Set an end of system flow target (equivalent to the bottom of baseflow) in regulated valleys (Gwydir, Namoi and Border Rivers) to protect baseflows to enable baseflow targets in the Barwon-Darling to be achieved in non-dry times. The end of system flow achieved through limitations on supplementary and floodplain harvesting access in the first instance and releasing a proportion of daily inflows to the dams(s) in each valley to meet the end of system flow target. This approach only makes releases each day if there is sufficient inflow to the storages over the preceding 24 hours and does not require reserves to be set aside. Releases not made in periods where the rolling 30-day average dam inflows fall below the 75th percentile (the dry inflow trigger). The Panel has not included a recommendation for an end of system flow rule for the regulated Macquarie-Cudgegong as the end of the system flows discharge into the Macquarie Marshes. 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.

Modelling that was used to inform the development of the connectivity actions in the Western Regional Water Strategy. Modelling base case provides the diversions under current conditions (Water Sharing Plan rules). The base case provides daily flows and diversions for the period 1895 to 2020 for the Barwon-Darling and the following regulated tributary valleys NSW Border Rivers Gwydir Namoi Macquarie Preliminary modelling analysis (bookend analysis) done for the Western Regional Water Strategy to understand the upper limit of possible connectivity benefits from imposing water restrictions in the Barwon-Darling and upstream regulated tributary rivers. This modelling assessed the change in daily flows from restricting all supplementary access in the tributary valleys, as well as Class A, B and C access 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.

This dataset contains best endeavours aggregation and depiction of regulated river water sources derived from In Force Water Sharing Plans (WSP) for Regulated systems, as gazetted under the NSW Water Management Act 2000. PLEASE NOTE: In the case of any discrepancy between this digital dataset and the published Water Sharing Plan (accessible on the www.legislation.nsw.gov.au site) the instrument as made by the Minister remains the authoritative source and should be used to both interpret the intent of the Plan and in subsequent decision making. Best endeavours have been made in collating relevant Water Sharing Plan boundary and attribution contained in this dataset. However, no warranty is provided as to the accuracy or currency of this representation. The department does not warrant and is not liable for the use of this material as per the licenced sharing conditions CC-BY 4.0.

A hydrodynamic, water-temperature, and water-quality model (CE-QUAL-W2; Wells, 2020) of the Link-Keno reach of the Klamath River (Oregon) was used for calendar years 2006–15 to run a series of base and recirculation scenarios. These model runs were implemented to test alternative scenarios for routing some of the Klamath Straits Drain discharge into Ady Canal. The model scenarios were configured for baseline conditions and three different sets of recirculation scenarios, including the maximum year-round recirculation without discharge limits (scenario 1), limited year-round recirculation fixed by the current pipe flow configuration from Klamath Straits Drain into Ady Canal (scenario 2), and limited seasonal recirculation (May-September), also fixed by the current pipe flow configuration (scenario 3). For calendar years 2012–15, a separate CE-QUAL-W2 model for the Klamath Straits Drain was used in lieu of the Klamath Straits Drain as a tributary directly into the Link-Keno reach of the Klamath River CE-QUAL-W2 model. Original calibration and simulation of the Klamath Straits Drain model was documented in Sullivan and Rounds (2018). Original calibration and simulation of the Link-Keno reach of the Klamath River was documented in Sullivan and others (2011). These recirculation scenarios will be used by the United States Bureau of Reclamation to better understand the effects of recirculating Klamath Straits Drain discharge into Ady Canal on constituent loads of total nitrogen, total phosphorus, and the 5-day biochemical oxygen demand (BOD5).

A hydrodynamic, water-temperature, and water-quality model (CE-QUAL-W2; Wells, 2020) of the Link-Keno reach of the Klamath River (Oregon) was used for calendar years 2006–15 to run a series of base and recirculation scenarios. These model runs were implemented to test alternative scenarios for routing some of the Klamath Straits Drain discharge into Ady Canal. The model scenarios were configured for baseline conditions and three different sets of recirculation scenarios, including the maximum year-round recirculation without discharge limits (scenario 1), limited year-round recirculation fixed by the current pipe flow configuration from Klamath Straits Drain into Ady Canal (scenario 2), and limited seasonal recirculation (May-September), also fixed by the current pipe flow configuration (scenario 3). For calendar years 2012–15, a separate CE-QUAL-W2 model for the Klamath Straits Drain was used in lieu of the Klamath Straits Drain as a tributary directly into the Link-Keno reach of the Klamath River CE-QUAL-W2 model. Original calibration and simulation of the Klamath Straits Drain model was documented in Sullivan and Rounds (2018). Original calibration and simulation of the Link-Keno reach of the Klamath River was documented in Sullivan and others (2011). These recirculation scenarios will be used by the United States Bureau of Reclamation to better understand the effects of recirculating Klamath Straits Drain discharge into Ady Canal on constituent loads of total nitrogen, total phosphorus, and the 5-day biochemical oxygen demand (BOD5).

Complete Report

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).