scholarly journals Development and application of the Riparian Mapping Tool to identify priority rehabilitation areas for nitrogen removal in the Tully - Murray basin, Queensland, Australia

2009 ◽  
Vol 60 (11) ◽  
pp. 1165 ◽  
Author(s):  
D. W. Rassam ◽  
D. Pagendam
Keyword(s):  
Riparian Zone ◽  
Nitrate Removal ◽  
Base Flow ◽  
Nitrate Contamination ◽  
Riparian Zones ◽  
Land Uses ◽  
Mapping Tool ◽  
Nitrogen Loads ◽  
Murray Basin ◽  
Raster Cell

One feature of riparian zones is their ability to significantly reduce the nitrogen loads entering streams by removing nitrate from the groundwater. A novel GIS model was used to prioritise riparian rehabilitation in catchments. It is proposed that high-priority areas are those with a high potential for riparian denitrification and have nearby land uses that generate high nitrogen loads. For this purpose, we defined the Rehabilitation Index, which is the product of two other indices, the Nitrate Removal Index and the Nitrate Interception Index. The latter identifies the nitrate contamination potential for each raster cell in the riparian zone by examining the extent and proximity of agricultural urban land uses. The former is estimated using a conceptual model for surface–groundwater interactions in riparian zones associated with middle-order gaining perennial streams, where nitrate is removed via denitrification when the base flow interacts with the carbon-rich riparian sediments before discharging to the streams. Riparian zones that are relatively low in the landscape, have a flat topography, and have soils of medium hydraulic conductivity are most conducive to denitrification. In the present study, the model was implemented in the Tully–Murray basin, Queensland, Australia, to produce priority riparian rehabilitation area maps.

scholarly journals Improved Accuracy of Riparian Zone Mapping Using Near Ground Unmanned Aerial Vehicle and Photogrammetry Method

2021 ◽  
Vol 13 (10) ◽  
pp. 1997
Author(s):  
Joan Grau ◽  
Kang Liang ◽  
Jae Ogilvie ◽  
Paul Arp ◽  
Sheng Li ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Precision Agriculture ◽  
Riparian Zone ◽  
Agricultural Landscapes ◽  
Agricultural Watershed ◽  
Riparian Zones ◽  
Surface Model ◽  
Low Resolution ◽  
Channel Network ◽  
Aerial Vehicle

In agriculture-dominant watersheds, riparian ecosystems provide a wide array of benefits such as reducing soil erosion, filtering chemical compounds, and retaining sediments. Traditionally, the boundaries of riparian zones could be estimated from Digital Elevation Models (DEMs) or field surveys. In this study, we used an Unmanned Aerial Vehicle (UAV) and photogrammetry method to map the boundaries of riparian zones. We first obtained the 3D digital surface model with a UAV. We applied the Vertical Distance to Channel Network (VDTCN) as a classifier to delineate the boundaries of the riparian area in an agricultural watershed. The same method was also used with a low-resolution DEM obtained with traditional photogrammetry and two more LiDAR-derived DEMs, and the results of different methods were compared. Results indicated that higher resolution UAV-derived DEM achieved a high agreement with the field-measured riparian zone. The accuracy achieved (Kappa Coefficient, KC = 63%) with the UAV-derived DEM was comparable with high-resolution LiDAR-derived DEMs and significantly higher than the prediction accuracy based on traditional low-resolution DEMs obtained with high altitude aerial photos (KC = 25%). We also found that the presence of a dense herbaceous layer on the ground could cause errors in riparian zone delineation with VDTCN for both low altitude UAV and LiDAR data. Nevertheless, the study indicated that using the VDTCN as a classifier combined with a UAV-derived DEM is a suitable approach for mapping riparian zones and can be used for precision agriculture and environmental protection over agricultural landscapes.

Elucidating sources and pathways of dissolved organic carbon in a small, forested catchment – A qualitative assessment of stream, soil and shallow groundwater

2021 ◽  
Author(s):  
Katharina Blaurock ◽  
Phil Garthen ◽  
Benjamin S. Gilfedder ◽  
Jan H. Fleckenstein ◽  
Stefan Peiffer ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Dissolved Organic Carbon ◽  
Soil Water ◽  
Riparian Zone ◽  
Stream Water ◽  
Shallow Groundwater ◽  
Drinking Water Treatment ◽  
Base Flow ◽  
Qualitative Assessment ◽  
Fluorescence Characteristics

<p>Dissolved organic carbon (DOC) constitutes the biggest portion of carbon that is exported from soils. During the last decades, widespread increases in DOC concentrations of surface waters have been observed, affecting ecosystem functioning and drinking water treatment. However, the hydrological controls on DOC mobilization are still not completely understood.</p><p>We sampled two different topographical positions within a headwater catchment in the Bavarian Forest National Park: at a steep hillslope (880 m.a.s.l.) and in a flat and wide riparian zone (770 m.a.s.l.). By using piezometers, pore water samplers (peepers) and in-stream spectrometric devices we measured DOC concentrations as well as DOC absorbance (A<sub>254</sub>/A<sub>365</sub> and SUVA<sub>254</sub>) and fluorescence characteristics (fluorescence and freshness indices) in soil water, shallow ground water and stream water in order to gain insights into the DOC source areas during base-flow and during precipitation events.</p><p>High DOC concentrations (up to 80 mg L<sup>-1</sup>) were found in soil water from cascading sequences of small ponds in the flat downstream part of the catchment that fill up temporarily. The increase of in-stream DOC concentrations during events was accompanied by changing DOC characteristics at both locations, for example increasing freshness index values. As the freshness index values were approaching the values found in the DOC-rich ponds in the riparian zone, these ponds seem to be important DOC sources during events. Our preliminary results point to a change of flow pathways during events.</p>

scholarly journals Nitrate-Utilizing Microorganisms Resistant to Multiple Metals from the Heavily Contaminated Oak Ridge Reservation

2019 ◽  
Vol 85 (17) ◽  
Author(s):  
Michael P. Thorgersen ◽  
Xiaoxuan Ge ◽  
Farris L. Poole ◽  
Morgan N. Price ◽  
Adam P. Arkin ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Metal Contamination ◽  
Nitrate Removal ◽  
Nitrate Contamination ◽  
Contaminated Site ◽  
Sequence Variant ◽  
Oak Ridge ◽  
Global Issue ◽  
16S Rna ◽  
High Concentrations

ABSTRACTContamination of environments with nitrate generated by industrial processes and the use of nitrogen-containing fertilizers is a growing problem worldwide. While nitrate can be removed from contaminated areas by microbial denitrification, nitrate frequently occurs with other contaminants, such as heavy metals, that have the potential to impede the process. Here, nitrate-reducing microorganisms were enriched and isolated from both groundwater and sediments at the Oak Ridge Reservation (ORR) using concentrations of nitrate and metals (Al, Mn, Fe, Co, Ni, Cu, Cd, and U) similar to those observed in a contaminated environment at ORR. Seven new metal-resistant, nitrate-reducing strains were characterized, and their distribution across both noncontaminated and contaminated areas at ORR was examined. While the seven strains have various pH ranges for growth, carbon source preferences, and degrees of resistance to individual and combinations of metals, all were able to reduce nitrate at similar rates both in the presence and absence of the mixture of metals found in the contaminated ORR environment. Four strains were identified in groundwater samples at different ORR locations by exact 16S RNA sequence variant analysis, and all four were found in both noncontaminated and contaminated areas. By using environmentally relevant metal concentrations, we successfully isolated multiple organisms from both ORR noncontaminated and contaminated environments that are capable of reducing nitrate in the presence of extreme mixed-metal contamination.IMPORTANCENitrate contamination is a global issue that affects groundwater quality. In some cases, cocontamination of groundwater with nitrate and mixtures of heavy metals could decrease microbially mediated nitrate removal, thereby increasing the duration of nitrate contamination. Here, we used metal and nitrate concentrations that are present in a contaminated site at the Oak Ridge Reservation to isolate seven metal-resistant strains. All were able to reduce nitrate in the presence of high concentrations of a mixture of heavy metals. Four of seven strains were located in pristine as well as contaminated sites at the Oak Ridge Reservation. Further study of these nitrate-reducing strains will uncover mechanisms of resistance to multiple metals that will increase our understanding of the effect of nitrate and metal contamination on groundwater microbial communities.

scholarly journals A Machine Learning Approach for Mapping Forest Vegetation in Riparian Zones in an Atlantic Biome Environment Using Sentinel-2 Imagery

2020 ◽  
Vol 12 (24) ◽  
pp. 4086
Author(s):  
Danielle Elis Garcia Furuya ◽  
João Alex Floriano Aguiar ◽  
Nayara V. Estrabis ◽  
Mayara Maezano Faita Pinheiro ◽  
Michelle Taís Garcia Furuya ◽  
...  
Keyword(s):  
Machine Learning ◽  
Environmental Planning ◽  
Riparian Zone ◽  
Learning Algorithms ◽  
Vegetation Mapping ◽  
Forest Vegetation ◽  
Machine Learning Algorithms ◽  
Riparian Zones ◽  
Support Vector ◽  
Sentinel 2

Riparian zones consist of important environmental regions, specifically to maintain the quality of water resources. Accurately mapping forest vegetation in riparian zones is an important issue, since it may provide information about numerous surface processes that occur in these areas. Recently, machine learning algorithms have gained attention as an innovative approach to extract information from remote sensing imagery, including to support the mapping task of vegetation areas. Nonetheless, studies related to machine learning application for forest vegetation mapping in the riparian zones exclusively is still limited. Therefore, this paper presents a framework for forest vegetation mapping in riparian zones based on machine learning models using orbital multispectral images. A total of 14 Sentinel-2 images registered throughout the year, covering a large riparian zone of a portion of a wide river in the Pontal do Paranapanema region, São Paulo state, Brazil, was adopted as the dataset. This area is mainly composed of the Atlantic Biome vegetation, and it is near to the last primary fragment of its biome, being an important region from the environmental planning point of view. We compared the performance of multiple machine learning algorithms like decision tree (DT), random forest (RF), support vector machine (SVM), and normal Bayes (NB). We evaluated different dates and locations with all models. Our results demonstrated that the DT learner has, overall, the highest accuracy in this task. The DT algorithm also showed high accuracy when applied on different dates and in the riparian zone of another river. We conclude that the proposed approach is appropriated to accurately map forest vegetation in riparian zones, including temporal context.

scholarly journals Feasible Ways Promoting Nitrate Removal in Riparian Zone Downstream of a Regulated River

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 2054
Author(s):  
Dongsheng Liu ◽  
Bei Zhu ◽  
Haoyu Zhu ◽  
Jian Zhao
Keyword(s):  
Ecological Restoration ◽  
Riparian Zone ◽  
Nitrate Removal ◽  
Reaction Model ◽  
Regulated River ◽  
Hyporheic Exchange ◽  
Fixed Degree ◽  
Chemical Methods ◽  
Physical Methods ◽  
Contaminated Area

Set in the downstream riparian zone of Xin’an River Dam, this paper established a 2D transversal coupling flow and solute transport and reaction model by verification within situ groundwater level and temperature. The denitrifying methods and principles in the riparian zone from the perspective of hyporheic exchange were explored, which provided a basis for the engineering techniques for river ecological restoration. Our studies have shown that under the condition of water level fluctuation, a biological method such as adding denitrifying bacteria biomass to a fixed degree (the same below) can greatly increase the denitrifying rate (1.52 g/d) in the riparian zone; chemical methods such as adding organic carbon into the surface water or groundwater can increase the total riparian nitrate removal (8.00–8.18 g) and its efficiency (19.5–20.0%) to a great extent; hydrogeological methods such as silt cleaning of the aquifer surface or local pumping around the contaminated area can increase the total riparian nitrate removal (1.06–14.8 g) to some extent, but correspondingly reduce the denitrifying efficiency (0.95–1.4%); physical methods such as designing the bank form into gentle slope or concave shape can slightly increase the total riparian nitrate removal (0.22–0.52 g) and correspondingly improve the denitrifying efficiency (0.25–0.85%). At the application level of river ecological restoration, integrated adopting the above methods can make the riparian denitrifying effect “fast and good”.

scholarly journals High-frequency measurements explain quantity and quality of dissolved organic carbon mobilization in a headwater catchment

2019 ◽  
Vol 16 (22) ◽  
pp. 4497-4516 ◽  
Author(s):  
Benedikt J. Werner ◽  
Andreas Musolff ◽  
Oliver J. Lechtenfeld ◽  
Gerrit H. de Rooij ◽  
Marieke R. Oosterwoud ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Dissolved Organic Carbon ◽  
High Frequency ◽  
Riparian Zone ◽  
Quality Parameters ◽  
Riparian Zones ◽  
Frequency Measurements ◽  
Seasonal Scale ◽  
Headwater Catchment

Abstract. Increasing dissolved organic carbon (DOC) concentrations and exports from headwater catchments impact the quality of downstream waters and pose challenges to water supply. The importance of riparian zones for DOC export from catchments in humid, temperate climates has generally been acknowledged, but the hydrological controls and biogeochemical factors that govern mobilization of DOC from riparian zones remain elusive. A high-frequency dataset (15 min resolution for over 1 year) from a headwater catchment in the Harz Mountains (Germany) was analyzed for dominant patterns in DOC concentration (CDOC) and optical DOC quality parameters SUVA254 and S275−295 (spectral slope between 275 and 295 nm) on event and seasonal scales. Quality parameters and CDOC systematically changed with increasing fractions of high-frequency quick flow (Qhf) and antecedent hydroclimatic conditions, defined by the following metrics: aridity index (AI60) of the preceding 60 d and the quotient of mean temperature (T30) and mean discharge (Q30) of the preceding 30 d, which we refer to as discharge-normalized temperature (DNT30). Selected statistical multiple linear regression models for the complete time series (R2=0.72, 0.64 and 0.65 for CDOC, SUVA254 and S275−295, resp.) captured DOC dynamics based on event (Qhf and baseflow) and seasonal-scale predictors (AI60, DNT30). The relative importance of seasonal-scale predictors allowed for the separation of three hydroclimatic states (warm and dry, cold and wet, and intermediate). The specific DOC quality for each state indicates a shift in the activated source zones and highlights the importance of antecedent conditions and their impact on DOC accumulation and mobilization in the riparian zone. The warm and dry state results in high DOC concentrations during events and low concentrations between events and thus can be seen as mobilization limited, whereas the cold and wet state results in low concentration between and during events due to limited DOC accumulation in the riparian zone. The study demonstrates the considerable value of continuous high-frequency measurements of DOC quality and quantity and its (hydroclimatic) key controlling variables in quantitatively unraveling DOC mobilization in the riparian zone. These variables can be linked to DOC source activation by discharge events and the more seasonal control of DOC production in riparian soils.

Assessment of Temporal and Spatial Variation of Nitrate Removal in Riparian Zones

2006 ◽  
Vol 116 (1-3) ◽  
pp. 197-215 ◽  
Author(s):  
Karel Dhondt ◽  
Pascal Boeckx ◽  
Niko E. C. Verhoest ◽  
Georges Hofman ◽  
Oswald Van Cleemput
Keyword(s):  
Spatial Variation ◽  
Nitrate Removal ◽  
Riparian Zones ◽  
Temporal And Spatial Variation ◽  
Temporal And Spatial

scholarly journals Quantifying the performance of automated GIS-based geomorphological approaches for riparian zone delineation using digital elevation models

2012 ◽  
Vol 16 (10) ◽  
pp. 3851-3862 ◽  
Author(s):  
D. Fernández ◽  
J. Barquín ◽  
M. Álvarez-Cabria ◽  
F. J. Peñas
Keyword(s):  
River Basin ◽  
Riparian Zone ◽  
Digital Elevation Models ◽  
Riparian Zones ◽  
River Networks ◽  
Riparian Areas ◽  
River Basin Scale ◽  
Digital Elevation ◽  
Basin Scale ◽  
Objective Quantification

Abstract. Riparian zone delineation is a central issue for managing rivers and adjacent areas; however, criteria used to delineate them are still under debate. The area inundated by a 50-yr flood has been indicated as an optimal hydrological descriptor for riparian areas. This detailed hydrological information is usually only available for populated areas at risk of flooding. In this work we created several floodplain surfaces by means of two different GIS-based geomorphological approaches using digital elevation models (DEMs), in an attempt to find hydrologically meaningful potential riparian zones for river networks at the river basin scale. Objective quantification of the performance of the two geomorphologic models is provided by analysing coinciding and exceeding areas with respect to the 50-yr flood surface in different river geomorphological types.

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