Hydrologic Metrics Research Articles

Environmental flow modelling of the Chalakkudi Sub-basin using ‘Flow Health’

Ecohydrological modelling and prescribing environmental flows (e-flows) is significant in the Integrated Water Resources Management (IWRM) practice. However, for many river basins, there is lack of data on ecosystems and on the relationships between e-flows and ecosystem functioning. This lack of sufficient ecosystem data is mostly addressed in ecohydrological modelling by using hydrological metrics as surrogates of river ecosystem. In this study, we are demonstrating how it helps e-flows modelling and real-life management decisions underway with respect to Inter-basin Water Transfer (IBWT) projects. Desktop model ‘Flow Health’ is used here to design e-flows regime for Chalakkudi Sub-basin in Southern Peninsular India. Chalakkudi Sub-basin is over abstracted with six large dams built as components of the Parambikulam Aliyar Project (PAP), Asia's largest IBWT network. The monthly e-flow regimes required to maintain alternate levels of ecosystem conservation are estimated in this paper. The additional flood flow volume required for these alternate levels is also discussed. The results are useful in the stakeholder engagement process for informed decision-making on e-flows and redefining the IBWT operations within a broad framework of IWRM.

Testing the relationship between testate amoeba community composition and environmental variables in a coastal tropical peatland

We investigated the ecology of testate amoebae (TA) in a coastal tropical peatland to evaluate their potential as environmental indicators in these ecosystems. At 10 positions in five locations in a transect running into the peatland away from the coast, we measured pore-water pH, pore-water electrical conductivity, soil moisture content (MC), and water-table depth (WTD). The WTD data were collected using dipwells fitted with self-recording pressure transducers that logged at 10-min intervals over a 25-day period. Multivariate statistical analysis showed that hydrological metrics (WTD and MC) were the strongest environmental controls on TA (p < 0.001) in this site, corroborating the single previous study from western Amazonia. Changes in pH and electrical conductivity, reflecting marine influence, were also significant, but less so (p < 0.05; p < 0.01 respectively). Transfer functions for WTD and MC were developed using weighted averaging partial least-squares regression, and were found to perform well under ‘leave-one-out’ cross validation (R2 = 0.80, RMSEP = 4.64 cm; R2 = 0.89; RMSEP = 1.57 cm). Our results clarify the autecology of several taxa found in tropical peatlands. Centropyxis aculeata is an unambiguous indicator of surface water, Hyalosphenia subflava “minor” (<60 μm length) is a dry indicator, whereas Hyalosphenia subflava “major” (>60 μm length) lives in wetter conditions. The difference in habitat preference of the two forms of Hyalosphenia subflava suggests that this taxon is most probably a species complex. We use the new high-quality dataset to test an existing transfer function from western Amazonia: the results show that the previous model has good predictive power for reconstructing past WTDs in tropical peatlands (r = 0.87; p < 0.005). The reconstruction of sea-level change from tropical coastal wetlands may prove problematic because the key indicators of marine influence, reflected in pH and electrical conductivity, are taxa with weak idiosomic tests that do not preserve readily in the peat archive (e.g. Tracheleuglypha dentata, Trinema lineare). Our work shows the potential of using high-quality hydrological measurements for increasing the precision of transfer function models.

Hydrologic metrics for status‐and‐trends monitoring in urban and urbanizing watersheds

AbstractLocal governmental agencies are increasingly undertaking potentially costly “status‐and‐trends” monitoring to evaluate the effectiveness of stormwater control measures and land‐use planning strategies or to satisfy regulatory requirements. Little guidance is presently available for such efforts, and so we have explored the application, interpretation, and temporal limitations of well‐established hydrologic metrics of runoff changes from urbanization, making use of an unusually long‐duration, high‐quality data set from the Pacific Northwest (USA) with direct applicability to urban and urbanizing watersheds. Three metrics previously identified for their utility in identifying hydrologic conditions with biological importance that respond to watershed urbanization—TQmean (the fraction of time that flows exceed the mean annual discharge), the Richards‐Baker Index (characterizing flashiness relative to the mean discharge), and the annual tally of wet‐season day‐to‐day flow reversals (the total number of days that reverse the prior days' increasing or decreasing trend)—are all successful in stratifying watersheds across a range of urbanization, as measured by total contributing area of urban development. All metrics respond with statistical significance to multidecadal trends in urbanization, but none detect trends in watershed‐scale urbanization over the course of a single decade. This suggests a minimum period over which dependable trends in hydrologic alteration (or improvement) can be detected with confidence. The metrics also prove less well suited to urbanizing watersheds in a semi‐arid climate, with only flow reversals showing a response consistent with prior findings from more humid regions. We also explore the use of stage as a surrogate for discharge in calculating these metrics, recognizing potentially significant agency cost savings in data collection with minimal loss of information. This approach is feasible but cannot be implemented under current data‐reporting practices, requiring measurement of water‐depth values and preservation of the full precision of the original recorded data. With these caveats, however, hydrologic metrics based on stage should prove as or more useful, at least in the context of status‐and‐trends monitoring, as those based on subsequent calculations of discharge.

Prediction of Hydrologic Characteristics for Ungauged Catchments to Support Hydroecological Modeling

AbstractHydrologic variability is a fundamental driver of ecological processes and species distribution patterns within river systems, yet the paucity of gauges in many catchments means that streamflow data are often unavailable for ecological survey sites. Filling this data gap is an important challenge in hydroecological research. To address this gap, we first test the ability to spatially extrapolate hydrologic metrics calculated from gauged streamflow data to ungauged sites as a function of stream distance and catchment area. Second, we examine the ability of statistical models to predict flow regime metrics based on climate and catchment physiographic variables. Our assessment focused on Australia's largest catchment, the Murray‐Darling Basin (MDB). We found that hydrologic metrics were predictable only between sites within ∼25 km of one another. Beyond this, correlations between sites declined quickly. We found less than 40% of fish survey sites from a recent basin‐wide monitoring program (n = 777 sites) to fall within this 25 km range, thereby greatly limiting the ability to utilize gauge data for direct spatial transposition of hydrologic metrics to biological survey sites. In contrast, statistical model‐based transposition proved effective in predicting ecologically relevant aspects of the flow regime (including metrics describing central tendency, high‐ and low‐flows intermittency, seasonality, and variability) across the entire gauge network (median R2 ∼ 0.54, range 0.39–0.94). Modeled hydrologic metrics thus offer a useful alternative to empirical data when examining biological survey data from ungauged sites. More widespread use of these statistical tools and modeled metrics could expand our understanding of flow‐ecology relationships.

Evaluation of infiltration‐based stormwater management to restore hydrological processes in urban headwater streams

AbstractUrbanization threatens headwater stream ecosystems globally. Watershed restoration practices, such as infiltration‐based stormwater management, are implemented to mitigate the detrimental effects of urbanization on aquatic ecosystems. However, their effectiveness for restoring hydrologic processes and watershed storage remains poorly understood. Our study used a comparative hydrology approach to quantify the effects of urban watershed restoration on watershed hydrologic function in headwater streams within the Coastal Plain of Maryland, USA. We selected 11 headwater streams that spanned an urbanization–restoration gradient (4 forested, 4 urban‐degraded, and 3 urban‐degraded) to evaluate changes in watershed hydrologic function from both urbanization and watershed restoration. Discrete discharge and continuous, high‐frequency rainfall‐stage monitoring were conducted in each watershed. These datasets were used to develop 6 hydrologic metrics describing changes in watershed storage, flowpath connectivity, or the resultant stream flow regime. The hydrological effects of urbanization were clearly observed in all metrics, but only 1 of the 3 restored watersheds exhibited partially restored hydrologic function. At this site, a larger minimum runoff threshold was observed relative to the urban‐degraded watersheds, suggesting enhanced infiltration of stormwater runoff within the restoration structure. However, baseflow in the stream draining this watershed remained low compared to the forested reference streams, suggesting that enhanced infiltration of stormwater runoff did not recharge subsurface storage zones contributing to stream baseflow. The highly variable responses among the 3 restored watersheds were likely due to the spatial heterogeneity of urban development, including the level of impervious cover and extent of the storm sewer network. This study yielded important knowledge on how restoration strategies, such as infiltration‐based stormwater management, modulated—or failed to modulate—hydrological processes affected by urbanization, which will help improve the design of future urban watershed management strategies. More broadly, we highlighted a multimetric approach that can be used to monitor the restoration of headwater stream ecosystems in disturbed landscapes.

Macroinvertebrate community responses to hydrological controls and groundwater abstraction effects across intermittent and perennial headwater streams

Intermittent rivers comprise a significant proportion of river networks globally and their spatial extent is predicted to increase with rising water abstraction pressures. Despite this, the ecological implications of hydrological modifications within intermittent rivers have received limited research attention. This paper examines macroinvertebrate assemblages across intermittent and perennial sections of headwater streams within the Hampshire Avon catchment (United Kingdom) over a five-year period. The composition of faunal assemblages was quantified in relation to four hydrological metrics: the duration of flowing conditions, the geographical proximity to the nearest perennial source along each watercourse (two observed flow parameters) and two modelled groundwater abstraction influences. The results highlight that macroinvertebrate communities inhabiting sites which dry periodically and are positioned at greater distances (>c. 2.5km) above the perennial source (the most upstream point of permanent flow within a given year) possessed the highest conservation values. These sites supported species that are rare in many areas of Europe (e.g. Ephemeroptera: Paraletophlebia werneri) or with limited geographical distribution across the United Kingdom (e.g. Trichoptera: Limnephilus bipunctatus). A range of faunal community diversity indices were found to be more sensitive to the antecedent flow duration and distance from the perennial source, rather than any effects of groundwater abstraction. Taxonomic richness responded most strongly to these observed flow parameters and varied more markedly with the distance from the perennial source compared to the antecedent flow duration. Several taxa were significantly associated with the observed flow parameters, particularly those predominantly inhabiting perennially flowing systems. However, the distance that such fauna could migrate into intermittent reaches varied between taxa. This research demonstrates the overriding importance of antecedent flow durations and the geographical proximity to perennial sources on macroinvertebrate communities within intermittent and perennial headwater streams.

Modeled hydrologic metrics show links between hydrology and the functional composition of stream assemblages.

Flow alteration is widespread in streams, but current understanding of the effects of differences in flow characteristics on stream biological communities is incomplete. We tested hypotheses about the effect of variation in hydrology on stream communities by using generalized additive models to relate watershed information to the values of different flow metrics at gauged sites. Flow models accounted for 54-80% of the spatial variation in flow metric values among gauged sites. We then used these models to predict flow metrics in 842 ungauged stream sites in the mid-Atlantic United States that were sampled for fish, macroinvertebrates, and environmental covariates. Fish and macroinvertebrate assemblages were characterized in terms of a suite of metrics that quantified aspects of community composition, diversity, and functional traits that were expected to be associated with differences in flow characteristics. We related modeled flow metrics to biological metrics in a series of stressor-response models. Our analyses identified both drying and base flow instability as explaining 30-50% of the observed variability in fish and invertebrate community composition. Variations in community composition were related to variations in the prevalence of dispersal traits in invertebrates and trophic guilds in fish. The results demonstrate that we can use statistical models to predict hydrologic conditions at bioassessment sites, which, in turn, we can use to estimate relationships between flow conditions and biological characteristics. This analysis provides an approach to quantify the effects of spatial variation in flow metrics using readily available biomonitoring data.

Use of geographical information system-based hydrological modelling for development of a raised bog conservation and restoration programme

Peat-accumulating active raised bog (ARB) constitutes an Annex I priority habitat under the European Union’s Habitats Directive (HD). Ecological monitoring of Irish special area of conservation (SAC) sites from the mid-1990s up to 2013 has shown that the network experienced ARB losses of 37% (730ha) since the HD came into law. Obligations to restore ARB coverage, while conserving existing priority habitat, require a scientifically-defensible methodology to underpin long-term management. GIS-based investigative tools provided a basis for linking ecological and hydrological field data with high resolution topographic data. Application of semi-empirical hydrological metrics, reflecting climate, topographic conditions and surface/near surface hydrological processes, to uncut (high) bog indicated ARB typically develops on uncut peatlands with slopes of between 0.2% and 0.6%, depending on effective rainfall; in more localised focused-flow flushes ARB may occur on slopes exceeding 1%. Locating topographically suitable high bog areas, currently lacking ARB, permitted identification of degraded raised bog (DRB), i.e. zones capable of regenerating to ARB. Across the SAC network modelling suggested DRB coverage is 1555ha, although not all may be restorable by tried-and-tested restoration technologies. Hydrological modelling has permitted identification of areas where restoration efforts may be focused for maximum benefit. On the other hand the approach has also highlighted the inability of restoration measures on high bog alone to meet the current shortfall in ARB and the requirement to consider additional approaches to restoration.

Classification of natural flow regimes in Poland

AbstractHydrological classifications are aimed at simplifying spatiotemporal variability of flow regimes and, secondly, at supporting environmental flow management. The objective of this study was to perform classification of natural flow regimes in Poland using an inductive approach based on a set of hydrological metrics (HMs) and to develop a model for prediction of class membership based on a set of environmental variables (EVs). A set of 147 gauges with unmodified flow regimes was identified, and for each gauge, values of 73 HMs and 28 EVs were computed. Classification was performed using k‐means and k‐medoids techniques, based on 4 principal components explaining 73.4% of variability in HMs. Out of 7 distinguished classes, 4 (P1–P4) were spread across the Polish Plain, 1 (U5) was restricted to uplands, and 2 (M6 and M7) to mountains. The between‐class differences in HMs and EVs were generally high, although classes P1 and P3 were not easily distinguishable. Mean predictive accuracy of the developed random forest model was 79%, which is high compared to other studies of this type. The lowest accuracies (0 and 50%) were achieved by 2 classes with the lowest counts. Variables representing diverse aspects: hydrography, climate, topography, and geology had the highest importance in the random forest model. Future research can benefit from the database of selected gauges with computed HMs, EVs, and assigned classes, freely available through a long‐lasting data repository. With this study, the first step towards application of the ELOHA framework for environmental flow management at regional scale has been achieved.

Evaluating species-specific changes in hydrologic regimes: an iterative approach for salmonids in the Greater Yellowstone Area (USA)

Despite the importance of hydrologic regimes to the phenology, demography, and abundance of fishes such as salmonids, there have been surprisingly few syntheses that holistically assess regional, species-specific trends in hydrologic regimes within a framework of climate change. Here, we consider hydrologic regimes within the Greater Yellowstone Area in the Rocky Mountains of western North America to evaluate changes in hydrologic metrics anticipated to affect salmonids, a group of fishes with high regional ecological and socioeconomic value. Our analyses assessed trends across different sites and time periods (1930–, 1950–, and 1970–2015) as means to evaluate spatial and temporal shifts. Consistent patterns emerged from our analyses indicating substantial shifts to (1) earlier peak discharge events; (2) reductions of summer minimum streamflows; (3) declines in the duration of river ice; and (4) decreases in total volume of water. We found accelerated trends in hydrologic change for the 1970–2015 period, with an average peak discharge 7.5 days earlier, 27.5% decline in summer minimum streamflows, and a 15.6% decline in the annual total volume of water (1 October–September 30) across sites. We did observe considerable variability in magnitude of change across sites, suggesting different levels of vulnerability to a changing climate. Our analyses provide an iterative means for assessing climate predictions and an important step in identifying the climate resilience of landscapes.

A Histogram Comparison Approach for Assessing Hydrologic Regime Alteration

AbstractThe histogram comparison approach (HCA) is proposed to assess the alteration of hydrologic regimes, which are characterized by the hydrologic metrics, for example, the indicators of hydrologic alteration. The HCA method considers alterations within the whole range of the hydrologic regime and estimates the alteration degree by comparing the pre‐impact and post‐impact histograms. A key parameter of the HCA method is the similarity degree, which considers both the class‐by‐class and cross‐class information of histograms and reflects how many features of the pre‐impact histogram remain in the post‐impact histogram. The alteration degree is defined as the mathematical maximum similarity degree, that is, 100%, subtracted by the actual similarity degree in the HCA method. Comparing the HCA method to the existing range of variability approach and histogram matching approach through theoretical analysis and case studies, the HCA method can eliminate some limitations of the range of variability approach and histogram matching approach methods and can more accurately and effectively assess the hydrologic regime alteration. The Ob and Yangtze Rivers, which are located in different climatic zones, are used as case studies. Hydrologic regime alterations impacted by reservoirs with different regulation abilities (daily, seasonally and yearly) were assessed using the HCA method, the results of which verified its rationality and practicability. More sites with a wider range of flow variations will be examined in the future to assess the applicability of the HCA method. Copyright © 2017 John Wiley &amp; Sons, Ltd.

Featured Collection Introduction: North Carolina Ecological Flows

Featured Collection Introduction: North Carolina Ecological Flows

Biological relevance of streamflow metrics: regional and national perspectives

AbstractProtecting the health of streams and rivers requires identifying ecologically significant attributes of the natural flow regime. Streamflow regimes are routinely quantified using a plethora of hydrologic metrics (HMs), most of which have unknown relevance to biological communities. At regional and national scales, we evaluated which of 509 commonly used HMs were associated with biological indicators of fish and invertebrate community integrity. We quantified alteration of each HM by using statistical models to predict site-specific natural baseline values for each of 728 sites across the USA where streamflow monitoring data were available concurrent with assessments of invertebrate or fish community integrity. We then ranked HMs according to their individual association with biological integrity based on random forest models that included HMs and other relevant covariates, such as land cover and stream chemistry. HMs were generally the most important predictors of biological integrity relative to ...

Predictability and selection of hydrologic metrics in riverine ecohydrology

AbstractThe natural flow regime is critical to the health of riverine ecosystems. Many hydrologic metrics (HMs) have been developed to describe natural flow regimes, quantify flow alteration, and provide the hydrologic foundation for the development of environmental flow standards. Many applications require the use of models to predict expected natural values of HMs from basin characteristics at sites with no observed records of unimpaired flows. However, the error associated with HM estimation has not been evaluated. The primary goal of our study was to provide guidance for river scientists and managers in the selection, use, and interpretation of HMs for stream classification and hydroecological investigations of river ecosystems. We evaluated the predictability of a broad suite of HMs for the conterminous USA based on random forest statistical models. We also examined how the predictability of metrics varied among unique components of the flow regime. Roughly 40% of 612 HMs we examined could be predict...

Using Natural Variability as a Baseline to Evaluate the Performance of Bias Correction Methods in Hydrological Climate Change Impact Studies

Abstract Postprocessing of climate model outputs is usually performed to remove biases prior to performing climate change impact studies. The evaluation of the performance of bias correction methods is routinely done by comparing postprocessed outputs to observed data. However, such an approach does not take into account the inherent uncertainty linked to natural climate variability and may end up recommending unnecessary complex postprocessing methods. This study evaluates the performance of bias correction methods using natural variability as a baseline. This baseline implies that any bias between model simulations and observations is only significant if it is larger than the natural climate variability. Four bias correction methods are evaluated with respect to reproducing a set of climatic and hydrological statistics. When using natural variability as a baseline, complex bias correction methods still outperform the simplest ones for precipitation and temperature time series, although the differences are much smaller than in all previous studies. However, after driving a hydrological model using the bias-corrected precipitation and temperature, all bias correction methods perform similarly with respect to reproducing 46 hydrological metrics over two watersheds in different climatic zones. The sophisticated distribution mapping correction methods show little advantage over the simplest scaling method. The main conclusion is that simple bias correction methods appear to be just as good as other more complex methods for hydrological climate change impact studies. While sophisticated methods may appear more theoretically sound, this additional complexity appears to be unjustified in hydrological impact studies when taking into account the uncertainty linked to natural climate variability.

Probabilistic Inference Coupled with Possibilistic Reasoning for Robust Estimation of Hydrologic Parameters and Piecewise Characterization of Interactive Uncertainties

AbstractThis paper presents a factorial possibilistic–probabilistic inference (FPI) framework for estimation of hydrologic parameters and characterization of interactive uncertainties. FPI is capable of incorporating expert knowledge into the parameter adjustment procedure for enhancing the understanding of the nature of the calibration problem. As a component of the FPI framework, a Monte Carlo–based fractional fuzzy–factorial analysis (MFA) method is also proposed to identify the best parameter set and its underlying probability distributions in a fuzzy probability space. Factorial analysis of variance (ANOVA) coupled with its multivariate extensions are performed to explore potential interactions among model parameters and among hydrological metrics in a systematic manner. The proposed methodology is applied to the Xiangxi River watershed by using the conceptual hydrological model (HYMOD) to demonstrate its validity and applicability. Results reveal that MFA is capable of deriving probability density functions (PDFs) of hydrologic model parameters. Moreover, the sequential inferences derived from the F test and its multivariate approximations disclose the statistical significance of parametric interactions affecting individual and multiple hydrological metrics, respectively. The findings presented here indicate that parametric interactions are complex in a fuzzy stochastic environment, and the magnitude and direction of interaction effects vary in different regions of the parameter space as well as vary temporally because of the dynamic behavior of hydrologic systems.

Linking the Budyko framework and the Dunne diagram

The spatial and temporal heterogeneity of climate, soils, topography and vegetation control the water and energy balances among catchments. Two well-known hydrological theories underpinning these processes are the Budyko framework and the Dunne diagram. Relating the scaling of water–energy balances (Budyko) and runoff generation mechanisms (Dunne) raises some important catchment comparison questions, namely: (i) how do streamflow characteristics vary according to the annual water and energy balances?; (ii) to what extent do biophysical drivers of runoff explain the observed streamflow variability?; and (iii) are there quantifiable process overlaps between these two approaches, and can they offer insights into the mechanics of catchment co-evolution? This study addresses these questions by analysing daily streamflow and precipitation time series data to quantify hydrological similarity across 355 catchments located along a tropical–temperate climatic gradient in eastern Australia. We used eight hydrological metrics to describe the hydrological response over a 33-year period (1980–2013). Hierarchical cluster, ordination analysis, the Budyko framework, and generalized additive models were used to evaluate hydrological similarity, extract the dominant response, and examine how the landscape and climatic characteristics of catchments influence the dominant streamflow response. The catchments were classified into five clusters based on the analysis of their hydrological characteristics and similarity, which vary along the annual water and energy balances gradient in the Budyko framework. Furthermore, we show that the streamflow similarity is explained by six catchment-specific biophysical factors that overlap with those described by the Dunne diagram for runoff generation, which in this case have the following order of relative importance: (i) Dryness Index; (ii) Fraction of Photosynthetically Active Radiation; (iii) Saturated Hydraulic Conductivity; (iv) Soil Depth; (v) Maximum Slope and (vi) Fraction of Woody Vegetation Cover. The research advances our understanding of the role of biophysical controls on hydrologic similarity and formal process links between the Budyko Framework and Dunne diagram of runoff mechanisms.

Development of large scale inland flood scenarios for disaster response planning based on spatial/temporal conditional probability analysis

Extreme event scenarios are useful for civil emergency services to help in developing contingency plans for responding effectively to major flooding incidents. In the UK, the official national risk register includes a scenario for inland flooding (from rivers and other sources), which is described in terms of a probability of occurrence over a five year period of between 1 in 200 and 1 in 20. This scenario was previously based on recent extreme floods, in conjunction with maps produced to aid in development planning on floodplains. At the time it was constructed, it was not feasible to assess scientifically the combined probability of a nationally-significant flood event of this type, therefore the scenario probability assessment was ambiguous. Recent developments in multivariate extreme value statistics now allow the probability of large scale flood events to be assessed with reference to hydrological summary statistics or impact metrics. Building on theory and pilot studies by Heffernan and Tawn [1], Lamb et al. [2] and Keef et al. [3], we describe the development of a set of national-scale scenarios based on a high-dimensional (ca. 1,100 locations) conditional probability analysis of extreme river flows and rainfall. The methodology provides a theoretically justified basis for extrapolation into the joint tail of the distribution of these variables, which is then used to simulate extreme events with associated probabilities. The probabilistic events are compared with current understanding of meteorological scenarios associated with significant, large-scale flooding in the UK, and with historical flooding, in order to identify plausible events that can inform national risk scenarios. Additionally, we combined scenarios of inland and coastal extremes that have been considered by linking the analysis discussed in this paper with methods presented in a companion paper by Wyncoll et al.

Low Flow Response Surfaces for Drought Decision Support: A Case Study from the UK

Droughts are complex natural hazards, and planning future management is complicated by the difficulty of projecting future drought and low flow conditions. This paper demonstrates the use of a response surface approach to explore the hydrological behavior of catchments under a range of possible future conditions. Choosing appropriate hydrological metrics ensures that the response surfaces are relevant to decision-making. Examples from two contrasting English catchments show how low flows in different catchments respond to changes in rainfall and temperature. In an upland western catchment, the Mint, low flows respond most to rainfall and temperature changes in summer, but in the groundwater dominated catchment of the Thet, changes in spring rainfall have the biggest impact on summer flows. Response surfaces are useful for understanding long-term changes, such as those projected in climate projections, but they may also prove useful in drought event management, where possible future conditions can be plotted onto the surface to understand the range of conditions the manager faces. Developing effective response surfaces requires considerable involvement and learning from catchment decision-makers at an early stage, and this should be considered in any planned application.

Recurrence intervals of spatially simulated hydrologic metrics for restoration of Cape Sable seaside sparrow (Ammodramus maritimus mirabilis) habitat

Marl prairie, a diverse graminoid-dominated freshwater vegetation community in the Florida Everglades, provides a specialized niche for the federally endangered Cape Sable seaside sparrow (CSSS). This paper describes a regional habitat suitability modeling approach to evaluating how changes in management from Everglades restoration may affect the CSSS. The Cape Sable Seaside Sparrow Marl Prairie Indicator (CSSSMarlPrairie) is a spatially explicit model that integrates frequency (return periods) of target hydrologic conditions to simulate the anticipated response of marl prairie CSSS habitats to fluxing hydropatterns resulting from restoration projects, water management operations, and climatic change. The model integrates CSSS field survey data with the hydrologic targets at the resolution of the hydrologic simulation model (in this case, the Regional Simulation Model). The application of return periods for hydrologic events provides a novel approach for simulation of anticipated marl prairie responses in the southern Everglades and is readily applicable to evaluating targets of modeled wetland restoration scenarios elsewhere. CSSSMarlPrairie is intended to be used for decision support, in association with a suite of ecological models for additional species of management concern, to facilitate planning of ecosystem restoration projects such as those in the Comprehensive Everglades Restoration Plan and recovery of the marl prairie habitats of the CSSS. A tentatively selected restoration plan for the central Everglades is projected to have mostly minor overall impacts to marl prairie CSSS habitats. Local substantial habitat shifts in and adjacent to designated habitat boundaries have been identified, however, that warrant management consideration.