to SPI classification (presented in lines 404-406), drought could be either in ‘severe’ or ‘extreme’ level.

Author Response

Comments and Suggestions for Authors

The revised version of the manuscript is improved addressing many of the comments and suggestions.

A main issue that has not been sufficiently dealt with is the utilised adjustment of RDI index, that should be further revised and discussed to avoid misinterpretation of the results:

The use of the net or effective precipitation instead of the total precipitation in RDI formulation is a rational approach that has been already discussed in the literature (e.g. see https://doi.org/10.1016/j.proeng.2016.11.072). However, the use of evapotranspiration in RDI (and similar drought indices such as SPEI) intends to represent the evaporative atmospheric demand (e.g. see https://doi.org/10.1007/s11269-006-9105-4), in contrast to other drought indices (such as PDSI) that practically incorporate water balance procedures. Therefore, the use of actual instead of potential evapotranspiration may have weaknesses and limitations, related to the soil/plant/atmosphere interaction and the direct dependence of actual evapotranspiration to precipitation (e.g. see https://doi.org/10.1002/joc.3887).

In order to evaluate efficiently the proposed adjustment of RDI, the above issues should be taken into account and included with proper justification / literature support in section 2.5, while the corresponding discussion in section 3.2.2 must be also enhanced.

Response: Additional paragraph explaining the rational of using actual not potential values has been added to page 9 and 10 lines 238-248. Processes happen in nature at actual level not at potential level. Sometimes the actual equals the potential but this is the exception not the norm. The reviewer might see more evidence of how important to use actual evaporation not potential in:

Ragab, J.G. Evans, A. Battilani and D. Solimando. 2017. Towards accurate estimation of crop water requirement without the crop coefficient: New approach using modern technologies. . Irrigation and Drainage, 66: 469–477

Wiley issued a press release on October 6, 2017 to highlight the importance of using actual evapotranspiration instead of potential:

https://newsroom.wiley.com/press-release/irrigation-and-drainage/research-may-lead-improvements-water-use-crop-irrigation

and

https://www.eurekalert.org/pub_releases/2017-10/w-rml100617.php

 

 Minor issues

- Please correct the calibration period in the caption of Fig. 5    Added to the caption page 11

- [line 415] The phase «‘extremely severe’ drought level» is not well used terminology; according to SPI classification (presented in lines 404-406), drought could be either in ‘severe’ or ‘extreme’ level. Corrected to extreme line 319 page14

Author Response File: Author Response.docx

Reviewer 2 Report

Dear Authors,

I’ve carefully read the revised version of the manuscript and, I’m happy to find out that the paper is has been improved in both quality of the presentation and scientific clarity.  Most of the comments and suggestions provided during the first review has been taken into consideration . However, few inconsistencies still remain to be clarified.

Following, I will refer first to the responses of the authors to my comments and suggestions after the first review, then to some inconsistencies in the revised version of the manuscript.

a)

Figure 1: – I cannot see any improvement in the quality of it. Please, look at the small map of GB which is totally blurred.

 

Line 462 (of version 1) “The use of the daily projected data of the weather generator with the DiCaSM model …” – You should explain how you have calculated the projected changes for the 30-year periods from the daily projected data. – It is not explained in the revised version Figure 13 seems to present the 30-yr average change relative to the baseline period. – Please, explicitly explain that in the text and, explicitly mention the baseline period in the figure caption. Regarding the range of values of the indices used in the study, I still think they should be better visible in a table even more they apply for all the indices.

b) In the revised version of the manuscript I’ve identified few mismatches that should be fixed. I will further refer to the lines in the clean version of revised manuscript.

- Lines 206-213: The RDI – the elements in the formulas (3) and (5) should be carefully explained , ie AEij in (3),  in (5)

Line 228: “if soil moisture at maximum holding capacity.” please, include “is”  Line 300: Figure 8. Please, modify like “ Six month –lag SPI … Line 324: I think, here, Figure 8 should be Figure 9 Line 328: Figures 7 and 8 should be Figures 8 and 9 Line 434: Here, something is missing .. Please, correct. Line 625: Figure 13 should be Figure 14

Author Response

Comments and Suggestions for Authors

Dear Authors,

I’ve carefully read the revised version of the manuscript and, I’m happy to find out that the paper is has been improved in both quality of the presentation and scientific clarity.  Most of the comments and suggestions provided during the first review has been taken into consideration. However, few inconsistencies still remain to be clarified.

Following, I will refer first to the responses of the authors to my comments and suggestions after the first review, then to some inconsistencies in the revised version of the manuscript.

a)

Figure 1: – I cannot see any improvement in the quality of it. Please, look at the small map of GB which is totally blurred.

When printed out, it looked all right. We will wait until the print proof comes out and check the quality again. These maps are not created by the authors but obtained from the archive.

 

Line 462 (of version 1) “The use of the daily projected data of the weather generator with the DiCaSM model …” – You should explain how you have calculated the projected changes for the 30-year periods from the daily projected data. – It is not explained in the revised version Figure 13 seems to present the 30-yr average change relative to the baseline period. – Please, explicitly explain that in the text and, explicitly mention the baseline period in the figure caption. Regarding the range of values of the indices used in the study, I still think they should be better visible in a table even more they apply for all the indices.

 

A paragraph has been added in page 17 lines 457-465 to explain in details the procedure.

b) In the revised version of the manuscript I’ve identified few mismatches that should be fixed. I will further refer to the lines in the clean version of revised manuscript.

- Lines 206-213: The RDI – the elements in the formulas (3) and (5) should be carefully explained , ie AEij in (3),  in (5)    Corrected page 9 line 214-218.

Line 228: “if soil moisture at maximum holding capacity.” please, include “is”  Included in line 233

Line 300: Figure 8. Please, modify like “ Six month –lag SPI … Line 324: I think, here, Figure 8 should be Figure 9 Line 328: Figures 7 and 8 should be Figures 8 and 9 Corrected in line 341-345

 Line 434: Here, something is missing ..  “As“ was missing and has been added. Please, correct. Line 625: Figure 13 should be Figure 14  corrected in line 656

Author Response File: Author Response.docx

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