the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Feb 2022
Spatiotemporal dynamics and interrelationship between soil moisture and groundwater over the Critical Zone Observatory in the Central Ganga plain, North India
Abstract. The understanding of spatiotemporal dynamics of Earth’s hydrological components and their controls is critical for efficient water resource management, especially in the agriculture-dominated landscapes. In this study, we utilize the empirical orthogonal function (EOF), random combination, and temporal stability approach on the soil moisture (SM) and depth to groundwater table (DTGT) observations from the Critical Zone Observatory in the Ganga basin to understand their spatiotemporal variability and optimal sampling strategies. Around 91 % of the observed DTGT spatial variations are explained by the first two spatial EOF whereas the first five EOFs explain only 67 % of the total SM variability. Topography and soil texture (% clay) are considered to be the leading factors that drive the spatial pattern of both the attributes. Furthermore, we noted that four SM sampling locations and two monitoring well, selected randomly can capture the mean spatial variability with an accuracy of 3 % vol /vol and 0.90 mgbl (meter below ground level) respectively. Moreover, four temporally stable SM sites and a single observation well are identified, which provide the spatial mean with an absolute error of ±2 % vol /vol and 0.36 mgbl respectively. Overall, this study provides an insight to spatiotemporal hydrological controls in an intensively managed landscape and has important implications for water resource management in such regions.
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RC1: 'Comment on hess-2022-47', Anonymous Referee #1, 28 Feb 2022
Review of “Spatiotemporal dynamics and interrelationship between soil moisture and groundwater over the Critical Zone Observatory in the Central Ganga plain, North India” by Dash et al.
In this study, different methods (empirical orthogonal function, random combination and temporal stability method approach) are applied to soil moisture and depth of 10 water tables of Critical Zone Observatory in Ganga Basin to understand their spatio-temporal variability and optimal sampling strategies. The topography and clay content of the soils are considered the most important factors determining the spatial pattern of the two quantities.
Unfortunately, I see the following fundamental problems with the study:
This a regional study that uses only existing methods, both in terms of measurement and methodology, so the results have no fundamental scientific added value outside the study area. Therefore, this work does not fit in this journal. Alternatively, there are many journals where regional studies like this can be published.
The temporal resolution of the data is rather poor. This is outdated nowadays, when sensors and data loggers can be acquired and operated for relatively little money.
The evaluation of groundwater levels with statistical methods is problematic because groundwater level measurements are usually not independent of each other, since they observe the same groundwater body. Unless the measurements took place in clearly delimited aquifers, but this was not explained in the text.
The statement that topography and the clay content of the soils are considered the most important factors determining the spatial pattern is not tenable, as the study area consists of irrigated agricultural fields. Therefore, the spatial pattern will strongly depend on the amount of water applied locally and the crops. Without taking this into account, the general statements cannot be made.
Finally, strategies for efficient irrigation water management are proposed that not based on the statistical analyses in this paper.
Citation: https://doi.org/10.5194/hess-2022-47-RC1 - AC1: 'Reply on RC1', Saroj Dash, 27 Apr 2022
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RC2: 'Comment on hess-2022-47', Anonymous Referee #2, 09 Apr 2022
Based on multi-year observations of soil moisture and groundwater table at spatially distributed sites over an agriculture-driven critical zone observatory, the authors investigate the spatiotemporal dynamics of both variables, using a series of analysis methods (incl. EOF, random combination, temporal stability analysis, etc). Based on the findings of these analyses combined with stakeholders' surveys, some water management strategies were proposed. The paper is very well written, structured, and clear. Below please find some main concerns:
1. Although the analysis carried out is very convincing in terms of finding representative sites/wells for understanding the spatial mean of the CZO, it is however not clear how the human activities (irrigation/groundwater extraction) will impact such analysis. There were several places the author indicate some spatiotemporal patterns to irrigation and pre-monsoon, post-monsoon precipitations. However, this information cannot be explicitly found in the manuscript. Please the authors try to clarify this information and explain their potential impacts on their findings.
2. The satellite data SMAP was mentioned in the manuscript. However, there is no satellite SM data used in this study. This reviewer thinks this is a miss of the opportunity. It would be great to link the in-situ measurement to remote sensing data, as such, it is more operational in a sense to monitor the impact of water management strategies on soil moisture, or even groundwater storage change. It is understandable that for GW storage, the current GRACE product is too coarse. However, for SMAP soil moisture data, you do can find 1km and 3km resolution products. Also from Sentinel-1 SM, it is 1km. As such, this reviewer would encourage the author to include satellite data in their analysis.
Some minor comments as below:
a. On page 10, line 230, this reviewer is wondering if you have the data about 'watering by farmers'?
b. Page 10, line 234-235, this reviewer think this is only happening when the GW table is shallow, right? Please clarify and provide some more discussions on this.
c. Line 265 'PC' should be 'EC'
d. Line 338, it would be convenient for readers if equations were given.
e. Line 344, these 'signals' should be marked out explicitly in Figure 9a
f. Line 414, 'in compared to' should be 'in comparison to'
Citation: https://doi.org/10.5194/hess-2022-47-RC2 - AC2: 'Reply on RC2', Saroj Dash, 27 Apr 2022
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EC1: 'Comment on hess-2022-47 from the editor', Nunzio Romano, 10 Apr 2022
Dear Authors,
Up to now, your submission has received comments from two reviewers. To keep the discussion step alive, I suggest you should start uploading some preliminary responses from your side.
Citation: https://doi.org/10.5194/hess-2022-47-EC1
Status: closed
-
RC1: 'Comment on hess-2022-47', Anonymous Referee #1, 28 Feb 2022
Review of “Spatiotemporal dynamics and interrelationship between soil moisture and groundwater over the Critical Zone Observatory in the Central Ganga plain, North India” by Dash et al.
In this study, different methods (empirical orthogonal function, random combination and temporal stability method approach) are applied to soil moisture and depth of 10 water tables of Critical Zone Observatory in Ganga Basin to understand their spatio-temporal variability and optimal sampling strategies. The topography and clay content of the soils are considered the most important factors determining the spatial pattern of the two quantities.
Unfortunately, I see the following fundamental problems with the study:
This a regional study that uses only existing methods, both in terms of measurement and methodology, so the results have no fundamental scientific added value outside the study area. Therefore, this work does not fit in this journal. Alternatively, there are many journals where regional studies like this can be published.
The temporal resolution of the data is rather poor. This is outdated nowadays, when sensors and data loggers can be acquired and operated for relatively little money.
The evaluation of groundwater levels with statistical methods is problematic because groundwater level measurements are usually not independent of each other, since they observe the same groundwater body. Unless the measurements took place in clearly delimited aquifers, but this was not explained in the text.
The statement that topography and the clay content of the soils are considered the most important factors determining the spatial pattern is not tenable, as the study area consists of irrigated agricultural fields. Therefore, the spatial pattern will strongly depend on the amount of water applied locally and the crops. Without taking this into account, the general statements cannot be made.
Finally, strategies for efficient irrigation water management are proposed that not based on the statistical analyses in this paper.
Citation: https://doi.org/10.5194/hess-2022-47-RC1 - AC1: 'Reply on RC1', Saroj Dash, 27 Apr 2022
-
RC2: 'Comment on hess-2022-47', Anonymous Referee #2, 09 Apr 2022
Based on multi-year observations of soil moisture and groundwater table at spatially distributed sites over an agriculture-driven critical zone observatory, the authors investigate the spatiotemporal dynamics of both variables, using a series of analysis methods (incl. EOF, random combination, temporal stability analysis, etc). Based on the findings of these analyses combined with stakeholders' surveys, some water management strategies were proposed. The paper is very well written, structured, and clear. Below please find some main concerns:
1. Although the analysis carried out is very convincing in terms of finding representative sites/wells for understanding the spatial mean of the CZO, it is however not clear how the human activities (irrigation/groundwater extraction) will impact such analysis. There were several places the author indicate some spatiotemporal patterns to irrigation and pre-monsoon, post-monsoon precipitations. However, this information cannot be explicitly found in the manuscript. Please the authors try to clarify this information and explain their potential impacts on their findings.
2. The satellite data SMAP was mentioned in the manuscript. However, there is no satellite SM data used in this study. This reviewer thinks this is a miss of the opportunity. It would be great to link the in-situ measurement to remote sensing data, as such, it is more operational in a sense to monitor the impact of water management strategies on soil moisture, or even groundwater storage change. It is understandable that for GW storage, the current GRACE product is too coarse. However, for SMAP soil moisture data, you do can find 1km and 3km resolution products. Also from Sentinel-1 SM, it is 1km. As such, this reviewer would encourage the author to include satellite data in their analysis.
Some minor comments as below:
a. On page 10, line 230, this reviewer is wondering if you have the data about 'watering by farmers'?
b. Page 10, line 234-235, this reviewer think this is only happening when the GW table is shallow, right? Please clarify and provide some more discussions on this.
c. Line 265 'PC' should be 'EC'
d. Line 338, it would be convenient for readers if equations were given.
e. Line 344, these 'signals' should be marked out explicitly in Figure 9a
f. Line 414, 'in compared to' should be 'in comparison to'
Citation: https://doi.org/10.5194/hess-2022-47-RC2 - AC2: 'Reply on RC2', Saroj Dash, 27 Apr 2022
-
EC1: 'Comment on hess-2022-47 from the editor', Nunzio Romano, 10 Apr 2022
Dear Authors,
Up to now, your submission has received comments from two reviewers. To keep the discussion step alive, I suggest you should start uploading some preliminary responses from your side.
Citation: https://doi.org/10.5194/hess-2022-47-EC1
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