Catchment Flow Research Articles

Comparing the hydrological performance of blue green infrastructure design strategies in urban/semi-urban catchments for stormwater management

ABSTRACT Blue green infrastructure (BGI), in recent decades, have been increasingly recognized as robust stormwater control measures to reduce urban flooding, promote infiltration, and restore a catchment's flow to its pre-development stage. However, studies comparing the hydrological benefits of BGI alternatives at catchment scale are often limited to single catchment or single/few BGI options scaled over a catchment. This study designed a set of BGI alternatives as a combination of different BGI facilities in terms of the following: (a) spatial distribution scale (end-of-pipe vs. decentralized) and (b) naturalness scale (less engineered vs. more engineered), in three different urban catchments representing an inner city, a residential suburb, and a new urban housing. In addition, their hydrological performances were compared. A 10-year return period design rain and a continuous rain series of 11 years were modelled for each BGI alternative using the computer model stormwater management model (SWMM). It was observed that in most catchments, decentralized alternatives (both engineered and natural) showed better potential to reduce the magnitude and frequency of flooding than centralized measures. Similarly, the tested decentralized natural, less engineered alternatives showed higher potential to increase infiltration than the decentralized engineered alternatives in all three catchments. Meanwhile, infiltration-based BGI alternatives showed similar potential to mimic pre-development flow as other decentralized BGI alternatives.

Streamflow Prediction with Time-Lag-Informed Random Forest and Its Performance Compared to SWAT in Diverse Catchments

This study introduces a time-lag-informed Random Forest (RF) framework for streamflow time-series prediction across diverse catchments and compares its results against SWAT predictions. We found strong evidence of RF’s better performance by adding historical flows and time-lags for meteorological values over using only actual meteorological values. On a daily scale, RF demonstrated robust performance (Nash–Sutcliffe efficiency [NSE] > 0.5), whereas SWAT generally yielded unsatisfactory results (NSE < 0.5) and tended to overestimate daily streamflow by up to 27% (PBIAS). However, SWAT provided better monthly predictions, particularly in catchments with irregular flow patterns. Although both models faced challenges in predicting peak flows in snow-influenced catchments, RF outperformed SWAT in an arid catchment. RF also exhibited a notable advantage over SWAT in terms of computational efficiency. Overall, RF is a good choice for daily predictions with limited data, whereas SWAT is preferable for monthly predictions and understanding hydrological processes in depth.

Big Disaster from Small Watershed: Insights into the Failure and Disaster-Causing Mechanism of a Debris Flow on 25 September 2021 in Tianquan, China

The occurrence of debris flow events in small-scale watersheds with dense vegetation in mountainous areas that result in significant loss of life and missing individuals challenges our understanding and expertise in investigating and preventing these disasters. This has raised concerns about the occurrence of large debris flow disasters from small watersheds. This study focused on a catastrophic debris flow that took place in Longtou Gully (0.45 km2) in Tianquan County, Ya’an City on 25 September 2021, which resulted in 14 deaths and missing individuals. Through comprehensive field investigations, high-precision remote sensing data analyses, and numerical simulations, we analyzed the triggering mechanisms and dynamic processes of this event. Our results indicate that the convergence hollow at the channel head exhibited higher hydraulic conditions during rainfall compared to gentle slopes and convex terrains, leading to the instability of colluvial soil due to the expansion of the saturated zone near the soil–bedrock interface. The entrainment of material eroded from the channel resulted in an approximately 4.7 times increase in volume, and the channel scarp with a height of about 200 m amplified the destructive power of the debris flow. We emphasize the need to take seriously the possibility of catastrophic debris flows in small-scale watersheds, with colluvial deposits in hollows at the channel head under vegetation cover that serve as precursor material sources, and the presence of channel scarps formed by changes in the incision rate of the main river, which is common in the small watershed on both sides. This study provides insights for risk assessment of debris flows in small-scale catchments with dense vegetation cover in mountainous areas, highlighting the importance of vigilance in addressing disasters in small-scale catchments, particularly in regions with increasing human–environment conflicts.

Development and application of a hybrid artificial neural network model for simulating future stream flows in catchments with limited in situ observed data

Development and application of a hybrid artificial neural network model for simulating future stream flows in catchments with limited <i>in situ</i> observed data

Investigating the Impact of Recent and Future Urbanization on Flooding in an Indian River Catchment

Socioeconomic growth in India has caused massive infrastructure development which has resulted in extensive damage to the natural environment. A consequence of this urbanization has been extensive monsoon flooding in many locations within the country. The impact of recent land use and land cover (LULC) change because of urbanization and a series of future LULC scenarios is assessed for the Meenachil river basin in central Kerala, India. This catchment flows into the Kuttanad administrative area, which has the country’s lowest elevation, an increasing population, and currently suffers from regular flooding. Hydrological modeling using SHETRAN and hydraulic modeling using HEC-RAS predicts that an extreme event will produce a 105% rise in flood depth in 2100 compared to 2005. A scenario that incorporates Nature-based Solutions suggests the rise in flood depth could be reduced by 44%. A catchment response for future development is needed but is hindered by different administrative boundaries within the river basins that flow into the Kuttanad administrative area, and so this study concludes by providing regional-scale planning recommendations that integrate hydrologic components.

Impacts of flow regime characterization on selected water quality parameters in Mthatha River catchment

Abstract The effects of altered streamflow types on selected water quality parameters provide useful knowledge and information for prompt water pollution management. This study assesses the impacts of inter- and intra-year seasonal variability in streamflow types on selected water quality parameters. The study uses percentiles, multivariance correlation, and agglomerative hierarchical clustering analysis (AHC) in XLSTAT statistics software to achieve the study aim. Historical dataset for streamflow, rainfall, and selected water quality parameters between 2012 and 2020 for the Mthatha River catchment (MRC), Eastern Cape, South Africa were used to characterize the different seasonal variability impacts with the selected water quality parameters at both the upper and lower reach of the river. The result of the inter and intra-year seasonal variability analyses show that the catchment's flow magnitude varies between 2.0 and 2.7 m3/s in summer while the results of the nonlinear polynomial relationship between the grouped streamflow regime show a coefficient of correlation (R2) values of 0.4264 and 0.5643, suggesting that a mild alteration occurs in the catchment. Decision-makers would find the study useful in controlling the pollutant effluent discharge into the river at different times and maintaining standard effluent requirements as mitigation strategies for sustaining the river ecosystem.

Use of Artificial Intelligence Modelling for the Dynamic Simulation of Urban Catchment Runoff

The complex topography and inherent nonlinearity affiliated with influential hydrological processes of urban catchments, coupled with limited availability of measured data, limits the prediction accuracy of conventional models. Artificial Neural Network models (ANNs) have displayed commendable progress in recognising and simulating highly complex, non-linear associations allied with input-output variables, with limited comprehension of the underlying physical processes. Therefore, this paper investigates the effectiveness and accuracy of ANN models, in estimating the urban catchment runoff, employing minimal and commonly available hydrological data variables – rainfall and upstream catchment flow data, employing two powerful supervised-learning-algorithms, Bayesian-Regularization (BR) and Levenberg-Marquardt (LM). Gardiners Creek catchment, encompassed in Melbourne, Australia, with more than thirty years of quality-checked rainfall and streamflow data was chosen as the study location. Two significant storm events that transpired within the last fifteen years - the 4th of February 2011 and the 6th of November 2018, were nominated for calibration and validation of the ANN model. The study results advocate that the use of the LM-ANN model stipulates accurate estimates of the historical storm events, with a stronger correlation and lower generalisation error, in contrast to the BR-ANN model, while the integration of upstream catchment flow alongside rainfall, vindicate for their collective impact upon the dynamics of the flow being spawned at the downstream catchment locations, significantly enhancing the model performance and providing a more cost-effective and near-realistic modelling approach that can be considered for application in studies of urban catchment responses, with limited data availability.

Integrated modeling of snow-covered areas and hydrological processes in the Larji Sub-Basin, Himachal Pradesh, India, using SRM and SWAT models

Abstract Alpine snow is crucial for the water cycle, as the runoff and environment of arid and semi-arid regions rely entirely on these glaciers. Mountain-fed rivers provides the water for domestic, agricultural irrigation, hydroelectric power, and other uses. Due to climate variability, river catchment flows may shift, causing floods and droughts that will aggravate the economy. This study estimated the SCA using Google Earth Engine (GEE) for the Larji River basin, situated in Himachal Pradesh, from the year 2001 to 2021. The snow cover area (SCA) varies from 0.7–22% in the basin. The present study highlights the effectiveness of cloud computing for assessing trends in snow-cover regions in the basin. Moderate Resolution Imaging Spectroradiometer (MODIS) snow product (MOD10A1 V6 Snow Cover Daily Global 500m product) is utilized for SCA calculation. This study simulates runoff from the Larji river, using Snow-melt Runoff Model (SRM) and Soil Water Assessment Tool (SWAT) for years (2019-2021). Furthermore, the Coefficient of determination (R2) Coefficient of corelation (r), Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) were used to evaluate the efficacy of models. This study will help the policymakers and stakeholders to carry out the water resource management practices in the study area.

On the existence of multiple states of low flows in catchments in southeast Australia

This study investigates whether low flow events in a catchment exhibit a possibility of switching regimes. If this happens, it can result in a catchment experiencing a flow anomaly that is even more extreme than what was historically considered a conventional low flow event. A Hidden Markov Modeling approach was used to identify shifts in the intensity of low flow events in catchments in southeast Australia. We found very strong evidence of low flow intensity exhibiting two distinct states (viz., a normal and an intensified state) for several catchments, providing convincing reasons to believe that low flows can and have undergone regime changes. The periods when the catchments exist in an intensified low flow state were associated with higher maximum and average monthly temperature (Δ≈+2.1,+1°C, respectively) and lower precipitation (Δ≈−25mm, a decline of 30%) compared to periods when these exist in their normal state.

How a reservoir modulates downstream water quality under declining upstream loading and progressing climate change

Reservoirs regulate water flow and pollutant transport in catchments. However, climate change can significantly impact their ability to perform this function. This study analysed a multi-decadal time series of data to examine the complex relationship between climate and nutrient pollution trends in the Möhne reservoir catchment. The study aimed at understanding the effect of the reservoir on downstream nutrient pollution in the face of a changing climate. The analysis revealed that upstream nutrient concentrations were higher than downstream, indicating a general nutrient-trapping effect of the reservoir. Upstream stations exhibited a declining trend in total nitrogen (TN) and total phosphorus (TP) concentrations. This was due to improved wastewater management and reduced nutrient mobilisation resulting from decreasing surface runoff and streamflow. At the downstream station, whereas TN concentrations decreased, TP concentrations mildly increased. These opposite downstream trends were likely due to rising temperatures and declining dissolved oxygen concentration within the reservoir, which might have favoured nitrogen denitrification and internal phosphorus loading, causing the decline and increase in downstream TN and TP concentrations, respectively. The contrasting downstream TN and TP trends alter the nutrient stoichiometry, which can profoundly affect the ecosystem's biogeochemical functioning. Therefore, in a warming climate, reservoirs may modulate nitrogen and phosphorus nutrients differently, leading to ecological discontinuities along river networks due to changes in TN-to-TP ratios. The study highlights the need to develop adaptable and precise nutrient pollution management strategies in reservoir catchments to address the challenges of climate change effectively.

Impact of glacier changes and permafrost distribution on debris flows in Badswat and Shishkat catchments, Northern Pakistan

Impact of glacier changes and permafrost distribution on debris flows in Badswat and Shishkat catchments, Northern Pakistan

Impact of land-use change on karst spring response by integration of surface processes in karst hydrology: The ISPEEKH model

Karst groundwater represents a source of freshwater for a quarter of the world's population. Modeling the hydrological behavior of karst aquifers while accounting for the spatial variability of the recharge processes and the land-use change impacts on water availability remains a challenge for karst water resources management. Therefore, this study proposes a new semi-distributed hydrological model named Integration of Surface ProcEssEs in Karst Hydrology (ISPEEKH) for simulating the surface-underground water flows in karst-dominated catchments. ISPEEKH couples the restructured version of the Soil and Water Assessment Tool (SWAT+) with a non-linear three-reservoir groundwater model that represents the epikarst and matrix-conduit flow components in a karst aquifer. ISPEEKH was applied to the Baget karst catchment (13.25 km2) in the Pyrénées mountains of southwest France, characterized by a conduit-dominated spring flow and low surface runoff. The model simulated the catchment daily discharge satisfactorily, with NSE = 0.67 and R2 = 0.68 for the 2008–2013 calibration period, and NSE = 0.65 and R2 = 0.69 for the 2014–2018 validation period. The catchment evapotranspiration and discharge amounted to 33 % and 67 % of the average annual precipitation, respectively, and nearly 80 % of the discharge was attributed to spring flow. The matrix-to-conduit flow accounted for 4–7 % of the monthly spring flow during the high-flow period (December to June), and up to 22 % during the low-flow period (July to October). ISPEEKH was then used to assess the hydrological response of the Baget catchment to land-use change scenarios of afforestation and deforestation for wood production and pasture development. Afforestation of the full catchment area did not alter the catchment hydrology significantly. Deforestation for wood production reduced annual evapotranspiration by 12–18 % and increased annual recharge by 7–8 %, resulting in annual discharge rising by 6–9 %. These changes in the water balance components were most noticeable during the low-flow season and would augment freshwater availability. Conversely, deforestation for pasture development raised annual evapotranspiration by 13–17 % while reducing annual recharge by around 7 % and discharge by 5–7 %. These changes in the hydrological components were most remarkable during the high-flow season and affected discharge below 2.5 m3.s−1.

A Predictive Model For Quantifying The Combined Effect Of Land Use Change And Climatic Variability On Sedimentation In Malaba Sub Catchment

Over the previous years, sedimentation in Malaba sub catchment has become a major problem, this research aimed at using SWAT as a predictive model to assess the impacts of historical and future climate change and land use changes on sedimentation in Malaba sub catchment. Two variables rainfall and temperature were considered under climate change. Four scenarios were modeled in SWAT during this study, the first scenario focused on historical sedimentation in the catchment, land use data of 2000 and weather data of 1990 to 2005 was used to simulate flow and sediment yield in the catchment. The second scenario focused on the current sediment yield in the catchment where land use data of 2020 and weather data of 2003 to 2020 was used to simulate the sediment yield and flow. Calibration and validation was done using SWAT CUP software. The calibrated and validated model was then used to further simulate two future scenarios. The two future scenarios used projected land use data and projected weather data. Land use data was projected using Clerk Labs Terr set software while weather data was projected using the Statistical Downscaling Model (SDSM). The third scenario considered projected land use data of 2035 and projected weather data of 2020 to 2035 to simulate flow and sediment yield of 2023 to 2035. The forth scenario considered projected land use data of 2050 and projected weather data of 2033 to 2050 to simulate catchment flow and sediment yield of 2036 to 2050. The results obtained from climate change analysis indicated un even changes, rainfall over the catchment is expected to increase, maximum temperature is expected to increase, minimum temperature is expected to reduce. Land use change results after comparison between the historical land use and projected land use indicated that from 2020 to 2050 cropland and built up area will increase while forests and water bodies will reduce. Average annual Sediment yield of 1993 to 2020 is expected to generally increase from 4975.4 tons/km2/year to an average annual sediment yield of 5525.6 tons/km2/year from 2023 to 2050. Therefore, mitigation measures should be adopted to ensure sustainable management of the catchment. Some of the recommendations made in this research are; Government through NEMA should put restrictions on cultivation close to the river banks, encourage planting trees within the catchment, bare lands within the catchment should be converted to other sustainable land uses. The study findings of this research shall be relevant for planning, design and management of reservoirs, dams, irrigation systems and sustainability of eco systems in the catchment.

Uncertainty in water transit time estimation with StorAge Selection functions and tracer data interpolation

Abstract. Transit time distributions (TTDs) of streamflow are useful descriptors for understanding flow and solute transport in catchments. Catchment-scale TTDs can be modeled using tracer data (e.g. oxygen isotopes, such as δ18O) in inflow and outflows by employing StorAge Selection (SAS) functions. However, tracer data are often sparse in space and time, so they need to be interpolated to increase their spatiotemporal resolution. Moreover, SAS functions can be parameterized with different forms, but there is no general agreement on which one should be used. Both of these aspects induce uncertainty in the simulated TTDs, and the individual uncertainty sources as well as their combined effect have not been fully investigated. This study provides a comprehensive analysis of the TTD uncertainty resulting from 12 model setups obtained by combining different interpolation schemes for δ18O in precipitation and distinct SAS functions. For each model setup, we found behavioral solutions with satisfactory model performance for in-stream δ18O (KGE &gt; 0.55, where KGE refers to the Kling–Gupta efficiency). Differences in KGE values were statistically significant, thereby showing the relevance of the chosen setup for simulating TTDs. We found a large uncertainty in the simulated TTDs, represented by a large range of variability in the 95 % confidence interval of the median transit time, varying at the most by between 259 and 1009 d across all tested setups. Uncertainty in TTDs was mainly associated with the temporal interpolation of δ18O in precipitation, the choice between time-variant and time-invariant SAS functions, flow conditions, and the use of nonspatially interpolated δ18O in precipitation. We discuss the implications of these results for the SAS framework, uncertainty characterization in TTD-based models, and the influence of the uncertainty for water quality and quantity studies.

Estimation of water supply and demand, using meteorological parameters from 1990 to 2020, in the micro-basin of the Chibunga river - Ecuador

The objective is to prove the climatological state of the Chibunga River micro-basin through a water balance based on hydro-meteorological information. Historical records of rainfall and temperature were used from 1990 to 2020 (30 years). By processing these data, it was possible to determine the catchment flow of the basin, which is reflected in the water supply, and to calculate the demand for water in the area, using population and endowment data. These two parameters are key to determining the scarcity index in the basin and thus to estimating the amount of water in the area. The meteorological station records were provided by the National Institute of Meteorology and Hydrology.Statistical and mathematical operations were carried out using the R programming language and ArcGis10x software. The weather patterns of the micro-basin are well defined and did not show temporal changes in any of the calculated parameters, the amounts varied between periods, and therefore the water supply, demand, and scarcity index. From the first to the second period, the scarcity index went from insignificant to moderate, closing the third period also with a moderate index, so that its value between periods was from 8.81 to 16.79%.

Simulation of the rainfall–runoff relationship using an HEC-HMS hydrological model for Dabus Subbasin, Blue Nile Basin, Ethiopia

Abstract Hydrological modeling is important to provide relevant hydrologic information from limited data. In this study, Hydrologic Modeling System (HEC-HMS) was used to simulate the rainfall–runoff relationship for the Dabus subbasin of the Blue Nile Basin. Daily precipitation and stream flow data from 2002 to 2019 were used as key input data for the model, together with soil and land use/land cover data, and a digital elevation model of the study area. Arc-GIS was employed in combination with Arc Hydro and HEC-GeoHMS tools for terrain processing and translating spatial information into model files for HEC-HMS, respectively. Model calibration was done with data from 2002 to 2014, while the validation was done from 2015 to 2019. Nash-Sutcliffe simulation efficiency (NSE), observation standardized ratio (RSR), and coefficient of correlation (R2) were used to assess the performance of the model. With NSE, RSR, and R2 values of 0.784, 0.334, and 0.816 for calibration, and 0.793, 0.323, and 0.875 for validation, the model simulation of stream flows was found in good agreement with the observed values. Therefore, the HEC-HMS model can be utilized to predict stream flows in ungauged catchments in the Dabus subbasin from measured rainfall data for proper water resource planning and management.

Natural attenuation of heavy metals via secondary hydrozincite precipitation in an abandoned Pb[sbnd]Zn mine

The Aran Valley in Catalonia (Spain) was the site of large-scale Zn, Pb, Cu, Fe, and Ag mining from the late 19th century until approximately 1950. Although mining activities ceased over 70 years ago, some of the abandoned mining relics (e.g. tunnels, processing facilities, and tailings dumps) exhibit elevated concentrations of metals in the associated water systems, thus posing a health risk in the neighboring ecosystem. In this study, the largest underground zinc mine in the Aran Valley (the Victoria Mine) was chosen as a field site to showcase the processes affecting metal mobility in the environment. Three sampling campaigns to the mine (2019, 2020 and 2021) provide a spaciotemporal dataset showing the evolution of solute concentrations through the system along a flow path. Rainwater from the upper catchment flows into the host rock above the mine, dissolving ore materials (primarily Zn (sphalerite) and Fe (pyrite) sulfides with Ni and Cd impurities) that cause elevated Zn, Ni, and Cd concentrations in the water that enters the mine. Precipitation of hydrozincite (Zn5(CO3)2(OH)6) along the gallery where water flows serves as a metal-removal mechanism resulting in significantly diminished metal concentrations (e.g. Zn from 155 to 10 ppm, Ni from 377 to 32 ppb, and Cd from 105 to 22 ppb). Characterization of the solid samples taken from the mine reveals several different morphologies, Zn zonations in hydrozincite (i.e. purity changes), and small amounts of smithsonite (ZnCO3) and calcite (CaCO3). In general, all solids show layering, which is a result of intermittent precipitation of distinct solid products. These precipitation patterns are likely a result of changing solute concentrations and precipitation rates. Variations in rain events change the water residence time in both the host rock and in the gallery, thereby altering the water composition. Solubility experiments and speciation calculations demonstrate that hydrozincite here does not have a constant Keq value, but rather a range of values (30.0 < log[Keq] < 37.68 at 7 °C). This behavior is presumed to be a result of precursor effects as amorphous solids with higher solubilities may form before the structured hydrozincite. Notably, all analyzed solids from the collected mine samples show significant amounts of amorphous material, demonstrated by broad XRD peaks along with significant impurities in the analyzed solids, leading to the hypothesis that there exists a variability in the solubility of hydrozincite beyond a pure end-member value.

Predicting the daily flow in ungauged catchments of the eastern part of the upper Blue Nile basin, Ethiopia

Predicting the daily flow in ungauged catchments of the eastern part of the upper Blue Nile basin, Ethiopia

Disentangling runoff generation mechanisms: Combining isotope tracing with integrated surface/subsurface simulation

The majority of runoff studies to date have reported a similar pattern of rapid rain-to-runoff conversion via overland flow and shallow subsurface water flow, as well as the ubiquity of thresholds and hysteresis in rainfall-runoff response. But each of those approaches has limitations in terms of inference and process description. Processes of water transport and mixing and how they influence runoff generation are still not well understood or quantified. In this study, HydroGeoSphere, a fully-integrated surface/subsurface flow model, was used together with stable isotopes for disentangling runoff generation mechanisms in a headwater catchment. The study area (0.21 km2) is the first-level tributary of the Xin’an Jiang River located in a humid climate region of eastern China. Water flow simulation elucidated the spatial water transport process, and isotope tracing quantified the complex water mixing process between the shallow soil and hillslope surface. This study provides insights into the rapid transformation of rainfall infiltration and mixing in soil and exfiltration to a hillslope. Results show that the stream runoff was separated into rainfall-induced overland flow (9 %), exfiltration-induced overland flow (including the 53 % of mixed water from rainfall infiltration and 6 % of the stored soil water), and subsurface flow (32 %). Exfiltration-induced overland flow was the dominant water source in the headwater catchment during a rainfall-runoff event. The mutual influence of rainfall infiltration and soil water exfiltration caused the shallow soil to rapidly become saturated, thus forming saturation excess overland flow. The consistence of estimated soil water velocity based on the integrated isotope and numerical modeling approach, at about 0.4 m/d nearby the stream channel, improved the reliability of model visualizations. Further analysis indicates that water flow paths and velocities responding to the rainfall event were attributed to the soil moisture conditions and topography. This study demonstrates that identifying the rapid mixing processes between the rain and the soil water was crucial for understanding hillslope overland flow and runoff generation in headwater catchments.

Multi-scale flume investigation of the influence of cylindrical baffles on the mobility of landslide debris

Debris flows travel downslope at high speed and often cause damage to the infrastructure of societies around the world. With increasing extreme rainfall events and urbanization in mountainous regions, effective structural countermeasures are in increasing demand. Over recent years, engineers have proposed the installation of an array of cylindrical columns, called baffles, to reduce the velocity of debris flows in catchments. However, existing design methods are highly empirical in nature, so it is unclear whether they are adequate or over designed, and appropriate specifications and arrangement of cylindrical baffles have still not been suggested. Moreover, previous experimental studies have predominantly modeled debris flows as dry granular flows at a laboratory scale. In this study, to investigate the effect of cylindrical baffles on the dynamic characteristics of debris flow, a series of small-scale flume tests was conducted using a flume equipped with devices to measure the flow interaction between baffles and the dynamic loads of debris flow. In addition, to investigate the scale effect of debris flows and cylindrical baffles on flow characteristics, large-scale tests were also performed according to different numbers of rows of baffles for similar baffle configurations confirmed by small-scale tests. Using the small- and large-scale test results, this study analyzed the energy dissipation and dynamic impact characteristics according to the height and number of rows of baffles. The analysis results showed that the use of baffles increased the energy dissipation of debris flows, and an additional row of baffles produced greater effects on the energy dissipation in the debris flows. Based on the test results, the average dynamic pressure coefficient for cylindrical baffles was 0.31.