Mapping groundwater‐dependent ecosystems using remote sensing measures of vegetation and moisture dynamics

Protection of groundwater‐dependent ecosystems (GDEs) is an important criterion in sustainable groundwater management, particularly when human water consumption is in competition with environmental water demands; however, the delineation of GDEs is commonly a challenging task. The Groundwater‐dependent Ecosystem Mapping (GEM) method proposed here is based on interpretation of the land surface response to the drying process derived from combined changes in two multispectral indices, the Normalised Difference Vegetation Index and the Normalised Difference Wetness Index, both derived from Landsat imagery. The GEM method predicts three land cover classes used for delineation of potential GDEs: vegetation with permanent access to groundwater; vegetation with diminishing access to groundwater; and water bodies that can persist through a prolonged dry period. The method was applied to a study site in the Ellen Brook region of Western Australia, where a number of GDEs associated with localised groundwater, diffuse discharge zones, and riparian vegetation were known. The estimated accuracy of the method indicated a good agreement between the predicted and known GDEs; Producer's accuracy was calculated as up to 91% for some areas. The method is most applicable for mapping GDEs in regions with a distinct drying period. Copyright © 2012 John Wiley & Sons, Ltd.     

A Global Synthesis of Managing Groundwater Dependent Ecosystems Under Sustainable Groundwater Policy

Groundwater is a vital water supply worldwide for people and nature. However, species and ecosystems that depend on groundwater for some or all of their water needs, known as groundwater dependent ecosystems (GDEs), are increasingly becoming threatened worldwide due to growing human water demands. Over the past two decades, the protection and management of GDEs have been incorporated into several water management policy initiatives worldwide including jurisdictions within Australia, the European Union, South Africa, and the United States. Among these, Australia has implemented the most comprehensive framework to manage and protect GDEs through its water policy initiatives. Using a science‐based approach, Australia has made good progress at reducing uncertainty when selecting management thresholds for GDEs in their water management plans. This has been achieved by incorporating appropriate metrics for GDEs into water monitoring programs so that information gathered over time can inform management decisions. This adaptive management approach is also accompanied by the application of the “Precautionary Principle” in cases where insufficient information on GDEs exist. Additionally, the integration of risk assessment into Australia's approach has enabled water managers to prioritize the most valuable and vulnerable ecologic assets necessary to manage GDEs under Australia's national sustainable water management legislation. The purpose of this paper is to: (1) compare existing global policy initiatives for the protection and management of GDEs; (2) synthesize Australia's adaptive management approach of GDEs in their state water plans; and (3) highlight opportunities and challenges of applying Australia's approach for managing GDEs under other water management policies worldwide.     

Mapping Potential Groundwater‐Dependent Ecosystems for Sustainable Management

Ecosystems which rely on either the surface expression or subsurface presence of groundwater are known as groundwater‐dependent ecosystems (GDEs). A comprehensive inventory of GDE locations at an appropriate management scale is a necessary first‐step for sustainable management of supporting aquifers; however, this information is unavailable for most areas of concern. To address this gap, this study created a two‐step algorithm which analyzed existing geospatial and remote sensing data to identify potential GDEs at both state/province and aquifer/basin scales. At the state/province scale, a geospatial information system (GIS) database was constructed for Texas, including climate, topography, hydrology, and ecology data. From these data, a GDE index was calculated, which combined vegetative and hydrological indicators. The results indicated that central Texas, particularly the Edwards Aquifer region, had highest potential to host GDEs. Next, an aquifer/basin scale remote sensing‐based algorithm was created to provide more detailed maps of GDEs in the Edwards Aquifer region. This algorithm used Landsat ETM+ and MODIS images to track the changes of NDVI for each vegetation pixel. The NDVI dynamics were used to identify the vegetation with high potential to use groundwater—such plants remain high NDVI during extended dry periods and also exhibit low seasonal and inter‐annual NDVI changes between dry and wet seasons/years. The results indicated that 8% of natural vegetation was very likely using groundwater. Of the potential GDEs identified, 75% were located on shallow soil averaging 45 cm in depth. The dominant GDE species were live oak, ashe juniper, and mesquite.     

Linking snowmelt‐derived fluxes and groundwater flow in a high elevation meadow system,Sierra Nevada Mountains,California

Quantifying snowmelt‐derived fluxes at the watershed scale within hillslope environments is critical for investigating local meadow scale groundwater dynamics in high elevation riparian ecosystems. In this article, we investigate the impact of snowmelt‐derived groundwater flux from the surrounding hillslopes on water table dynamics in Tuolumne Meadows, which is located in the Sierra Nevada Mountains of California, USA. Results show water levels within the meadow are controlled by a combination of fluxes at the hillslope boundaries, snowmelt within the meadow and changes in the stream stage. Observed water level fluctuations at the boundaries of the meadow show the hydrologic connection and subsequent disconnection between the hillslope and meadow aquifers. Timing of groundwater flux entering the meadow as a result of spring snowmelt can vary over 20 days based on the location, aspect, and local geology of the contributing area within the larger watershed. Identifying this temporal and spatial variability in flux entering the meadow is critical for simulating changes in water levels within the meadow. Model results can vary significantly based on the temporal and spatial scales at which watershed processes are linked to local processes within the meadow causing errors when boundary fluxes are lumped in time or space. Without a clear understanding of the surrounding hillslope hydrology, it is difficult to simulate groundwater dynamics within high elevation riparian ecosystems with the accuracy necessary for understanding ecosystem response. Copyright © 2010 John Wiley & Sons, Ltd.     

Influence of Seasonal Variations in Sea Level on the Salinity Regime of a Coastal Groundwater–Fed Wetland

Seasonal variations in sea level are often neglected in studies of coastal aquifers; however, they may have important controls on processes such as submarine groundwater discharge, sea water intrusion, and groundwater discharge to coastal springs and wetlands. We investigated seasonal variations in salinity in a groundwater‐fed coastal wetland (the RAMSAR listed Piccaninnie Ponds in South Australia) and found that salinity peaked during winter, coincident with seasonal sea level peaks. Closer examination of salinity variations revealed a relationship between changes in sea level and changes in salinity, indicating that sea level–driven movement of the fresh water‐sea water interface influences the salinity of discharging groundwater in the wetland. Moreover, the seasonal control of sea level on wetland salinity seems to override the influence of seasonal recharge. A two‐dimensional variable density model helped validate this conceptual model of coastal groundwater discharge by showing that fluctuations in groundwater salinity in a coastal aquifer can be driven by a seasonal coastal boundary condition in spite of seasonal recharge/discharge dynamics. Because seasonal variations in sea level and coastal wetlands are ubiquitous throughout the world, these findings have important implications for monitoring and management of coastal groundwater–dependent ecosystems.     

Near real time satellite imagery to support and verify timely flood modelling

The study investigates the capability of coarse resolution synthetic aperture radar (SAR) imagery to support flood inundation models. A hydraulic model of a 98‐km reach of the River Po (Northern Italy) was calibrated on the October 2000 high‐magnitude flood event with extensive and high‐quality field data. During the June 2008, low‐magnitude flood event a SAR image was acquired and processed in near real time (NRT) in order to provide adequate data for quick verification and recalibration of the hydraulic model. Copyright © 2009 John Wiley & Sons, Ltd.     

Long‐term effects of aquifer overdraft and recovery on groundwater quality in a Ramsar wetland: Las Tablas de Daimiel National Park,Spain

Las Tablas de Daimiel National Park is one of Spain's most representative groundwater‐dependent ecosystems. Under natural conditions, water inflows combined brackish surface water from River Gigüela with freshwater inputs from River Guadiana and the underlying aquifer. Since the mid‐1970s, aquifer overexploitation caused the desiccation of the wetlands and neighbouring springs. The National Park remained in precarious hydrological conditions for three decades, with the only exception of rapid floods due to extreme rainfall events and sporadic water transfers from other basins. In the late 2000s, a decrease in groundwater abstraction and an extraordinarily wet period reversed the trend. The aquifer experienced an unexpected recovery of groundwater levels (over 20 m in some areas), thus restoring groundwater discharge to springs and wetlands. The complex historical evolution of the water balance in this site has resulted in substantial changes in surface and groundwater quality. This becomes evident when comparing the pre‐1980 groundwater quality and the hydrochemical status in the wetland in two different periods, under “dry” and “wet” conditions. Although the system is close to full recovery from the groundwater‐level viewpoint, bouncing back in the major hydrochemical constituents has not yet been obtained. These still appear to evolve in response to the previous overexploitation state. Moreover, in some sectors, there are groundwater‐dependent ecosystems that remain different to those found in preoverexploitation times. The experience of Las Tablas de Damiel provides an observatory of long‐term changes in wetland water quality, demonstrating that the effects of aquifer overexploitation on aquatic ecosystems are more than a mere alteration of the water balance and that groundwater quality is the key to aquifer and aquatic ecosystem sustainability.     

Timely Low Resolution SAR Imagery To Support Floodplain Modelling: a Case Study Review

It is widely recognised that remote sensing can support flood monitoring, modelling and management. In particular, satellites carrying Synthetic Aperture Radar (SAR) sensors are valuable as radar wavelengths can penetrate cloud cover and are insensitive to daylight. However, given the strong inverse relationship between spatial resolution and revisit time, monitoring floods from space in near real time is currently only possible through low resolution (about 100 m pixel size) SAR imagery. For instance, ENVISAT-ASAR (Advanced Synthetic Aperture Radar) in WSM (wide swath mode) revisit times are of the order of 3 days and the data can be obtained within 24 h at no (or low) cost. Hence, this type of space-borne data can be used for monitoring major floods on medium-to-large rivers. This paper aims to discuss the potential for, and uncertainties of, coarse resolution SAR imagery to monitor floods and support hydraulic modelling. The paper first describes the potential of globally and freely available space-borne data to support flood inundation modelling in near real time. Then, the uncertainty of SAR-derived flood extent maps is discussed and the need to move from deterministic binary maps (wet/dry) of flood extent to uncertain flood inundation maps is highlighted.     

Investigation of submarine groundwater discharge to tidal rivers: Evidence for regional and local scale seepage

Fluxes of submarine groundwater discharge (SGD) were investigated into two tidal rivers on the north and south shore of Long Island, NY, during July 2015. Ground‐based handheld thermal infrared (TIR) imagery, combined with direct push‐point piezometer sampling, documented spatially heterogeneous small‐scale intertidal seepage zones. Pore waters were relatively fresh and enriched in nitrogen (N) within these small‐scale seeps. Pore waters sampled just 20 cm away, outside the boundary of the ground‐based TIR‐located seepage zone, were more saline and lower in N. These ground‐based TIR‐identified seeps geochemically represented the terrestrial fresh groundwater endmember, whereas N in pore waters sampled outside of the TIR‐identified seeps was derived from the remineralization of organic matter introduced into the sediment by tidal seawater infiltration. A ²²²Rn (radon‐222) time‐series was used to quantify fresh SGD‐associated N fluxes using the N endmembers sampled from the ground‐based TIR pore water profiles. N fluxes were up‐scaled to groundwater seepage zones identified from high‐resolution airborne TIR imagery using the two‐dimensional size of the airborne TIR surface water anomalies, relative to the N flux from the time‐series sampling location. Results suggest that the N load from the north‐shore tidal river to Long Island Sound is underrepresented by at least 1.6–3.6%, whereas the N load from SGD to a south‐shore tidal river may be up to 9% higher than previous estimates. These results demonstrate the importance of SGD in supplying nutrients to the lower reaches of tidal rivers and suggest that N loads in other tidal river environments may be underestimated if SGD is not accounted for.     

Factors Influencing Variability in Groundwater Monitoring Data Sets

“Random” variability in groundwater monitoring data sets reduces the ability to identify long‐term concentration trends. This, in turn, increases the time and cost required to evaluate the effectiveness of natural attenuation and other groundwater remedies. To better understand the factors influencing variability in groundwater monitoring results, we have analyzed three large groundwater monitoring data sets. For the three data sets, the long‐term trend in contaminant concentration in each well accounted for an average of 30% to 40% of the overall variation in contaminant concentration. Understanding the causes of the remaining variability would support the development of improved groundwater monitoring methods. All three data sets show large differences in the temporal monitoring records between individual wells (e.g., coefficient of variation for monitoring results from individual wells ranges from 0.08 to 4.6) indicating that well and aquifer factors are more important contributors to variability than sample collection and analysis factors. However, the depth to groundwater (R² = 0.020) and distance between water level and screened interval (R² = 0.049) accounted for only a portion of the differences in variability between wells and other aquifer characteristics evaluated and were not correlated with the observed variability in monitoring results. Unidentified factors were apparently much more important contributors to variability than these factors. The monitoring data sets exhibited two distinct timescales for variability: Time‐independent variability that was apparent even when wells were re‐sampled within a few days and a long‐term variability likely associated with the long‐term concentration trend. The observation of time‐independent variability suggests that frequent monitoring of contaminated monitoring wells serves primarily to characterize sources of variability unrelated to the long‐term trend of primary interest.     

TEMPORAL MONITORING OF SOIL MOISTURE USING ERS-1 SAR DATA

Multi-temporal synthetic aperture radar (SAR) imagery from the European Remote Sensing Satellite (ERS-1) was evaluated for monitoring soil moisture at the Romney Marsh test site as part of the UK SAR Calibration and Crop Backscatter Experiment. A total of 18 C-band (5.3 GHz) ERS-1 SAR images were acquired during the three day orbit and co-registered. Accurate calibration of the backscatter measurements was achieved using calibration constants derived from an analysis of corner reflector target responses. Mean backscatter measurements were recorded for each field and compared with field data on soil moisture, surface roughness and rainfall patterns. A comparison of daily and hourly rainfall and soil moisture measurements with backscatter for different cover types showed that the observed trends in backscatter are dominated by moisture effects. A high positive correlation between volumetric soil moisture in the range 10–40% was observed for bare soil fields. A much weaker positive relationship between soil moisture and backscatter was observed for grassland fields.     

Use of Nested Flow Models and Interpolation Techniques for Science‐Based Management of the Sheyenne National Grassland,North Dakota,USA

Noxious weeds threaten the Sheyenne National Grassland (SNG) ecosystem and therefore herbicides have been used for control. To protect groundwater quality, the herbicide application is restricted to areas where the water table is less than 10 feet (3.05 m) below the ground surface in highly permeable soils, or less than 6 feet (1.83 m) below the ground surface in low permeable soils. A local MODFLOW model was extracted from a regional GFLOW analytic element model and used to develop depth‐to‐groundwater maps in the SNG that are representative for the particular time frame of herbicide applications. These maps are based on a modeled groundwater table and a digital elevation model (DEM). The accuracy of these depth‐to‐groundwater maps is enhanced by an artificial neural networks (ANNs) interpolation scheme that reduces residuals at 48 monitoring wells. The combination of groundwater modeling and ANN improved depth‐to‐groundwater maps, which in turn provided more informed decisions about where herbicides can or cannot be safely applied.     

Post-earthquake building damage assessment in Yushu using airborne SAR imagery

The synthetic aperture radar (SAR) plays an important role in earthquake emergency response because of its all-time and all-weather imaging capabilities. On April 14, 2010, an MS7.1 earthquake occurred in Yushu county, Qinghai province of China, causing a lot of buildings collapsed. In this paper, the building damage in Yushu city due to the earthquake was assessed quantitatively using high-resolution X-band airborne SAR image. The features of the buildings with different damage levels (collapsed, partial collapsed, non-collapsed) in the SAR image were analyzed first. Based on these building features, we interpreted the individual building damage in Yushu city block by block and got the numbers of the collapsed, partial collapsed and non-collapsed buildings separately for each block, referring to pre-earthquake QuickBird image when necessary. Let the damage index of individual collapsed, partial collapsed, non-collapsed building be 1, 0.5, 0 respectively, the remote sensing damage index of each block was then calculated through remote sensing damage index equation. Finally, the preliminary quantitative relationship between the remote sensing damage index interpreted from the SAR image and that interpreted from the optical image was built up. It can be concluded that a desirable damage assessment result can be derived from high-resolution airborne SAR imagery.     

Time vs. Money: A Quantitative Evaluation of Monitoring Frequency vs. Monitoring Duration

The National Research Council has estimated that over 126,000 contaminated groundwater sites are unlikely to achieve low ug/L clean‐up goals in the foreseeable future. At these sites, cost‐effective, long‐term monitoring schemes are needed in order to understand the long‐term changes in contaminant concentrations. Current monitoring optimization schemes rely on site‐specific evaluations to optimize groundwater monitoring frequency. However, when using linear regression to estimate the long‐term zero‐order or first‐order contaminant attenuation rate, the effect of monitoring frequency and monitoring duration on the accuracy and confidence for the estimated attenuation rate is not site‐specific. For a fixed number of monitoring events, doubling the time between monitoring events (e.g., changing from quarterly monitoring to semi‐annual monitoring) will double the accuracy of estimated attenuation rate. For a fixed monitoring frequency (e.g., semi‐annual monitoring), increasing the number of monitoring events by 60% will double the accuracy of the estimated attenuation rate. Combining these two factors, doubling the time between monitoring events (e.g., quarterly monitoring to semi‐annual monitoring) while decreasing the total number of monitoring events by 38% will result in no change in the accuracy of the estimated attenuation rate. However, the time required to collect this dataset will increase by 25%. Understanding that the trade‐off between monitoring frequency and monitoring duration is not site‐specific should simplify the process of optimizing groundwater monitoring frequency at contaminated groundwater sites.     

Diagnostic monitoring of a changing environment: an alternative UK perspective

Adaptive management of the marine environment requires an understanding of the complex interactions within it. Establishing levels of natural variability within and between marine ecosystems is a necessary prerequisite to this process and requires a monitoring programme which takes account of the issues of time, space and scale. In this paper, we argue that an ecosystem approach to managing the marine environment should take direct account of climate change indicators at a regional level if it is to cope with the unprecedented change expected as a result of human impacts on the earth climate system. We discuss the purpose of environmental monitoring and the importance of maintaining long-term time series. Recommendations are made on the use of these data in conjunction with modern extrapolation and integration tools (e.g. ecosystem models, remote sensing) to provide a diagnostic approach to the management of marine ecosystems, based on adaptive indicators and dynamic baselines.     

Formulation and application of the unsaturated/saturated catchment models SUSCAT and WEC‐C

This paper describes the formulation and application of a coupled unsaturated/saturated model framework developed to investigate the impact of mining on catchment water yield and groundwater dynamics. The model conceptualization was implemented in both a finite‐element (SUSCAT) and finite‐difference (WEC‐C) solution scheme and found to give similar results. The model framework simulates a coupled surface‐water and groundwater system in which a physically based solution scheme was used to simulate one‐dimensional movement through the unsaturated zone, and a distributed model was used to simulate two‐dimensional saturated groundwater flow. Each soil column comprises a series of layers, each layer being connected to adjacent cells. Subsurface lateral flow is considered when any cell within a layer develops a saturated thickness. Simulation results presented are based on a catchment in the Darling Range, Western Australia that was progressively mined and subsequently rehabilitated. The results predicted the groundwater system beneath the mine areas to have a peak rise owing to mining of between 2 and 4 m. Six years after mining, and following vegetation rehabilitation, the groundwater rise had reduced to 1 m above simulated unmined levels. The corresponding streamflow increase as a result of mining was estimated to peak at 21 mm/year and declined to 7·4 mm/year eight years after revegetation of the mined areas. The simulated groundwater response and streamflow results derived from both models were found to be consistent with observed data. Copyright © 2002 John Wiley & Sons, Ltd.     

Coastal pollution hazards in southern California observed by SAR imagery: stormwater plumes, wastewater plumes, and natural hydrocarbon seeps

Stormwater runoff plumes, municipal wastewater plumes, and natural hydrocarbon seeps are important pollution hazards for the heavily populated Southern California Bight (SCB). Due to their small size, dynamic and episodic nature, these hazards are difficult to sample adequately using traditional in situ oceanographic methods. Complex coastal circulation and persistent cloud cover can further complicate detection and monitoring of these hazards. We use imagery from space-borne synthetic aperture radar (SAR), complemented by field measurements, to examine these hazards in the SCB. The hazards are detectable in SAR imagery because they deposit surfactants on the sea surface, smoothing capillary and small gravity waves to produce areas of reduced backscatter compared with the surrounding ocean. We suggest that high-resolution SAR, which obtains useful data regardless of darkness or cloud cover, could be an important observational tool for assessment and monitoring of coastal marine pollution hazards in the SCB and other urbanized coastal regions.     

Evaluation of multi-sensor satellite data for monitoring different drought impacts

Drought is a natural disaster that significantly affects human life; therefore, precise monitoring and prediction is necessary to minimize drought damage. Conventional drought monitoring is based predominantly on ground observation stations; however, satellite imagery can be used to overcome the disadvantages of existing monitoring methods and has the advantage of monitoring wide areas. In this research, we assess the applicability of drought monitoring based on satellite imagery, focusing on historic droughts in 2001 and 2014, which caused major agricultural and hydrological issues in South Korea. To assess the applicability and accuracy of the drought index, drought impact areas in the study years were investigated, and spatiotemporal comparative analyses between the calculated drought index and previously affected areas were conducted. For drought monitoring based on satellite imagery, we used hydro-meteorological factors such as precipitation, land surface temperature, vegetation, and evapotranspiration, and applied remote sensing data from various sensors. We verified the effectiveness of using precipitation data for meteorological drought monitoring, vegetation and land surface temperature data for agricultural drought monitoring, and evapotranspiration data for hydrological drought monitoring. Moreover, we confirmed that the Standard Precipitation Index (SPI) can be indirectly applied to agricultural or hydrological drought monitoring by determining the temporal correlation between SPI, calculated for various time scales, and satellite-based drought indices.     

3D post‐stack interval velocity analysis with effective use of datuming

Interval velocity analysis using post‐stack data has always been a desire, mainly for 3D data sets. In this study we present a method that uses the unique characteristics of migrated diffractions to enable interval velocity analysis from three‐dimensional zero‐offset time data. The idea is to perform a standard three‐dimensional prestack depth migration on stack cubes and generate three‐dimensional common image gathers that show great sensitivity to velocity errors. An efficient ‘top‐down’ scheme for updating the velocity is used to build the model. The effectiveness of the method is related to the incorporation of wave equation based post‐stack datuming in the model building process. The proposed method relies on the ability to identify diffractions along redatumed zero‐offset data and to analyse their flatness in the migrated local angle domain. The method can be considered as an additional tool for a complete, prestack depth migration based interval velocity analysis.     

Patterns of remotely sensed floodplain saturation and its use in runoff predictions

Principal components analysis (PCA) is applied to a time series of European Remote Sensing (ERS) synthetic aperture radar (SAR) scenes of the Alzette River floodplain (Grand‐Duchy of Luxembourg). These images cover markedly different hydrological conditions during several winter seasons in order to enable the examination of the decrease of the radar backscattering signal during drying‐up phases following important flood events. At the floodplain scale, with homogeneous land use and constant topography, the first principal components (PCs) are mainly dominated by the variance related to the changing areas. The PCs are thus mainly controlled by subsurface and surface water dynamics. The field observations of a densely equipped piezometric network in the floodplain are used to calculate a mean soil saturation index (SSI) continuously. A classification scheme, based on the PCs and k‐means algorithm, leads to the segmentation of the floodplain into several hydrological behaviour classes with distinctive responses versus changing moisture conditions. To validate this classification method with ground‐based estimations, the relation between the mean backscattering values of microplots within each PCA‐derived hydrological class and the water table measurements, expressed by means of the SSI, is evaluated. Results show that each class of microplots is characterized by the slope of the ‘backscattering–SSI’ function and by the SSI threshold value at which groundwater resurgence appears. The water ponding implies very low signal return due to the specular backscattering effect on the water surface. Based on established relationships between measured initial water table depths, runoff coefficients and rainfall‐induced water table rises, these results are used to discuss the potential of SAR‐derived information in flood management applications. Copyright © 2005 John Wiley & Sons, Ltd.