Mixed-methods Approach to Flood Hydrology in Ungauged Catchments

<p><h3>Project Summary</h3></p>
<p>Flooding, particularly in the tropics, is expected to be more frequent and severe. Thus, improved modeling and characterization are needed to better understand, predict, and manage flooding. However, there are still many data-limited regions that have several ungauged catchments and limited hydrogeological data. In these data-limited regions, local knowledge and non-instrumental data can provide information of past extreme floods to better characterize a catchment’s hydrology.

<p>Household surveys from individuals directly impacted by a recent extreme storm event could fill critical knowledge gaps in instrumental records by providing estimates of peak timing of rainfall and discharge along different parts of the catchment. This data can be quantified and averaged to create a hydrograph and can enhance the understanding of flooding in data-limited catchments when used in-conjunction with other data sources. However, interpreting or calibrating qualitative information from human data to improve estimates of flood magnitude and duration is difficult. Areas of uncertainty include inaccurate human perception and memory, high variability, erroneous information, and personal biases in framing surveys and selecting information. Despite these uncertainties, human observations can provide information about flow paths, geomorphic change, and flood impacts not usually captured using quantitative methods. Household survey data also provides voices to local communities and enhances geographic understanding of flooding.

<p>This research project uses a transformative mixed methods approach that combines household surveys and paleohydrology proxy measures as an example to reconstruct hydrographs from an extreme event in an ungauged catchment. The primary research objective is to quantify relationships between rainfall and discharge in a representative ungauged catchment using local proxy measures and participant observations. The specific research objective is to reconstruct the most extreme event that has occurred a representative ungauged catchment using a combination of paleohydrology, household survey, and hydrology methods as an example of how these methods improve flood knowledge in data-limited regions.

<p>This project was conducted from 2018 to 2022 in Ostional, a representative ungauged catchment in the Pacific coastal region of Nicaragua. Mixed methods were used to construct flood hydrographs from Tropical Storm Nate in October 2017 in different parts of the catchment to demonstrate the value of using local knowledge and experiences to assess flooding from an extreme storm event. With a recent increase in late season tropical cyclones hitting Nicaragua, the methods and study location are ideal to increase understanding of current and historic magnitudes and timing of peak floods. Accurate knowledge of extreme flooding is critical for infrastructure development; thus, the study methods and results are critical to improve flood planning and management. Lastly, the study methods and results can advance understanding and help improve flood management and predictions to and inform policy and management strategies in any data-limited region.