The River Risk Ratings provide a comprehensive view of how river condition and risk have been assessed across New South Wales over the past three decades. This collection brings together historic and contemporary datasets developed from the 1990s to the present, illustrating the evolution of assessment methodologies used to understand river health, hydrological stress, and ecological vulnerability. Together, these datasets link spatial layers, tabular data, and supporting reports — forming a single point of truth for understanding how NSW river systems have been evaluated through time. The River Risk Ratings are comprised of three key components, each reflecting a distinct period and methodology in river risk assessment: 1. River Risk Ratings – Historic Stress Rivers Assessment (1990s) A historic dataset derived from the original Stress Rivers Approach (SRA) developed during the 1990s, prior to the introduction of the Water Management Act 2000. This early method classified rivers according to stress indicators such as water extraction pressure and ecological condition. It represents one of the first systematic attempts to quantify river stress across NSW and serves as an important baseline for later risk assessments. 2. River Risk Ratings – Historic Macro Risk Assessment (2000s) yet to publish A historic risk dataset developed during the 2000s by water planners. This macro-level assessment expanded on the earlier SRA work by incorporating hydrological and ecological metrics to evaluate risk at the catchment scale. It informed early water-sharing and planning frameworks under the emerging Water Management Act 2000 and provides continuity between the early and modern risk assessment models. 3. River Risk Ratings – Contemporary Risk Assessment (2016–Present) yet to publish The current and ongoing statewide river risk dataset developed from 2016 to the present. It consolidates a decade of river risk ratings into a centralised database, supported by spatial layers and associated reports (including those linked to the MDBA Water Resource Plans). This represents the most up-to-date and standardised approach to river risk assessment in NSW and forms the operational basis for future updates. How to Access the Data on the SEED Open Data Portal This landing page provides an overview only. To view or download the data, perform the following:,

The NSW River Condition Index (RCI) is the primary long-term reporting tool for assessing riverine condition. It is used to combine a range of indicators into a single condition score. The indicators include riparian vegetation, geomorphic condition, hydrologic stress, biodiversity, catchment disturbance and water quality. The RCI was developed using the Framework for the Assessment of River and Wetland Health (FARWH) approach. The FARWH is an accepted approach applied throughout Australia. The FARWH method uses existing data collection activities and converts them into a standardised and nationally comparable representation of river health. The River Condition Index: method document provides a detailed explanation of the index and how it has been applied across NSW.

The excel file contains time series data of flow rates, concentrations of alachlor , atrazine, ammonia, total phosphorus, and total suspended solids observed in two watersheds in Indiana from 2002 to 2007. The aggregate time series data corresponding or representative to all these parameters was obtained using a specialized, data-driven technique. The aggregate data is hypothesized in the published paper to represent the overall health of both watersheds with respect to various potential water quality impairments. The time series data for each of the individual water quality parameters were used to compute corresponding risk measures (Rel, Res, and Vul) that are reported in Table 4 and 5. The aggregation of the risk measures, which is computed from the aggregate time series and water quality standards in Table 1, is also reported in Table 4 and 5 of the published paper. Values under column heading "uncertainty" reports uncertainties associated with reconstruction of missing records of the water quality parameters. Long-term records of the water quality parameters were reconstructed in order to estimate the (R-R-V) and corresponding aggregate risk measures. This dataset is associated with the following publication: Hoque, Y., S. Tripathi, M. Hantush , and R. Govindaraju. Aggregate Measures of Watershed Health from Reconstructed Water Quality Data with Uncertainty. Ed Gregorich JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI, USA, 45(2): 709-719, (2016).