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Hydrogeosphere Modelling for Innovative Watershed Planning and Management

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Hydrogeosphere Modelling for Innovative Watershed Planning and Management HydroGeoSphere Modelling for Innovative Watershed Planning and Management Owen Steele | Ducks Unlimited Canada Mason Marchildon | Oak Ridges Moraine Groundwater Program Latornell 2017 Our Roots • Canada’s largest conservation organization, founded in 1938 • 6.4 million wetland acres conserved nationally with 947,785 secured provincially. • Over 3,600 wetland conservation projects provincially, providing wetland and waterfowl habitat. Our Growth • Waterfowl • Biodiversity • Species at risk • Natural Green Infrastructure o surface water quality o flood attenuation o groundwater recharge o carbon sequestration Our Direction • Increased policy support for both protecting and restoring wetlands • Incorporating wetlands and wetland restoration planning into land use planning • Designated infrastructure funding for wetland restoration • Engaging in more science to inform restoration investment and effort Wetland modelling Water quality Wetland Residence “hydrologic function” time Water quantity Flow Hydroperiod attenuation Today’s presentation will focus specifically on watershed hydrology, and modelling wetlands and the role they play in peak flow attenuation. “Does the presence of wetlands help mitigate floods?” Characteristics of a “Wetland” 1. Predominance of water near or above ground surface 2. Hydric soil conditions that differ from adjacent non-wetland areas 3. Vegetation specifically adapted to wet conditions Maltby and Acreman (2011) Groundwater-wetland interaction Discharge regime Recharge regime (water gained from the GW system) (water lost to the GW system) Hayashi and Rosenberg (2002) Why is groundwater important? Discharge regime: reduced storage capacity upwelling Why is groundwater important? Recharge (dry) regime: increased absorptivity recharge A dynamic interaction • Groundwater-wetland interaction is “bi-directional” • In time: Rosenberry and Winter (1997) observed “flow reversals” • In space: discharge and recharge can occur simultaneously at different locations within the same wetland (Roulet, 1990) Many others have acknowledged/recognized the dynamic nature of groundwater-wetland relationships, flow reversals, bi-directionality, etc: Hammer and Kadlec, 1986; Gilvear et.al., 1993; Restrepo et.al., 1998; McKillop et.al., 1999; Metcalfe and Buttle, 1999; Brassard et.al., 2000; Mansell et.al., 2000; Price and Waddington, 2000; Vining, 2002; Crowe et.al., 2004; Thompson et.al., 2004; Krause and Bronstert, 2005; Sun et.al., 2006; Acreman and Miller, 2007; Dietrich et.al., 2007; Kazezyilmaz-Alhan et.al., 2007; Jolly et.al., 2008; Hattermann et.al., 2008; Kazezyelmaz-Alhan and Medina Jr., 2008; Gasca and Ross, 2009; Thompson et.al., 2009; Maltby and Acreman, 2011; McLaughlin and Cohen, 2013; Golden et.al., 2014; Charbonneau and Bradford, 2016; Rahman et.al., 2016. Context WETLAND-centric Gauged outlet WATERSHED-centric Past modelling efforts: traditional models • Most wetland modelling employed existing codes: • SWAT (Wang et.al., 2008; Feng et.al., 2013; Evenson et.al., 2015; Rahman et.al., 2016; Rahman et.al., 2016) • PRMS (Vining, 2002) • SWMM (Charbonneau and Bradford, 2016) • SWIM (Hattermann et.al., 2008) • Others have created their own model codes: (Hammer and Kadlec, 1986; Ogawa and Male, 1986; Wynn and Liehr, 2001; Mansell et.al., 2000; Sun et.al., 1998) Past modelling efforts: traditional models • All these models are “hydrological” in the sense that they fail to incorporate a dynamic groundwater-wetland interaction. • Many of the models require modification to incorporate wetland function, otherwise, • Modellers have to apply a “creative use of the model outputs” (Francesconi et.al., 2016) Past modelling efforts: traditional models • These models historically used for flood forecasting • Meant for predicting flow at a gauge ( ) • Does not matter how water got to the gauge, only that it matches the observed Gauged outlet Past modelling efforts: traditional models • These models historically used for flood forecasting • Meant for predicting flow at a gauge ( ) • Does not matter how water got to the gauge, only that it matches the observed • All wetlands are aggregated into one super wetland Gauged outlet Past modelling efforts: common assumptions • Wetlands are “de-spatialized,” neglecting the importance of location and proximity (Rosenberry and Winter, 1997; Mitsch and Gosselink, 2000; Golden et.al., 2014) • Unidirectional exchange, perched conditions/no vertical seepage (Hammer and Kadlec, 1986; Mansell et.al., 2000; Wynn and Liehr, 2001; Wang et.al., 2008; Kazezyelmaz-Alhan and Medina Jr., 2008; Feng et.al., 2013; Evenson et.al., 2015; Rahman et.al., 2016) • Wetlands are treated conceptually similar to impervious areas (Wang et.al., 2008 – HEW) • Wetlands modelled as flow diversions/partitioned into “open” and “closed” portions (Wang et.al., 2008 – HEW) Past modelling efforts: common assumptions • Wetlands represented as system drains, from the groundwater model perspective (Restrepo et.al., 1998) • Wetland function assumed to be identical and linearly additive. • Average/steady-state groundwater table (Hattermann et.al., 2008; Ameli and Creed, 2017) • Prescribed groundwater discharge assumes an infinite aquifer source (as noted by Acreman and Miller, 2007) • Negligible net groundwater influence (Mansell et.al., 2000) Past modelling efforts: common assumptions • Groundwater system can be represented as a single-layer/2D unconfined system, with an impervious bottom (Sun et.al., 1998; Charbonneau and Bradford, 2016; Rahman et.al., 2016; Ameli and Creed, 2017) • Pre-defined, constant contributing area (Evenson et.al., 2015) • Wetlands represented as ponds with a constant surface area (Evenson et.al., 2015) • No lateral seepage (Evenson et.al., 2015) Wetland modelling: is there an alternative? discretization “distributed” model Wetland modelling: comparison Traditional Distributed, Integrated vs. • Requires extra parameterization • NONE – wetlands are emergent!! • Contributing area • Can disregard all those assumptions • Stage-storage-discharge relationships • Storage capacity • Transfer functions • Require code modification • Models can be used out-of-the-box • Aggregation of wetlands and their • Wetlands modelled independently function • Pre-defined seepage rate or • Explicit representation of the groundwater discharge rates that groundwater system must remain constant Calibration has little-to-no value (with respect to modelling aggregate wetland function at the watershed scale) “Satisfactory calibration of a model, such as closure of the water balance, does not guarantee that the conceptual understanding is correct; rather it confirms that the conceptual understanding is plausible.” (Acreman and Miller, 2007) “…differences in model performance as measured by standard performance criteria metrics should not be applied to evaluate the absolute utility of model revisions. Performance criteria metrics … are intended to evaluate a model’s capacity to predict streamflow values – not the model’s capacity to accurately represent hydrologic processes within a system…” (Evenson et.al., 2015) Why the resistance? Acreman and Miller, 2007 blames large effort on the seldom use of integrated, process-based distributed models, for example: 1. Surface water/groundwater interaction too hard to model (Price and Waddington, 2000) 2. Require high expertise (Golden et.al., 2014; Ameli and Creed, 2017) 3. High computation requirements (Ameli and Creed, 2017) 4. Difficult to represent individual wetlands at the watershed scale (Rahman et.al., 2016) 5. Heavy data requirements (Golden et.al., 2014) Wetland modelling of the Credit River Watershed • 950 km² watershed • 4,063 identified wetlands, covering 79 km² • 1,370 km mapped drainage features • 30% agriculture, 29% developed Wetland modelling of the Credit River Watershed • Built using HydroGeoSphere • Fully integrated, process- based, distributed • 164,781 elements x 17 layers • All wetlands (>4,000) and all stream reaches represented independently • Hydrogeology adapted from existing Source Water Protection model Wetland modelling of the Credit River Watershed Wetland modelling of the Credit River Watershed Experiment: dynamic wetlands? The model can be run year round to capture seasonal saturation levels. Experiment: flow reversal is apparent As saturation decreases, the number of wetlands originally discharging decreases, as the function reverts to a recharging regime. Wetland function is dependent on seasonality. Experiment: flow reversal is apparent Spring freshet Experiment: flow reversal is apparent Winter or early summer Experiment: flow reversal is apparent Mid summer or fall Experiment: flow reversal is apparent Mid summer Experiment: flow reversal is apparent Late summer Conclusions We need to move forward and learn from the past • Traditional modelling attempts have been upfront in their limitations. • Wetlands in southern Ontario are dynamic groundwater dependent ecosystems, and thus must be treated so. • Wetland attenuation depends on antecedent conditions which depend on the groundwater system. • Proper tools that alleviate the issues are available today. • With these tools, wetlands become an emergent property, not pre-defined by the modeller. • Tendency to require heavy data requirements… Conclusions • ORMGP model custodianship program • Funded by the regions of York, Peel, Durham, and Toronto • 58 models with peer-reviewed hydrostratigraphy • From the Credit River through Lower Trent • All available upon request Thank you Owen Steele Head of Conservation
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