Estimating the Water Requirements for Plants of Floodplain Wetlands

elationships is so imperfect, it is unlikely that a single water regimedescription will relate to a single vegetation condition description.Rather, it is likely that several different water regimes (expressed astolerance ranges) will, to the best of our predictive ability, result in thesame vegetation condition.Instead of using relationships in an optimising manner (what waterregime is needed to achieve a specific vegetation condition) it is morerealistic to use them in a simulation manner. Simulation, or scenariotesting,asks: “If this is the water regime, then what is the vegetationlikely to be?” Or even “If no plan it put in place, then will the vegetationbe the same?” (Note 39). Determining the water regime to achieve avegetation target by simulation necessarily requires iteration. Themodelling described in this section is all simulation.The results of a simulation describe the expected vegetation patterns(spatial and or temporal) under a particular water regime. Simulationsmay be undertaken for the historical climate conditions with changedwater management scenarios, or for stochastic climate conditionsunder a range of water management scenarios. Stochastic climateconditions are generated based on the statistical properties of thehistoric record, and therefore represent ‘typical’ climatic sequences.These are neither forecasts nor projections. As well as watermanagementscenarios, climate-change scenarios may be of interest.These may include changes in rainfall amounts, rainfall variability, ortemperature, and humidity changes that will alter evapotranspiration.Climate change scenarios are investigated by modifying the climateinput data, either the historic climate data, or the stochasticallygenerated climate data. Climate- and water-management changescenarios may of course be combined to investigate the likely range ofwetland vegetation outcomes for different possible futures.Note 39The ‘do-nothing’ optionThe ‘do-nothing’ option is just asimportant a scenario in decisionmakingas all the other flowmanagement options, and shouldhave equal treatment.The do-nothing option describeswhat the vegetation is likely to be,based on current trends.It can be explored using hydrologicsimulations, trend analysis or justvegetation data transitionprobabilities, such as Markov chains.This is a specialised area of dataanalysis.The approaches to modelling vegetation response can be categorisedaccording to how the water regime is modelled and the nature of thevegetation–hydrology relationships. Depending on the nature of therelationships, predictions may include the pattern of temporal changesin vegetation at a ‘point’ under given water regimes, the static spatialpattern of vegetation at some future ‘equilibrium’ condition, or a morecomplex combination of the spatial and temporal dynamics of thewetland vegetation under different water regimes. Four categories areused below to describe the major differences in modelling.Category 1: hydrologic/expert opinionApproaches in this category rely on hydrologic modelling (waterbalance) of the water regime, and vegetation–hydrology relationshipsderived from expert opinion. Relationships of this type may bequalitative and stated as logic rules, as in expert systems, may usequantitative but non-dimensional representations such as index values,or may use quantitative empirical relationships or ‘rules of thumb’ basedon experience.Although approaches in this category are the simplest, there is aconsiderable range in their complexity because of the different levels ofspatial detail used in hydrology modelling, and to the range incomplexity of expert-derived relationships.Section 7: Predicting Vegetation Responses 85