the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 30 Jul 2021
Modelling groundwater recharge, actual evaporation and transpiration in semi-arid sites of the Lake Chad Basin: The role of soil and vegetation on groundwater recharge
Abstract. The Lake Chad Basin, located in the center of North Africa, is characterized by strong climate seasonality with a pronounced short annual precipitation period and high potential evapotranspiration. Groundwater is an essential source for drinking water supply as well as for agriculture and groundwater related ecosystems. Thus, assessment of groundwater recharge is very important although difficult, because of the strong effects of evaporation and transpiration as well as limited available data.
A simple, generalized approach, which requires only a small number of field data, freely available remote sensing data, and well-established concepts and models, is tested for assessing groundwater recharge in the southern part of the basin. This work uses the FAO-dual Kc concept to estimate E and T coefficients at six locations that differ in soil texture, climate, and vegetation conditions. Measured values of soil water content and chloride concentrations along vertical soil profiles at these locations together with different scenarios for E and T partitioning and a Bayesian calibration approach are used to numerically simulate water flow and chloride transport. Average potential groundwater recharges and the associated model uncertainty at the six locations are assessed for the time-period 2003–2016.
Model results show that interannual variability of groundwater recharge is generally higher than the uncertainty of the modelled groundwater recharge. Furthermore, the soil moisture dynamics at all locations are limited by water availability for evaporation in the uppermost part of the soil and by water uptake in the root zone rather than by the reference evapotranspiration.
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RC1: 'Comment on hess-2021-390', Anonymous Referee #1, 14 Aug 2021
The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2021-390/hess-2021-390-RC1-supplement.pdf
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AC1: 'Reply on RC1', Sara Vassolo, 22 Sep 2021
In the attached file, replies on RC1 comments have been written in blue to differentiate from comments from the reviewer
The authors should stress on the novelty of this paper. In my understanding, they try to provide an affordable low-cost approach in a data-poor region to assess groundwater recharge. Nevertheless, the description of Materials and Methods is poorly described, unclear and some parts are “gray”. Precipitation and ET are given at monthly scale. The authors then declare that they set up Hydrus-1D at monthly scale (line 185). As far as I know, time units in Hydrus-1D are seconds, minutes, hours, days and years. The authors are invited to give more detailed information on the Hydrus-1D version. Did the authors use year fractions? In any case, running Hydrus-1D at monthly scale provides only a gross water balance simulation.
The section Data and Methods has been rewritten to provide more clarification on the data used. A new section Modelling methodology has been added to explain more in detail the methods applied in the modelling activities.
We used Hydrus-1D with a daily time-step. Because data are given at monthly, they were considered invariable over the month. By doing this, variability of input data is missed. However, results show that the method is still valid for evaluation of mean recharge
The manuscript is potentially interesting for the readers, however it needs substantial revisions before publication in light of the following comments:
1) I invite the authors to thoroughly revise Materials and Methods by adding a methodological sub-section in which they describe step-by-step the proposed approach. Maybe they can add a flowchart, a schematic overview to clarify all steps.
A section Modelling methodology has been added as proposed.
2) Session 2.5 is very unclear. I suggest to substantially revise this part. The authors declare that they have monthly P and ET from 1970 to 2019 (line 123). Then in line 192 they set up a burn-in period of 80 years to relax the impact of unknown initial conditions on model simulations. How can this be possible? In Fig. 6 I see simulations of groundwater recharge from 2005 up to 2019. I do not understand the impact of the 7 scenarios on model results.
The section has been rewritten. The modelling periods are thoroughly described. We modelled for a period of time long enough to allow for the exchange of at least 1-time the water volume of the column. Because percolation velocity depends on soil properties, the modelling periods were different depending on the location.
Data on Ke, Kcb and vegetation root are given as ranges. To investigate the model sensitivity to these ranges, scenarios were created.
3) In sub-Session 2.5.2 the authors use the bulk density in Rosetta in Hydrus-1D. How can you sample a known soil volume from the auger? Please clarify it in sub-session 2.3. It is recommended to add the Richards equation, the van Genuchten (1980) equation for soil water retention function and hydraulic conductivity function by declaring all soil hydraulic parameters (θr,s, n, α and Ks)
Bulk density was not measured in the field. Values were obtained by multiplying the gravimetric water contents by typical bulk densities from Global Gridded Surfaces of Selected Soil Characteristics database (Global Soil Data Task Group, 2000) for each soil type (lines 171-174).
Richards and van Genuchten equations have been added (sections 3.2.1 and 3.2.2).
4) The description of scenarios and model calibration in section 2.5.5 and 2.5.6 is unclear at all. I
Scenarios are described in section 3.2.5 (lines 300-305)
Citation: https://doi.org/10.5194/hess-2021-390-AC1
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AC1: 'Reply on RC1', Sara Vassolo, 22 Sep 2021
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RC2: 'Comment on hess-2021-390', Adane Zablon, 24 Aug 2021
The article provides valuable insight on water balance to a geographic area with limited data. That said, minor comments include that the manuscript can be improved by correcting some spellings, grammatical errors, and technical language.
Major comments include that the chloride concentration input variability in time and space is not very well explained. This has implications on the recharge values, partitioning, and other water balance components. The manuscript can also delve more into uncertainty and statistical analysis in the discussion section and go beyond comparison with only Tewolde et al. 2019.
Other comments are included in the edited PDF.
- AC2: 'Reply on RC2', Sara Vassolo, 22 Sep 2021
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RC3: 'Comment on hess-2021-390', Anonymous Referee #3, 26 Aug 2021
The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2021-390/hess-2021-390-RC3-supplement.pdf
- AC3: 'Reply on RC3', Sara Vassolo, 22 Sep 2021
Status: closed
-
RC1: 'Comment on hess-2021-390', Anonymous Referee #1, 14 Aug 2021
The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2021-390/hess-2021-390-RC1-supplement.pdf
-
AC1: 'Reply on RC1', Sara Vassolo, 22 Sep 2021
In the attached file, replies on RC1 comments have been written in blue to differentiate from comments from the reviewer
The authors should stress on the novelty of this paper. In my understanding, they try to provide an affordable low-cost approach in a data-poor region to assess groundwater recharge. Nevertheless, the description of Materials and Methods is poorly described, unclear and some parts are “gray”. Precipitation and ET are given at monthly scale. The authors then declare that they set up Hydrus-1D at monthly scale (line 185). As far as I know, time units in Hydrus-1D are seconds, minutes, hours, days and years. The authors are invited to give more detailed information on the Hydrus-1D version. Did the authors use year fractions? In any case, running Hydrus-1D at monthly scale provides only a gross water balance simulation.
The section Data and Methods has been rewritten to provide more clarification on the data used. A new section Modelling methodology has been added to explain more in detail the methods applied in the modelling activities.
We used Hydrus-1D with a daily time-step. Because data are given at monthly, they were considered invariable over the month. By doing this, variability of input data is missed. However, results show that the method is still valid for evaluation of mean recharge
The manuscript is potentially interesting for the readers, however it needs substantial revisions before publication in light of the following comments:
1) I invite the authors to thoroughly revise Materials and Methods by adding a methodological sub-section in which they describe step-by-step the proposed approach. Maybe they can add a flowchart, a schematic overview to clarify all steps.
A section Modelling methodology has been added as proposed.
2) Session 2.5 is very unclear. I suggest to substantially revise this part. The authors declare that they have monthly P and ET from 1970 to 2019 (line 123). Then in line 192 they set up a burn-in period of 80 years to relax the impact of unknown initial conditions on model simulations. How can this be possible? In Fig. 6 I see simulations of groundwater recharge from 2005 up to 2019. I do not understand the impact of the 7 scenarios on model results.
The section has been rewritten. The modelling periods are thoroughly described. We modelled for a period of time long enough to allow for the exchange of at least 1-time the water volume of the column. Because percolation velocity depends on soil properties, the modelling periods were different depending on the location.
Data on Ke, Kcb and vegetation root are given as ranges. To investigate the model sensitivity to these ranges, scenarios were created.
3) In sub-Session 2.5.2 the authors use the bulk density in Rosetta in Hydrus-1D. How can you sample a known soil volume from the auger? Please clarify it in sub-session 2.3. It is recommended to add the Richards equation, the van Genuchten (1980) equation for soil water retention function and hydraulic conductivity function by declaring all soil hydraulic parameters (θr,s, n, α and Ks)
Bulk density was not measured in the field. Values were obtained by multiplying the gravimetric water contents by typical bulk densities from Global Gridded Surfaces of Selected Soil Characteristics database (Global Soil Data Task Group, 2000) for each soil type (lines 171-174).
Richards and van Genuchten equations have been added (sections 3.2.1 and 3.2.2).
4) The description of scenarios and model calibration in section 2.5.5 and 2.5.6 is unclear at all. I
Scenarios are described in section 3.2.5 (lines 300-305)
Citation: https://doi.org/10.5194/hess-2021-390-AC1
-
AC1: 'Reply on RC1', Sara Vassolo, 22 Sep 2021
-
RC2: 'Comment on hess-2021-390', Adane Zablon, 24 Aug 2021
The article provides valuable insight on water balance to a geographic area with limited data. That said, minor comments include that the manuscript can be improved by correcting some spellings, grammatical errors, and technical language.
Major comments include that the chloride concentration input variability in time and space is not very well explained. This has implications on the recharge values, partitioning, and other water balance components. The manuscript can also delve more into uncertainty and statistical analysis in the discussion section and go beyond comparison with only Tewolde et al. 2019.
Other comments are included in the edited PDF.
- AC2: 'Reply on RC2', Sara Vassolo, 22 Sep 2021
-
RC3: 'Comment on hess-2021-390', Anonymous Referee #3, 26 Aug 2021
The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2021-390/hess-2021-390-RC3-supplement.pdf
- AC3: 'Reply on RC3', Sara Vassolo, 22 Sep 2021
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