River forcing at work: ecological modeling of prograding and regressivedeltas

1, 2 3 4 4*Enrique Reyes , Jay F. Martin , John W. Day , G. Paul Kemp and Hassan Mashriqui1 2Coastal Ecology Institute, Louisiana State University, Baton Rouge, LA 70803, USA; Department of Food,

3Agricultural and Biological Engineering, Ohio State University, Columbus, OH 43210-1057, USA; CoastalEcology Institute and Department of Oceanography and Coastal Sciences, Louisiana State University, Baton

4Rouge, LA 70803, USA; Special Programs, School of the Coast and Environment, Louisiana State*University, Baton Rouge, LA 70803, USA; Author for correspondence (e-mail: ereyes@lsu.edu; phone:

11-225-578 2734; fax: 11-225-578 6326)

Received 24 August 2001; accepted in revised form 26 September 2002

Key words: Atchafalaya river, Coastal land loss, Delta growth, Landscape modeling, Louisiana, Mississippi river,Sea level rise

Abstract

Two explicit landscape simulation models were used to investigate habitat shifts in coastal Louisiana due tovarying river forcing and sea level rise scenarios. Wetland conversion to open water and yearly shifts of marshhabitats in two contrasting estuarine regions were examined; the Atchafalaya delta which is a prograding delta areawith strong riverine input, and the Barataria Basin is a regressive delta with high wetland loss which is isolatedfrom riverine input. The models linked several modules dynamically across spatial and temporal scales. Bothmodels consisted of a vertically integrated hydrodynamic model coupled with process-based biological modules ofabove and below ground primary productivity and soil dynamics. The models explored future effects of possiblesea level rise and river diversion plans for 30 and 70-year projections starting in 1988. Results showed thatincreased river forcing had large land preservation impacts, and indicated that healthy functioning of theMississippi Delta depends largely on inputs of freshwater, nutrients, and sediments in river water. These types ofmodels are useful for research and as management tools for predicting the effects of regional impacts on structurallandscape level changes.

Introduction 1983; Boesch et al. 1994). Such changes are believedto underlie the general pattern of displacement of

Coastal wetlands across southeastern Louisiana are freshwater vegetation by more salinity tolerant com-being lost as they convert to open water, due to a munities, and vegetation die-off followed by conver-combination of sea level rise and subsidence (Day et sion to open water (Wells 1996; Roberts 1997). Inal. 1997, 2000; Wells 1996). Thus, coastal wetlands contrast, active sediment deposition, when associatedserve as models for the effects of accelerated sea level with river discharge, leads to land progradationrise (Day and Templet 1989). Annual variability in (Roberts 1997). An example of this active land build-mean sea level (MSL) can be several centimeters per ing can be found in the Atchafalaya delta at the mouthyear (Baumann 1980), and can result in increased of the Atchafalaya River (Figure 1).penetration of salinity into wetlands (Penland et al. Most wetlands in the Mississippi Delta estuarine1988). However, penetration of salinity is further complex are losing elevation with respect to MSL atenhanced as these areas naturally sink as the soft variable rates (Penland and Ramsey 1990). Penland etsediments deposited on them by rivers consolidate al. (1996) argued that 46% of the loss could beand compress under their own weight (Hatton et al. attributed to natural causes and about 35% to indirect

103 2004 Kluwer Academic Publishers. Printed in the Netherlands.Wetlands Ecology and Management 12: 103–114, 2004.

Figure 1. The State of Louisiana showing location for the Barataria and Western Basins.

human activities. To examine this problem, we pres- thors calculated that direct causes, such as canalent two contrasting regions: the Barataria Basin and dredging accounted for 12% for the whole Louisianathe region comprised by the wetlands of Vermilion coast. Day et al. (2000) found that only 9.2% of theand Cote Blanche Bays, and the Atchafalaya delta, losses could be directly attributed canal development.here defined as the Western Basins (Figure 1). Coastal However, their regressions showed a wide degree ofland loss rates vary temporally, mean annual land loss spatial variability depending on the amount of canalsrates in Barataria and the Western Basins for three present. Indirect losses also vary spatially, Reeddifferent periods are presented in Table 1, with a (1995) estimated that indirect land loss due to canal

2 2mean for all periods of 22.63 km and 2.87 km , dredging alone could account for more than 30% inrespectively (Britsch and Dunbar 1993). These au- Barataria. These figures indicate that local anthro-

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Table 1. Annual loss rates for three different periods in the Western Bays and Barataria Basins.

Interval Western Bays Barataria2 21 2 21(km yr ) (km yr )

1931–1956 2.41 7a a1956–1978 3.41 3.3 16 21.55 25.50b b1978–1988 2.57 4.4 0.8 19 35.40 27.11

Source: Britsch and Dunbar (1993) USFWS Martin et al. (2002) Dunbar et al. (1992) USFWS Reyes et al. (2000)a bNote: 1956–74 and 1983–1990 intervals.

pogenic modifications have had different effects in sive wetlands in each basin, which range from fresh-each basin making it difficult to assess changes on a water forested wetlands and marshes in the upperregional basis. basins to brackish and saline marshes near the coast.

Understanding these habitat changes is critical to Both basins are dynamic systems undergoingassess the long-term effects of evolving forcing func- change due to natural and human processes. Thetions (e.g., river discharge, sea level rise) on restora- Barataria basin has been isolated from direct rivertion approaches. The objectives of this study were to inflow since 1904. Precipitation provides its main(1) construct a multiple scale process model for the source of freshwater (Wiseman et al. 1990a, 1990b);Barataria and the Western Basins to understand and however, the Mississippi River exerts an indirectpredict regional habitat change and (2) assess wetland influence on salinity in the lower basin by reducingresponse to long-term indirect and cumulative impacts salinity in the nearshore Gulf of Mexico (Perret et al.of different river water contributions. 1971; Fuller et al. 1995). This area has experienced a

Coastal habitat evolution has been addressed using dramatic wetland loss over the last five decades, with2spatially articulated landscape models under diverse about 22% (788 km ) lost (Fuller et al. 1995). The

scenarios for nearly two decades (Sklar et al. 1985; Western Bays basins are directly influenced by dis-Costanza et al. 1990; White 1991; White et al. 1991; charge of the Atchafalaya River (Roberts et al. 1980;Reyes et al. 1994; Martin et al. 2000; Reyes et al. Penland and Ramsey 1990; Roberts 1997). As a2000). These dynamic spatial interaction models in- result, a new delta is forming in Atchafalaya Bay andcorporate location-specific algorithms that allow feed- this area is one of the few locations in southernback between the local processes and landscape dy- Louisiana that has experienced net land gain (Robertsnamics, so that both the landscape and the intensity of and van Heerden 1992; Boesch et al. 1994).the processes affecting it change through time(Boumans and Sklar 1990). Previously, we haveexamined historical conditions and management alter- Methodsnatives for Barataria and the Western basins (Reyes etal. 2000; Martin et al. 2002). In this paper, we present A landscape habitat simulation model was built forthe results of varying the environmental functions, each region. Each is a dynamic spatial model withnamely river discharge and sea level rise, and their variable time and spatial scales, using a finite differ-long-term effects on these two different regions. ence, 2-dimensional, vertically integrated hydrologic

module coupled to a primary productivity module.Output from the hydrodynamic and productivity mod-

Study area ules is submitted to a soil module and then evaluatedby a habitat-switching algorithm that redefines the

The Barataria coastal basin is an estuarine-wetland habitat mosaic on a biannual basis. Specific details forsystem located between the natural levees of the the modules and their interactions have been docu-Mississippi River and Bayou Lafourche. It is roughly mented previously (White et al. 1997; Martin 2000;

2triangular in shape with an area of 6100 km . The Reyes et al. 2000).Western Basins are bordered by Freshwater Bayou on Forcing functions to the models consist of historicalthe west and the Atchafalaya River on the east and data series spanning 1956 through 1995 that include

2occupies about 6765 km (Figure 1). There are exten- climatic variables (precipitation, wind, temperature),

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river flow and sediment concentration, relative sea- iteratively until the model results matched historicallevel rise (RSLR-comprised of subsidence and eus- conditions (i.e., the 1988 habitat map), thereforetatic sea-level rise), tides and salinity. implicitly incorporating those local processes that

might have regional effects.Calibration The resulting maps for the calibration are presented

in Figure 2 for both the Barataria Basin Model (BBM)Both models were calibrated by comparing results and the Western Basins Model (WBM). A usefulagainst historical conditions. The models were run for estimate of habitat agreement is how well the simu-1978 to 1987 using habitat classified U.S. Fisheries & lated landscape agrees with the actual landscape mapWildlife Service (USFWS) maps for initial conditions in terms of overall wetland and water areas. In thisand final spatial comparison. These maps were ob- case, total wetland area is the sum of marsh andtained as rasterized images (USGS National Wetlands swamp. The percent disagreement was 3% for BBMResearch Center 1999), and aggregated into five and 2% for WBM. The model has also to reproducerepresentative habitats (Table 2). the spatial distribution of the different habitat types.

This calibration exercise examined how much the Therefore, we evaluated how well the model wasmodeled ecological processes across the landscape calibrated by comparing the habitat agreement of thecompensated for the land loss processes not modeled, simulated and real maps using a goodness of fit thatbut implicit in the real landscape dynamics. Large- compared the spatial pattern of habitat cells at multi-scale dynamics performed by this landscape model, ple resolutions (Costanza 1989). This analysis gave ado not explicitly incorporate local processes (e.g., value above 85 for both basins (Martin 2000; Reyes etcanals and spoilbanks). The calibration was done al. 2000) out of 0 (no match) to 100 (perfect match).

Table 2. Summary of scenario results performed in each basin.2Resulting habitat coverage (km )

Scenario Intermediate Fresh Swamp Brackish Salt Open Calibrationname marsh marsh marsh marsh water fit

Western Basins 1988 USWFS map 219 727 461 674 76 6465Base case

(calibration; 1977–87) 238 737 462 701 77 6407 94.93Normal conditions

(1988–2018) 172 1185 462 442 55 6306(1988–2058) 300 1383 461 152 58 6268

High river forcing(1988–2018) 302 1588 468 110 22 6132 88.64(1988–2058) 216 1793 462 79 30 6042 86.84

No river forcing(1988–2018) 289 1159 465 301 53 6355 92.39(1988–2058) 225 1264 460 50 58 6565 89.25

Twice SLR rate(1988–2018) 289 1264 465 196 53 6355 91.67(1988–2058) 225 1263 460 50 58 6566 88.06

Barataria Basin 1988 USWFS map 755 1022 734 460 2952Base case

(calibration; 1977–87) 723 1002 722 634 2854 89.32Normal conditions

(1988–2018) 396 1017 236 217 4057High river forcing

(1988–2018) 1022 1022 293 159 3427 85.63Low river

(1988–2018) 612 1022 567 389 3335 76.74Twice SLR rate

(1988–2018) 240 1014 150 200 4319 94.77

Notes: USWFS 5 U.S. Wildlife & Fisheries Service; SLR 5 sea level rise. Fit values for Base Case scenarios were computed against 1988USWFS habitat map. Fit values for river forcing options were computed against the 2018 normal conditions habitat map.

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Figure 2. Habitat classified USFWS maps for 1988 and resulting maps from the calibration exercise.

Comparisons of maps produced for the same area and each basin (a 70-year prediction is also presented fortime periods by Chabreck and colleagues (1968; the WBM). To run simulations into the future, theo-Chabreck and Linscombe 1978) and the USFWS retical time series and boundary conditions needed tohabitat classification (USGS National Wetlands Re- be chosen. We repeated the original time series insearch Center 1999) indicated a disagreement of 7%, reverse order, as climate tends to be cyclic (Thomsonindicating that matches with the goodness of fit 1995). The forcing functions and boundary conditionsroutine greater than 93% were within the error of are actual data for years 1955–1992, but when themapping (Fuller et al. 1995). year 1993 was simulated, the climate from 1991 was

used, 1994 simulation used climate from 1990, and soon.

Results The 2018 habitat distribution for the BBM (Figure23) converted an area of 1,105 km to open water from

After accepting the precision of the calibrating for 1988 to 2018 (Table 2), or about 48% of total wetland2both regions, the evolution of the basins, from 1988 to area loss. The largest decline (498 km ) was for

22018, was explored for a series of scenarios (Table 2). brackish marsh, while only 5 km of swamp were lost.The first scenario, referred to as Normal Conditions Spatially, this means that the greatest loss occurred in(NC), simulated a future continuation of current the middle and lower basin where brackish marshtrends. Later simulations are evaluated by comparing dominates, whereas the upper basin, dominated byresults against this NC scenario. swamp habitat, remained relatively unchanged. Time

series for daily inundation, biomass and salinity (c.f.,Normal conditions scenario Figure 9 in Reyes et al. 2000) showed that the land

change in the middle basin was due to increased waterThe NC scenario consisted of a 30-year simulation for level and diminishing plant productivity, while the

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Figure 3. Resulting habitat distribution of Western and Barataria Basins under the Normal Conditions scenario for years 2018 and 2058.

lower basin suffered due to rising sea level and studies and the possibility of increased water flowincreased salinity. through diversions, we considered this a plausible

The WBM study area experienced a 7.4% gain in scenario.wetland during the 30-year NC scenario (9.1% for the For the BBM, the main inflow was through the70-year run), which was due to the expansion of fresh southeastern boundary as the Mississippi River dis-

2marsh coverage (458 km ) associated with the progra- charges to the Gulf. A smaller percentage of the inputdation of the Atchafalaya Delta (Figure 3, Table 2). water, however, gets delivered through smaller diver-The areas around the Atchafalaya Delta sustained sions on the West side of the lower river (the Westtheir original habitat, in contrast with such areas as the Point la Hache and Namoi siphons, see Figure 1).ocean side of Marsh Island that started to break up. Results from this scenario showed that land loss in the

2Although the Atchafalaya River now only carries 30% BBM was reduced by 630 km compared to NCof the total Mississippi River flow (Roberts 1997), (Figure 4). The overall change was a 33% reductionthis forcing caused considerable delta growth and a in wetland loss. The preservation of fresh marsh was

2near stable condition in pre-existing marshes in the largely responsible (626 km ) for this difference, invicinity of the river mouths. contrast to salt marsh which had a 27% decline (58

2km loss) compared to the normal conditions scenarioAdditional river discharge scenario (Table 2).

Historically the Atchafalaya River discharge hasthThis scenario simulated a two-fold increase of river gone from insignificant at the beginning of the 19

water into the basins. Models of global warming century to about 30% of the total flow of the Mis-predict an increase in the discharge of the Mississippi sissippi and Red Rivers at present (Roberts 1997).as a direct result of modifications of the hydrologic This increase in discharge now is coupled with effortscycle (Miller and Russell 1992). Based on these to control flow through the Mississippi River. Simula-

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Figure 4. Resulting habitat distribution of Western and Barataria Basins under the high river discharge scenario for years 2018 and 2058.

tions for the WBM using a doubled Atchafalaya River wetlands were preserved from the NC scenario, and2discharge increased both the water and sediment 92 km more than the Additional River discharge

delivered to the estuary and increased the growth of scenario. Most of these gains were in brackish mar-2the delta by 174 km compared to the NC for the year shes that almost doubled in extension (Table 2),22018 and by 226 km for the year 2058 (Figure 4). By showing, perhaps, a homogeneous influence of water

doubling river input, brackish and salt marshes were conditions for all the landscape. That is, 30 years ofsubjected to freshwater influence and this freshening constant salinity influence and little flooding seem to

2of the habitat resulted in a transformation of 506 km favor salt tolerant communities.into a combination of intermediate, fresh marsh and The scenario for WBM reduced the Atchafalayaopen water across the study area (Table 2). River flow by 0.5, decreasing the growth of the deltas

and increased land loss relative to NC (Figure 5).Restricted river discharge scenario Habitat extension for 2018 was similar to BBM,

brackish and salt marshes coverage was higher thanA restriction of river inputs is exemplified by the with the Increased River Discharge scenario. Thiscurrent situation in the Barataria basin. Since 1904, behavior, however, changed to substantial losses

2Barataria basin has been isolated from direct river (about 300 km ; Table 2) for the year 2058. Reductioninflow where presently a combination of RSLR and of river input increased land loss and salt intrusion toincreasing salinity has led to a drastic loss of wetlands the area resulting in this higher land loss.(Condrey et al. 1995; Day et al. 2000). For an in-creased restriction of river discharge in this basin, a Increased sea level rise scenariolow river discharge year (1964) was used every yearfor 30 years. The results of this low river scenario Future scenarios of coastal areas must consider the

2paint a complex picture (Figure 5). A total of 722 km possibility of an acceleration of sea level rise due to

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Figure 5. Resulting habitat distribution of Western Basins under no flow scenario and Barataria Basin under the low river flow scenario foryears 2018 and 2058.

2global warming. In the previous scenarios the rate 17 km , however, when compared to the Additional21used for eustatic sea level rise was 0.18 cm yr (an River Discharge scenario, as saltwater intrusion

average for the values reported by Gornitz et al. occurred the salt marshes expanded (an increase of 412(1982)). The increased SLR scenario evaluated a rate km ).

21of 0.4 cm yr , double the current rate, but well For the WBM, the same decreasing trend of marshwithin the range of values calculated by several area was observed compared to the NC runs (Figure

2authors (Hoffman 1984; Emery and Aubrey 1991; 6). By 2018 fresh marsh increased to 79 km but atGornitz 1995), and representative of the ‘best guess’ the end of the simulation, there was a net loss of 120

2rates estimated by the IPCC (Houghton et al. 1996). km . Salt marshes, however, kept the same coverage.This rate was applied starting in 1988 and continued When open water extension is compared with theuntil the end of the simulation period. Additional River Discharge scenario, it becomes evi-

2Increasing the SLR rate for both regions resulted in dent how pronounced the fresh (120 km ) and brac-2extensive losses of inland habitats (Table 2). While kish marsh (102 km ) losses can be (Table 2).

for Barataria, the absolute total land loss was of 2622km by 2018; the Western Bays showed a lower loss

2 2of 55 km by 2018 and 298 km by 2058. This Discussionpresents a clear image of the influence of saltwaterintrusion and increased water logging in both basins Sustainable management of the coast should be based(Figure 6). on a sound understanding of the natural functioning of

Overall, fresh and brackish marshes lost from 30 to coastal ecosystems that includes the role of river50% of the area remaining in the Normal Conditions discharge and its subsidy of energy and materialsscenario. Salt marshes in Barataria basin decreased by (Day et al. 1997, 2000). The functioning of coastal

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Figure 6. Resulting habitat distribution of Western and Barataria Basins under the double sea level rise rate scenario for years 2018 and 2058.

wetlands is strongly affected by several energetic water interact through time (Cornell and Karlsonpulsed events (such as floods, storms and tides) which 1997; Peckarsky et al. 1997). The models were notserve to enhance productivity, increase materials flux- sensitive to local factors such as canal dredging, ores, and alter the morphology and evolution of these natural ones like nutria eat-outs or fires (Ludwigsystems (Day et al. 1995a; Hopkinson and Vallino 1999; Nielson 1999).1995; Odum et al. 1995). The importance of river Simulation results showed the importance of riverflood events is increasingly recognized in restoration discharge. Overall, increased river input to bothecology and attempts to reconnect rivers with their basins resulted in net gains or preservation of largenatural floodplains (Day et al. 1995b; Galat et al. areas of marsh. Although the flow alterations pre-1998; Hensel et al. 1998; Molles et al. 1998; Toth et sented here may seem extreme, they do have a histori-al. 1998). cal and future relevance (Miller and Russell 1992).

The principal regional factors driving long-term Simulated reductions in riverine inputs mimic actualtrends in land-loss and habitat change in coastal trends of riverine input, as indicated by the presentLouisiana are (1) sea level rise and subsidence, (2) conditions in Barataria (a total freshwater reduction ofaltered inflows of freshwater and sediments from the about 70%; Reed and Nyman 1995). Manipulations toMississippi and Atchafalaya Rivers, and (3) modi- the river discharge are now occurring in the Westernfications to internal hydrology (Gagliano et al. 1981; Bays area. The Atchafalaya discharge has gone from aBaumann et al. 1986; Salinas et al. 1986; Coleman historical 50% of the total Mississippi River flow1988; Day and Templet 1989; Boumans and Day prior to 1963, when a flood control structure was built,1993; Reed 1995; Day et al. 1997, 2000; Turner to 30% or less depending on flood probabilities (Kes-1997). These landscape models were driven by the sel 1988; Roberts 1997). Compounding these manipu-first two dominant regional processes and were, there- lations of river flow, the amount of sediments reach-fore, sensitive to factors that affect how land and ing the Mississippi is about 75% less than historical

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conditions due to natural and anthropogenic changes and throughput into both basins, restricted freshwater(Kessel 1988, 1989; Cahoon et al. 1995; Reed 1995; inflows, and the rate of land loss increases.Wells 1996; Day et al. 2000; Perez et al. 2000; Stow et Landscape models of this type are one of the fewal. 2001). tools that can be used to predict the effects of complex

We tested the effects of long-term climate changes spatial interactions and cumulative, long-term effectsin both basins. As the climate conditions became of global changes (Costanza et al. 1990; Boesch et al.more extreme (i.e., increased SLR scenario) land loss 1994). The use of these landscape models to evaluateincreased (Table 2). Relatively high rates, on the the interaction of natural processes and human im-

2 21 pacts across regions and investigation cause and effectorder of 30 to 40 km yr are predicted even with therelationships of different climate change predictionshighest river forcing scenarios. The comparisons ofat specific locations, can be a valuable wetland man-the variability of the fit indices in both basins (Tableagement tool.2) suggest that Barataria is more susceptible to habitat

changes (the range of values is larger) than theWestern Bays marshes, which have the influence ofthe Atchafalaya River and are more resistant to

Acknowledgementschanges in weather and river discharge effects.Using the goodness-of-fit index as an indicator of

The Barataria-Terrebonne National Estuary Programbeneficial processes was not straightforward. Lower(BTNEP) through the LA Department of Environ-values only indicate the amount of discrepanciesmental Quality and the New Orleans District of thebetween the resulting map and the NC scenario. BothU.S. Army Corps of Engineers provided financialhigh and low river forcing scenarios had low fit valuessupport for this study. The authors would like tofor both basins, in contrast to the high values for theacknowledge the assistance of the BTNEP and theincreased SLR scenario in the Barataria Basin. TheseWBM Scientific and Technical Committee membersvalues argue for the use of the fit number along with afor their important input in the development of thesevisual interpretation of the resulting map to determinemodels. Our heartfelt thanks to Ms Emily Hyfield forthe net benefits of a management strategy. Theseher assistance editing and proofreading.results along with the NC scenario also indicate that

interannual variability could be responsible for thelargest changes in marsh stability. Accretion, vegeta-tion productivity and sediment inputs alone cannot Referencescompensate for the effects of increased sea-level rise

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