Combination of the extended resumption of flow rule inclusive of additional trigger sites, end of system flow target translucency releases and connectivity environmental water allowance Bourke flow trigger. Note: See Analysis of the Connectivity Expert Panel Recommendations: Hydrologic modelling assessment.pdf (attached) for more details. Note: If you would like to ask a question, make any suggestions, or tell us how you are using this dataset, please visit the NSW Water Hub which has an online forum you can join.

The Panel recommended that the Gwydir, Namoi and NSW Border Rivers regulated water sharing plans should include a ‘connectivity’ environmental water allowance (EWA) to provide pulses as needed for water quality and other environmental outcomes during dry times. Replenishment releases triggered by the dam inflows falling below the 75th percentile on average over 30 days. Up to two large replenishment releases of 20 GL made each year in each valley triggered by low inflows into storage dams. Release triggered on 31 October and 28 February each year if the inflows to the valley storage dams are less than the 75th percentile. Releases are made to achieve at least a week of flows at Bourke with peak flows above 972 ML/d for up to 10 days and at least 30 GL total event volume. A connectivity environmental water allowance was not considered for the regulated Macquarie River as it empties into the Macquarie Marshes rather than the Barwon-Darling. Note: See Analysis of the Connectivity Expert Panel Recommendations: Hydrologic modelling assessment.pdf (attached) for more details. Note: If you would like to ask a question, make any suggestions, or tell us how you are using this dataset, please visit the NSW Water Hub which has an online forum you can join.

Flow rates for imposing restrictions have been set at below baseflow for 90 consecutive days at trigger sites, flow rates for lifting restrictions have been set at the lower small fresh threshold for restriction trigger sites; flow rates must exceed the small fresh threshold for 14 days at restriction trigger sites for lifting restrictions. Supplementary and floodplain harvesting has been restricted in the regulated NSW Border Rivers, Namoi, Gwydir and Macquarie River systems when the closest downstream section in the Barwon –Darling is restricted. The 30 GL cumulative flow trigger at Bourke for lifting restrictions has been removed. Three additional trigger locations included as recommended by Panel: Mungindi, Collarenebri and Louth. Note: See Analysis of the Connectivity Expert Panel Recommendations: Hydrologic modelling assessment.pdf (attached) for more details. Note: If you would like to ask a question, make any suggestions, or tell us how you are using this dataset, please visit the NSW Water Hub which has an online forum you can join.

This time series hydrologic modelling was done at the direction of the Connectivity Expert Panel. The panel used the modelling data to inform the proposed protection of base flow and resumption of flow targets presented in Connectivity Expert Panel Final Report 2024. The Connectivity Expert Panel was convened by the Minister for Water to provide advice on the adequacy and potential improvements to rules in the NSW Northern Basin water sharing plans that might materially impact on hydrological connectivity. The Panel was asked to consider the adequacy of current and proposed targets and triggers for restricting supplementary and floodplain harvesting, as well as A, B and C class licences in the Barwon-Darling. Note: If you would like to ask a question, make any suggestions, or tell us how you are using this dataset, please visit the NSW Water Hub which has an online forum you can join.

Long-term average annual extraction limit (LTAAEL) is a regulatory limit set on annual water extractions from a river system. It ensures that average extractions over the long term are sustainable, and thus help prevent environmental degradation. In NSW these limits are defined by water sharing plans (WSPs). Every WSP outlines how the water in a river system will be shared over a 10-year period. They also define: • how LTAAEL compliance is to be assessed for each river system • what conditions will trigger noncompliance action • what compliance action can be taken. The Natural Resources Commission regularly reviews all WSPs to ensure extractions from each river system are within the limits set, and the Murray-Darling Basin Authority reviews sustainable diversion limit (SDL) compliance each year. To assess compliance, we model LTAAEL using a model that has been configured to represent the development and management rules defined by a system WSP (this refers to as LTAAEL model). We then compare this modelled LTAAEL with the modelled under current conditions long-term average annual extractions (LTAAEs) (which are usually those modelled by the annual permitted take, or APT, model). Although, the LTAAEL includes multiple types of water use, the compliance assessment is based on the total. We do this annually using the best available models, and the outcomes are published on the DPE website. Where river system’s LTAAE exceed LTAAEL, the system is considered noncompliant. If the noncompliance trigger conditions in the WSP are met, noncompliance action is taken. The data set provided contains flows at several gauges in each river system, as simulated by the annually extended LTAAEL model. Notwithstanding the model’s inherent limitations, these are a fair representation of those we would expect under WSP operation and development conditions. They can be compared with flows simulated by other key scenario models, such as annual permitted take (APT) model or without development (WOD) model.

Optimal hydrograph separation (OHS) is a two-component, hydrograph separation method that uses a two-parameter, recursive digital filter (RDF) constrained via chemical mass balance to estimate the base flow contribution to a stream or river (Rimmer and Hartman, 2014; Raffensperger et al., 2017). A recursive digital filter distinguishes between high-frequency and low-frequency discharge data within a hydrograph, where high-frequency data corresponds to quick flow or storms and low-frequency data corresponds to base flow. The two parameters within the RDF are alpha and beta, both are unitless. Alpha is defined as the recession constant and typically found through recession analysis. For the purposes of this data release and study, we derived alpha from a groundwater flow coefficient (gwflow_coef) defined in the National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS) (Regan et al., 2018). The second parameter, beta, is defined as the maximum value of the base flow index (Eckhardt, 2005). Beta is optimized using specific conductance and mass balance techniques, where a hydrograph is split into quick flow and base flow and specific conductance values are proposed for these streamflow components. OHS uses two model types to estimate base flow specific conductance from stream specific conductance, referred to as 'SCfit' and 'sin-cos' model types. The 'SCfit' model type uses a peak-fitting algorithm to define time periods where the stream is entirely comprised of base flow, whereas the 'sin-cos' model type emulates seasonal variation in streamflow specific conductance with a sine-cosine function to pinpoint when base flow contributes to streamflow. For more information and equations regarding model type and OHS methods, please see the associated publication (Foks et al., 2019). OHS was applied to 1076 stream gages within the conterminous United States (CONUS) where daily streamflow and daily or discrete measurements of specific conductance were collected. Gages were selected for this method if they were of "reference quality" as defined by the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES-II) dataset (Falcone, 2011). Of these 1076 sites, 825 had "successful" OHS models - implying good agreement between observed and simulated stream specific conductance. This data release contains the results of applying OHS to hundreds of stream gages of varying watershed characteristics, summary of watershed and hydro-climatological characteristics for each site (Falcone, 2011; USGS, 2003), and a comparison of OHS-defined base flow to base flow -analogous flow components within the NHM-PRMS (gwres_flow and slow_flow) (Regan et al., 2018; Regan et al., 2019). For this data release and study, comparisons of OHS-defined base flow were made to the "by HRU" calibration of the NHM-PRMS (Hay, 2019).

Optimal hydrograph separation (OHS) is a two-component, hydrograph separation method that uses a two-parameter, recursive digital filter (RDF) constrained via chemical mass balance to estimate the base flow contribution to a stream or river (Rimmer and Hartman, 2014; Raffensperger et al., 2017). A recursive digital filter distinguishes between high-frequency and low-frequency discharge data within a hydrograph, where high-frequency data corresponds to quick flow or storms and low-frequency data corresponds to base flow. The two parameters within the RDF are alpha and beta, both are unitless. Alpha is defined as the recession constant and typically found through recession analysis. For the purposes of this data release and study, we derived alpha from a groundwater flow coefficient (gwflow_coef) defined in the National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS) (Regan et al., 2018). The second parameter, beta, is defined as the maximum value of the base flow index (Eckhardt, 2005). Beta is optimized using specific conductance and mass balance techniques, where a hydrograph is split into quick flow and base flow and specific conductance values are proposed for these streamflow components. OHS uses two model types to estimate base flow specific conductance from stream specific conductance, referred to as 'SCfit' and 'sin-cos' model types. The 'SCfit' model type uses a peak-fitting algorithm to define time periods where the stream is entirely comprised of base flow, whereas the 'sin-cos' model type emulates seasonal variation in streamflow specific conductance with a sine-cosine function to pinpoint when base flow contributes to streamflow. For more information and equations regarding model type and OHS methods, please see the associated publication (Foks et al., 2019). OHS was applied to 1076 stream gages within the conterminous United States (CONUS) where daily streamflow and daily or discrete measurements of specific conductance were collected. Gages were selected for this method if they were of "reference quality" as defined by the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES-II) dataset (Falcone, 2011). Of these 1076 sites, 825 had "successful" OHS models - implying good agreement between observed and simulated stream specific conductance. This data release contains the results of applying OHS to hundreds of stream gages of varying watershed characteristics, summary of watershed and hydro-climatological characteristics for each site (Falcone, 2011; USGS, 2003), and a comparison of OHS-defined base flow to base flow -analogous flow components within the NHM-PRMS (gwres_flow and slow_flow) (Regan et al., 2018; Regan et al., 2019). For this data release and study, comparisons of OHS-defined base flow were made to the "by HRU" calibration of the NHM-PRMS (Hay, 2019).

Optimal hydrograph separation (OHS) is a two-component, hydrograph separation method that uses a two-parameter, recursive digital filter (RDF) constrained via chemical mass balance to estimate the base flow contribution to a stream or river (Rimmer and Hartman, 2014; Raffensperger et al., 2017). A recursive digital filter distinguishes between high-frequency and low-frequency discharge data within a hydrograph, where high-frequency data corresponds to quick flow or storms and low-frequency data corresponds to base flow. The two parameters within the RDF are alpha and beta, both are unitless. Alpha is defined as the recession constant and typically found through recession analysis. For the purposes of this data release and study, we derived alpha from a groundwater flow coefficient (gwflow_coef) defined in the National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS) (Regan et al., 2018). The second parameter, beta, is defined as the maximum value of the base flow index (Eckhardt, 2005). Beta is optimized using specific conductance and mass balance techniques, where a hydrograph is split into quick flow and base flow and specific conductance values are proposed for these streamflow components. OHS uses two model types to estimate base flow specific conductance from stream specific conductance, referred to as 'SCfit' and 'sin-cos' model types. The 'SCfit' model type uses a peak-fitting algorithm to define time periods where the stream is entirely comprised of base flow, whereas the 'sin-cos' model type emulates seasonal variation in streamflow specific conductance with a sine-cosine function to pinpoint when base flow contributes to streamflow. For more information and equations regarding model type and OHS methods, please see the associated publication (Foks et al., 2019). OHS was applied to 1076 stream gages within the conterminous United States (CONUS) where daily streamflow and daily or discrete measurements of specific conductance were collected. Gages were selected for this method if they were of "reference quality" as defined by the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES-II) dataset (Falcone, 2011). Of these 1076 sites, 825 had "successful" OHS models - implying good agreement between observed and simulated stream specific conductance. This data release contains the results of applying OHS to hundreds of stream gages of varying watershed characteristics, summary of watershed and hydro-climatological characteristics for each site (Falcone, 2011; USGS, 2003), and a comparison of OHS-defined base flow to base flow -analogous flow components within the NHM-PRMS (gwres_flow and slow_flow) (Regan et al., 2018; Regan et al., 2019). For this data release and study, comparisons of OHS-defined base flow were made to the "by HRU" calibration of the NHM-PRMS (Hay, 2019).

Optimal hydrograph separation (OHS) is a two-component, hydrograph separation method that uses a two-parameter, recursive digital filter (RDF) constrained via chemical mass balance to estimate the base flow contribution to a stream or river (Rimmer and Hartman, 2014; Raffensperger et al., 2017). A recursive digital filter distinguishes between high-frequency and low-frequency discharge data within a hydrograph, where high-frequency data corresponds to quick flow or storms and low-frequency data corresponds to base flow. The two parameters within the RDF are alpha and beta, both are unitless. Alpha is defined as the recession constant and typically found through recession analysis. For the purposes of this data release and study, we derived alpha from a groundwater flow coefficient (gwflow_coef) defined in the National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS) (Regan et al., 2018). The second parameter, beta, is defined as the maximum value of the base flow index (Eckhardt, 2005). Beta is optimized using specific conductance and mass balance techniques, where a hydrograph is split into quick flow and base flow and specific conductance values are proposed for these streamflow components. OHS uses two model types to estimate base flow specific conductance from stream specific conductance, referred to as 'SCfit' and 'sin-cos' model types. The 'SCfit' model type uses a peak-fitting algorithm to define time periods where the stream is entirely comprised of base flow, whereas the 'sin-cos' model type emulates seasonal variation in streamflow specific conductance with a sine-cosine function to pinpoint when base flow contributes to streamflow. For more information and equations regarding model type and OHS methods, please see the associated publication (Foks et al., 2019). OHS was applied to 1076 stream gages within the conterminous United States (CONUS) where daily streamflow and daily or discrete measurements of specific conductance were collected. Gages were selected for this method if they were of "reference quality" as defined by the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES-II) dataset (Falcone, 2011). Of these 1076 sites, 825 had "successful" OHS models - implying good agreement between observed and simulated stream specific conductance. This data release contains the results of applying OHS to hundreds of stream gages of varying watershed characteristics, summary of watershed and hydro-climatological characteristics for each site (Falcone, 2011; USGS, 2003), and a comparison of OHS-defined base flow to base flow -analogous flow components within the NHM-PRMS (gwres_flow and slow_flow) (Regan et al., 2018; Regan et al., 2019). For this data release and study, comparisons of OHS-defined base flow were made to the "by HRU" calibration of the NHM-PRMS (Hay, 2019).

Time series of modelled daily flow rates in megalitres per day across the NSW river systems – Border Rivers Valley. Individual for each available river gauge data sets are attained via best available at the time of publishing hydrologic model/s and over the historic climate period (usually from early to mid-1890s to a water year previous to the date of publishing). Specific scenario data sets are expected to be updated annually and subject to quality requirements may be used in relevant studies. The naming structure of the individual files is "Gauge number_watercourse@Gauge name".