Anthropogenic risk assessment of riverine habitat using geospatial modelling tools for conservation and restoration planning: a case study from a tropical river Pranhita, India.

The riverine ecosystem provides multiple benefits to human community and contributes to the sustainable development of the ecoregion. The growing dependency on these ecosystems has largely contributed to aggravating the ecological risks, habitat degradation, and loss of ecosystem services. The present study evaluates the ecological risk emanating from nine anthropogenic stressors including river use, hydro-morphology, catchment pollution, and biological stressor on river Pranhita in Godavari Basin of Peninsular India using InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Habitat Risk Assessment model. The primary field survey, remote sensing, and secondary data-assisted spatial modelling results revealed low ecological risk (R = 0.65 of 3) in river Pranhita due to anthropogenic activities. Sediment loading, the inflow of nitrogen, and habitat fragmentation were the major stressors with relatively higher risk score (> 1); influence on a sizeable portion of riverine habitat (29-75% of the total area under high-risk zone) indicates the mounting threat from catchment activities. The low-risk value observed in protected river reaches as compared to unprotected areas is likely to be influenced by the abundant presence of intact riparian vegetation which mitigate the catchment stressors and minimal anthropogenic activity within protected areas. This study demonstrates the application of InVEST HRA model for ecological risk assessment of riverine ecosystems and fish assemblages along with their input data generation framework. This has the potential for prioritization of sensitive habitats based on computed ecological risk and stressor identification based on their exposure and consequences for developing appropriate mitigation measures. This model is spatially explicit and accommodates user-defined criteria for ecosystem-level assessment at a regional and national scale to facilitate the resource managers and policymakers for conservation and restoration planning and implementation of targeted management measures for sustainable development.

Quantitative assessment of sediment delivery and retention in four watersheds in the Godavari River Basin, India, using InVEST model - an aquatic ecosystem services perspective.

Sediment export and retention are important ecosystem processes in any landscape causing soil erosion and sediment loading in waterways consequently affecting the health of aquatic habitats downstream. The present study quantifies sediment export and retention in four watersheds, viz., Hivra, Satrapur, Konta, and Jagdalpur in the Godavari River Basin, India, using Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) ecosystem service modelling tool. The  results revealed that the sediment export yields ranged from 0.75 (Hivra) to 2.77 t/ha/year (Jagdalpur). The mean deviation between modelled values and observed sediment export yield was - 11.11%, which indicated good prediction by the model. The sediment retention ranged from 16.04 (Hivra) to 101.52 t/ha/year (Konta). Most sediment export and retention occurred on cropland or shrubland land use land cover types in all four watersheds. For decision making on soil conservation, soil loss tolerance limits have been established for these watersheds. For aquatic habitats, sediment concentration is considered more important than the total annual sediment export, since water turbidity is an important determinant of water quality, and the aquatic lives therein. Therefore, the temporal distribution of rainfall and corresponding sediment export becomes important, since these two factors determine the sediment concentration as well as turbidity in the waterbody. In current study, "Precipitation Concentration Index adjusted Sediment Export Yield Index" was developed to account for the effects of the temporal rainfall distribution and its impact on sediment export. The index for four watersheds was quantified (Hivra > Satrapur > Konta > Jagdalpur), which is concordant to the turbidity values reported by respective gauge stations. Thus, the proposed index can efficiently capture the impact of temporal rainfall distribution on sediment export, and consequently its effect on water turbidity. The study revealed the potential of InVEST model to quantify the sediment export and retention in the watersheds studied. Together with the proposed index, it would help the policy makers in making informed decisions for planning conservation strategies for aquatic biodiversity.