The generation of hydrological data for accurate flood predictions requires robust and, ideally, dense monitoring systems. This requirement is challenging in locations such as the Himalayas, which are characterised by unpredictable hydroclimatic behaviour with dramatic small-scale spatial and temporal variability. River level monitoring sensors that are affordable and easy-to-operate could support flood risk management activities in the region. We therefore identify potential for a local participatory monitoring network that also serve to overcome existing data gaps, which represent the main bottleneck for establishing an effective community-based flood early-warning system. We have applied a citizen science-based hydrological monitoring approach in which we tested low-cost river level sensors. Initial results, collected over summer 2017 from two stations on the River Karnali, suggest that our system can successfully be operated by non-scientists, producing river level data that match those obtained from an adjacent government-operated high-tech radar sensor. We discuss potential opportunities to integrate these low-cost sensors into existing hydrological monitoring practice. Combined with an adaptive, community-led approach to resilience building, we argue that our low-cost sensing technology has the potential not only to increase spatial network coverage in data-scarce regions, but also to empower and educate local stakeholders to build flood resilience.