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Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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2

Hydrologic Modeling

EAA RESPONSE TO COMMITTEE’S FIRST REPORT

After the publication of the first National Research Council report (2015), the Edwards Aquifer Authority (EAA) established a Recommendations Review Work Group (RRWG) to identify and develop a plan for responding to all of the report’s recommendations. The recommendations for the hydrologic model (see Chapter 1 page 17) included advancing the conceptual model of the system by using telescoping meshes to accommodate shorter time scales, better representing conduits and barriers, and quantitatively assessing and presenting model uncertainty in formal EAA documents. According to the RRWG (EAA, 2015a), some recommendations were already being implemented by the EAA, such as continued work on recharge estimation, others were mentioned as important to the EAA but work had yet to commence, while some recommendations are clearly not being worked on. In addition, the EAA created a Five-Year plan for hydrologic modeling. The objective of the Five-Year plan is the continued updating of the hydrologic model, including such steps as conducting uncertainty analysis with the ensemble method, documenting the model, and obtaining a peer review.

The Five-Year plan involves continued development of a single model, MODFLOW, although the Habitat Conservation Plan (HCP) mandated the creation of a second model of the groundwater system, which was based on FEFLOW. The RRWG did not resolve whether the EAA would move forward with one or both hydrologic models, but because the Five-Year plan prescribes use of the MODFLOW model only, it appears that the EAA’s re-

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

sponse to this recommendation has been resolved. The continuing challenge for the EAA is how to incorporate the learnings from the FEFLOW effort while maintaining a focus on the MODFLOW model.

According to the RRWG and the Five-Year plan, conceptual model changes are planned for future model versions, but not any time in the near future (such as the next five years). Nonetheless, the conceptual model changes suggested in NRC (2015) may substantially improve the quality of the model predictions and the model’s usefulness as a planning and aquifer management tool, and some could be accomplished in the next five years. The section below suggests a path for evaluating and incorporating some of the most critical recommendations made in NRC (2015). The following are discussed: more emphasis on conceptual model improvements, further extension of uncertainty analysis, more careful evaluation of recharge estimation, and improved descriptions of the modeling plans. In general, the Five-Year plan would be greatly improved with additional detail, including better documentation of all activities involving the model and a timeline for specific model updates and improvements.

Improve Conceptual Model of Aquifer

Use Knowledge Gained from FEFLOW Effort

NRC (2015) recommended that improvements to the conceptual model of the Edwards Aquifer gained during the development of the FEFLOW model should be used in the future. The FEFLOW model was built using substantial resources, and it represents a considerable improvement to the physical representation of the system. In particular, the use of an unstructured grid, which permits the simulation of conduits explicitly, and the incorporation of the contributing zone into the model domain, are viewed as important enhancements. The calibration results of the FEFLOW model did reveal some inadequacies (Fratesi et al., 2015), and further work would be needed to improve the calibration. Thus, continued use of the MODFLOW model, which was further along in calibration, was determined to be the future course. Nonetheless, there are still opportunities to incorporate concepts from the FEFLOW effort into the current MODFLOW model. For example, extensive stratigraphic data that were compiled for the FEFLOW model could help inform knowledge of interformational flows, an uncertainty in the current model. In addition, the lessons learned from incorporating the contributing zone in FEFLOW will be useful for recharge estimation in the MODFLOW model and should be articulated now. Conduit and barrier features in the MODFLOW model were adjusted based on FEFLOW modeling, but additional evaluation of these features could be considered (see below). Some model runs, even if not

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

rigorously calibrated, to help understand the sensitivity to these conceptual differences, would better support the model selection and prepare for the planned revisions in 2018 or 2019 to incorporate new features.

Test Conceptual Models Using Smaller Model Areas

In NRC (2015), the Committee made recommendations to both incorporate conduits and use telescoping grids. The latter recommendation provides a way to test conceptual models by taking advantage of parameter variation and calibration constrained to a smaller region. Thus, it is technically feasible to refine the model without excessive runtimes or cost, which was a concern of the RRWG. The refined model can be a gridded area nested within the larger model (a telescoping grid), or a separate model grid can be created. Indeed, the FEFLOW model examined subareas to focus calibration on smaller regions (Figure 2.4.2.3-2 from Fratesi et al., 2015).

Because telescoping grids are used to model a portion of the total area with a refined mesh, they make incorporation of conduits and finer time steps easier, as the model area under consideration is smaller. While there are additional costs associated with running these smaller models, they are small compared to the cost of the FEFLOW effort, which involved developing a second fully calibrated model. Modeling smaller areas can address some of the RRWG’s concerns about cost and feasibility in testing conceptual models because there is no need to reconceptualize the entire HCP model.

Using telescoping grids or smaller model areas to explore model sensitivity to features such as conduits can help address systematic errors that have been observed in the current model. Predictions from the current model have a better match to observed values at low flows than at high flows. This type of systematic error tends to be caused by conceptual errors. A telescoping model could be used to compare different methods of incorporating conduits (e.g., high conductivity zones versus line elements in unstructured grids). A small region near key springs (e.g., using the estimated capture area for a given spring rather than the entire San Antonio pool) could be modeled with increasingly complex conduit patterns to see if they improve high flow calibration. Uncertainty about conduit locations does not need to limit the use of models to test concepts. For example, such models can be used to test whether simple or complex networks produce a match to spring flows and whether there are different networks activated at high flow in contrast to low flow. The sensitivity of the model to conduits and other heterogeneity patterns could thus be extended beyond what was proposed in the Five-Year plan (which does not clearly explain how conduits will be incorporated). In addition, finer time steps may provide improved prediction of both high and low discharge, but in particular improved prediction of high discharge in response to storms.

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

Because information is lost when coarse, simplified models are constructed, doing some modeling at a finer scale can inform the reliability of the large scale results. The refining of temporal and spatial scales is common practice in hydrologic modeling. NRC (2015) discussed the importance of improving conceptual model understanding by incorporating conduits into future modeling. It is likely that even extensive efforts to calibrate the model may not yield satisfactory results if the model’s conceptual representation of the aquifer is not adequate. The use of sensitivity analysis on heterogeneity framed around conduit configurations and taking advantage of telescoping grids could help resolve long-standing debates about the role of conduits in model forecasts. These uncertainties need to be addressed to provide confidence in the models and bring the modeling up to current practices. Note that the type of conceptual model testing described here could be considered as modeling additional scenarios that help establish confidence in the model. The suggestions above do not fundamentally change the model or lead to development of a new model but simply allow the exploration of the model sensitivity to changes in the conceptual model of the aquifer.

Uncertainty Analysis

NRC (2015) describes five methods of uncertainty analysis that could be applied to a groundwater model of the Edwards Aquifer, which are showing error bars on spring-flow and water-level predictions, sensitivity analysis using the ensemble approach, testing the model’s predictive abilities using data from a time period not included in the model (see subsequent section), PEST predictive uncertainty analysis (Brakefield et al., 2015), and data collection for reducing predictive uncertainty. These methods are listed in order from easiest to most difficult to implement.

The RRWG identified uncertainty analysis in the Five-Year plan, but only the ensemble approach is mentioned. That is, the Committee was presented with plans to use an ensemble approach in which about 10 variations of recharge estimates would be applied to the model (see details in Recharge section below). Recharge estimates are a good place to start an ensemble uncertainty analysis, because it is clear that recharge originating in the contributing zone and the interformational inflows are some of the most uncertain inputs and have a large influence on water levels and spring flows. However, using only one approach for uncertainty analysis does not line up with the report recommendation to explore more techniques and parameters.

In one of the first hydrologic modeling presentations to the Committee (Winterlee, 2014), the model results were shown for four recharge scenarios and results presented in terms of calibration targets. The current plan expands the recharge scenarios, but again presents results in terms of

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

calibration targets with no statistical analysis (Winterlee, 2015). There was no indication that other conceptual-model parameters, boundary conditions, or other assumptions will be included in an ensemble approach for uncertainty analysis.

Another recommendation made in NRC (2015) was to display error bars in documentation of the groundwater model predictions; this was supported by the RRWG. Nonetheless, the Five-Year plan does not mention error bars, and modeling results shown at the committee meeting on February 2, 2016, did not incorporate them.

Although uncertainty analysis lends credence to models, arguments against its application include, among others, that it cannot be understood by policy makers and the public. However, Pappenberger and Beven (2006) explain why arguments such as this are not tenable. Uncertainty analysis can be used to illustrate possible ranges in the effects of system stressors and, therefore, enhances the interpretation of model results. Rather than letting the concern about public perceptions limit best practices in modeling, techniques should be applied to improve model design and data collection that decrease uncertainty (Anderson et al., 2015; Pappenberger and Beven, 2006). The potential for uncertainty analysis to increase transparency and lead to better decisions is exemplified by the case study of Enzenhoefer et al. (2014) summarized in Box 2-1.

Consideration of Recharge

NRC (2015) applauded the EAA’s focus on refining estimates of recharge in the hydrologic modeling. At the Committee meeting held February 3, 2016, the EAA indicated their continued interest in exploring recharge by developing an ensemble of recharge estimates that incorporates variations on assumptions related to recharge mechanics. The specific details of the methods and assumptions that will be applied were not described to the Committee, other than to say that the spatial variability of recharge may vary between estimates. All the model parameters that were originally calibrated will be recalibrated for each of the ensemble simulations for recharge estimates. This is similar to the approach taken by Brakefield et al. (2015), a recent Edwards Aquifer model in which the need for recalibration is described in detail. The ensemble of recharge estimates will include modifications to estimates based on the Puente (1978) method (the use of which is required by the HCP). For example, the original Puente method resulted in peaks in simulated spring flow hydrographs that were much larger than observed values for some periods. Therefore, peaks in the recharge estimates will be arbitrarily reduced in the ensemble of recharge estimates.

Beyond Puente, there appear to be at least two additional recharge estimation methods that have been applied to the groundwater modeling

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×
Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

efforts to date. First, a new recharge estimation method was applied to the FEFLOW model using NEXRAD1-estimated precipitation data. According to the FEFLOW final report (Fratesi et al., 2015), there were problems with using NEXRAD estimates, including that (1) the estimates were not available for 2001 to 2002 and (2) there were “data gaps and suspicious data.” It is possible that these problems could have been avoided by using Daymet data (https://daymet.ornl.gov/ and http://cida.usgs.gov/gdp), which contains gridded weather parameters for the United States at a 1-km resolution for 1980 to the present. The data are based on weather-station data, and the spatial interpolation accounts for topography. At this time, it is not clear if this method will be further developed by the modeling team.

Second, the EAA spent considerable time developing recharge estimates using the Hydrologic Simulation Program—Fortran (HSPF) (http://water.usgs.gov/software/HSPF/). The prioritization matrix found in EAA (2015a) indicates that development of the HSPF model for recharge estimation will continue. However, no new progress on HSPF modeling since the first Committee meeting (February 2014) has been presented. The Committee recommends that recharge estimates from the HSPF method be included in the ensemble approach being used for uncertainty analysis (see section below).

Beyond these methods, there are other methods for estimating recharge that would enhance the ensemble, including a soil-water-balance (SWB) model developed by the U.S. Geological Survey (USGS) that estimates spatially distributed daily recharge on the basis of gridded weather and soils data (Westenbroek et al., 2010). Like the FEFLOW recharge estimation method discussed above, the SWB model utilizes Daymet data as input. The Committee recommends using as many different recharge estimation methods as feasible, and varying uncertain recharge parameters within these methods, to create the ensemble. The ensemble will provide a range of possible outcomes for spring flows; this range can be examined for calibration periods and validation periods, and, most importantly, for future scenarios predicted by the model.

Updating the MODFLOW Model: Adaptive Modeling

Although adaptive modeling was embraced by the RRWG, the next step in updating the conceptual model in the Five-Year modeling plan is not until 2019. That delay does not ensure that the hydrologic model uses the most recent tools and data available. The suggestions mentioned above would move the model further toward adaptive techniques. In addition, there are other steps that could be taken which include providing

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1 NEXRAD stands for Next-Generation Radar, a network of high-resolution weather radars operated by the National Weather Service.

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

more detailed plans, improving data management, and regular updating of the model with new field data. The Five-Year plan could provide more details about what updates are going to be incorporated. Providing more specifics about what updates will occur enhances communication.

The importance of collecting additional field data to improve the groundwater model was discussed in some detail in NRC (2015). For example, data collection can help to better understand the mechanics of flow toward springs, by characterizing conduits and evaluating hydraulic connections between the Trinity and the Edwards aquifers (which is a key part of the current groundwater research effort). Another example of data collection that would benefit the modeling is the incorporation of all available pumping data. Finally, variations in rainfall observed in the past few years would be enormously helpful in identifying strengths and weaknesses of the model; incorporating these data into model testing should receive a high priority. The Five-Year plan mentions assessing new data in 2017, but does not yet show an iterative approach between data collection and model updates. Field efforts are ongoing in other parts of the EAA and other organizations, such as the USGS and the Southwest Research Institute (SWRI). There should be a member of the modeling team who communicates regularly with the monitoring team about how current research can be incorporated into the model. Effective communication between data-collection staff and modeling staff is critical to maximize the effectiveness of both of these groups. Although long-term field research involves significant resources, such investment in bridging between field research and modeling will be cost effective in the long run.

While we urge including more details in the Five-Year plan for hydrologic modeling, we also recognize there is an inherent conflict between detailing a Five-Year plan and allowing for adaptive management of a model (i.e., updating as results and tools become available). The purpose of doing more planning is not to provide a road map that is immutable, but rather to provide a framework for discussing and improving the model. That is, it may be necessary to update the Five-Year plan more frequently than every five years (e.g., every two to three years) if new information becomes available and the original plan becomes outdated.

SCENARIOS FOR HYDROLOGIC MODELING

The MODFLOW model is expected to continue to be the primary groundwater modeling tool for the HCP. It is essential that the EAA strives to improve the predictive skills of the model for the anticipated refinements to the flow protection measures that may be necessary in Phase 2. Once the current improvements to the model are complete, it should be used to test a variety of scenarios, which will not only improve the con-

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

fidence in the model itself but also will help develop strategic decisions associated with adaptive management and revisions to minimization and mitigation measures. The Committee’s ecological modeling interim report (NASEM, 2016) discusses the importance of using models to test concepts and understand parameters and system conditions, not just produce predictions, which can be highly uncertain. Similarly, the hydrologic model is not just a tool to produce head maps and discharge values at springs that are compared to targets, but should also be used to evaluate scenarios that help understand what processes are important in the system.

The definition of the term “scenarios” in this section is broader than what is typically used for understanding system behavior under uncertainty. In view of the potentially significant economic costs associated with the four flow protection measures, it is extremely important to ensure that the model has adequate predictive skills under alternative future condition. Hence, the testing of the model against recent observations not used in the calibration (referred to as model validation) is suggested as a particular scenario to verify that the predictive skills of the model are acceptable and to determine if further improvements are needed. The first section below recommends testing the model against the most recent drought period (2011-2014) and the wet year of 2015. These years should have more accurate data (e.g., pumping) and management interventions that can enhance the confidence in the model as a predictive tool. Several modeling scenarios that can be run are then described, including lesser and more severe droughts as compared to the drought of record, optimization of the EAA’s so-called “bottom-up package” of the four spring flow protection measures, understanding the influence of spatial patterns of pumping, and potential implications of land-use changes in the contributing zone on the water budget in the region. These scenarios are designed to ensure that the EAA meets the requirements of the adaptive management phase of the HCP by having a model that has been tested under a variety of conditions and by optimizing the flow protection measures in order to ensure that they meet specified goals.

Testing the Model by Comparing Predictions to the 2011-2015 Data

One of the recommendations for uncertainty analysis in NRC (2015) was to test the most recent version of the MODFLOW model against data from periods outside the period of calibration. The planned calibration period for the MODFLOW model is the period 2001-2011 (Winterlee, 2016). The model will then be used to evaluate the drought of record as a test of the accuracy of the model for simulating drought conditions. If the drought of record is not simulated adequately, the EAA may need to proceed with further calibration. If calibration is needed after attempting

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

to validate the model, a description of what additional calibration was necessary should be documented in the model report. The ongoing efforts to improve the model, including a recalibration, should produce a better tool for future applications. This type of approach for using the model for conditions that have not been observed is not atypical and probably the only way to develop water resources management plans.

To improve the predictive skills of the model further, the MODFLOW model should be tested for periods outside the drought of record but under less extreme conditions and where more accurate data are available. The question that this scenario is trying to answer is “How accurately can the model predict conditions outside the time period used in the calibration?” In particular, the Commiteee recognizes the importance of simulating the more recent drought of 2011 to 2014 using current model parameters. These years are embedded in a longer-term drier period, which appears to have started in 2003 and which had a cumulative rainfall deficit of 82 inches (see Figure 2-1). The period is important as it includes more accurate well withdrawal data, better rainfall and flow information, extensive water level datasets, and, more importantly, the implementation of selected flow protection measures. For instance, the annual recharge during 2014 was only about 107,000 acre-feet, which was the second lowest recharge since 1934. On March 2012, the Uvalde pool reached the Stage V

Image
FIGURE 2-1 Regional mean deficit (annual and cumulative) rainfall from 2003 to 2014. The bars show the cumulative rainfall deficit for the period 2003-2014.
SOURCE: EAA (2015b).
Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

critical period management trigger for the first time. During this drought event, the precipitation was lower and groundwater usage was higher, yet spring flow did not dip quite as low in 2014 as it did during the 1950s. The difference may have been due to HCP conservation measures that were implemented during this period. Data and information gained during their implementation could be useful to test and improve the current model. It is important to note that the EAA may need to devote resources to acquire rainfall, pumpage, and other data necessary for simulating conditions during the 2011 to 2014 period. Finally, it would also be instructive to use the very wet year of 2015 to test model predictions (i.e., the recovery of the aquifer after a period of drought could be a sensitive test of model behavior).

The exercise of testing the model using the 2011 to 2015 period is likely to reveal the limitations of the current model. In addition, scenario testing should provide information on relative effects of withdrawals and effectiveness of management measures that were implemented during this period.

Performance of the System under a Variety of Drought Conditions

To date, the only scenario that the EAA has sought to run in the hydrologic model is the management program that includes the four spring flow protection measures (aka the bottom-up package) under conditions of the drought of record. These measures include the Voluntary Irrigation Suspension Program Option (VISPO), the Regional Water Conservation Program (RWCP), Aquifer Storage and Recovery (ASR), and Stage V Critical Management Period reductions. The model has simulated the effects of these measures on spring flow at Comal Springs during a repeat of the drought of record (Figure 2-7 in NRC 2015 and in many other documents). The model run used system demands that reflected the “permitted” withdrawals given by Initial Regular Permits. The total demand was approximately 572,000 acre-feet per year which was distributed spatially according to the 2008 pumping pattern in each county. The bottom-up package was also designed for the climatic conditions of the drought of record, the 1951-1956 period (HCP main report, and Appendix K). This period was the most severe drought recorded since 1934, and because of its duration and magnitude, the hydrologic effects were significant as was evident from the cessation of spring flow at Comal Springs for 144 days in 1956. Available evidence suggests that the six-year drought was indeed a very rare event, particularly with respect to duration. Droughts in the region are usually of shorter duration, although they could be more or less intense. From an extended record (280 years from 1700 to 1979) of Palmer Drought Severity Index (PDSI) developed using a correlation to tree ring data, droughts exceeding three years in duration occurred only four times, and three of

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

them in the 1700s (EARIP, 2012). The drought of record was the fourth and most intense (EARIP, 2012).

Although the drought of record is a rare event (both in intensity and duration), the Committee had suggested that the 1950s drought may not represent the true worst-case scenario as the baseline for hydrologic modeling (NRC, 2015). Tree-ring data and other studies have indicated the possibility of more severe “mega-droughts.” In view of the nature of the study and level of protection needed for the species that are threatened or endangered, it may be prudent to design a hydrologic scenario that simulates climatic and socioeconomic conditions which are more severe than what was used for the HCP. The question such a scenario is designed to answer is “How sensitive is the model to extreme conditions?” Another compelling reason for such an analysis is the vulnerability of the region to climate change. Mace and Wade (2008) and Loáiciga et al. (1996) have suggested that the Edwards Aquifer is the groundwater resource in Texas most vulnerable to climate change. While recognizing the lack of data for more severe drought scenarios, the use of paleo data (e.g., tree rings) and possibly stochastic modeling of rainfall patterns should be explored for the development of extreme scenarios. The climate scenarios should be designed considering the results of climate-model predictions available from regional climate models that are nested within general circulation models. Spatial variability in rainfall within the Edwards Aquifer region, and the variations in pumping patterns, both of which will impact spring flows, should also be explored in scenario investigations.

Past droughts of shorter duration with more or less intensity are also of interest in understanding the effectiveness of flow protection measures and to test the model’s accuracy. A review of PDSI records available for the NOAA Climate Divisions 6 and 7 in Texas covering the Edwards Aquifer region clearly shows the occurrence of such less severe droughts (see Figure 2-2).

Setting aside the drought of record (1951-1956), there are many other periods when the severity of drought was in the categories of mild or more severe; all of them are shorter in duration than the drought of record, generally two to four years. The following periods can be identified from Figure 2-2: 1909-1911, 1933-1934, 1962-1963, 1988-1989, and 2011-2014. The effect of the shorter drought periods can be seen clearly in the observed spring flow record at Comal Springs, and during many of the droughts, the flow decreased below 100 cfs (see Figure 2-3). Consequently, they represent lesser extremes but were severe enough to cause a significant decrease in spring flows. Testing how well the model can predict responses during such lesser extremes may demonstrate its applicability to a variety of climatic conditions and further enhance the confidence in the model for adaptive management and for other applications in Phase 2 of the HCP.

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×
Image
FIGURE 2-2 The Committee compiled and graphed these data of the Monthly Palmer Drought Severity Index (PDSI) for the 1895-2015 period for NCDC Climate Division 6 in Texas. The drought indicators of PDSI= –2, –3, and –4 are noted as dashed lines. The shaded boxes show wet (blue) and dry (brown) years. The drought severity scale is (a) –1.0 to –2.0 = mild drought; (b) –2.0 to –3.0 = moderate drought; (c) –3.0 to –4.0 = severe drought; and (d) greater than –4.0 = extreme drought. Developed by the Committee using the data from: https://www1.ncdc.noaa.gov/pub/data/cirs/climdiv/.
NCDC = National Climate Data Center.

Optimize the Bottom-Up Package

Another useful scenario for the hydrologic modelers to run can answer the question “Can implementation of the four spring flow protection measures of the HCP be optimized?” In the HCP, the four measures in the bottom-up package were used in an incremental manner, buiding the package by superimposing one measure onto another previously implemented measure. For example, since VISPO alone is not adequate in achieving spring flow targets, a combined package of VISPO and the RWCP was tested. It was determined that all four measures were necessary to achieve spring flow targets under the conditions of the drought of record with all permitted withdrawals. All measures were accounted for in the model by making changes to water withdrawals. There is no information on any at-

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×
Image
FIGURE 2-3 Observed flows at Comal Spring.
SOURCE: www.edwardsaquifer.org/dataflow/api/chart.
Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

tempt to optimize the combination of measures, including the magnitude and spatial implementation of each or the order in which they might be implemented. The Committee recommends that the EAA undertake an optimization analysis of various combinations of the bottom-up package. In such an analysis, the objective function could be formulated to minimize the deviations of the spring flow and water level targets. From this exercise a different combination of measures with different magnitudes may emerge as the optimal combination that minimizes the deviations from the spring flow targets or cost of implementation.

Understanding the relative effectiveness of various flow protection measures may prove to be extremely valuable for adaptive management and potential revisions of the bottom-up package in Phase 2. Not all droughts will be as severe as the drought of record and, as discussed in a previous section, there will be many more droughts that are less severe. Some of these droughts will require implementation of flow protection measures. Depending on the magnitude of the drought, a particular measure alone may provide the level of protection needed to maintain spring flows necessary to achieve the biological goals of the HCP. For instance, in certain situations, using only the ASR option, which appears to have the greatest “lift” in terms of improving spring flows, may be adequate. The optimization exercises described above will provide the necessary information for decision making either in an adaptive management setting or for revisions of flow protection measures that may be necessary in Phase 2 of the HCP.

Influence of Spatial Pattern of Pumping

The groundwater model includes pumping from a large number of wells and well fields within its model domain that are spatially distributed in a non-uniform manner. In general, certain wells or group of wells may have a larger influence on spring flows than others that are located remotely with respect to the locations of the springs. A comprehensive analysis of this could provide useful information for developing various options for implementing flow protection measures during future droughts. This scenario can answer the question “Which wells have the greatest influence on index wells or discharges from the springs?”

Such a sensitivity analysis involves conducting field tests using a set of wells thought to have the highest sensitivity to water levels at index wells and flows at springs. Pumping at these wells could be increased by some percentage for a certain length of time (e.g., one-two months); with careful monitoring, the data from such a field test could provide valuable information for further validation of the model. Ideally, such a test should be conducted during a period in which the withdrawals have the largest influence and the other stressors (e.g., rainfall) are minimal. Consequently, the ideal

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

time for such a test should be selected carefully. The wells belonging to a large permit holder (e.g., the San Antonio Water System) may have to be used for this testing since it would be difficult to facilitate the involvement of a large number of individual well owners.

The sensitivity analysis should be followed by an optimization modeling exercise to determine the combination of wells and well fields that would be most effective in achieving the hydrologic goals of the HCP. This analysis may be conducted for droughts of various magnitudes. The optimization package may include the contraints due to, say, water rights of certain users. The groundwater management package developed by the USGS is an appropriate tool for optimization analysis (see Box 2-2).

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

Significant Growth and Land-use Change in the Recharge Area

The Edwards Aquifer region encompassing as many as 12 counties in South Central Texas is located in one of the fastest-growing regions in the country. During the decade of 2000-2010, the population in the region increased by about 20 percent (Lal et al., 2012). Over the next two to three decades, further growth is expected. It is estimated that between 2010 and 2040 as much as 240,000 acres of available undeveloped land will be converted to developed land (County of Bexar, 2015). The projected land-use change will most likely result in conversion of agricultural land to urban growth, and such conversions typically have a significant impact on rainfall-runoff-recharge processes in a basin. According to Lal et al. (2012), there has been a net reduction of about 130,000 acres of total farmland between the years 2002 and 2007 alone. Urbanization typically results in rapid runoff with decreasing opportunities for recharge.

Since recharge is one of the most important components of the water budget, any change in its characteristics due to land-use changes in the region, and in particular over the contributing zone, has the potential to impact spring flow characteristics. Another complicating factor that would negatively impact recharge quantity is climate change. Projected warming and potentially drier conditions in the basin may lead to less recharge.

A scenario with projected land-use changes and likely change in climate (but no change in water withdrawals by well pumping) over the next two to three decades should be simulated to answer the question “How would a changes in recharge amount due to changing land use impact spring flows?” It should be noted that the current empirical method of estimating recharge calibrated using historical data (i.e., the Puente method) may not allow an assessment of the impact of land-use changes. One of the more physically based models of recharge previously discussed, such as HSPF or the soil-water-balance model by Westenbroek et al. (2010), will be required for such a scenario investigation.

MODEL MANAGEMENT: USING THE MODEL IN MAINTENANCE MODE

Because the EAA’s groundwater management model (MODFLOW model) will be used for long-term planning, it is most useful if updated and improved periodically. Improvements may be the result of the availability of additional observations and other supporting data, updates to the conceptual model and hydrogeologic framework, improved versions of the model code, and better parameter and uncertainty estimation methods. The Committee recommends further improvement and model testing to prepare the model for maintenance mode.

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

Versioning

Once the model moves from the development and calibration stage to operational mode, it should be formally documented as a public record at a high level of transparency. Each periodic model update should be formalized and documented in a peer-reviewed report as a citable model version. Rigorous model description leads to more effective future use of the model, particularly as EAA personnel changes over time. The Committee recommends the use of a formal versioning system, consisting of a model archive and peer-reviewed report identified by a unique version number, with a model update occurring about every five years. At a minimum, model updates would include an assessment of the model’s skill in simulating the additional five years of spring flow and water-level records, possibly including recalibration. This assessment should be described in the report and used to track the model’s predictive skill with each successive version; hopefully this skill would improve over time. The model archive should be made available to other government agencies and interested parties for the purpose of simulating specific scenarios of interest or for confirming the EAA’s published simulation results.

Decision Support System

To ensure minimum continuous spring flows, the HCP specifies flow protection measures, some of which are triggered at specific groundwater elevations at selected index wells. For example, the Stage V Critical Management Period pumping reductions of 44 percent are triggered at 625 feet mean sea level (MSL) at well J-17 and 840 feet MSL at well J-27. In planning for Phase 2 of the HCP, consideration should be given to developing a more refined framework that incorporates modeling into the decision criteria rather than relying on triggers based on measured groundwater elevations at specific wells. Hence, the Committee recommends the development of a decision support system (DSS) to be used in Phase 2 of the HCP in order to apply the model to short-term decisions (e.g., a one-month time frame). This is necessary because short-term decisions that should be made quickly might be substantially delayed if a DSS is not in place as an objective guide. A DSS would clearly direct these decisions on the basis of different model outcomes. A good DSS is developed and applied with the understanding that model predictions, although uncertain, represent the best available science on which to base management decisions.

The DSS should include a protocol for continually incorporating real-time data (e.g., groundwater levels, rainfall, and well withdrawals) and for scheduling frequent model simulations to predict water levels and spring flows for the short-term future. The next step in developing the DSS would

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

be to define the actions to be taken on the basis of an agreed upon probability that a particular outcome will occur. For example, the 12-month outlook of the water levels at an index well would be presented probabilistically, and a pre-determined action would be taken if there is reasonable probability that the water level will be at or below a critical value within that 12-month period. This way, early management actions can alleviate probable undesirable outcomes later. Such a tool would be even more valuable if future climate outlooks are incorporated into the probabilistic predictions. An example of such an approach, known as Position Analysis, is described in Box 2-3. In this case, the approach applies a range of probabilistic meteorological conditions for one- to two-year predictions of Lake Okeechobee water levels.

CONCLUSIONS AND RECOMMENDATIONS

Although a number of improvements to the groundwater model calibration have been achieved since the 2015 NRC report, continued model development would improve the reliability and predictive capability of the model. Particularly useful would be to evaluate the sensitivity of the model to the various scenarios described herein and to test the model’s ability to predict spring flow and well levels under recent climatic conditions.

The EAA is encouraged to incorporate additional recommendations from the first Committee report, such as more extensive uncertainty analysis, testing conceptual models on subgrids, and better documentation of model updates (including incorporation of new field data). More extensive uncertainty analysis will enhance confidence in the model results. Telescoping grids can be used to test conceptual models using a smaller area, which can address questions that are difficult to answer with the larger grid. In addition to documenting changes in the model, updating model parameters and input data more frequently assures that the latest information is used to make model predictions.

The groundwater model should be tested against the 2011 to 2015 period, which was not used in model calibration. This period, which includes both very dry and wet years, offers a remarkable opportunity to validate the model and enhance confidence in the model for future applications. Testing the model using the 2011-2015 period is likely to reveal the limitations of the current model. In addition, it should provide information on relative effects of withdrawals and effectiveness of management measures that were implemented during this period. The hydrologic, climatic, and well withdrawal data and the information on management actions for 2011-2015 should be more accurate than those from prior years, allowing for a more reliable assessment of the model.

Several scenarios are suggested for the hydrologic model, including optimizing the bottom-up package, evaluating spatial variations in pump-

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

ing, and predicting how significant growth and land-use change in the recharge area might affect spring flows. Testing a variety of scenarios will not only improve the confidence in the model itself but will also help develop strategic decisions associated with adaptive management and revisions to minimization and mitigation measures.

The Five-Year plan for the hydrologic model should include formal versioning and a decision support system that will be useful in future phases of HCP. The model should be updated every five years, with each new version including a peer-reviewed report and permanent archive of the numerical

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
×

model that is available to the public. A decision support system will help minimize the subjectivity of management decisions that require a rapid response and should be included in Phase 2 of the HCP.

REFERENCES

Anderson, M. P., W. W. Woessner, and R. J. Hunt. 2015. Applied Groundwater Modeling: Simulation of Flow and Advective Transport. Academic Press.

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Banta, E. R., and D. P. Ahlfeld. 2013. GWM-VI—Groundwater Management with Parallel Processing for Multiple MODFLOW versions: U.S. Geological Survey Techniques and Methods 6-A48.

Brakefield, L. K., J. T. White, N. A. Houston, and J. V. Thomas. 2015. Updated numerical model with uncertainty assessment of 1950–56 drought conditions on brackish-water movement within the Edwards Aquifer, San Antonio, Texas. U.S. Geological Survey Scientific Investigations Report 2015–5081, 54 pp., http://dx.doi.org/10.3133/sir20155081.

Cadavid, L. G., R. Van Zee, C. White, P. Trimble, and J. T. B. Obeysekera. 1999. Operational Hydrology in South Florida Using Climate Forecast. American Geophysical Union, Proceedings of the Nineteenth Annual Hydrology Days, August 16-20.

County of Bexar. 2015. Southern Edwards Plateau, Habitat Conservation Plan Prepared by Bowman Consulting Group, LTD 310 Bee Cave Road, suite 1000, Austin, Texas 78746. Project Number 005520-01-001.

EAA. 2015a. National Academy of Sciences—Review of the Edwards Aquifer Habitat Conservation Plan. Report 1 Implementation Plan. EAA August 20, 2015.

EAA. 2015b. Hydrologic Data Report for 2014. Report No. 15-01, November 2015.

EARIP. 2012. Habitat Conservation Plan. Edwards Aquifer Recovery Implementation Program.

Enzenhoefer, R., T. Bunk, and W. Nowak. 2014. Nine steps to risk-informed wellhead protection and management: A case study. Groundwater 52(S1):161-174.

Fratesi, S. B., R. T. Green, F. P. Bertetti, R. N. McGinnis, N. Toll, H. Başağaoğlu, L. Gergen, J. R. Winterlee, Y. Cabeza, and J. Carrera. 2015. Final Report: Development of a Finite-Element Method Groundwater Flow Model for the Edwards Aquifer. SWRI Project No. 20-17344

Hirsch, R. M. 1978. Risk Analysis for a Water-Supply System—Occoquan Reservoir, Fairfax and Prince William counties, Virginia. Hydrologic Science Bulletin 23(4):476-505.

Lal, R., B. A. Stewart, V. Uddameri, and V. P. Singh. 2012. Competition between Environmental, Urban, and Rural Groundwater Demands and the Impacts on Agriculture in Edwards Aquifer Area, Texas. Pp. 117-130 In: Soil Water and Agronomic Productivity. CRC Press.

Loáiciga H. A., J. B. Valdes, R. Vogel, J. Garvey, and H. H. Schwarz. 1996. Global warming and the hydrologic cycle. Journal of Hydrology 174 (1 and 2):83-128.

Mace, R. E., and S. C. Wade. 2008. In hot water? How climate change may (or may not) affect the groundwater resources of Texas. Gulf Coast Association of Geological Societies Transactions 58:655-668.

NASEM (National Academies of Sciences, Engineering, and Medicine). 2016. Evaluation of the Predictive Ecological Model for the Edwards Aquifer Habitat Conservation Plan: An Interim Report as Part of Phase 2. Washington, DC: The National Academies Press. doi: 10.17226.23577.

NRC (National Research Council). 2015. Review of the Edwards Aquifer Habitat Conservation Plan: Report 1. Washington, DC: The National Academies Press.

Pappenberger, F., and K. J. Beven. 2006. Ignorance is bliss: Or seven reasons not to use uncertainty analysis. Water Resources Research 42(5).

Prudic, D. E., L. F. Konikow, and E. R. Banta. 2004. A new Streamflow-Routing (SFR1) Package to simulate stream-aquifer interaction with MODFLOW-2000: U.S. Geological Survey Open-File Report 2004-1042, 95 pp.

Puente, C. 1978. Method of Estimating Natural Recharge to the Edwards aquifer in the San Antonio area, Texas. U.S. Geological Survey Water-Resources Investigations 78-10, 34.

Smith, J. A., G. N. Day, and M. D. Kane. 1992. Nonparametric framework for long-range streamflow forecasting. Journal of Water Resources Planning and Management, ASCE 118(1), 82-92.

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Tasker, G. D., and P. D. Dunne. 1997. Bootstrap position analysis for forecasting low flow frequency. Journal of Water Resources Planning and Management ASCE 123(6):359-367.

Westenbroek, S. M., V. A. Kelson, W. R. Dripps, R. J. Hunt, and K. R. Bradbury. 2010. SWB—A modified Thornthwaite-Mather soil-water-balance code for estimating groundwater recharge. U.S. Geological Survey Techniques and Methods 6-A31, 60 p.

Winterlee, J. 2014. MODFLOW Verification Analysis pptx file. Sent to the NRC Committee on 2/14/2014.

Winterlee, J. 2015. EAA Modeling Program Update. Presentation to the National Academies’ Committee on 10/29/2015.

Winterlee, J. 2016. EAA Modeling Program Update. Presentation to the National Academies’ Committee on 2/3/2016.

Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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Suggested Citation:"2 Hydrologic Modeling." National Academies of Sciences, Engineering, and Medicine. 2017. Review of the Edwards Aquifer Habitat Conservation Plan: Report 2. Washington, DC: The National Academies Press. doi: 10.17226/23685.
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The Edwards Aquifer in south-central Texas is the primary source of water for one of the fastest growing cities in the United States, San Antonio, and it also supplies irrigation water to thousands of farmers and livestock operators. It is also is the source water for several springs and rivers, including the two largest freshwater springs in Texas that form the San Marcos and Comal Rivers. The unique habitat afforded by these spring-fed rivers has led to the development of species that are found in no other locations on Earth. Due to the potential for variations in spring flow caused by both human and natural causes, these species are continuously at risk and have been recognized as endangered under the federal Endangered Species Act(ESA). In an effort to manage the river systems and the aquifer that controls them, the Edwards Aquifer Authority and stakeholders have developed a Habitat Conservation Plan (HCP). The HCP seeks to effectively manage the river-aquifer system to ensure the viability of the ESA-listed species in the face of drought, population growth, and other threats to the aquifer. The National Research Council was asked to assist in this process by reviewing the activities around implementing the HCP.

Review of the Edwards Aquifer Habitat Conservation Plan: Report 2 reviews the progress in implementing the recommendations from the Committee's first report, seeking to clarify and provide additional support for implementation efforts where appropriate. The current report also reviews selected Applied Research projects and minimization and mitigation measures to help ensure their effectiveness in benefiting the listed species.

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