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Environmental Sustainability
 

Environmental Sustainability

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Environmental Sustainability

Environmental Sustainability

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    Environmental Sustainability Environmental Sustainability Presentation Transcript

    • ENVIRONMENTAL SUSTAINABILITY INDICATORS Department of Geography Kings College London
    • RESEARCH TEAM Principle Investigators: Dr Angela Davenport – Kings College London Prof. Angela Gurnell – Kings College London Collaborating Scientists: Prof. Geoff Petts – University of Birmingham Dr Patrick Armitage – CEH Dorset Field Support: May Lee – Kings College London
    • AIMS & OBJECTIVES
      • Aims :
      • To develop and disseminate a set of Environmental Sustainable Urban River Indicators for application across the EU and Candidate Countries.
      • To aid development and dissemination of a transferable method of land-use planning in urbanised river basins.
      • Objectives:
      • To develop a transferable set of Environmental Sustainability Indicators for urbanised river basins.
      • To contribute to a new urban river planning methodology (utilising latest G.I.S. techniques) that will support the delivery of the Water Framework Directive.
    • DEVELOPMENT OF ENVIRONMENTAL SUSTAINABILITY RIVER INDICATORS
      • A hierarchical approach to managing urban river data
      • A reach scale survey designed for urban rivers
      • Primary Indicators - Stretch Scale Aggregate Indices
      • Secondary Indicators - Stretch Scale Classifications
      • A reach scale scoring system for scenario modelling by river managers
      • Tertiary Indicators - Network Scale Water Quality, Water Quantity, Floodplain Constraints
    • DRAINAGE BASIN SECTOR Unbranched tributary or network section between tributary junctions STRETCH 500m length of a single engineering type HABITAT Physical habitat feature (riffle, bar) PATCH Patch of vegetation or sediment A HIERARCHY OF SPATIAL SCALES AT WHICH URBAN RIVER DATA MAY BE COLLECTED Catchment Characteristics River corridor land use Water quality data River flow data Channel morphology Geomorphic features Reinforcement materials Flow types Vegetation Sediments Hydraulic data Biological data Sediments Hydraulic data Biological data
    • RESEARCH APPROACH PHASE 4 Scenario Modelling PHASE 1 Collection of information Transfer of data to database PHASE 2 Development of sustainable indicators. PHASE 3 Validation May/June 2004
      • The URS provides a wealth of information on urban rivers that can be queried to assess urban river corridor character and change.
      • Like the RHS, the survey includes a large number of measurements.
      • The measurements are recorded on three different measurement scales: frequencies, percentages, and other variable-specific scaled measurements.
      • Synthetic indices were developed to integrate the measurements into PRIMARY INDICATORS expressed across similar measurement scales and ranges to describe MATERIALS, PHYSICAL HABITAT and VEGETATION properties of urban river stretches.
      PRIMARY INDICATORS REACH SCALE AGGREGATE INDICES
    • SOME MATERIALS INDICES = (-8*BO -7*CO -3.5*GP -1.5*SA + 1.5*SI + 9*CL) (BO + CO + GP + SA + SI + CL) SEDCAL Bed Sediment Calibre Index = (0*NONE) + (1*BIO) + (2*OMP) + (3*SOL) x 3 (NONE+BIO+OPM+SOL)   BANKPROT Level and durability of bank protection The proportion of the banks occupied by solid bank protection (range 1-10) Proportion Solid Bank Protection The proportion of the banks occupied by open matrix bank protection (range 1-10) Proportion Open Matrix Bank Protection The proportion of the banks occupied by biodegradable bank protection (range 1-10) Proportion Biodegradable Bank Protection Proportion of banks free of bank protection (range 1-10) Proportion No Bank Protection = 10 x No. spot-checks with immobile materials No. spot-checks Proportion Immobile Bank Materials = (-8*BO -7*CO -1.5*GS +1.5*EA + 9*CL) (BO + CO + GS + EA + CL) BANKCAL Bank Material Calibre Index = 10 x No. spot-checks with immobile materials No. spot-checks Proportion Immobile Substrate Index Description Index Name
    • SOME PHYSICAL HABITAT INDICES A count of in-channel habitats types, including both physical habitat features and flow type habitats. Number of Habitat Types The proportion of the banks (range 1-10) occupied by artificial bank profiles. Proportion Artificial Bank Profiles The number of different types of artificial bank profile. Number Artificial Bank Profiles The proportion of the banks occupied by natural bank profiles (proportion in the range 1-10). Proportion Natural Bank Profiles The number of different types of natural bank profile ascertained from cumulative measurements. Number Natural Bank Profiles the flow type which is recorded the most times in the spot checks scored according to the level of hydraulic disturbance indicated (range 1-10). Dominant Flow Type the number of different flow types recorded Number of Flow Types Index name and description Index Name
    • SOME VEGETATION INDICES Accumulated measures of water odours, sediment odours, oils, surface scum and gross pollution. Total Pollution Score The percentage cover for all macrophyte types summed and then divided by 10. Average Channel Vegetation Cover The dominant type is the macrophyte with the largest total percentage cover recorded in the range 0-10 according to its gross flow resistance. Dominant Channel Vegetation Type A count of the number of macrophyte types in the stretch. Number Channel Vegetation Types Tree features scored 0,1 and 2 according to APE and summed. Total Tree Feature Score Tree cover is scored for each bank (range 0-5) and the scores are added Total Tree Score = 3(0*B + 1*U + 2*S + 3*C) / (B + U + S + C) BANKVEG Bank Vegetation Structure Index Index description Index Name
      • Cluster analysis was used to develop three classifications (Materials, Physical, Vegetation) or secondary indicators of urban river stretches from the primary indicators
      • Because of the similar numerical range of the primary indicators, cluster analysis was applied to the untransformed data.
      • Ward’s clustering algorithm was used.
      SECONDARY INDICATORS REACH SCALE CLASSIFICATIONS
    • SEVEN CLASSES OF URBAN RIVER STRETCH DEFINED BY THEIR MATERIALS CHARACTERISTICS
    • Heavily engineered, straight planforms and high levels of reinforcement on the banks and the bed. High proportions (ca. 100%) of solid bank protection (concrete, laid stone etc.) and immobile substrate. HEAVILY ENGINEERED: HE Artificial (mixed sinuosity) planforms and cross-sections with extensive reinforcement High proportions (50-90%) of solid bank protection (concrete, laid stone etc.) but low proportions of immobile substrate (i.e. bed reinforcement). MODERATELY ENGINEERED: ME Artificial (mainly straight) planforms and cross-sections with extensive reinforcement High (ca. 90-100%) proportions of open matrix bank protection and moderate proportions (ca. 20-50%) of solid bank protection. Low proportions of immobile substrate. ENGINEERED: EN Artificial (usually sinuous) planforms, and cross-sections with significant reinforcement Coarser bed and bank materials (SEDCAL, BANKCAL). Moderate proportions (ca. 30-85%) of open matrix protection (gabions, rip rap etc). LIGHTLY ENGINEERED: LE Natural sinuous planforms and cross-sections with limited reinforcement Low proportions of bank protection. Finer (typically clay) substrates (SEDCAL) and bank materials (BANKCAL). SEMI-NATURAL (FINE): SNF Artificial (mainly straight) planforms, and cross-sections but with limited reinforcement Low proportions of bank protection, with mixed substrates typically corresponding to silt/sand with some gravels (SEDCAL). SEMI-NATURAL (MIXED): SNM More natural planforms and cross sections (developed through natural processes, recovery or restoration), typically with some sinuosity. Low proportions of bank protection. Coarser substrates (SEDCAL) and bank materials (average BANKCAL). SEMI-NATURAL (COARSE): SNC Description of Broad Engineering Characteristics Description of Discriminating Primary (Materials) Indicators Group Name: Abbreviation
    • SIX CLASSES OF URBAN RIVER STRETCH DEFINED BY THEIR PHYSICAL HABITAT CHARACTERISTICS
    • Predominantly artificial straight planforms No evidence of active channel recovery through bank erosion. Flow almost entirely glides. Typically contain 0 bars. High Props of Art Bank Profiles (ca. 100%). Very Low Props of Nat Bank Profiles (ca. 0%). 1-2 Habitat Types. UNIFORM STABLE: US Predominantly artificial straight planforms Little evidence of channel recovery through bank erosion. Channel dominated by glides. Typically contain 1-2 vegetated/unvegetated bars. High Props of Art Bank Profiles (ca. 100%) and low Props of Nat Bank Profiles (ca. 0-30 %). 3-4 Habitat Types. UNIFORM MODERATELY ACTIVE: UM Predominantly artificial planforms most with some sinuosity. Some evidence of active channel recovery through bank erosion. Some evidence of mixed flow regime with no pool formation. Typically contain 2-6 vegetated/unvegetated bars High Props of Art Bank Profiles (ca. 100%), and moderate to high Props of Nat Bank Profiles (ca. 0-50%). 5-9 habitat types. UNIFORM ACTIVE: UA Predominantly artificial sinuous planforms. High levels of bank recovery from engineering. Some evidence of mixed flow regime with pool formation. Typ contain 1-4 vegetated/ unvegetated bars. Moderate Props of Art Bank Profiles (40-100%) and high Props of Nat Bank Profiles (50-100%). < 7 habitat types. RECOVERING: RC Predominantly natural sinuous planforms. Flow dominated by glides with no evidence of pool formation. Typically contain 0-4 vegetated/unvegetated bars. Very low Props of Art Bank Profiles and very high Props of Nat Bank Profiles. <7 Habitat Types. SEMI-NATURAL (STABLE): SNS Predominantly natural sinuous planforms. Mixed flow regime, some evidence of pool formation. Typically contain 7-8 vegetated/ unvegetated bars. Very low Props Art Bank Profiles and very high Props of Nat Bank Profiles. > 7 Habitat Types. SEMI-NATURAL (ACTIVE): SNA Description of Broad Engineering Characteristics Typical Physical Habitat Characteristics Description of Discriminating Primary (Physical) Indicators Group Name: Abbreviation
    • EIGHT CLASSES OF URBAN RIVER STRETCH DEFINED BY THEIR VEGETATION CHARACTERISTICS
    • Mainly artificial planforms with some sinuosity. Unvegetated stretches with high Total Tree Scores combined with high bank top vegetation complexity. Unvegetated High Complexity: UHC Mainly artificial planforms usually straight but some display sinuosity. Unvegetated stretches with higher Total Tree Scores, combined with low average bank top and high average bank face complexity. Unvegetated Mod Complexity: UMC Mainly artificial planforms usually straight but some display sinuosity. An aggregate group comprised of unvegetated channels with either relatively low levels of Total Tree Scores or with a higher tree cover combined with low bank face and top complexity. Unvegetated Low Complexity: ULC Mainly artificial straight planforms. Channels dominated by algae Algal Channels: ALG Artificial planforms usually straight but some display sinuosity. Vegetated channels with high Total Tree Scores equivalent to semi-continuous – continuous tree cover. Vegetated High Trees: VHT Mainly artificial straight planforms with some natural planforms. Vegetated channels with low Total Tree Scores and low bank face BANKVEG and top BANKVEG indices. Vegetated Low Complexity: VLC Mainly artificial straight channels. Vegetated channels with low Total Tree Scores and a higher bank face than bank top complexity Vegetated Mod Complexity: VMC2 Mainly sinuous channels, either natural or artificial. Vegetated channels with low Total Tree Scores representing isolated scattered to occasional clumps, and a higher mean bank top than bank face vegetation complexity Vegetated Mod Complexity: VMC1 Description of Broad Engineering Characteristics Description of Discriminating Primary (Vegetation) Indicators Group Name: Abbreviation
      • three broad secondary environmental indicators (Materials, Physical Habitat, Vegetation)
      • all are associated with the type of engineering to some degree
      • the strongest associations are with Materials and the weakest are with Vegetation.
      • Thus, the indicators can be used to consider the consequences of changes in engineering and in vegetation and pollution management.
      The classifications illustrate:
    • Index Immobile Substrate Index Bank Protection (Inverse of Index No Bank Protection) BANKCAL SEDCAL Dominant Protection Type (Proportion OMP, Proportion SOL) MATERIALS CLASS < 8 ≥ 8 ≤ 1 > 1 ≤ 7 > 7 ≥ 9 ≥ -1.5 <-1.5 OPEN MATRIX SOLID SNF SNC SNM LE EN ME HE ≥ 2.5 < 2.5
    • Index Artificial Bank Profiles Index Natural Bank Profiles Number of Habitat Types PHYSICAL CLASS ≤ 5 > 5 ≥ 9 < 9 >5 ≤ 5 ≤ 7 >7 1 – 2 3 - 4 5+ SNS SNA RC US UM UA
    • Dominant Vegetation Type Total Tree Score Average BANKVEG (Face) Average BANKVEG (TOP) VEGETATION CLASS OTHER ALGAE NONE ≤ 6 >6 ≤ 6 >6 >5 ≤ 5 ≤ 6.5 >6.5 ≤ 4 > 4 <6 ≥ 6 UHC ULC UMC ALG VHT ≤ 4 VLC VMC2 VMC1
    • DEVELOPING A SCORING SYSTEM FOR MANAGING URBAN RIVER STRETCHES
      • Required to combine the different classifications to produce a single index of the overall quality of a stretch.
      • The scores assigned to the materials classes reflect the change from semi-natural (score = 1) to heavily engineered stretches (score = 5).
      • Scores assigned to the physical classes reflect the degree to which the channel has been modified and the degree to which the channel is recovering either some or all of its physical habitat features.
      • Scores assigned to the vegetation classes reflect the level and type of in-channel vegetation, and the complexity of the riparian vegetation.
      • A vegetated channel is more desirable than an unvegetated channel (except Algal channels).
      • A complex riparian habitat is more desirable than a uniform one.
      • A moderate to high tree cover is preferable to either no trees or a channel completely shaded by trees.
      • With the exception of the ALG class, a mixture of these vegetation classes is required at the catchment or sector level, to provide variation along the river.
    • 7 ALG (algal) 6 ULC (unvegetated low complexity) 5 HE (Heavily engineered) 5 VLC (Vegetated low complexity) 6 US (uniform stable) 4 ME (moderately engineered) 4 UMC (unvegetated moderate complexity) 5 UM (uniform moderately active) 4 EN (engineered) 3 UHC (unvegetated high complexity) 4 UA (uniform active) 2 LE (lightly engineered) 2 VHT (vegetated high trees) 3 SNS (semi-natural stable) 2 SNM (semi-natural mixed) 1 VMC2 (vegetated moderate complexity) 2 RC (recovering) 1 SNC (semi-natural coarse) 1 VMC1 (vegetated moderate complexity) 1 SNA (semi-natural active) 1 SNF (semi-natural fine) Score Class Score Class Score Class VEGETATION PHYSICAL HABITAT MATERIALS
    • SCORES & MANAGEMENT RECOMMENDATIONS FOR URBAN RIVER STRETCHES Stretches with varying levels of engineering, but displaying some level of either recovery or activity, with little vegetation complexity or too much tree cover. The recommendation is, where possible, to reduce the levels of immobile substrates and bank materials and increase sinuosity. Tree cover and bank top and face vegetation should be managed to provide increased variety and complexity. These channels show moderate to high levels of activity and should be targeted for rehabilitation where opportunities arise. M: SNC/SNM/LE/ME P: RC/UA/US/SNS V: ULC/UHC/VMC2 9-11 Average Semi-natural, recovering and a few uniform channels displaying some activity, with good vegetation complexity and tree cover. The recommendation is to remove any remaining reinforcement to allow the channel to recover more freely. These stretches should also be protected from further development. M: SNC/LE P: RC/SNS/UA/UM V: VMC1 & 2/ UHC/VHT 6-8 Good Predominantly semi-natural and recovering stretches, with good vegetation and tree cover. The recommendation is to leave these stretches free of management and to protect them from development. M: SNC/SNF P: SNA/RC/SNS V: VMC1 & 2/ UHC/VHT 3-5 Very Good MANAGEMENT RECOMMENDATIONS ASSOCIATED CLASSES (M=Materials; P=Physical; V=Vegetation) SCORE GRADE
    • SCORES & MANAGEMENT RECOMMENDATIONS cont.. Heavily engineered, algal-dominated, stable channels with little vegetation complexity. Significant improvements to water quality should be initiated, followed by a detailed assessment of rehabilitation needs. Aesthetic rehabilitation may be the best option in the short term. Wherever possible this should be followed by some reduction in the level of reinforcement and an increase in channel sinuosity. M: HE P: US V: ULC/ALG 17-18 Very Poor Moderate to heavily engineered channels with low to moderate levels of activity, low complexity of bank vegetation, few trees and often algal dominated channels. The recommendation is to assess the water quality for improvement of in-channel vegetation diversity, and undertake a detailed assessment of the level of rehabilitation required to improve the physical condition of the channel. Where possible, a reduction of reinforcement level and/or type and an increase in sinuosity of the channel is desirable. Tree planting should be introduced to improve riparian complexity. M: HE/ME/EN P: UM/US/UA V: ULC/UMC/ VLC/ALG 14-16 Poor Stretches with varying levels of modification showing high levels of activity, combined with low bank vegetation complexity or algal dominated channels with few trees. These channels show moderate to high levels of activity and should be targeted for rehabilitation where opportunities arise. The recommendation is to reduce or alter the level and/or type of reinforcement and increase channel sinuosity where possible. Increased tree cover through planting, and management of the bank face and top vegetation to improve complexity should be undertaken. Algal dominated channels should also be assessed for improvements to water quality. M: SNC/LE/HE P: UA/UM V: ULC/UMC/ ALG 12-13 Below Average MANAGEMENT RECOMMENDATIONS ASSOCIATED CLASSES (M=Materials; P=Physical; V=Vegetation) SCORE GRADE
    • VERY GOOD GOOD
    • AVERAGE BELOW AVERAGE
    • POOR VERY POOR
    • A SCORING SYSTEM FOR SCENARIO MODELLING
      • Direct human modification can only be applied to certain components of the decision trees, since others are not directly physically manipulable:
      • Materials: All components of the Materials decision tree (exc. BANKCAL and SEDCAL) can be directly manipulated. The decision tree can be used to assess a new Materials score based on a scenario of changed engineering within 5 classes.
      • Physical Habitat: The proportion of artificial bank profiles can be manipulated but the proportion of natural bank profiles cannot. However, one important reason why there are more natural/active bank profiles in some classes than in others is the level of sinuosity of the channels. sinuous, Therefore a highly sinuous, intermediate or straight channel planforms have been introduced to discriminate between these three groups of classes for scenario modelling.
      • Vegetation: Algal channels reflect relatively poor water quality and so cannot be influenced by physical modification of reaches. For the other classes, presence or absence of in-channel vegetation cover cannot easily be manipulated, although shading of the channel will reduce the in-channel vegetation. Tree cover and the complexity of the riparian vegetation (BANKVEG) are manipulable factors that discriminate between the classes. Thus, the presence or absence of in-channel vegetation cover provides a context around which manipulation of vegetation on the banks can be undertaken.
    • ≤ 4 >4 ≤ 4 <6 ≤ 6 ≤ 6 >6 >6 >6 ≤ 6 ≤ 6 or >6 Average BANKVEG (Top) Total Tree Score Average BANKVEG (Face) Dominant Vegetation Type Vegetation 1 2 4 5 Natural relatively high sinuosity Artificial moderate sinuosity Artificial low sinuosity Artificial straight ≤ 50% >50% >50% SNS, SNA RC UA US,UM Sinuosity Proportion Artificial Profiles Physical YES Predominantly Solid Protection 1 1 2 3 4 5 6 7 >5 >6.5 ≤ 6.5 ≤ 5 Vegetated Vegetated Vegetated Unvegetated Unvegetated Vegetated Unvegetated Algae VMC1 VMC2 VHT UHC UMC VLC ULC ALG 1 2 4 4 5 YES ≤ 10% >10% ≤ 70% >70% >70% ≥ 90% <80% <80% <80% <80% ≥ 80% SN (F, M & C) LE EN ME HE Predominantly Open Matrix Protection Proportion Bank Protection Proportion Immobile Substrate Materials Score Threshold Values for Discriminating Indicators Class
      • Certain changes in the engineering of reaches (i) may be inherently unstable because of the energy of river flows, or (ii) may not meet flood-defence requirements.
      • If water quality is low, changes in physical habitat are unlikely to yield any ecological benefit.
      • Even if water quality and flow regimes do not present constraints on the outcomes of changes in the secondary environmental indicators, land use and land availability may restrict the space available for such changes.
      TERTIARY INDICATORS NETWORK SCALE WATER QUALITY, WATER QUANTITY, FLOODPLAIN CONSTRAINTS
      • FLOW-RELATED INDICATORS illustrate constraints in:
      • achieving flood defence targets (high flow magnitude),
      • ensuring that any stretch–scale modifications do not result in major channel instabilities (high flow energy),
      • ensuring that there is sufficient aquatic habitat to support species during low flows (low flow magnitude and depth).
      • WATER QUALITY INDICATORS illustrate constraints in:
      • Water quality that is too low for ecological benefits to accrue from physical habitat improvement
      • Water quality that may be close to threshold conditions
      • BIOTIC INDICATORS illustrate constraints in:
      • propagule availability
      • the level of degradation at a site due to water quality problems
      • FLOODPLAIN LANDUSE INDICATORS illustrate constraints in:
      • the spatial extent of land available for channel modification
      • the quality of available land
      • The data generated by the URS, the synthetic indices and the classifications provide a range of important indicators for the assessment of the quality of urban rivers and their potential for enhancement or rehabilitation.
      • The analyses indicate the over-riding impact of engineering on the physical character of urban rivers and thus the potential to investigate potential changes in physical character as a consequence of changes in engineering design
      • The robustness of both the URS methodology and the classifications derived from it have been illustrated by the similarity in the classifications derived from more than one survey of the River Tame (West Midlands) and from a survey of the River Ravensbourne (London).
      • The entire methodology will be tested on two other urban river systems in mainland Europe
      CONCLUSIONS