SYSTEM SCALE PLANNING METHODOLOGY

The report details a System Scale Planning (SSP) framework applied to Nepal's hydropower sector, specifically the Karnali Basin. Using a Multi-Objective Evolutionary Algorithm (MOEA) and integration with the SWITCH energy model, the methodology identifies 'pareto-optimal' portfolios of projects that balance installed capacity and cost against environmental and social metrics. Key findings demonstrate that strategic project selection can significantly reduce biodiversity and livelihood impacts for a given level of energy output, and that restricting development on mainstem rivers (Scenario K03) can achieve a favorable balance of low environmental impact and low system cost.

• System Scale Planning (SSP) is a quantitative, multi-criteria framework designed to help decision-makers visualize trade-offs between different hydropower development solutions rather than assessing projects individually.
• The SSP model utilizes a Multi-Objective Evolutionary Algorithm (MOEA) to identify 'pareto-optimal' solutions, which are portfolios where no single metric can be improved without diminishing another.
• In the Karnali Basin, strategic selection of dams can drastically reduce biodiversity impacts; for a specific installed capacity, some solutions can cut the impacted length of river by more than half compared to others.
• Integration with the SWITCH energy model shows that the 'Karnali-secondary' scenario (K03), which prohibits projects on the Karnali mainstem, results in only a 0.1% increase in system costs compared to the reference scenario while reducing environmental impacts.
• Analysis of national-scale scenarios indicates that existing protected areas in Nepal are insufficient to protect High Conservation Value (HCV) rivers from hydropower impacts because dams may be built upstream or along protected area boundaries.
• The methodology employs 'weighted kilometers' to measure impacts, where the length of affected river is multiplied by a High Conservation Value (HCV) score (0-5) to prioritize high-value reaches.
• The SSP analysis identifies a trade-off for solutions with approximately 4,000 MW installed capacity between minimizing sediment capture and minimizing recreational impacts to rivers.
• The 'Nepal-FFR' scenario (N01), which restricts development on free-flowing rivers, results in the lowest environmental impact (404 km of affected rivers) but increases system costs by approximately 8.8% compared to the reference scenario.

APA

Martin, E., Grill, G., Sada, R., & Opperman, J. (2020). SYSTEM SCALE PLANNING METHODOLOGY. WWF International. https://www.worldwildlife.org/documents/661/60oexxoaxq_USAID_Paani_SSP_Report_FINAL.pdf

Chicago

Martin, Erik, Günther Grill, Rajesh Sada, and Jeff Opperman. SYSTEM SCALE PLANNING METHODOLOGY. WWF International, 2020. https://www.worldwildlife.org/documents/661/60oexxoaxq_USAID_Paani_SSP_Report_FINAL.pdf.

Wikipedia

{{cite report |last1=Martin |first1=Erik |last2=Grill |first2=Günther |last3=Sada |first3=Rajesh |last4=Opperman |first4=Jeff |title=SYSTEM SCALE PLANNING METHODOLOGY |publisher=WWF International |date=December 2020 |url=https://www.worldwildlife.org/documents/661/60oexxoaxq_USAID_Paani_SSP_Report_FINAL.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{martin2020system, author = {Martin, Erik and Grill, Günther and Sada, Rajesh and Opperman, Jeff}, title = {{SYSTEM SCALE PLANNING METHODOLOGY}}, institution = {WWF International}, year = {2020}, month = dec, url = {https://www.worldwildlife.org/documents/661/60oexxoaxq_USAID_Paani_SSP_Report_FINAL.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }