the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Oct 2023
The influence of human activities on streamflow reductions during the megadrought in Central Chile
Nicolás Alamos
Camila Alvarez-Garreton
Ariel Muñoz
Alvaro González-Reyes
Abstract. Central Chile has experienced a protracted megadrought since 2010 (up to date), with annual precipitation deficits ranging from 25 % to 70 %. Drought propagation has been intensified during this time, with streamflow reductions up to 30 % larger than those expected from historical records. This intensification has been attributed to the cumulative effect of precipitation deficits associated to catchment memory in near-natural basins of central Chile. However, the additional effect of water extractions on drought intensification in disturbed basins remains an open challenge. In this study, we assess the effects of climate and water use on streamflow reductions during the last three decades in four major agricultural basins in central Chile, with particular focus on the ongoing megadrought. We address this by contrasting streamflow observations with near-natural streamflow simulations representing the discharge that would have occurred without water extractions. Near-natural streamflow estimations are obtained from rainfall-runoff models trained over a reference period with low human intervention (1960–1988). We characterise hydrological droughts driven by precipitation and human activities during the evaluation period (1988–2020) in terms of the frequency, duration and intensity of near-natural and observed seasonal streamflow deficits, respectively.
Our results show that before the megadrought onset (1988–2009), streamflow in the four basins was 2 to 20 % lower than the streamflow during the undisturbed period. Between 81 to 100 % of these larger deficits were explained by water extractions. During the megadrought (2010–2020), streamflow was reduced in a range of 47 to 76 % among the different basins, compared to the reference period. During this time, the climatic contribution to streamflow reductions increased and had a lower relative contribution, accounting for 27 to 51 % of streamflow reduction. During the complete evaluation period, human activities have amplified the propagation of droughts, with more than double the frequency, duration, and intensity of hydrological droughts in some basins, compared to those expected by precipitation deficits only. We conclude that while the primary cause of streamflow reductions during the megadrought has been the lack of precipitation, water uses have not diminished during this time, causing an exacerbation of the hydrological drought conditions and aggravating their impacts on human water consumption, economic activities, and natural ecosystems.
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Nicolás Alamos et al.
Status: open (until 19 Dec 2023)
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RC1: 'Comment on hess-2023-246', Anonymous Referee #1, 28 Nov 2023
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Álamos et al. – The influence of human activities on streamflow reductions during the megadrought in Central Chile
General comments
In this manuscript, the authors investigate the influence of human activities in streamflow reductions before and during the megadrought in central Chile. Their approach is based on the comparison between near-natural streamflow simulations and actual observations. The former is estimated using a linear rainfall-runoff regression model trained on a period of low human-interventions identified according to water uses’ timeseries. The research question is very timely, given the ongoing drought in Chile. At the same time, the manuscript underscores the importance of understanding the role of human activities in either exacerbating or mitigating drought events – a crucial analysis given the increasing human influence in our catchments. I highly encourage the publication of the manuscript after revisions, as there are a few methodological aspects that need to be further specified and a few discussion points that could be further expanded.
On the methodological side, I really appreciate the considerations given to assess possible changes in catchment response driven by the persistent drought conditions, which could have introduced biases to the results. As well as, the thorough analysis for the selection of the low-human intervention period used for the training of the model. However, a few methodological aspects can be further specified. For instance, the authors used a linear regression model to capture the relationship between annual rainfall and runoff. However, relationship between rainfall and runoff are hardly linear and further information on the choice of this model would be beneficial. Further, the implication of the low performance of the winter rainfall-runoff model on the final results need to be discussed.
Specific comments
Abstract: The abstract is informative, yet quite lengthy and could benefit from concise rephrasing. The initial problem statement (lines 13 -17) and methodology (lines 19-24), spanning several lines, could be condensed to give more emphasis on the results of the study. For instance, the problem statement could be introduced as following: "Since 2010, central Chile has experienced a protracted megadrought. Intensification of the drought has been attributed to the effect of cumulative precipitation deficits linked to catchment memory. Yet, the influence of water extractions on drought intensification is still unclear." Additionally, in line 26, the term 'undisturbed period' is introduced for the first time. For improving clarity, I would suggest to explicitly write that you are referring to a period with low human intervention.
Lines 43-46: this paragraph is a bit disconnected from the first and third paragraphs. I recommend merging it with the first paragraph to enhance overall flow. You could make the text more concise by eliminating the reference to climate change (as it is not the focus of your analysis) and starting to introduce the concept of hydrological drought soon after the first sentence. Or you could connect the first and second paragraphs by introducing a transitional statement like: These alterations in the water cycle may have implications for drought occurrences. If meteorological droughts (..) are mainly controlled by regional climate, hydrological droughts (..) are also influenced by..
Line 53: the word “dominated” is not very appropriate and could be replaced with “driven”. Also, I think you mean: “anthropic water uses”;
Line 57-58 is quite confusing. What do you mean with ‘adaptation and mitigation water management plans’?
Lines 67-69: The sentence is quite disconnected from the previous paragraph: above you mentioned the hydrological drought and water scarcity problem in central Chile, while later you give an example of the possible influence of human activities on the propagation of drought. Or you delete: "for example" or you already introduce in the previous paragraph the potential impact that human activities may have on the intensification and propagation of drought;
Line 67: I would suggest providing the geographical location of the Petorca river basin (as you do for the Aculeo Lake on line 70).
Lines 88-89: It is not very clear: do you mean that annual precipitation concentrates usually during winter (then delete ‘a few’) or that most of the precipitation during the last TOT years occurred only during a few winters or something else?
Lines 96-97: While knowing the actual extent of agricultural land cover is valuable, grasping the influence of these areas at catchment scale becomes challenging without information on the catchment size. I would suggest providing the percentage of the total catchment area covered by agriculture areas. Similarly, it would be good to know the annual water consumption in relation to mean annual flow (particularly in cases of minimal streamflow variation throughout the year).
Figure 1: In Panel A, the proxy station (green diamond) in the Limari catchment (light blue) is not visible. Could this be due to the absence of fill-in gaps in the timeseries extracted from the outlet represented by the red diamond? In Panel C, the colors are quite hard to distinguish. The majority of the area is categorized as 'others,' making it less informative. The agriculture regions are difficult to see, with clearer concentrations observed mainly in Aconcagua and Limari. Moreover, the colors used for urban and mountain landcover are notably similar.
Line 108: Monthly mean streamflow? Same applies, for line110: monthly mean or sum precipitation?
Figure 2: In the text under step 2, the use of the plural in indicating the period of low anthropic activities might be confusing. It may appear as if the model was trained in multiple periods, whereas, in reality, only one continuous period of low water consumption was identified. It would be clearer to use 'in the period' instead. Same applies for line 129, where I would write ‘in a period’.
Line 136: First time you are using the term ‘anthropic variables’, I would continue using the term 'water uses’ for consistency.
Eq. 2: Is the rainfall-runoff model applied on an annual or monthly scale? It is good to specify in the text what 't' is. And to change the time scale of your time series do you use the average or the sum? I suggest providing this information in the text.
Eq. 2 and Eq. 3: You are considering a linear relationship between precipitation and runoff, however annual runoff data is generally skewed and not linearly correlated to precipitation. Several researchers, for example, used a linear rainfall-runoff relationship only after verifying the assumption of a normal distribution of rainfall values and subsequently transforming the runoff data with a Box-Cox transformation to ensure they follow a normal distribution (Saft et al., 2015: The influence of multiyear drought on the annual rainfall-runoff relationship: An Australian perspective, Avanzi et al., 2020: Climate elasticity of evapotranspiration shifts the water balance of Mediterranean climates during multi-year droughts). The decision to employ a linear regression model for capturing the rainfall-runoff relationship should be then justified in the text or explicitly mentioned as a limitation in the analysis within the discussion section. In line 167 -170, you mentioned that multiple regression equations have been tested, however you do not specify in the text which other regression equations have been used. Further clarification on this can provide valuable information.
Line 192: The choice of the threshold for detecting hydrological drought should be justified, since influencing the periods in which near-natural and observed streamflow are compared.
Figure 4: The terms streamflow and runoff in the caption and figure have been used interchangeably, although different. Is the blue line indicating runoff or annual streamflow? The same occurs in Table 1 (line 234).
Table 2: I found it strange that the mean bias error for Equi and Aconcagua is 0% even though they have a low r-squared (under 70%). Could it be that this is because the model both over- and under-estimate during the training period and so the average bias converges to 0? And how does this low model performance for some catchments in winter affect the results in Figure 7? Could it be that the difference you capture between the near-natural streamflow and the observed streamflow is the error in the model estimation of the near-natural flow instead of the additional water stress resulted from water abstractions? Because with a low r-squared and high mean bias in the regression model for the winter season, it might be that you are capturing the bias in the near-natural streamflow more than the difference between the near-natural streamflow and the observed streamflow.
Further, in the Study Area section (2.1), you also mention that the winter season is the most important for water replenishment since the high concentration in precipitation in that season (Garreaud et al., 2017).
Additionally, you use annual time series on water uses of industry, energy, mining, livestock, and drinking water sectors. But information from the literature on how these uses change over a year (e.g., intensified in summer or winter) can better help interpret the results and might give relevance to a particular season over another.
Some reflections on the above points in the discussion section might be helpful.
Figure 6: I would move Figure 6 in section 3.2 since you already refer to it in that section. You can also think to merge this figure with table 2 (indeed in line 267-268 you mention the r-squared values, which however are not shown in the figure).
Figure 7: Precipitation and near-natural streamflow have very similar colors, I would differentiate the colors a bit more.
Section 4.1: Would it be possible to compare the results on the impacts of human activities on water availability together with the differences in trends of water users (Figure 5)? Water uses for agriculture and mining differ between catchments and over time with some peaks, lows, and some constant values. Perhaps reflecting on this could provide valuable information for local authorities trying to understand which water sector has the greatest impacts on drought intensification.
Lines 336-337: maybe good to briefly specify somewhere in the text that groundwater does not contribute to streamflow in the catchment under analysis (if this is the case).
Lines 357-372: There is a bit of disconnection between the previous paragraph and this one. Although, you start the paragraph by referring to the intensification of streamflow deficits, you then discuss about drought impacts (357-363) to then start to talk about human activities (Line 363). I would actually remove the part from ‘’Although..”(line 357) to “US$56 million during 2010-2020” (line 363) or move it below.
Grammar check: Line 56: ‘’to assess catchments’ vulnerability’’; Line 60: ‘’we focus on central Chile’’; Line 71: ‘by using’ instead of ‘and used’ (to reduce the use of ‘end’); Line 96: land cover (without s); Line 176: ‘compared’; Line 199: ‘defined’ (consistent with the past tense form used for the method section).
Citation: https://doi.org/10.5194/hess-2023-246-RC1
Nicolás Alamos et al.
Nicolás Alamos et al.
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