Evaluation of Ecosystem-Based Adaptation Measures for Sediment Yield in a Tropical Watershed in Thailand

Ecosystem-based adaptation (EbA) can potentially mitigate watershed degradation problems. In this study, various EbA measures were evaluated using a bio-physical model called the Soil and Water Assessment Tool (SWAT), in a small, forested watershed named Hui Ta Poe, in the northeastern region of Thailand. The developed watershed model was first used to investigate the effect of various degraded watersheds due to land-use changes on the sediment yield in the study area. The most degraded watershed produced an annual average sediment yield of 13.5 tons/ha. This degraded watershed was then used to evaluate the effectiveness of various EbA measures such as reforestation, contouring, filter strips, and grassed waterways in reducing the sediment yield. Under all individual and combined EbA scenarios analyzed, there was a significant reduction in sediment yield; however, the maximum reduction of 88% was achieved with a combined scenario of reforestation, grassed waterways, and filter strips. Reforestation alone was found to be the second-best option, which could reduce the sediment yield by 84%. Contouring alone was the least effective, with a reduction in sediment yield of only 23%. This study demonstrates the usefulness of implementing EbA measures for sediment management strategies to address watershed degradation, which is a severe problem across the globe.

Evaluation of Debris Flows for Flood Plain Estimation in a Small Ungauged Tropical Watershed for Hurricane Otto

The variability of climate, increase in population, and lack of territorial plans in Costa Rica have caused intense disasters with human and economic losses. In 2016, Hurricane Otto hit the country’s northern area, leaving substantial damages, including landslides, debris flows, and flooding. The present study evaluated different scenarios to estimate flooded areas for Newtonian (clean water), and non-Newtonian flows with volumetric sediment concentrations (Cv) of 0.3, 0.45, 0.55, and 0.65 using Hydro-Estimator (HE), rain gauge station, and the 100-year return period event. HEC–HMS modeled the rainfall products, and FLO-2D modeled the hydrographs and Cv combinations. The simulation results were evaluated with continuous statistics, contingency table, Nash Sutcliffe Efficiency, measure of fit (F), and mean absolute differences (E) in the floodplains. Flow depths, velocities, and hazard intensities were obtained in the floodplain. The debris flood was validated with field data and classified with a Cv of 0.45, presenting lower MAE and RMSE. Results indicated no significant differences in flood depths between hydrological scenarios with clean-water simulations with a difference of 8.38% in the peak flow. The flood plain generated with HE rainfall and clear-water condition presented similar results compared to the rain gauge input source. Additionally, hydraulic results with HE and Cv of 0.45 presented E and F values similar to the simulation of Cv of 0.3, demonstrating that the HE bias did not influence the determination of the floodplain depth and extent. A mean bias factor can be applied to a sub-daily temporal resolution to enhance HE rain rate quantifications and floodplain determination.