Drought is a function of both natural and human influences, but fully characterizing the interactions between human and natural influences on drought remains challenging. To better characterize parts of the drought feedback loop, this study combines hydrological and societal perspectives to characterize and quantify the potential for drought action. For the hydrological perspective, we examine historical groundwater data, from which we determine the decadal likelihoods of exceeding hydrologic thresholds relevant to different water uses. Stakeholder interviews yield data about how people rate the importance of water for different water uses. We combine these to quantify the Potential Drought Action Indicator (PDAI). The PDAI is demonstrated for a study site in south-central Oklahoma, where water availability is highly influenced by drought and management of water resources is contested by local stakeholders. For the hydrological perspective, we find that the historical decadal likelihood of exceedance for a moderate threshold associated with municipal supply has ranged widely: from 23 % to 75 %, which corresponds well with natural drought variability in the region. For the societal perspective, stakeholder interviews reveal that people value water differently for various uses. Combining this information into the PDAI illustrates that potential drought action increases as the hydrologic threshold is exceeded more often; this occurs as conditions get drier and when water use thresholds are more moderate. The PDAI also shows that for water uses where stakeholders have diverse views of importance, the PDAI will be diverse as well, and this is exacerbated under drier conditions. The variability in stakeholder views of importance is partially explained by stakeholders' cultural worldviews, pointing to some implications for managing water when drought risks threaten. We discuss how the results can be used to reduce potential disagreement among stakeholders and promote sustainable water management, which is particularly important for planning under increasing drought.
Drought can pose significant challenges to meeting the water needs of society and ecosystems, which has led to increased interest in understanding and managing drought risk now and into the future (e.g., Georgakakos et al., 2014). There are many definitions of drought, with the classic definitions including meteorological, hydrological, agricultural, and socioeconomic (Wilhite and Glantz, 1985). Similarly, many different drought indices have been developed (Mishra and Singh, 2010). The main driver of drought in most definitions and indices of drought is natural climate variability (Van Loon, 2016a), which is where efforts to improve prediction and modeling have focused (see Mishra and Singh, 2011, and references therein). Even with advances in drought prediction, drought remains one of the most expensive hazards affecting the United States (NCDC, 2015), reinforcing the idea that social factors must also be considered for drought planning (Wilhite and Buchanan-Smith, 2005; Bachmair et al., 2016).
The need for more proactive drought planning has led to increased interest in the development of drought management plans (e.g., Wilhite et al., 2000, 2005; Knutson et al., 1998). Drought risk management requires identifying drought indicators and triggers (Steinemann and Hayes, 2005), which can be developed and evaluated using stakeholder processes to make them useful for decision-making (Steinemann and Cavalcanti, 2006; Steinemann et al., 2015). Further, the need to better link drought indices with impacts has been recognized (Bachmair et al., 2016). Frameworks to link drought indicators directly with impacts are emerging (Bachmair et al., 2016; Stagge et al., 2015; Towler and Lazrus, 2016), though there is still a need for more systematic impact monitoring (Lackstrom et al., 2013). Ostrom (1990) found that assessments that can account for how people value, perceive, and make decisions about resources such as water, particularly when water is scarce, are critical for guiding policies that meet management goals and stakeholder needs and thus promote sustainable management of water resources. Dessai and Sims (2010) explored public perceptions of drought and climate change to understand barriers to action and paths towards sustainable management. Lazrus (2016) examined how stakeholders perceive drought and how drought intersects with their cultural processes.
Recent work has highlighted how the natural and human causes of drought are intertwined and that researchers must consider both in any examination of drought (Van Loon, 2016a). This general notion has been echoed in the hydrologic science literature (Wagener et al., 2010), as well as the natural hazard (Jones and Preston, 2011) and climate change literature (Oppenheimer et al., 2014). This has also motivated the new science of socio-hydrology, which explores the dynamics and coevolution of human and water systems (Sivapalan et al., 2012). Van Loon et al. (2016b) describe a new framework that explicitly acknowledges the human dimension of drought. They outline several research gaps, including a gap in our understanding of the human feedbacks on drought.
Understanding human feedbacks on drought is important but has not been well studied, partially because of its complexity and potential for nonlinear feedbacks (Van Loon et al., 2016b). Drought feedbacks can be influenced by many factors, for example, through science and technology (Polsky and Cash, 2005), historical lessons learned (McLeman et al., 2014), and management strategies (Maggioni, 2015). Further, feedbacks may be positive (i.e., the drought is made worse) or negative (i.e., the drought condition is alleviated) (Pulwarty, 2003; Tijdeman et al., 2018). In addition, these interactions and feedbacks can result in changing the normal drought reference baseline (Van Loon et al., 2016b). However, fully characterizing the feedback loops between human and natural influences on drought remains challenging.
The goal of this paper is to provide an experimental methodology towards a
better characterization of several components of the drought feedback loop,
specifically to gain understanding on how and why people might take action
in response to drought. To this end, we develop an indicator to characterize
how natural influences on drought inform
We demonstrate the PDAI through a place-based assessment of drought risk in south-central Oklahoma, where water availability is highly influenced by drought and management of water resources is contested by local stakeholders; we provide some background and describe this study site in Sect. 2. Section 3 outlines the methodology: Sect. 3.1 and 3.2 outline the details of the methods used to assess the hydrological and social perspectives, respectively. Details about how the PDAI is developed are provided in Sect. 3.3. In Sect. 3.4, we describe additional interview data on the stakeholder worldviews and provide an overview of the social science theory. Results for our study site are shown in Sect. 4.
The goal of this paper is to gain insights into the potential for human
action on drought, and one suggested way to do this is to study a particular
water system in detail (Sivapalan et al., 2012). As such, the PDAI is developed and demonstrated for the
Arbuckle-Simpson Aquifer (ASA), a groundwater resource that underlies an area
of about 520 square miles (1350 km
In this paper, we explicitly combine hydrological and societal perspectives, but historically these two perspectives would likely be examined in isolation. In fact, this work builds upon and extends two previous studies that focused on the same ASA case study but were disciplinary in nature: Lazrus (2016) and Towler and Lazrus (2016). Lazrus (2016) describes results of stakeholder interviews collected for the ASA; it offers an anthropological perspective, examining how stakeholders perceive drought and how those perceptions intersect with their cultural processes. Lazrus (2016) was motivated by the hydrological context of the ASA but did not engage directly with any quantitative meteorological or hydrological analysis. On the other hand, Towler and Lazrus (2016) take a hydrological perspective, developing a generalized framework that links meteorological drought indices with hydrologic threshold exceedances that are relevant to ASA stakeholders. To identify some of the hydrological thresholds and provide social context, Towler and Lazrus (2016) draw on qualitative insights gathered from the interviews but do not directly incorporate any of the quantitative interview results into the analysis. In this paper, we extend these two studies to offer a novel, quantitative, interdisciplinary approach, which results in a derivative product, adding value to the preceding studies. Although the PDAI is experimental, conducting this type of study is critical, given the grand challenge of engaging in interdisciplinary research at the climate–water–society interface (McNeeley et al., 2011).
Conceptual overview of the methodology that combines a hydrological perspective from historical groundwater data with a societal perspective from stakeholder interview data to quantify the Potential Drought Action Indicator (PDAI); stakeholder worldviews from the interviews and social science theory are used to explore management implications.
Figure 1 provides the conceptual overview of the study methodology, which is detailed in the subsequent sections.
To characterize natural influences on drought, we examine drought from a hydrological perspective. Taking a hydrological, rather than meteorological, perspective is advocated by Van Loon et al. (2016b), given the closer connection of surface water and groundwater with societal use and management. Here, we use a groundwater (GW) well that has relevance to the community (Towler and Lazrus, 2016), has a long available record, and is monitored by water managers in the community: the USGS Fittstown well (USGS 343457096404501). We use data from the beginning of the GW monitoring record through the year the interviews were conducted, which corresponds to 1959–2012. Details of this dataset can be found in Towler and Lazrus (2016).
To connect the hydrologic perspective with human action, we examine the historical groundwater data in terms of decision-relevant thresholds (Jones, 2001). From Towler and Lazrus (2016), we identify two main thresholds relevant to water uses asked about in the interviews (see Sect. 3.2). The first threshold is called a “moderate” threshold: this is a groundwater level of 111 ft (33.8 m) below the surface, which is decision relevant because it is when the aquifer begins to be closely monitored because of potential impacts to municipal supply. The second threshold is the “severe” threshold: this is when the groundwater level lowers further, to 117 ft (35.7 m) below the surface, which is the level at which artesian springs in the area have minimal flow or stop flowing altogether, affecting uses such as wildlife and recreation. For illustrative purposes, we also look at an “extreme” threshold of groundwater levels to 120 ft (36.6 m) below the surface, which have been experienced in the aquifer and further the likelihood of minimal or stopped spring flows (see Fig. 2 in Towler and Lazrus, 2016).
Monthly groundwater time series; blue line is a local smoother
average, green line is the moderate threshold (
To quantify the threshold exceedance, we calculate the percent frequency of
exceedance We note that groundwater threshold levels are negative;
so here we define “exceedance” as going below (more negative) than the
threshold.
We also calculate the Pearson correlation coefficient (
To understand how community members in the ASA region might respond to
natural influences on drought, we use stakeholder interview data from a previous
investigation (Lazrus, 2016). Stakeholder interviews (
For this study, we examined the following question: how do people perceive the importance of water for various uses? We make the assumption that the more important water is perceived to be for a particular use, the greater the potential will be for taking action – in this case, conserving water for that use.
To understand the importance of water for various uses, interviewees were asked how important (on a Likert scale of 1–5, with 5 being very important) water resources are in their community for (a) people's livelihoods, (b) recreational activities, (c) spiritual fulfillment, (d) cultural practices, (e) habitat for plants and animals, and (f) availability of drinking water. Data from these questions were used directly and called “importance ratings”, which were integrated into the PDAI (see Sect. 3.3).
We express the PDAI as a function,
Here,
We are also interested in exploring
To this end, we examined how peoples' importance ratings from Sect. 3.2 were related to their worldviews. If so, it would help us to understand how the PDAI could be operationalized – that is, might people respond more favorably to water management strategies that reflected their own management preferences based on their cultural worldviews? For the CTR, interview questions about worldview used previously tested measures for individualism and egalitarianism developed by Smith and Leiserowitz (2014) as well as additional questions informed by the CTR that reflected the particular water management context of the ASA; all questions can be seen in Tables 1 and 2 of Lazrus (2016). These questions asked people whether they strongly agreed, agreed, neither agreed nor disagreed, disagreed, or strongly disagreed (on a five-point Likert scale) to a series of statements. Responses were summed for each interviewee to determine a value for individualism or egalitarianism. Follow-up open-ended questions allowed interviewees to elaborate on their worldview preferences and importance ratings.
Figure 2 shows the historical monthly groundwater time series, including the
moderate threshold (111 ft/33.8 m below the surface) and severe threshold (117 ft/35.7 m below the surface) introduced in Sect. 3.2. Groundwater drought
likelihood is calculated as the number of months within each 5-,10-,15-, and 20-year running window that the level went below
a particular threshold. Drought likelihoods for the selected time windows
(5,10,15, and 20 years) are shown in Fig. 3.
Results for each time window follow similar patterns, though as expected, the
shorter the time window, the greater variability in the likelihood. We
selected the 10-year running window for calculating the PDAI (e.g., Fig. 3b),
as it strikes a balance between shorter time windows that have high
variability (e.g., 5-year windows) and longer time windows (e.g., 15
and 20 years) where much of the variability is smoothed out. Figure 3b shows
the decadal likelihood for the moderate and severe threshold. As expected,
the higher the threshold, the higher the likelihood of exceedance (i.e., a
moderate threshold is exceeded more often than the severe threshold).
Further, the likelihoods are correlated (
Correlation between select drought indices
Groundwater drought likelihood (
Table 2 shows the exceedance likelihoods of select decades from the historical record for both moderate and severe. First, we look at the three most recent decades (i.e., 1983–1992, 1993–2002, and 2003–2012), in which relatively wet, average, and dry conditions occurred. For 2003–2012, the moderate threshold was exceeded 61 % of the time, which we refer to as the “dry/recent” decade. In the next most recent decades, the exceedance likelihood decreased to 35 % (1983–1992) and 31 % (1993–2002), which we refer to as “average/recent” and “wet/recent” decades, respectively. To put this into context, for the moderate threshold, the decade with the lowest exceedance likelihood was 23 % (1985–1994), which we call the “wettest” decade, and the decade with the highest exceedance was 75 % (1959–1968), or the “driest” decade. Results follow similar patterns for the severe threshold (Table 2).
Decadal likelihood (
Stakeholder interviews reveal that there is more consensus on the importance of water for some water uses than others (Fig. 4). On average, water was deemed most important for drinking water, followed closely by habitat for wildlife and supporting livelihoods. The importance of water for these uses was similar for most stakeholders interviewed, as is evident by the tightness of the box plot (Fig. 4). On the other hand, there was a spread in responses for recreation, cultural practices, and spiritual fulfillment. Some of the spread in responses on these measures may be due to how interviewees interpreted the water uses (Lazrus, 2016).
Rated importance of water for each water use from stakeholder
surveys (
The spread in responses indicates that different stakeholders place different levels of importance on some water uses, such as water for recreation which shows a broader spread than water for drinking water, habitat, or livelihood. For example, one interviewee underscored the importance of water, describing that “Murray County is one of the top tourist attractions with Arbuckle Lake and Chickasaw National Recreation Area. So water is the absolute key” (Interview 1). Demonstrating a very different perspective, another interviewee noted that “Recreation and water are not critical to me. I mean in this part of the world, they do not necessarily go hand in hand because it's a relatively dry place, and there are not that many places to really go and play in the water” (Interview 5).
Empirical cumulative density functions (eCDFs) for the PDAI
(Potential Drought Action Indicator) for water uses using the moderate
threshold
The PDAI is calculated for all of the water uses (Fig. 5). Here, the top row shows results for water uses using the moderate threshold (Fig. 5a–c) and the bottom row shows results for water uses using the severe threshold (Fig. 5d–f). Because the results across the rows are quite similar, we will focus on the results for drinking water (Fig. 5a) and then recreation (Fig. 5d).
First, we focus on drinking water, which is an example of a water use which exhibited more consensus among interviewees. For drinking water, to calculate the PDAI, we use the moderate threshold, since this is the threshold at which municipal supply is monitored (see Sect. 3.1). Figure 5a shows the PDAI for drinking water for the different drought conditions (e.g., wet/recent, dry/recent) from Table 2. Results are shown as empirical cumulative density functions (eCDFs) to reflect the discrete nature of the importance ratings. In the eCDFs, the vertical lines represent the PDAI values, and the horizontal lines represent the percentage of data that are equal to or less than that value. In Fig. 5a, as the eCDF moves across drought conditions from wettest to driest, the PDAI shifts towards higher values, reflecting the increased potential for action under drier conditions. Specifically, the wettest decade has an average PDAI value of 1.1, and the driest decade has an average PDAI value of 3.7. Given the stakeholder consensus on the importance for drinking water, for each drought condition there is very little range – that is, the eCDFs are fairly vertical. Results are similar when the moderate threshold is used for the other two water uses, habitat and livelihood, that showed strong consensus (Fig. 5b and c).
Next, we focus on the PDAI for recreation, a water use that shows diverse importance ratings from stakeholders (Fig. 5d). For recreation, to calculate the PDAI, we use the severe threshold, since that is the threshold at which artesian springs have minimal flow or no longer flow (see Sect. 3.1). Figure 5d shows the PDAI for recreation for the select decadal drought conditions, using the severe threshold likelihoods from Table 2. Similar to drinking water, we see that as we move from wetter to drier decades, the PDAI also increases; for example, from wet/recent to dry/recent, the average PDAI values are 0.3 and 1.5, respectively. However, given the stakeholder diversity in importance ratings, as we move towards drier conditions, the PDAI becomes more diffuse, spanning a great range of values: in the wet/recent, the PDAI spans from 0.08 to 0.4, or for 0.32 units of the PDAI scale, and in the dry/recent decade it spans from 0.4 to 1.9, or 1.5 units on the PDAI scale, indicating a wide range in stakeholder appetite for potential action. Interestingly, the wet/recent decade (1993–2002) was also the wettest decade on record, with the groundwater threshold only being exceeded 8 % of the time. Results are similar when the severe threshold is used for the other two water uses that showed diverse ratings, i.e., cultural practices and spiritual fulfillment (Fig. 5e and f).
In Fig. 6, we also looked at recreation under the possibility of a new “normal” drought baseline (Van Loon, 2016b). It has been suggested that human adaptation to new drought normals can be illustrated by changing thresholds (Vidal et al., 2012; Wanders et al., 2015); here, we show how this could influence the PDAI. To this end, we look at a more extreme threshold that has been identified for recreation (i.e., GW levels below 120 ft/36.6 m; see Sect. 3.1) under the dry/recent period: the eCDF curve shifts back to the left, towards lower action potential, with an average PDAI of 0.9, reflecting this new normal. This is relevant given climate change projections that suggest that the ASA will likely become drier in the future (Towler et al., 2016; Liu et al., 2012).
Empirical cumulative density functions (eCDFs) for the PDAI (Potential Drought Action Indicator) for recreation under the wet/recent (1993–2002), normal/recent (1983–1992), and dry/recent (2003–2012) decade for the severe threshold, as well as the dry/recent decade for the extreme threshold.
Finally, in Fig. 7, we narrow our focus to the most recent decade (i.e., dry/recent, 2003–2012) and compare both drinking water and recreation with the moderate and severe thresholds, respectively. From Fig. 7, we see that drinking water has a higher action potential than recreation: the average PDAI for drinking water is 3, while it is about 1.5 for recreation. This is an artifact of the thresholds selected for each respective water use (i.e., moderate for drinking water and severe for recreation). This makes sense from a human standpoint, since drinking water is a primary consumptive use, and recreation is a more discretionary use. However, this could be more subjective for other water uses (e.g., spiritual fulfillment). Although it may seem counterintuitive at first, we purposely pair the moderate threshold with the primary use to indicate this hierarchy, but this does not mean that exceedance of the severe threshold would not also prompt action (or further action) to ensure adequate drinking water supplies. However, it does make the assumption that for a more discretionary use, like recreation, action would not be prompted until this severe threshold was exceeded.
Empirical cumulative density functions (eCDFs) for the PDAI (Potential Drought Action Indicator) for recreation using the severe (Sev) threshold and for drinking water using the moderate (Mod) threshold for the dry/recent decade (2003–2012).
Another key point from Fig. 7 is that drinking water spans a smaller range on the PDAI scale than recreation, which is more diffuse. Specifically, for drinking water, the eCDF only falls between 2.4 and 3.5; this is due to the agreement across respondents on the importance of water to this use (i.e., Fig. 4). On the other hand, the recreation PDAI eCDF covers a larger range of values – here it spans from 0.4 to 1.9, similarly reflecting the range of stakeholder responses. This shows that for water uses where values are diverse, the appetite for potential action will be diverse as well.
In summary, the key points from these results: the PDAI increases with (1) drier decadal drought conditions and (2) water use thresholds that are exceeded more often. Further, it shows that for water uses where perceived importance is diverse among stakeholders, the PDAI will be diverse as well, and this is exacerbated under drier conditions.
Summed responses for individualism versus egalitarianism for each
interviewee (
To understand the management implications, we need to look at the results
alongside the CTR. Results from the CTR questions show that both
individualist and egalitarian worldviews were represented by the
interviewees (Fig. 8) and that some of the spread in the importance
responses can be explained by worldview (Table 3). Although the correlations
are relatively low, 8 out of 12 are statistically significant at the
90th percentile or higher. Further, the sign of each correlation
coefficient is opposite between the egalitarianism and individualism
measures, indicating that people holding each worldview have opposing
importance ratings (Table 3). The water use that showed the highest
correlation with worldview was recreation:
Correlation and statistical significance of worldviews, as quantified by the egalitarian and individualist measures, with importance ratings for each water use.
Results from the CTR questions, along with the PDAI, point to some
implications for water management policy. The CTR posits that disagreement over
resource management strategies may arise among constituents with diverse
worldviews for two reasons (McNeeley and Lazrus, 2014): first,
as demonstrated in Table 3, worldviews explain some of the variance in how
important people think that local water resources are for different
activities – and thus presumably
Conceptual map of drought feedback loop components addressed in this study (solid blue lines) and remaining gaps (dashed blue lines). Numbers correspond to discussion points in the conclusions.
We develop and demonstrate this methodology as a step towards closing the drought feedback loop but note that there are caveats and limitations that warrant discussion. A conceptual overview of the contribution of our study to the drought feedback loop is shown in Fig. 9, and we use this figure to identify five places where there is scope for future enhancements; each number below corresponds to a place in the drought feedback loop in Fig. 9.
For the natural influence on drought, we examine the probability of
groundwater drought. In our case, the groundwater levels are closely related
to rainfall recharge, which is a function of natural climate variability. We
recognize that this is not the case for many groundwater aquifers, where
human activities, such as groundwater extraction, may trump the natural
climate signal (e.g., Tarhule and Bergey, 2006), often leading to water
scarcity rather than a natural phenomenon of temporary water deficiency. In
many systems a full water balance would need to be examined to understand
the relative contributions of extraction versus moisture deficit to the
likelihood of going below a relevant hydrologic threshold. Further, other
aquifers may have different properties; for example, some aquifers' natural
response may be different and the levels may not closely resemble rainfall. Our interviews were conducted following a drought event, and we recognize
that the timing of the interviews will likely affect the responses, possibly
introducing a bias. For instance, interviews conducted during wet or average
conditions might elicit less polarized responses, since drought impacts
have not been recently experienced. We note that our approach of applying the
interview responses across different climate conditions (i.e., wettest to
driest) makes the assumption that the importance of water uses and
management preferences are stationary. We acknowledge that different climate
conditions, as well as cultural change, technological innovation, climate
adaptation, and other processes, are likely to influence the cultural factors
we investigated here and may mediate how people interact with their
environments. Future work could investigate how responses change with
different climate conditions over time and the subsequent implications for
drought action. However, hazards and disasters research is almost always
conducted immediately after an event, so this is a wise-spread
epistemological issue with both pros and cons in terms of what we learn from
post-disaster research. We use stakeholders' importance ratings as a proxy for their willingness to
take action in relation to particular water uses, where by “action” we
generally mean some effort towards drought mitigation. The interviews
included questions about the importance of different water uses to test the
application of the cultural theory of risk (usually applied in a more global
sense) to a specific water management issue, which had not been done before
(Lazrus, 2016). For the purposes in this paper, multiplying the importance
ratings by the probability served as a way to make an objective
characterization of drought subjective; that is, we wanted to modulate the
groundwater drought probability by each individual stakeholder's lens. The formulation of the PDAI strongly affects the conclusions drawn. Our
formulation of the PDAI follows from other precedents in risk management
that take the product of the likelihood of an event and its importance
(Jones and Preston, 2011; Oppenheimer et al., 2014). However, the functional
form of the PDAI is flexible, allowing it to be tailored to other locations.
As such, we note that the PDAI, as well as the best data to use to calculate
it, will depend on the needs of the community, as well as the water system
context. We use social science theory to interpret our results and to better
understand the theoretical underpinnings of how and why people take action
in response to drought. However, we note that empirical validation is
important for indicator development and refinement. We recommend that future
project designs include a validation component in the methodology. This
could take the form of follow-up interviews, such as direct feedback from
stakeholders on whether the indicator reflects their willingness to take action
for certain water uses at certain drought levels. Methods, including
stakeholder processes, for developing and evaluating drought indicator
effectiveness have been put forth in the drought community (Steinemann and
Hayes, 2005; Steinemann and Cavalcanti, 2006; Steinemann et al., 2015). Other
options for validation can be indirect, such as looking at historical data,
like government and local reports, media, and/or other collected response
information – e.g., the US Drought Impact Reporter (DIR) in the United States (Wilhite et al., 2007).
Tijdeman et al. (2018)
examined the relationship between drought indicators and impact data from the DIR; however, it has
been noted that the DIR would benefit from a more systematic and coordinated
collection effort (Lackstrom et al., 2013), which presents challenges for its
interpretation. Promising methods for mining social media, such as Twitter,
have also been developed (Demuth et al., 2018) and could be adapted for
evaluative purposes.
Related to the points above is the question about how the PDAI could connect with existing operational products and its transferability to other locations. In our case, groundwater threshold exceedance was linked with water use impacts. Ideally, the PDAI could be modified to incorporate an operational drought indicator that is associated with impacts; however, evaluations of the connection between monitored indicators and impacts have been limited (Bachmair et al., 2016). In terms of the transferability of the social perspective, the idea behind the cultural theory of risk worldview measures is that they are loosely universal; that is, they should apply fairly generally to any context within the broad culture for which they were initially put together – in this case, the United States (Smith and Leiserowitz, 2014). However, worldview measures can also be tailored to a particular context (Lazrus, 2016), which might need to be revised for other applications.
Our study implements a conceptual methodology combining hydrological and societal perspectives to understand drought action potential. Results from stakeholder interviews in the study site reveal that people perceive the relative importance of water for various uses differently, as shown by the notable variability that existed across certain water uses. A retrospective analysis of groundwater threshold exceedance shows that, in recent decades, stakeholders experienced a wide range of likelihoods of exceeding relevant thresholds, and these corresponded to drought indices. These pieces of information are brought together through the PDAI. We find that for a given water use, drier conditions increase the frequency of exceeding the groundwater threshold and hence increase the PDAI. The PDAI is tied to the threshold selected for each water use: we find that the PDAI is higher for more moderate thresholds, i.e., thresholds that are exceeded more often. And conversely, as thresholds become more extreme, which can illustrate human adaptation to the new drought normal, the PDAI decreases. Finally, we find that for water uses where stakeholder values are diverse, the PDAI will be diverse as well, and this is exacerbated under drier conditions.
We can also ask why values might be diverse and what that might mean about
how people are affected by water scarcity and how they will respond. To this
end, the study also examined worldview, as measured by the CTR, which can
help to diagnose
Although reducing disagreement is always important for promoting sustainability, it is particularly important for management planning under potentially increasing drought due to climate change, as has been predicted for this area (Towler et al., 2016; Liu et al., 2012). We examined this by examining possible adaptation to a new normal, where we illustrate how a more extreme threshold lowers the PDAI.
Although the methodology to develop the PDAI is experimental, we posit that explicit efforts to combine natural and human perspectives are critical to gaining a deeper and more nuanced understanding of drought feedbacks, and this paper provides a novel contribution to this end.
Groundwater data from the USGS Fittstown well
(USGS 343457096404501) are available from the USGS National Water Information
System Web Interface
Inquiries on the stakeholder data from the interviews can be sent to hlazrus@ucar.edu.
ET, HL, and DP collaborated to develop the main idea for the work. ET took the lead on all the analyses and manuscript preparation and revisions. HL contributed to the societal results and discussion.
The authors declare that they have no conflict of interest.
Thank you to community members in the Arbuckle-Simpson Aquifer area, Julie Demuth, and Rebecca Morss. This study is supported by National Oceanic and Atmospheric Administration grant NA11OAR4310205 and National Science Foundation EASM grants AGS-1048829 and AGS-1419563. NCAR is sponsored by the National Science Foundation. Edited by: Nunzio Romano Reviewed by: Anne Van Loon and two anonymous referees