Display Name: Torrent Fish - Modelled Distribution
Description: The Fish Predicted Distribution data gives an indication of where freshwater fish may be present in rivers and streams. Created by linking the New Zealand Freshwater Fish Database (NZFFD) to the REC 2 data. For more information please see the report below.objective://id:A3796708@objective.envbop.netFish Distribution FieldsField NameDescriptionangaus_Prob_EFPredicted probability of capture of shortfin eels (Anguilla australis) with electric fishing.angdie_Prob_EFPredicted probability of capture of longfin eels (Anguilla dieffenbachii) with electric fishing.angdie_Prob_NETPredicted probability of capture of longfin eels (Anguilla dieffenbachii) with netting methods.angdie_Prob_VISPredicted probability of capture of longfin eels (Anguilla dieffenbachii) with visual methods.caraur_Prob_EFPredicted probability of capture of goldfish (Carassius auratus) with electric fishing.caraur_Prob_EF_RESPredicted probability of capture of goldfish (Carassius auratus) with electric fishing from within their range of occurrence.chefos_Prob_EFPredicted probability of capture of torrentfish (Cheimarrichthys fosteri) with electric fishing.galano_Prob_EFPredicted probability of capture of roundhead galaxias (Galaxias anomalus) with electric fishing.galano_Prob_EF_RESPredicted probability of capture of roundhead galaxias (Galaxias anomalus) with electric fishing from within their range of occurrence.galarg_Prob_EFPredicted probability of capture of giant kokopu (Galaxias argenteus) with electric fishing.galbre_Prob_EFPredicted probability of capture of koaro (Galaxias brevipinnis) with electric fishing.galdep_Prob_EFPredicted probability of capture of flathead galaxias (Galaxias depressiceps) with electric fishing.galdep_Prob_EF_RESPredicted probability of capture of flathead galaxias (Galaxias depressiceps) with electric fishing from within their range of occurrence.galdiv_Prob_EFPredicted probability of capture of dwarf galaxias (Galaxias divergens) with electric fishing.galdiv_Prob_EF_RESPredicted probability of capture of dwarf galaxias (Galaxias divergens) with electric fishing from within their range of occurrence.galfas_Prob_EFPredicted probability of capture of banded kokopu (Galaxias fasciatus) with electric fishing.galgol_Prob_EFPredicted probability of capture of gollum galaxias (Galaxias gollumoides) with electric fishing.galgol_Prob_EF_RESPredicted probability of capture of gollum galaxias (Galaxias gollumoides) with electric fishing from within their range of occurrence.galmac_Prob_EFPredicted probability of capture of inanga (Galaxias maculatus) with electric fishing.galmar_Prob_EFPredicted probability of capture of bignose galaxias (Galaxias macronasus) with electric fishing.galmar_Prob_EF_RESPredicted probability of capture of bignose galaxias (Galaxias macronasus) with electric fishing from within their range of occurrence.galpau_Prob_EFPredicted probability of capture of alpine galaxias (Galaxias paucispondylus) with electric fishing.galpau_Prob_EF_RESPredicted probability of capture of alpine galaxias (Galaxias paucispondylus) with electric fishing from within their range of occurrence.galpos_Prob_EFPredicted probability of capture of shortjaw kokopu (Galaxias postvectis) with electric fishing.galpro_Prob_EFPredicted probability of capture of upland longjaw galaxias (Galaxias prognathus) with electric fishing.galpro_Prob_EF_RESPredicted probability of capture of upland longjaw galaxias (Galaxias prognathus) with electric fishing from within their range of occurrence.galspd_Prob_EFPredicted probability of capture of Otago flathead galaxias (Galaxias sp. D) with electric fishing.galspd_Prob_EF_RESPredicted probability of capture of Otago flathead galaxias (Galaxias sp. D) with electric fishing from within their range of occurrence.galspn_Prob_EFPredicted probability of capture of Northern flathead galaxias (Galaxias sp. N) with electric fishing.galspn_Prob_EF_RESPredicted probability of capture of Northern flathead galaxias (Galaxias sp. N) with electric fishing from within their range of occurrence.galvul_Prob_EFPredicted probability of capture of Canterbury galaxias (Galaxias vulgaris) with electric fishing.galvul_Prob_EF_RESPredicted probability of capture of Canterbury galaxias (Galaxias vulgaris) with electric fishing from within their range of occurrence.gamaff_Prob_EFPredicted probability of capture of mosquito fish (Gambusia affinis) with electric fishing.gamaff_Prob_EF_RESPredicted probability of capture of mosquito fish (Gambusia affinis) with electric fishing from within their range of occurrence.geoaus_Prob_EFPredicted probability of capture of lamprey (Geotria australis) with electric fishing.gobbas_Prob_EFPredicted probability of capture of crans bully (Gobiomorphus basalis) with electric fishing.gobbas_Prob_EF_RESPredicted probability of capture of crans bully (Gobiomorphus basalis) with electric fishing from within their range of occurrence.gobbre_Prob_EFPredicted probability of capture of upland bully (Gobiomorphus breviceps) with electric fishing.gobbre_Prob_EF_RESPredicted probability of capture of upland bully (Gobiomorphus breviceps) with electric fishing from within their range of occurrence.gobcot_Prob_EFPredicted probability of capture of common bully (Gobiomorphus cotidianus) with electric fishing.gobgob_Prob_EFPredicted probability of capture of giant bully (Gobiomorphus gobioides) with electric fishing.gobhub_Prob_EFPredicted probability of capture of bluegill bully (Gobiomorphus hubbsi) with electric fishing.gobhut_Prob_EFPredicted probability of capture of redfin bully (Gobiomorphus huttoni) with electric fishing.oncmyk_Prob_EFPredicted probability of capture of rainbow trout (Oncorhynchus mykiss) with electric fishing.oncmyk_Prob_EF_RESPredicted probability of capture of rainbow trout (Oncorhynchus mykiss) with electric fishing from within their range of occurrence.onctsh_Prob_EFPredicted probability of capture of chinook salmon (Oncorhynchus tshawytscha) with electric fishing.perflu_Prob_EFPredicted probability of capture of perch (Perca fluviatilis) with electric fishing.perflu_Prob_EF_RESPredicted probability of capture of perch (Perca fluviatilis) with electric fishing from within their range of occurrence.retret_Prob_EFPredicted probability of capture of common smelt (Retropinna retropinna) with electric fishing.rhoret_Prob_EFPredicted probability of capture of black flounder (Rhombosolea retiaria) with electric fishing.salfon_Prob_EFPredicted probability of capture of brook char (Salvelinus fontinalis) with electric fishing.salfon_Prob_EF_RESPredicted probability of capture of brook char (Salvelinus fontinalis) with electric fishing from within their range of occurrence.saltru_Prob_EFPredicted probability of capture of brown trout (Salmo trutta) with electric fishing.saltru_Prob_EF_RESPredicted probability of capture of brown trout (Salmo trutta) with electric fishing from within their range of occurrence.saltru_Prob_NETPredicted probability of capture of brown trout (Salmo trutta) with netting methods.saltru_Prob_NET_RESPredicted probability of capture of brown trout (Salmo trutta) with netting methods from within their range of occurrence.The River Environment Classification (REC) is a database of catchment spatial attributes, summarised for every segment in New Zealand's network of rivers. The attributes were compiled for the purposes of river classification, while the river network description has been used to underpin models.Typically, models (e.g. CLUES and TopNet) would use the dendritic (branched) linkages of REC river segments to perform their calculations. Since its release and use over the last decade, some errors in the location and connectivity of these linkages have been identified. The current revision corrects those errors, and updates a number of spatial attributes with the latest data.REC2 provides a recut framework of rivers for modelling and classification. It is built on a newer version of the 30m digital elevation model, in which the original 20m contours were supplemented with, for example, more spot elevation data and a better coastline contour. Boundary errors were minimised by processing contiguous areas (such as the whole of the North Island) together, which wasn't possible a decade ago. Major updates include the revision of catchment land use information, by overlaying with the latest land cover database (LCDB3, current as at 2008), and the update of river and rainfall statistics with data from 1960-2006.REC FieldsField NameField AliasDescriptionnzsegmentNZ SegmentReach identifier to be used with REC2 (supercedes nzreach in REC1).StreamOrderStream OrderA number describing the Strahler order a reach in a network of reaches.HydroIDHydro IDSegment number for each reachNextDownIDNext Down IDSegment number of the most downstream reachCatchmentAreaM2Catchment Area (m2)Watershed area in m2CumulativeAreaM2Cumulative Upstream Area (m2)Area upstream of a reach (and including this reach area) in m2.LengthDownstreamLength Downstream (m)The distance to coast from any reach to its outlet reach, where the river drains (m).HeadwaterHeadwater1 denotes that a stream is a “source” (headwater) stream. 0 for non-headwater streams.HydseqHydseqA unique number denoting the hydrological processing order of a river segment relative to others in the newtork.Euclid DistanceEuclid DistanceThe straight line distance of a reach from the reach “inlet” to its “outlet”.UpElevationUp Elevation (m asl)Height (asl) of the upstream end of a reach section in a watershed (m).DownElevationDown Elevation (m asl)Height (asl) of the downstream end of a reach section in a watershed (m).UpCoordinateXUp X CoordinateEasting of the upstream end of a river segment in m (NZTM2000).DownCoordinateXDown X CoordinateEasting of the downstream end of a river segment in m (NZTM2000).DownCoordinateYDown Y CoordinateNorthing of the downstream end of a river segment in m (NZTM2000).UpCoordinateYUp Y CoordinateNorthing of the upstream end of a river segment in m (NZTM2000).SinuositySinuosityActual distance divided by the straight line distancegiving the degree of curvature of the streamNZReach_REC1NZ Reach - REC1The REC1 identifiying number for the corresponding\closest reach from REC1 (can be used to retrieve the REC management classes)HeadwaterDistanceHeadwater Distance (m)Distance of the furthermost “source” or headwater reach from any reach (m).SegmentSlopeMeanSegment Slope (mean)Mean segment slope along length of reach.LIDLake IDLake Identifier number (LID) of overlapping lake.ReachTypeReach TypeA value of 2 is assigned if the segment is an outlet to the lake, otherwise 0 or null.FromNodeFrom NodeUnique number of preceding river segment's outlet node.ToNodeTo NodeUnique number of following river segment's inlet node.BOP_MFE14505Predictions.csv (objective://id:A3764116@objective.envbop.net)Some fields from this dataset have been joined to the REC 2.4 riverlines.These columns are hydrological predictions transferred from NZReach (REC_DN_v1) to nzsegment (REC_DN_v2.4) using an area correction as appropriate. The advantage of these data is that they were generated using the methods and predictor variables published in Booker and Woods (2014) and Booker (2013). The disadvantage is that one has to accept an uncertainty introduced as a result of mapping from REC_DN_v1 onto REC_DN_v2.4. For this reason the REC_DN_v1 NZReach from which each estimate has been transferred is supplied (see data in objective at the link above). The distance between each REC_DN_v1 NZReach and REC_DN_v2.4 segment is also supplied.Please do remember that hydrological estimates at ungauged sites can come with considerable uncertainties. These are quantified and discussed in the associated papers. FRE3NoWindowCount = predicted frequency of events exceeding three times the long-term median with no windows (n per year) from the random forest method as described in Booker (2013).Reference: Booker, D.J. (2013) Spatial and temporal patterns in the frequency of events exceeding three times the median flow (FRE3) across New Zealand. Journal of Hydrology (NZ), 52, 15-40.The following columns are predictions from the random forest method as described in Booker and Woods (2014), with mean daily flow data collated for that paper.Field NameField AliasDescriptionFRE3NoWindowCountFRE3 No Window CountThe number of floods per year that exceed 3x the mean flow. ‘No Windows’ mean no application of a minimum period between eventsFebFebAssume this has something to do with flow in February – but check with scientists for confirmation.Q5_normCumecsQ5 Normalised (cumecs)1 in 5 year 7 day low flow in cumecs normalised by upstream catchment area.Q5_norm_LperSecQ5 Normalised (l/s)As Q5_normCumecs but in litres/second (cumecs * 1000)Q50CumecsQ50 (cumecs)Median Flow - the flow which is exceeded 50 percent of the time.MALFCumecsMALF (cumecs)Total flow volume divided by the duration of the recordMALF_LperSecMALF (l/s)As MALFCumecsbut in litres/second (cumecs * 1000)MeanFlowCumecsMean Flow (cumecs)Total flow volume divided by the duration of the recordReference: Booker, D.J.; Woods, R.A. (2014) Comparing and combining physically-based and empirically-based approaches for estimating the hydrology of ungauged catchments. Journal of Hydrology DOI: 10.1016/j.jhydrol.2013.11.007.Note that a smearing factor was included in the back transformation calculation of flow variables with units of cumecs (m3s-1). See for further details, Booker, D.J. (2015) Hydrological indices for national environmental reporting. NIWA client report to Ministry for the Environment, CHC2015-015, March 2015, 39pp.