Rainfall Monitoring Data Research Articles

Vegetation–Topographic Landscape and the Influence of Water and Sediment in the Shule River Basin

The study of the effect of vegetation cover on water and sediment content is of great significance for the in-depth understanding of ecological and environmental effects in river basins and the formulation of corresponding management measures. Based on the monitoring data of rainfall and runoff of Panjiazhuang and Dangchengwan Hydrologic Stations in Shule River Basin from 2000 to 2020 and the sediment discharge of Changmabao, methods such as geographic information technology (GIS), landscape pattern analysis, land use transfer matrix, correlation analysis, principal component analysis, and linear regression analysis were used to study water and sediment change, land use pattern, vegetation change characteristics, and local water and sediment change in Shule River Basin and construct vegetation–topographic landscape factors. The main research results are as follows: (1) Vegetation coverage in the Shule River Basin increased year by year from 2000 to 2020, with a cumulative increase of 0.064 in 20 years. Vegetation cover has a significant effect on water and sediment content, and the correlation is −0.966. (2) The cultivated land area of the Shule River Basin increased by 604 km2 from 2000 to 2020, and the conversion rate was 67%. From 2000 to 2020, the water area increased by 442 km2, and the conversion rate was 51%. The area of grassland and forest increased by 198 km2 and 12 km2, respectively, and the conversion rate was 68% and 33%, respectively. Forest had the highest transfer rate (0.67). The lowest conversion rate was 0.32 for grassland. (3) The variation coefficient of water and sediment content in Shule River Basin during 1971–2020 was 45.21%, and the highest variation coefficient during 2001–2010 was 49.15%. The lowest variation coefficient was 39.73% during 2011–2020. The annual sediment transport in the Shule River Basin fluctuates greatly and has a high degree of dispersion during 1971–2020. (4) The results of the landscape index in Shule River Basin during 2000–2020 had a small difference, with a difference of less than 0.5. According to the principal component analysis of landscape index and water and sediment content, the maximum patch index (LPI) had the strongest positive correlation with water and sediment content (0.958). The diversity index SHDI had the strongest negative correlation with water and sediment content (−0.995).

Water availibility of Karo Lake, Obi Island, South Halmahera

Lake Karo is one of the largest water sources on Obi Island. Obi Island has a large potential for water resources that can be used optimally by the local communities. This hydrological analysis purposed to calculate the water availability in Karo Lake. Water availability is the amount of water that is estimated to continue to exist in a location with a certain amount and within a certain period of time. Water availability is calculated by dependable discharge using the Mock method. The basis for the calculation of the Mock method is to calculate the rain that falls on the water catchment area, some will be lost as evapotranspiration, some will immediately become surface runoff and some will absorb into the ground (infiltration). The analysis used climate data, topography, and the area of the water catchment area in the watershed. In order to obtain an accurate dependable discharge calculation, it is necessary to have long-term rainfall monitoring data. The data used in the calculation of the Mock method is monthly rainfall data for the last 20 years from Rainfall Station data around the study location. The results of Digital Elevation Model data processing, the catchment area in the Lake Karo watershed is 65.11 km2. Based on the results of calculations using Mock method, the water availability in Lake Karo is always available year-round with a dependable discharge of Q80 is 1.8 m3/second. The water availability can be used for any purpose of the local communities.

Analysis of the effect of rainfall center location on the flash flood process at the small basin scale

Abstract With the increasing frequency of extreme convective weather, the spatial–temporal variability of rainfall becomes more diversified. As a result of the insufficient quality of rainfall monitoring data in mountainous areas, the flash flood simulation usually does not consider the effect of the rainfall center location. In this work, the GPU Accelerated Surface Water Flow and Associated Transport hydrodynamic model is used to simulate the flash flood discharge process. The effect of the rainfall center location and the basin scale on the discharge process were analyzed based on simulated data. The results show that when the rainfall center is in the upstream and midstream basins, because of gravitational potential energy conversion, the total flood volume and the flood peak discharge increase to 2–10 times, and the peak time of flash flood caused by 100 mm rainfall amount can be advanced by up to 3,000 s compared to the 20 mm rainfall amount condition. The peak discharge and the delay of peak time increase with the increase of rain peak coefficient. In addition, the increase of the basin area enhances the effect of the rainfall center location. This work is helpful to quantify the effect of the rainfall center location, which can clarify the uncertainty of flash flood simulation caused by not considering the rainfall center factor.

Impact analysis of repeated improper treatment of bridge site slopes to bridge across

The bridge site slope in Zhengjiawan has been renovated several times in response to the adverse geological conditions of the Zhengjiawan ancient landslide (ZAL) in China. However, improper control and treatment measures have caused the structural failure of the Zhengjiawan bridge (ZB). Based on long-term field monitoring data of rainfall, temperature, bridge deformation, and bridge site slope displacements, this paper analyses the impact of repeated improper treatment on bridge site slopes to bridge across. Furthermore, it summarized the interrelationship between bridge deformation and bridge site slopes under natural rainfall and improper treatment measure conditions, and proposed a set of solutions for bridge site slope control and treatment. The results show that the destruction of ZB is primarily attributed to the deformation of ZAL, natural rainfall is the main trigger controlling the intermittent creep of the ZAL, while the construction of anti-slide pile and deviation rectification of bridge abutment result in significant deformation of ZAL. The deformation of ZB and ZAL were synchronous, and the monthly displacement difference ranged from 0.18 to 5.19 mm. The failure of the ZB structure resulting from the ZAL is attributed to the insufficient shear strength of the weak loose soil comprising the landslide, which fails to withstand the sliding force induced by continuous heavy rainfall. Additionally, the original anti-slide pile inadequately controls the deformation of the landslide. By setting the second-row anti-slide pile, adding the cross-sectional area of the bridge pier foundation, and installing drainage pipes, the safety of the bridge is effectively guaranteed. The control and treatment of ZAL show that preventing bridge pier deformation should be prioritized followed by controlling and treating bridge site slopes, and this study provides insights into interactions between unstable landslide treatments and bridge structures which may serve as a reference for similar projects.

Correction of Fused Rainfall Data Based on Identification and Exclusion of Anomalous Rainfall Station Data

High-quality rainfall data are crucial for accurately forecasting flash floods and runoff simulations. However, traditional correction methods often overlook errors in rainfall-monitoring data. We established a screening system to identify anomalous stations using the Hampel method, Grubbs criterion, analysis of surrounding measurement stations, and radar-assisted verification. Three rainfall data-fusion methods were used to fuse rainfall station data with radar quantitative precipitation estimation data; the accuracies of the fused data products with and without anomalous data identification were compared. Validation was performed using four 2012 rainfall events in Hebei Province. The 08:00–19:00 July 3 rainfall event had the highest number of anomalous stations (11.5% of the total), while the 01:00–17:00 August 9 event had the lowest number (7.8%). By comparing stations deemed to be anomalous with stations that were actually anomalous, we determined that the accuracy of reference station determination using Hampel’s method and Grubbs’ test was 94.2%. Radar-assisted validation improved the average accuracy of anomalous station identification during the four typical rainfall events from 89.7 to 93.7%. Excluding anomalous data also significantly impacted the efficacy of rainfall-data fusion, as it improved the quality of the rainfall station data. Among the performance indicators, 95% improved after the exclusion of anomalous data for all four rainfall events.

Trend analysis of groundwater levels in the monitoring boreholes within basalt formations in Dak Lak province

Groundwater from the basalt formations is the main source for the irrigation domestic use in Dak Lak province. Groundwater levels are important information for sustainable management water resouces in the region. The evolution of Groundwater level in the basalt aquifer in Dak Lak province is analyzed and evaluated by using the statistical test method. The results of the Mann-Kendall test indicated that the annual groundwater level had downward trend at 6/8 monitoring holes. The reduction was approximately from 0.03 m/year to 0.1 m/year at boreholes LK71T, LK29T, and CB1-II with high reliability in statistics (p-value < 10%). The downward trend also appeared at 6/8 observed boreholes in the rainy season (0.05÷0.2 m/year) and dry seasons (0.03÷0.15 m/year). Groundwater level changed, in this work, was interpreted and linked to precipitation data. Comparison with annual rainfall monitoring data during the period 2010÷2016 at three stations in the study area, the Pearson correlation coefficient showed that the changed in rainfall amount overtime govern the groundwater level in the study area. Specifically, the results have identified a close correlation between the groundwater level at the boreholes LK29T, C4a, LK71T, and LK75T with average rainfall in the dry season in the study area. The strong correlation continued to be maintained at 3/8 monitoring holes (C4a, LK29T, and LK75T) in rainy season. Mann-Kendall statistical method and Pearson correlation can be applied to analyze long-term Groundwater level changes for sustainable management and exploitation of groundwater resources.

Machine learning for the definition of landslide alert models: a case study in Campania region, Italy

Landslide early warning systems at regional scale are typically based on correlations between landslides that occurred in the past and rainfall monitoring data in order to identify trigger rainfall thresholds. Recently, the availability of large datasets of atmospheric measurements allows including additional variables, increasing the reliability of the models. However, conducting the analyses with traditional techniques can be quite complex and time-consuming. The purpose of this preliminary study is to demonstrate that machine learning techniques can be used to analyze monitoring data in order to select the most relevant variables for the triggering of shallow rainfall-induced landslides at regional scale. The models developed herein were tested in one of the alert zones defined by civil protection for the management of geo-hydrological risk in Campania region, Italy. Two data sources were used in the analysis. The atmospheric variables are derived from the ERA5-Land atmospheric reanalysis. The data on landslide events are retrieved from “FraneItalia”, a georeferenced catalog of landslides occurred in Italy developed by consulting online sources from 2010 onwards. The models developed were calibrated and validated in order to define combinations of rainfall variables and soil water content for the prediction of the occurrence of landslides. Finally, the performance of the models was assessed using statistical indicators derived from contingency matrices.

A Quantitative Analysis Method of Regional Rainfall-Induced Landslide Deformation Response Variation Based on a Time-Domain Correlation Model

Landslide deformation is the most intuitive and effective characterization of the evolution of landslides and reveals the inherent risk of landslides. Considering the inadequacy of existing deformation monitoring data for early warnings regarding landslide hazards, resulting in insufficient disaster response times, this paper proposes a time-domain correlation model. Based on the process of rainfall-induced landslide deformation, the time-domain correlation between regional rainfall and landslide deformation is proposed, which can reflect the temporal characteristics of landslide responses to rainfall, and the calculation method of the impulse response function is designed to quantitatively model and calculate the correlation. Furthermore, rainfall monitoring data are used to optimize the landslide deformation monitoring indicator system for early warnings regarding landslide instability. The feasibility of the method proposed in this paper is verified by analyzing the historical monitoring data of rainfall and landslide deformation at nine typical locations in five landslide hazard areas in Fengjie County, Chongqing city. (1) The correlation models for the XP landslide involve a delayed rainfall response time of 5 for deformation, respectively, as well as the existence of a cycle of 55–56 days, which means that the above area can advance the landslide warning by one lag time based on the cycle; (2) The correlation models for the OT landslide show consistent correlations under a 48–50-day cycle, which means that the deformation in the above areas can be predicted based on rainfall accumulation. (3) The HJWC landslide presents a turbulence correlation, which means that other monitoring data need to be supplemented and analyzed.

Components, acidification characteristics, and sources of atmospheric precipitation in Beijing from 1997 to 2020

Policies such as the Air Pollution Prevention and Control Action Plan have been implemented in Beijing to address acid rain pollution. In this study, we evaluate the effects of these policies by analyzing rainfall monitoring data from 1997 to 2020, acidification characteristics, and chemical components of precipitation in Beijing. We found that precipitation pH values had significantly changed in 2008, showing an overall declining trend during 1997–2008 before gradually recovering. The frequency of acid rain was first increased and then decreased, reaching zero levels after 2017. The multi-year average pH in urban (1997–2020), suburban (1997–2020), and background (2004–2020) sites was 5.74 ± 0.67 Â, 6.53 ± 0.54 Â, and 6.49 ± 0.64 Â, respectively. The predominant cations in precipitation were NH4+ and Ca2+, where Ca2+ concentrations dropped from 332.1 μeq·L−1 in 1997 to 179.3 μeq·L−1 by 2015 and 81.39 μeq·L−1 by 2020. In contrast, NH4+ concentrations were first increased from 193.4 μeq·L−1 in 1997 to 270.5 μeq·L−1 in 2015 and then decreased to 206.78 μeq·L−1 by 2020. The concentration of the predominant anions, SO42− and NO3−, was generally decreased; SO42− concentration was decreased from 350.88 μeq·L−1 in 1999 to 88.19 μeq·L−1 in 2020. However, NO3− underwent a down-up-down trend, dropping slowly from 125.3 μeq·L−1 in 1997 to 52.2 μeq·L−1 in 2004, then significantly increasing to 173.06 μeq·L−1 in 2014 before showing a downward trend in volatility. The [SO42−]:[NO3−] ratio was gradually decreased from 3.3 in 1997 to 1.5 in 2015, then dropped to 0.9 in 2020, indicating that the type of precipitation gradually shifted from a predominantly sulfuric acid type to a more mixed type. Conversely, the [Ca2+]:[NH4+] ratio showed a decreasing trend, suggesting NH4+ as the principal neutralizing agent in recent years. The correlation coefficients among the major crustal source components (Ca2+, K+, and Mg2+) were relatively high in the precipitation, suggesting that the contribution from ground dust was significant. The major acidic anions were primarily attributed to human activities.

Group-occurring landslides and debris flows caused by the continuous heavy rainfall in June 2019 in Mibei Village, Longchuan County, Guangdong Province, China

From June 10th to 13th, 2019, a continuous heavy rainfall occurred in Longchuan County, Guangdong Province, causing many landslide hazards. Among Longchuan County districts, Mibei Village is one of the hardest-hit areas and suffered severe losses. In this paper, field investigation, remote sensing image interpretation, and UAV aerial photography were used to investigate and analyze hazard characteristics. Combined with rainfall monitoring data, laboratory and field tests data, and existing research results, the characteristics and failure mechanism of group-occurring landslides in Mibei Village were studied. Because of the continuous heavy rainfall, 327 landslides occurred in the study area, mainly distributed in the north of the Mibei River and along the X158 road. The terrain slope of landslide hazards ranged from 35° to 45°, and the slope structure can be divided into two types. Granite residual soil was the main part of landslide mass, and sliding surface developed along with the interface between bedrock and covering layer. The continuous heavy rainfall from June 10th to 13th was the main triggering factor of the disaster. The total precipitation was 281.3 mm, and the rainfall on June 10th was 153.5 mm. The rain led to the continuous increase in volume water content in granite residual soil and completely weathered granite. The shear strength and parameters of the two materials changed differently, and slope stability continued to decrease, and then landslides occurred under terrain conditions and engineering excavation space. Untimely support and unreasonable support measures for the excavation slope exacerbated the disaster. The development degree of debris flows in the study area was very low, and debris flows were shown as the secondary disaster of landslides. The branch gully terrain is the key to transforming the landslide into the debris flow, and a large amount of loose deposits in the main gully will become the potential source of debris flow in the future.

Deep Learning as a Tool to Forecast Hydrologic Response for Landslide‐Prone Hillslopes

AbstractEmpirical thresholds for landslide warning systems have benefitted from the incorporation of soil‐hydrologic monitoring data, but the mechanistic basis for their predictive capabilities is limited. Although physically based hydrologic models can accurately simulate changes in soil moisture and pore pressure that promote landslides, their utility is restricted by high computational costs and nonunique parameterization issues. We construct a deep learning model using soil moisture, pore pressure, and rainfall monitoring data acquired from landslide‐prone hillslopes in Oregon, USA, to predict the timing and magnitude of hydrologic response at multiple soil depths for 36‐hr intervals. We find that observation records as short as 6 months are sufficient for accurate predictions, and our model captures hydrologic response for high‐intensity rainfall events even when those storm types are excluded from model training. We conclude that machine learning can provide an accurate and computationally efficient alternative to empirical methods or physical modeling for landslide hazard warning.

Effects of Sponge City Development on Soil Moisture and Water Quality in a Typical City in the Loess Plateau in China

Changes in soil moisture following the establishment of sponge cities play a key role in the regulation of the relationship between surface runoff and rain resources in arid and semi-arid regions of the Loess Plateau. Based on soil moisture and rainfall monitoring data obtained at the fine-scale (per 10-cm depth and hourly), temporal and spatial variation in soil moisture under different sponge measures and their responses to rain events were analyzed, in addition to water quality changes were investigated by water sampling. The results showed, from 2000 to 2018, the area of farmland greatly decreased from 56.88 % to 5.02 % in Guyuan, while the area of construction land increased from 29.24 % to 45.96 %. The area of changes in Guyuan accounted for 63.68% of the total area. Precipitation in July and August was large, and accounted for 19.11% and 23.24% of the multi-year average precipitation, respectively. The grasslands and sunken green spaces exhibited good water retention effects, with average soil moisture of 14.40 % and 13.77 % during the study period, and 18.48 % and 15.52 % during the rain event, respectively. During the rain event, the total nitrogen (TN), ammonia nitrogen (NH3-N), available phosphorus (AP) and total phosphorus (TP) can be effectively reduced by the sunken green spaces, with average concentrations of 0.79 mg/L, 0.28 mg/L, 0.03 mg/L and 0.05 mg/L, respectively. The development of sponge measures could improve the urban ecological environment and hydrological conditions in the Loess Plateau, and increase the potential utilization of urban rainwater resources.

Quantitative assessment of background pollutants using a modified method in data-poor regions.

Heavy background pollutant loads pose a difficult problem for the assessment and management of regional water quality, especially in areas where surface water quality is less affected by anthropogenic pollution. Deducting background values from those derived from water quality monitoring is a new method for evaluating surface water environments in areas with heavy background loads. In this study, river source reserves in Heilongjiang province were evaluated with an export coefficient model (ECM) that considers the rainfall influence factor, has an improved timescale, and is based on synchronous rainfall monitoring data and concentrations. Moreover, the ECM was combined with a mechanism model. The chemical oxygen demand, ammonia nitrogen, and other water quality indices are affected by background environment, and therefore, suitable export coefficients for the study area were determined and a regression equation between the rainfall influence factor and precipitation was established. By combining the ECM and mechanism model, the concentrations entering the river during eight rainfall events in 2018 were predicted, and the background value was calculated to evaluate surface water quality. The predicted values were found to approximate the monitored values. Therefore, this study is of great significance for water quality assessment and management in areas with heavy background pollutant loads.

Drainage controls on the Donglingxing landslide (China) induced by rainfall and fluctuation in reservoir water levels

Rainfall, groundwater, and fluctuation in reservoir levels are considered among the main external factors affecting the stability of slopes. The impact of groundwater is particularly evident during the rainy season. In this paper, a case study on a geological investigation of the Donglingxing (DLX) landslide is presented to demonstrate a drainage control strategy. Due to the characteristics of the landslide and the limitations on the construction of stabilizing piles, a drainage tunnel system is herein used to reduce the risk of landslide. A comprehensive analysis is conducted on the monitoring data of rainfall, groundwater levels, reservoir water level, and drainage discharges from the tunnels. Based on field measurement data on groundwater level, water discharge, and deformation of the landslide before and after construction of the drainage tunnel, the effectiveness of the drainage tunnel system is evaluated. The results indicate that the drainage tunnel is effective in increasing the stability of landslide, and this work can serve as a reference case for other landslides.

APLICAÇÃO DO MÉTODO WTF NO ESTUDO DA VARIAILIDADE DA RECARGA EM AQUÍFERO URBANO

A expansão dos espaços urbanos causa diversos impactos ao meio ambiente, sendo a alteração da recarga de aquíferos um dos componentes hidrológicos mais afetados. Apesar do aporte de recarga por fontes não contínuas, como vazamentos de águas de abastecimento e esgoto, a impermeabilização provoca diminuição das áreas permeáveis, dificultando a infiltração das águas pluviais. O presente trabalho visa estimar a recarga direta (reserva reguladora) de origem natural em área urbana e avaliar sua variabilidade espacial, utilizando como estudo de caso a cidade de Frederico Westphalen. A estimação da recarga foi realizada para o período de um ano, por meio da aplicação do método WTF, utilizando dados de monitoramento pluviométrico e o monitoramento hidrogeológico, realizado com periodicidade mensal em treze poços localizados em lotes urbanos. A recarga total estimada na área foi de aproximadamente 245,57 mm/ano, correspondendo a 9,46% da precipitação total (2.596,8 mm), sendo observado que, quanto maior a espessura da camada não saturada, maior a taxa de recarga quantificada. Os resultados apresentados fornecem subsídios para a gestão das águas pluviais urbanas, além de demostrarem a necessidade urgente de ampliação e preservação das áreas permeáveis em zonas urbanas.

Regional debris flow susceptibility analysis based on principal component analysis and self-organizing map: a case study in Southwest China

A method was developed to analyze the susceptibilities of 541 regional basins affected by debris flows at the Wudongde Dam site in southwest China. Determining susceptibility requires information on source material quantity and occurrence frequency. However, the large number of debris flows can hinder the individual field investigation in a each small basin. Factors that may trigger debris flows can be identified using remotely sensed interpretation information. Susceptibility analysis can then be conducted based on these factors. In this study, SPOT5 satellite imagery, digital elevation models (DEM), a lithology distribution map, and rainfall monitoring data were used to identify 12 debris flow trigger factors: basin relief ratio, slope gradient in the initiation zone, drainage density, downslope curvature of the main channel, vegetation coverage, main channel aspect, topographic wetness index, Melton’s ruggedness number, lithology, annual rainfall, form factor, and cross-slope curvature of the transportation zone. Principal component analysis was used to obtain the eight principal components of these factors that contribute to susceptibility results. Then, a self-organizing map method was adopted to analyze the principal components, which resulted in a debris flow susceptibility classification. Field validation of 26 debris flow basins was used to evaluate the errors of the susceptibility classification, as well as assess the causes of such errors. The study found that principle component analysis and self-organizing map methodologies are good predictors of basin susceptibility to debris flows.

Sustainable yield of a karst aquifer system: a case study of Jinan springs in northern China

Based on the long-term monitoring data of rainfall, groundwater levels, groundwater abstraction, spring flow rates and groundwater quality, an assessment has been undertaken of the sustainable yield of a karst aquifer system in Shandong Province, northern China, to maintain perennial outflow of the karst springs while meeting water demands. One of the fundamental indicators for sustainable yield of groundwater is identified as maximum allowable water-level drawdown. A regional three-dimensional finite-difference numerical model has been developed to optimize the schemes associated with well fields and their locations and sustainable yields, in the Jinan spring catchment and its adjacent karst groundwater catchments, with the aim of maintaining the water level higher than the allowable lowest water level of 27.5 m above sea level. Furthermore, measures necessary to move towards sustainable use of the karst groundwater are outlined, drawing on contingency plans of water-source replacement and artificial recharge, dual water supply (based in water quality), use of the spring waters themselves, and groundwater quality protection.

AiNet- and GIS-based regional prediction system for the spatial and temporal probability of rainfall-triggered landslides

We developed a real-time forecasting system, aiNet-GISPSRIL, for evaluating the spatiotemporal probability of occurrence of rainfall-triggered landslides. In this system, the aiNet (a kind of artificial neutral network based on a self-organizing system) and GIS are merged for integrating the rainfall conditions into various environmental factors that influence the landslide occurrence and for simulating the complex non-linear relationships between landslide occurrence and its related conditions. Zhejiang Province (101,800 km2 in area), located in the southeast coastal region of China, is highly prone to the occurrence of landslides during intensive rainfall. Since 2003, the aiNet-GISPSRIL has been used to predict landslides during the rainy seasons in the region. The aiNet-GISPSRIL uses the regional 24-h forecast rainfall information and the real-time rainfall monitoring data from the rain-gauge network as its inputs, and then provides 24-h forecast of the landslide probability for every 1 × 1-km grid cell within the region. Verification studies on the performance of the aiNet-GISPSRIL show that the system has successfully predicted the dates and localities of 304 landslides (accounting for 66.2% of reported landslides during the period). During the period from 2003 to 2007, because the system provided the probability levels of landslide occurrences up to 24-h in advance, gave locations of potential landslides, and timely warned those individuals at high-risk areas, more than 1700 persons living in the risk sites had been evacuated to safe ground before the landslides occurred and thus casualty was avoided. This highly computerized, easy-operating system can be used as a prototype for developing forecasting systems in other regions that are prone to rainfall-triggered landslides.

The role of inter-event time definition and recovery of initial/depression loss for the accuracy in quantitative simulations of highway runoff

A long-term runoff monitoring was carried out in a highway drainage system in Winterthur, Switzerland. Several runoff quantity simulations were carried out using the distributed model ‘InfoWorks-CS’. Serial rainfall monitoring data were used for investigation of water runoff behaviour from the highway. The inter-event time definition was calculated from the runoff simulation and applied for better accurate runoff volume determination. Under continuous rainfall condition, the quantity simulation showed a good agreement with the measured hydrograph. However, in some cases where rainfall was not continuous, overestimation of runoff volume and difference in peak height/timing was found after rainfall halting. It was believed that the initial/depression loss on road surface was recovered during the halting period of rainfall and caused the difference in the runoff volume and peak height/timing difference in simulation. The consideration of regenerated depression loss significantly improved runoff simulation results in the on-and-off type rainfall events. This result showed that it was essential to estimate the inter-event time definition to consider appropriateness of the initial or intermediate loss.

A long-term suspended solids runoff simulation in a highway drainage system

A long-term monitoring investigation was carried out in a highway drainage system in Winterthur, Switzerland. Several runoff quality and quantity simulations were carried out using the distributed model 'InfoWorks-CS'. Serial rainfall monitoring data was used for investigation of SS runoff behavior from the highway. Under continuous rainfall conditions, the quantity simulation showed a good agreement with the measured hydrograph. However, in some cases where rainfall was not continuous, overestimation of the peak height was found at the later stage after the end of the rainfall. It was believed that the initial/depression loss on the road surface was recovered during the halting period of rainfall. The consideration of regenerated depression loss significantly improved runoff simulation results in the on-and-off type rainfall events. A single event quality simulation underestimated the SS load in light rainfall events. One of the reasons was possibly inadequate consideration of pipe sediment conditions. A long term simulation was carried out to establish the initial condition of surface and pipe sediment for the target event. The newly simulated pollutograph gave a good agreement with the measured one. It revealed that it was essential to consider appropriateness of the initial condition of pipe sediment as well as surface sediment.