Groundwater-dependent Vegetation Research Articles

Simulating groundwater uptake and hydraulic redistribution by phreatophytes in a high-resolution, coupled subsurface-land surface model

Abstract Several new functions representing groundwater dependent vegetation were incorporated into a coupled subsurface-land surface model, ParFlow.CLM, in order to adequately describe groundwater water uptake, hydraulic redistribution, and plant water stress. The modified model was used to conduct three-dimensional, stand-scale simulations of a Mediterranean oak savanna in California. It performed well and captured daily, hourly and spatial water and energy dynamics, as well as groundwater evapotranspiration rates. The new model was then compared to various approaches, the original ParFlow.CLM and a version using a root water uptake compensation equation. During the dry season, the modified model closely predicted the measured transpiration rate while the original model predicted that it would become zero and the compensation approach overestimated it by nearly double. The modified model also allowed for analysis of several key ecohydrological processes, namely the hydraulic redistribution when plants were both active and dormant, the leaf water potential, and xylem cavitation.

Describing the spatial–temporal dynamics of groundwater-dependent vegetation (GDV): A theoretical methodology

The composition, abundance and age structure of groundwater-dependent vegetation (GDV) are tightly coupled with groundwater level variation. Modeling the space–time dynamics of GDV is valuable for ecosystem conservation and recovery. But there are few modeling frameworks on GDV space–time dynamics. In this study, we propose a stochastic process-based theoretical framework, and develop a Species-specific Theoretical Evolution Model (STEM) to analyze and simulate GDV dynamics.In the model, the groundwater level variation is described as stochastic processes. Based on this method, the temporal dimension of vegetation dynamics is involved. The model focuses on the life cycle of same-aged population and divides this life cycle into two evolution phases. Each phase is formulated with a stochastic differential equation respectively. The solution processes interpret the probability distributions of GDV, and the plot-wised model application in a certain geomorphology area derives different typical distribution patterns for the population abundance and lifespan. The results also reveal the positive effects of water regulations on vegetation restoration.This framework describes the spatial–temporal dynamics of GDV rather than providing a stationary solution. It can adapt to the non-stationarity of groundwater level variations and distinctive sensitivity during the plants life cycle because of the Markov property of stochastic equations. The model can also help to predict vegetation responses under the groundwater level variations.

Changes in foliage projective cover and its implications for mapping groundwater dependent vegetation across a precipitation gradient

AbstractAdequate protection of groundwater dependent vegetation (GDV) at the landscape scale (>104 km2) is often hampered as their extent is poorly mapped. Remote sensing data sets have previously been used to delineate GDV by analysing both actual and changes, in green biomass over space and time. The rationale behind such approaches is based on the phenological characteristics of GDV, which often retain greater mean green biomass during dry periods, in comparison to vegetation with access to soil moisture only. However, such methods are hampered by inadequate knowledge about how average annual precipitation, seasonality, and differing water regimes of vegetation communities within a landscape influence green biomass. Therefore, we aimed to test for amount of foliage projective cover (FPC) and variation in FPC as indicators of GDV presence. We assessed differences in the FPC of GDV at 3 sites across a 1,500 mm−1 year−1 precipitation gradient, ranging from arid inland to humid coastal environments in Southern Queensland, Australia. Overall, we found that average annual precipitation had the largest influence on predicting FPC followed by seasonality. During winter in the semi‐arid and humid environments (season with least precipitation), FPC for non‐GDV was higher than subsurface GDV. For our study area, GDV delineation on the basis of higher green biomass than surrounding vegetation was effective when average annual precipitation was less than ~600 mm−1 year−1.

Large‐scale regional delineation of riparian vegetation in the arid and semi‐arid Pilbara region, WA

AbstractMultiscene Landsat 5 TM imagery, Principal Component Analysis, and the Normalized Difference Vegetation Index were used to produce the first region‐scale map of riparian vegetation for the Pilbara (230,000 km2), Western Australia. Riparian vegetation is an environmentally important habitat in the arid and desert climate of the Pilbara. These habitats are supported by infrequent flow events and in some locations by groundwater discharge. Our analysis suggests that riparian vegetation covers less than 4% of the Pilbara region, whereas almost 10.5% of this area is composed of groundwater dependent vegetation (GDV). GDV is often associated with open water (river pools), providing refugia for a variety of species. GDV has an extremely high ecological value and are often important Indigenous sites. This paper demonstrates how Landsat data calibrated to Top of Atmosphere reflectance can be used to delineate riparian vegetation across 16 Landsat scenes and two Universal Transverse Mercator spatial zones. The proposed method is able to delineate riparian vegetation and GDV, without the need for Bidirectional Reflectance Distribution Function correction. Results were validated using ground truth data from local and regional scale vegetation surveys.

A detection problem: Sensitivity and uncertainty analysis of a land surface temperature approach to detecting dynamics of water use by groundwater-dependent vegetation

Sustainable management of groundwater-dependent vegetation (GDV) requires the accurate identification of GDVs, characterisation of their water use dynamics and an understanding of associated errors. This paper presents sensitivity and uncertainty analyses of one GDV mapping method which uses temperature differences between time-series of modelled and observed land surface temperature (LST) to detect groundwater use by vegetation in a subtropical woodland. Uncertainty in modelled LST was quantified using the Jacobian method with error variances obtained from literature. Groundwater use was inferred where modelled and observed LST were significantly different using a Student's t-test. Modelled LST was most sensitive to low-range wind speeds (<1.5 m s−1), low-range vegetation height (<=0.5 m), and low-range leaf area index (<=0.5 m2 m−2), limiting the detectability of groundwater use by vegetation under such conditions. The model-data approach was well-suited to detection of GDV because model-data errors were lowest for climatic conditions conducive to groundwater use.

Characterising groundwater use by vegetation using a surface energy balance model and satellite observations of land surface temperature

This study presents a novel ‘model-data’ approach to detect groundwater-dependent vegetation (GDV), through differences in modelled and observed land surface temperatures (LST) in space and time. Vegetation groundwater use is inferred where modelled LST exceeds observed LST by more than a threshold determined from consideration of systematic and random errors in model and observations. Modelled LST was derived from a surface energy balance model and LST observations were obtained from Terra-MODIS thermal imagery. The model-data approach, applied in the Condamine River Catchment, Queensland, Australia, identified GDV coincident to existing mapping. GDV were found to use groundwater up to 48% of the time and for as many as 56 consecutive days. Under driest of conditions, groundwater was estimated to contribute up to 0.2 mm h−1 to total ET for GDV. The ability to both detect the location and water-use dynamics of GDV is a significant advancement on previous remote-sensing GDV methods.

Economic returns of groundwater management sustaining an ecosystem service of dust suppression by alkali meadow in Owens Valley, California

This paper addresses the economic tradeoff between pumping groundwater and maintaining a native plant community that provides an ecosystem service of dust suppression. A dynamic ecological economic simulation model was created to assess net benefits of production (i.e., economic rent) from groundwater management while requiring a producer to maintain or restore native groundwater dependent vegetation in a well-field in Owens Valley, California. Historic groundwater withdrawal during dry conditions followed by recharge during wet conditions has reduced vegetation cover, soil stability and contributed to the drying of springs and seeps. Findings indicate adaptive management that pumps less water, but high volumes in wet years and low volumes in dry years, generates greater economic rent while supplying water, sustaining alkali meadow and maintaining dust suppression. Adaptive management generates economic rent of $82.6 million (in 2011 $) compared to status quo management of $30.5 million over 50years pumping less annual groundwater than status quo at respective levels of 73% (6830acre-ft; baseline conditions) and 56% (4952acre-ft; climate change scenario). Under a climate change scenario and a 2.0m root-zone or less, it would be cost effective to cease groundwater pumping rather than incur substantial restoration costs of the native plant community.

Recovery of treeless subalpine vegetation in Kosciuszko National Park after the landscape-scale fire of 2003

The vegetation of fire-prone landscapes is influenced by the frequency, severity, seasonality, return interval and stochastic patterning of fire as well as the responses of its component species. An expected increase in fire frequency and severity in association with global warming may result in compositional changes within, and spatial reorganisation of, plant communities; indeed, some plant communities may even face extinction. Vegetation dominated by fire-sensitive species may be most vulnerable to change in fire frequency. A landscape-scale fire in Kosciuszko National Park in 2003 provided an opportunity to compare recovery in vegetation dominated by resprouters and fire-sensitive, obligate seeders. We hypothesised that if plant assemblages had failed to recover after 10 years in terms of species richness and cover they would have been dominated by seeder species pre-fire. After 10 years, two of the six vegetation types investigated had recovered and these were indeed dominated by resprouter species. Two groundwater-dependent vegetation types (one resprouter-dominated and one dominated by fire-sensitive species) were close to recovery. However, the other two types, non-groundwater-dependent shrublands dominated by both seeder and resprouter species, were still far from recovery at that time, with shrub cover reduced and grass cover increased. The likelihood of recovery after 10 years therefore does not appear to be solely a consequence of the regeneration strategies of the dominant species. Post-fire environmental factors (e.g. grazing, disease, climate) may be just as important as regeneration strategies in determining recovery time. Because not all vegetation had recovered after 10 years, prediction of minimum tolerable fire intervals at a landscape scale is impossible at this time. Future fire management needs to be adaptive, taking into account post-fire influences, rather than prescriptive.

Potential impacts of groundwater conservation measures on catchment-wide vegetation patterns in a future climate

Context In temperate Europe, warming, summer droughts, and increased winter precipitation are predicted to have profound effects on vegetation performance and composition. Especially groundwater dependent vegetation will be affected. These impacts within the landscape may negatively affect the connectivity within ecological networks.

Groundwater nitrogen and the distribution of groundwater-dependent vegetation in riparian areas in agricultural catchments

Eutrophication is a major threat for several species-rich habitat types e.g. fens and meadows in riparian discharge areas throughout Europe, but few data are available to support the supposition that nutrient-contaminated groundwater from agricultural land is the direct cause for the continued decline of these formerly widespread habitat types. In the present study we investigated the role of nitrogen for the distribution of groundwater-dependent vegetation types in discharge areas in Denmark. Specifically we hypothesised (1) that the nitrogen availability in riparian discharge areas is linked to agricultural intensity in the topographic catchment and (2) that the spatial distribution of vegetation in riparian areas is influenced by nitrogen in the groundwater e.g. high productive reed beds dominate in areas with high levels of groundwater nitrogen, whereas species rich fens occur in areas with lower levels of groundwater nitrogen reflecting that incoming nutrients influence the productivity within the areas. We find evidence that the percentage of agriculture in the topographic catchment directly influenced the amount of nitrate in the discharging groundwater in the study areas and that groundwater nitrogen is closely coupled to the distribution of groundwater-dependent vegetation. Meadow and reed bed vegetation being highly productive were associated with higher levels of nitrate in the groundwater compared to low productive rich fen vegetation. From these findings we recommend that protected groundwater-dependent vegetation is mapped in groundwater discharge areas and that only those without presence of protected habitats are considered in rewetting plans to mitigate nutrient loss from agricultural production.

Reprint of: ``Climate change effects on water-dependent ecosystems in south-western Australia'' [J. Hydrol. 434--435 (2012) 95--109

► The effect of future climate scenarios on surface water and groundwater resources was assessed. ► The associated risk to water dependent ecosystems was inferred. ► The greatest impact was projected for a dry future climate scenario. ► Reduction in ecologically significant river flow rates is particularly large. ► Groundwater dependent ecosystems are under high and severe risks over 20% of their current area. The effect of future climate scenarios on surface water and groundwater resources has been shown to have a consequent impact on water-dependent ecosystems. A regional-scale analysis of changes in water resources as a result of changing climate was undertaken in south-western Australia; a region with a large number of nationally and internationally recognised water-dependent ecosystems. The paper examines the potential environmental impacts of a substantial reduction in rainfall and an increase in temperature as projected by global climate models (GCMs) on river and groundwater-dependent terrestrial vegetation by 2030. Climate change effects on environmentally significant flow regimes were evaluated by applying the climate projections from 15 GCMs under three global warming ‘scenarios to rainfall–runoff and groundwater models. It was estimated that under a dry future climate scenario, the frequency of river flow rates important for ecological communities is likely to be reduced by up to 2 months per year, which is likely to cause a significant level of stress to ecological communities. Additionally, the duration of no-flow periods may increase by more than 120 days in some streams. Under a dry future climate scenario, groundwater-dependent vegetation is projected to be at a high risk in over 19% of its current habitat area. Water-dependent ecosystems are also projected to be affected by an increase in groundwater abstraction. The results indicate that the projected impacts of future climate conditions are not likely to be uniform across the region but overall they could cause a continuing threat to water-dependent ecosystems. The implementation of water management plans should place particular emphasis on the ecological water requirements in 6 of the 13 river catchments in south-western Australia and in areas where groundwater abstraction is high. The climate projections and ecological impacts are a continuation of the trends that have taken place in the past three decades.

Distribution patterns of groundwater‐dependent vegetation species diversity and their relationship to groundwater attributes in northwestern China

ABSTRACTThe study of the patterns of plant species diversity and the factors influencing these patterns is the basis of ecology and is also fundamental to conservation biology. Groundwater‐dependent vegetation (GDV) must have access to groundwater to maintain their growth and function, and this is especially common in arid and semi‐arid regions, including north‐western China. In this paper, plant species diversity and groundwater attributes (composition and depth) were investigated in 31 plots in the Ejina Delta in north‐western China to determine whether groundwater attributes influenced patterns species diversity in GDV. Detrended canonical correspondence analyses and generalised additive models were performed to analyse the data. A total of 29 plant species were recorded in the 31 plots; perennial herbs with deep roots had an advantage over all other groups, and GDV species diversity was primarily affected by groundwater depth (GWD), salinity (SAL) and total dissolved solids (TDS), HCO3−, Ca2+, pH, and SO42−. The herb layer species diversity and total species diversity reached their maximum in similar, moderate environmental conditions. The diversity of the tree species was influenced by SAL and TDS and was maximal at large values of GWD and low values of SAL and TDS. The diversity of shrub species was affected by Ca2+ and Mg2+ and was maximal low GWD and high SAL and TDS. Patrick's and Shannon–Wiener's index of the total community diversity presented a bimodal pattern along gradients of GWD and SAL, whilst Simpson's and Pielou's index showed a partially unimodal pattern. On the basis of field investigation and the analysis of field data, we concluded that the perfect combination of GWD and SAL for GDV species diversity is 2 m and 1·8 g l−1, respectively. The appropriate combination range is 2–5 m and 1·8–4·2 g l−1, and the critical combination for the damaged GDV species diversity is 5 m and 4·2 g l−1. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Climate change effects on water-dependent ecosystems in south-western Australia

The effect of future climate scenarios on surface water and groundwater resources has been shown to have a consequent impact on water-dependent ecosystems. A regional-scale analysis of changes in water resources as a result of changing climate was undertaken in south-western Australia; a region with a large number of nationally and internationally recognised water-dependent ecosystems. The paper examines the potential environmental impacts of a substantial reduction in rainfall and an increase in temperature as projected by global climate models (GCMs) on river and groundwater-dependent terrestrial vegetation by 2030. Climate change effects on environmentally significant flow regimes were evaluated by applying the climate projections from 15 GCMs under three global warming ‘scenarios to rainfall–runoff and groundwater models. It was estimated that under a dry future climate scenario, the frequency of river flow rates important for ecological communities is likely to be reduced by up to 2 months per year, which is likely to cause a significant level of stress to ecological communities. Additionally, the duration of no-flow periods may increase by more than 120 days in some streams. Under a dry future climate scenario, groundwater-dependent vegetation is projected to be at a high risk in over 19% of its current habitat area. Water-dependent ecosystems are also projected to be affected by an increase in groundwater abstraction. The results indicate that the projected impacts of future climate conditions are not likely to be uniform across the region but overall they could cause a continuing threat to water-dependent ecosystems. The implementation of water management plans should place particular emphasis on the ecological water requirements in 6 of the 13 river catchments in south-western Australia and in areas where groundwater abstraction is high. The climate projections and ecological impacts are a continuation of the trends that have taken place in the past three decades.

Response of Terrestrial-Aquatic Palm Ecotone (Morichal) to Anthropogenic Disturbance in the Orinoco Lowlands

The study tested the assumption that the effect of land-use changes on hydrological dynamics and edaphic features of an aquatic-terrestrial ecotone have led to vegetational patchiness and decrease primary productivity (NPP). On the basis of the depletion of a groundwater-fed stream, three study sites corresponding to interrupted, intermittent and permanent streams were selected throughout the ecotone in the Sunsunes catchment (Orinoco basin, Venezuela). To describe the human impact on land cover, patchiness, biodiversity, hydrological and edaphic features, NPP and nutrient availability, we use structural and functional approaches. Hydrological (i.e., duration of inundation and maximum inundation height), soil chemical (e.g., Ca concentration, available phosphorous, soil organic matter) and physical (i.e., water-filled pore spaces) features were the best predictors of anthropogenic disturbance. In the ecotone, the tree species invasion from well-drained savannas increased woody cover as described by a stretched exponential model. Groundwater drawdown in the interrupted and intermittent streams increased with 74 and 34 colonizer species from well-drained savannas. The NPP of the ecotonal vegetation along the interrupted stream (909 g C/m2/yr) was a higher sink as compared to the intermittent and permanent streams (580 g C/m2/yr). Anthropogenic stress along with natural disturbance resulted in a decline in the system´s functioning. In contrast to hydrology, the effect of the nutrient addition (i.e., liming and phosphorous) on the carbon accumulation by species was not significant. Therefore, the functional response of the system was more sensitive to hydrology regime. The results indicate impact on the ecotones occurred in short term, and that vulnerability to climate is crucial of groundwater-dependent vegetation.

Leaf nitrogen allocation and partitioning in three groundwater-dependent herbaceous species in a hyper-arid desert region of north-western China

Groundwater-dependent vegetation (GDV) is useful as an indicator of watertable depth and water availability in north-western China. Nitrogen (N) is an essential limiting resource for growth of GDV. To elucidate how leaf N allocation and partitioning influence photosynthesis and photosynthetic N-use efficiency (PNUE), three typical GDV species were selected, and their photosynthesis, leaf N allocation and partitioning were investigated in the Taklamakan Desert. The results showed that Karelinia caspica (Pall.) Less. and Peganum harmala L. had lower leaf N content, and allocated a lower fraction of leaf N to photosynthesis. However, they were more efficient in photosynthetic N partitioning among photosynthetic components. They partitioned a higher fraction of the photosynthetic N to carboxylation and showed higher PNUE, whereas Alhagi sparsifolia Shap. partitioned a higher fraction of the photosynthetic N to light-harvesting components. For K. caspica and P. harmala, the higher fraction of leaf N was allocated to carboxylation and bioenergetics, which led to a higher maximum net photosynthetic rate, and therefore to a higher PNUE, water-use efficiency (WUE), respiration efficiency (RE) and so on. In the desert, N and water are limiting resources; K. caspica and P. harmala can benefit from the increased PNUE and WUE. These physiological advantages and their higher leaf-area ratio (LAR) may contribute to their higher resource-capture ability.

Modelling groundwater-dependent vegetation patterns using ensemble learning

Abstract. Vegetation patterns arise from the interplay between intraspecific and interspecific biotic interactions and from different abiotic constraints and interacting driving forces and distributions. In this study, we constructed an ensemble learning model that, based on spatially distributed environmental variables, could model vegetation patterns at the local scale. The study site was an alluvial floodplain with marked hydrologic gradients on which different vegetation types developed. The model was evaluated on accuracy, and could be concluded to perform well. However, model accuracy was remarkably lower for boundary areas between two distinct vegetation types. Subsequent application of the model on a spatially independent data set showed a poor performance that could be linked with the niche concept to conclude that an empirical distribution model, which has been constructed on local observations, is incapable to be applied beyond these boundaries.

Random forests as a tool for ecohydrological distribution modelling

An important issue in ecohydrological research is distribution modelling, aiming at the prediction of species or vegetation type occurrence on the basis of empirical relations with hydrological or hydrogeochemical habitat conditions. In this study, two statistical techniques are evaluated: (i) the widely used multiple logistic regression technique in the generalized linear modelling framework, and (ii) a recently developed machine learning technique called ‘random forests’. The latter is an ensemble learning technique that generates many classification trees and aggregates the individual results. The two different techniques are used to develop distribution models to predict the vegetation type occurrence of 11 groundwater-dependent vegetation types in Belgian lowland valley ecosystems based on spatially distributed measurements of environmental conditions. The spatially distributed data set under investigation consists of 1705 grid cells covering an area of 47.32 ha. After model construction and calibration, both models are applied to independent test data sets using two-fold cross-validation and resulting probabilities of occurrence are used to predict vegetation type distributions within the study area. Predicted vegetation types are compared with observations, and the McNemar test indicates an overall better performance of the random forest model at the 0.001 significance level. Comparison of the modelling results for each individual vegetation type separately by means of the F-measure, which combines precision and recall, also reveals better predictions by the random forest model. Inspection of the probabilities of occurrence of the different vegetation types for each grid cell demonstrates that correct predictions in central areas of homogeneous vegetation sites are based on high probabilities, whereas the confidence decreases towards the margins of these areas. Threshold-independent evaluation of the model accuracy by means of the area under the receiver operating characteristic (ROC) curves confirms good performances of both models, but with higher values for the random forest model. Therefore, the incorporation of the random forest technique in distribution models has the ability to lead to better model performances.

Groundwater-dependent ecosystems: the where, what and why of GDEs

Until the early 1970s, the management of water resources in Australia was predominantly concerned with the assessment, development and harnessing of new water resources for irrigation, urban and industrial, stock and domestic water supply. The consequences of excessive and unsympathetic groundwater abstraction on groundwaterdependent (phreatophytic) vegetation, such as tree decline and mortality, have been observed throughout Australia (Arrowsmith 1996; Hatton and Evans 1998; Clifton and Evans 2001). With increasing demand for water and a changing climate regime, the need to mitigate the environmental impacts of groundwater development is increasing. Current borefield operation in Australia is largely responsive to consumption demand and often in conflict with environmental needs for groundwater, resulting in drought stress and sometimes death of phreatophytic vegetation and other impacts on GDEs. Groundwater resource managers commonly ask how much water can be taken from the aquifer while still maintaining a low level of risk to GDEs. This requires quantified information on the relationship between the health of a GDE and groundwater depth (or other parameter; see Eamus et al. 2006a). Recommendations are generally made by defining the acceptable level to which groundwater can be allowed to fall, while maintaining important environmental values (see Murray et al. 2006). The Council of Australian Governments (COAG) endorsed reforms in 1994 to achieve a sustainable water industry that included allocations for the environment

A functional methodology for determining the groundwater regime needed to maintain the health of groundwater-dependent vegetation

In the past, the phrase ‘environmental allocations of water’ has most often been taken to mean allocation of water to rivers. However, it is now accepted that groundwater-dependent ecosystems are an important feature of Australian landscapes and require an allocation of water to maintain their persistence in the landscape. However, moving from this theoretical realisation to the provision and implementation of a field-based management regime is extremely difficult. The following four fundamental questions are identified as being central to the effective management of groundwater-dependent ecosystems (GDEs): (1) How do we identify GDEs in the field; put another way, which species or species assemblages or habitats are reliant on a supply of groundwater for their persistence in the landscape; (2) what groundwater regime is required to ensure the persistence of a GDE; (3) how can managers of natural resources (principally water and habitats), with limited time, money and other resources, successfully manage GDEs; and (4) what measures of ecosystem function can be monitored to ensure that management is effective? This paper explicitly addresses these questions and provides a step-by-step theoretical and practical framework for providing answers. In particular, this paper provides an introduction to some of the relevant literature and from this, presents a synthesis, presented in the form of a functional methodology for managing groundwater dependent ecosystems.

Groundwater Management in Central Berlin

The Spreebogen area in central Berlin is the site of a large and complex tunnelling project that calls for three parallel tunnels to serve long distance trains, a subway line and a roadway. The tunnels for the long distance and subway rail lines are shield tunnels, while the road tunnel is being built by the open-pit technique. Extensive environmental impact studies were conducted for this large project to assess the existing situation and forecast the impact of construction on the surface water and groundwater. The Tiergarten Park, with its groundwater-dependent vegetation has been given particular attention in these studies.