Min Rainfall Research Articles

Investigation on the effect of fine solid wastes on the runoff purification performance of porous asphalt mixture

Fine solid wastes such as coal fly ash (CFA), diatomite, and red mud have been widely applied as alternative fillers for porous asphalt pavement (PAP), and have varying impacts on the mechanical performance of materials. However, whether they will affect the runoff purification performance of PAP has not been studied yet. Based on the laboratory simulation rainfall test, this study investigated the purification performance of porous asphalt mixture (PA) with three fine solid wastes fillers. Combined with the analysis of multi-scale pore characteristics of PA, the purification mechanism was further discussed. The results show that pollutants are mainly removed within 3 cm on the surface of PA in 20–30min rainfall. Diatomite and red mud fillers can effectively increase the removal rates of some heavy metals and nutrients by 20–40%. On the one hand, diatomite and red mud can leach some ions, which are conducive to physical adsorption and chemical degradation (including chemical precipitation and ion change) of pollutants. On the other hand, they also contain abundant porous structures and large specific surface areas, which significantly improve the micro-surface physical properties of PA and enhance the interaction between PA and pollutants.

Responses of Runoff and Soil Loss on Slopes to Land Use Management and Rainfall Characteristics in Northern China.

Soil conservation measures are widely used to control soil erosion and sediment loss; however, their proper usage relies on a deep understanding of the responses of runoff and sediment loss to land management and rainfall characteristics. In the present study, a long-term (2014–2020) monitored dataset derived from ten runoff plots in the upstream catchment of the Miyun Reservoir in Beijing, China, was used to study runoff and sediment loss responses to land use management and rainfall characteristics. The study results show that plots with no soil conservation measures had the highest runoff depth of 75 mm and suffered the highest sediment loss, at a rate of 3200 t km−2 yr−1. The terraced and vegetated plots generated lower runoff depths, with soil loss rates less than 213.0 t km−2 yr−1. With the exception of the contour tillage plots on steep slopes, the vegetation and engineering measures can efficiently reduce runoff and sediment loss, with both runoff and sediment reduction efficiencies higher than 76%. Statistical analyses indicate that, on the plots of bare soil and cultivation without soil conservation measures, runoff and sediment loss were mainly affected by the maximum 30 min rainfall intensity. However, on the plots with soil conservation measures, they were mainly determined by rainfall amount and duration. The sediment loss rate can be well fitted with the runoff depth using a power function. Based on the analyses, water-saving soil conservation measures are recommended for the study area. In addition, the size of terraces should be reconsidered on gentle slopes, and the coverage of forest, shrubs, and grass on slopes should be reduced, thus allowing for more surface runoff generation to ensure drinking water safety. In general, for the study area, soil conservation measures are required on the bare soil and cultivated slopes.

Evaluating methods for debris-flow prediction based on rainfall in an Alpine catchment

Abstract. The prediction of debris flows is relevant because this type of natural hazard can pose a threat to humans and infrastructure. Debris-flow (and landslide) early warning systems often rely on rainfall intensity–duration (ID) thresholds. Multiple competing methods exist for the determination of such ID thresholds but have not been objectively and thoroughly compared at multiple scales, and a validation and uncertainty assessment is often missing in their formulation. As a consequence, updating, interpreting, generalizing and comparing rainfall thresholds is challenging. Using a 17-year record of rainfall and 67 debris flows in a Swiss Alpine catchment (Illgraben), we determined ID thresholds and associated uncertainties as a function of record duration. Furthermore, we compared two methods for rainfall definition based on linear regression and/or true-skill-statistic maximization. The main difference between these approaches and the well-known frequentist method is that non-triggering rainfall events were also considered for obtaining ID-threshold parameters. Depending on the method applied, the ID-threshold parameters and their uncertainties differed significantly. We found that 25 debris flows are sufficient to constrain uncertainties in ID-threshold parameters to ±30 % for our study site. We further demonstrated the change in predictive performance of the two methods if a regional landslide data set with a regional rainfall product was used instead of a local one with local rainfall measurements. Hence, an important finding is that the ideal method for ID-threshold determination depends on the available landslide and rainfall data sets. Furthermore, for the local data set we tested if the ID-threshold performance can be increased by considering other rainfall properties (e.g. antecedent rainfall, maximum intensity) in a multivariate statistical learning algorithm based on decision trees (random forest). The highest predictive power was reached when the peak 30 min rainfall intensity was added to the ID variables, while no improvement was achieved by considering antecedent rainfall for debris-flow predictions in Illgraben. Although the increase in predictive performance with the random forest model over the classical ID threshold was small, such a framework could be valuable for future studies if more predictors are available from measured or modelled data.

Investigating event-based temporal patterns of design rainfall in a tropical region

ABSTRACT This study investigated the temporal rainfall pattern in order to facilitate rainfall design, which normally requires a good understanding of the temporal patterns of rainstorm events. The analysis employed a storm-event-based approach using the concept of inter-event time definition (IETD) and rainfall depth/duration/intensity thresholds. The 5-min rainfall data at three raingauge stations were analysed to determine representative quartiles of a design storm in a tropical city. The temporal characteristics of the design storm could be determined from the rainfall depth ratios of consecutive peak rainfalls for each interval of storm duration, and time to the first peak rainfall depending on each quartile’s rainstorm events. The determination of the quantile distribution of tropical rainfall could help improve the representativeness of design rainfall and facilitate rainfall–runoff modelling for urban flood control in a tropical region.

Influence of Wind-Induced Effects on Laser Disdrometer Measurements: Analysis and Compensation Strategies

Nowadays, laser disdrometers constitute a very appealing tool for measuring surface precipitation properties, by virtue of their capability to estimate not only the rainfall amount and intensity, but also the number, the size and the velocity of falling drops. However, disdrometric measures are affected by various sources of error being some of them related to environmental conditions. This work presents an assessment of Thies Clima laser disdrometer performance with a focus on the relationship between wind and the accuracy of the disdrometer output products. The 10-min average rainfall rate and total rainfall accumulation obtained by the disdrometer are systematically compared with the collocated measures of a standard tipping bucket rain gauge, the FAK010AA sensor, in terms of familiar statistical scores. A total of 42 rainy events, collected in a mountainous site of Southern Italy (Montevergine observatory), are used to support our analysis. The results show that the introduction of a new adaptive filtering in the disdrometric data processing can reduce the impact of sampling errors due to strong winds and heavy rain conditions. From a quantitative perspective, the novel filtering procedure improves by 8% the precipitation estimates with respect to the standard approach widely used in the literature. A deeper examination revealed that the signature of wind speed on raw velocity-diameter spectrographs gradually emerges with the rise of wind strength, thus causing a progressive increase of the wrongly allocated hydrometeors (which reaches 70% for wind speed greater than 8 m s−1). With the aid of reference rain-gauge rainfall data, we designed a second simple methodology that makes use of a correction factor to mitigate the wind-induced bias in disdrometric rainfall estimates. The resulting correction factor could be applied as an alternative to the adaptive filtering suggested by this study and may be of practical use when dealing with disdrometric data processing.

Identifying optimal ridge practices under different rainfall types on runoff and soil loss from sloping farmland in a humid subtropical region of Southern China

The relationship between different rainfall types, different soil management practices, and soil erosion is not yet fully understood. In-situ observations of soil and water loss on sloping farmland in the red soil region of southern China with a subtropical monsoon environment were taken at 12 runoff plots with four treatments, i.e, downslope ridges, downslope ridges with hedgerow intercropping, contour ridges, and bare flat land as control, over a seven-year period from 2012 to 2018. During this time, 253 natural rainfall events were classified into three rainfall types by K-means clustering according to the rainfall depth, maximum-30 min rainfall intensity and rainfall duration, and surface runoff and soil erosion processes in relation to the rainfall types under different ridge practices were analyzed. The results show that water-induced soil erosion on the flat land control was significant, with average annual soil loss of 76.73 t·ha−1·yr−1, reaching the “intense erosion” classification, and ridge practices were confirmed to reduce annual runoff and soil loss in all rainfall events by 18.9–62.0% and 68.9–86.3%, respectively. On the whole, rainfall events can be divided into three types: intense, normal, and long-duration. Among them, intense and normal rainfall cause the majority of soil (88.5–93.7%) and water (75.0–83.8%) loss in this area, but the efficiencies in runoff and soil reduction during long-duration rainfall events were the lowest, or even negative on farmlands with only downslope ridges. 20% of the total rainfall events, in which 84.3–92.2% were intense and normal rainfall events, contributed to 29–33% of the total rainfall depth, 68–89% of the total runoff depth, and 94–98% of the total soil loss. Rainfall depth played a dominant role in generating runoff, while runoff accumulation was a main factor influencing on soil loss. Findings from our study indicate that by choosing a more appropriate ridge practice according to different rainfall types, there can be a positive effect on soil and water conservation.

Rainfall spatio-temporal correlation and intermittency structure from micro-γ to meso-β scale in the Netherlands

AbstractWe investigate the spatio-temporal structure of rainfall at spatial scales from 7m to over 200 km in the Netherlands. We used data from two networks of laser disdrometers with complementary interstation distances in two Dutch cities (comprising five and six disdrometers, respectively) and a Dutch nationwide network of 31 automatic rain gauges. The smallest aggregation interval for which raindrop size distributions were collected by the disdrometers was 30 s, while the automatic rain gauges provided 10-min rainfall sums. This study aims to supplement other micro-γ investigations (usually performed in the context of spatial rainfall variability within a weather radar pixel) with new data, while characterizing the correlation structure across an extended range of scales. To quantify the spatio-temporal variability, we employ a two-parameter exponential model fitted to the spatial correlograms and characterize the parameters of the model as a function of the temporal aggregation interval. This widely used method allows for a meaningful comparison with seven other studies across contrasting climatic settings all around the world. We also separately analyzed the intermittency of the rainfall observations. We show that a single parameterization, consisting of a two-parameter exponential spatial model as a function of interstation distance combined with a power-law model for decorrelation distance as a function of aggregation interval, can coherently describe rainfall variability (both spatial correlation and intermittency) across a wide range of scales. Limiting the range of scales to those typically found in micro-γ variability studies (including four of the seven studies to which we compare our results) skews the parameterization and reduces its applicability to larger scales.

Analysis of Rainfall Erosivity Trends 1980–2018 in a Complex Terrain Region (Abruzzo, Central Italy) from Rain Gauges and Gridded Datasets

The erosive capacity of precipitation depends on its intensity, volume, and duration. The rainfall erosivity factor (R) of the Universal Soil Loss Equation (USLE) requires high frequency (subhourly) data. When these are not available, R can be estimated from simplified indices such as the Modified Fournier Index (MFI), the Precipitation Concentration Index (PCI), and the Seasonality Index (SI), which are computed from monthly precipitation. We calculated these indices for 34 stations in the complex terrain Abruzzo region (central Italy) during 1980–2018, based on both gauge (point) and grid datasets. Using 30-min rainfall data of 14 stations, we verified that MFI and PCI are reliable predictors of R (R2 = 0.91, RMSE = 163.6 MJ mm ha−1 h−1 year−1). For MFI, grid data do not capture the peaks in high-altitude stations and the low values in some inland areas, detected by the point dataset. Grid data show significant MFI positive trends in 74% of the stations, while the point data display significant positive trends in only 26% of stations and significant negative trends in four stations in the inland areas. The grid data complex orography requires preliminary validation work.

Estimation of the annual rainfall erosivity index based on hourly rainfall data in a tropical region

The annual mean rainfall erosivity (R) indicates the potential soil loss caused by the precipitation and runoff and is used to predict the soil loss from agricultural hillslopes. R is calculated from rainfall stations with continuously recording rainfall databases. However, many short-term real-time rainfall databases that also relate to the rainfall intensity are not readily available around Taiwan, with the hourly rainfall data being predominantly available. The annual mean rainfall erosivity calculated by the 10-min rainfall data accumulation converted to the 30-min rainfall data (R<sub>10_30</sub>) can be estimated using the annual mean rainfall erosivity calculated by the 10-min rainfall data accumulation convert to the hourly rainfall data (R<sub>10_60</sub>) that are calculated from the kinetic energy calculated by the 10-min rainfall data accumulation converted to the hourly rainfall data (E<sub>60j</sub>). The maximum 60-min rainfall intensity calculated by the 10-min rainfall data accumulation converted to the hourly rainfall data (I<sub>60j</sub>) has been established in rainfall stations throughout southern Taiwan. The 10-min rainfall data set consists of 15 221 storm events from 2002 to 2017 monitored by 51 rainfall stations located in the tropical regions in Taiwan. According to the results of this study, the average conversion factors of the kinetic energy (1.04), rainfall erosivity (1.47), and annual mean rainfall erosivity (1.30) could be estimated based on the 10-min rainfall data.

Effects of vegetation cover and slope on soil erosion in the Eastern Chinese Loess Plateau under different rainfall regimes.

Soil erosion is a critical environmental problem of the Chinese Loess Plateau (CLP). The effects of vegetation cover on soil erosion reduction under different rainfall types are not well understood especially in the eastern Chinese Loess Plateau (ECLP). In this study, we monitored runoff and sediment yield at the Fengjiagou water and soil conservation station with five types of vegetation cover (arbor trees (ARC), shrubs (SHC), arable (ABC), natural vegetation (NVC), and artificial grass (APC)) and three slope gradients (10°, 15°, and 20°) in the ECLP. Based on long-term monitoring data, five rainfall types were classified by the maximum 30 min rainfall intensity (I30). We also quantitatively revealed the interactive effects of different types precipitation, vegetation cover and slope gradients on regional soil erosion. The results showed that (1) The RII (13 times) and RIII (eight times) type are the most threatening erosive rainfall in this region. (2) The ARC and SHC type were most beneficial for soil and water conservation in the ECLP; The APC and ABC are not conductive to the prevention of regional soil erosion. (3) Runoff and sediment yields increased with the slope gradient. The farmland is vulnerable to soil erosion when the slope gradient exceeds 10°. The results of this study can improve the understanding of regional soil erosion processes on the ECLP and provide useful information for managing regional water and land resources.

Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess

Structure from motion (SfM) photogrammetry is a cost-effective topographic survey tool capable of producing high-quality 3-dimensional structure of a landform. Yet its application has rarely been reported in rill and interrill erosion at the relatively small spatial scales, especially when taking place in the loess that is vulnerable to erosion. The objective was to examine the accuracy and limits of SfM in quantifying rill and interrill erosion occurring in a typical loess during consecutive rainfall simulations. The loess collected from the plough layer of a cropland in the Loess Plateau of China was packed into a 200 × 100 × 35 cm runoff plot and received simulated rainfall at the intensity of 90 mm h−1 on three slopes of 10°, 15° and 20°. A portable laser scanner (LS) and SfM were used to measure soil surface at every 30 min until rill emergence and after another 30-min rainfall aiming to study rill development. Meanwhile, runoff and sediment samples were collected at the plot outlet and oven-dried to calculate the soil loss. The results showed that the elevation differences calculated by subtracting digital elevation models (DEMs) derived by SfM and LS mainly fell between −2 and 2 mm. Moreover, the root mean square error (RMSE) and mean absolute error (MAE) were mostly smaller than 3 mm, suggesting accurate soil erosion measurement made by SfM at the plot scale. Considering the surface variations, the relative RMSE and MAE, i.e., dividing over the mean elevations measured by LS, were found to decrease as soil erosion proceeded and rills emerged. The rill morphology comparison, however, suggested a better fit of SfM for rills larger than 9 cm in maximum surface width, 6.0 × 10−2 m2 in area and 0.9 × 10−3 m3 in volume. In accordance with DEM comparisons, the soil losses estimated by SfM and LS were statistically similar. Nevertheless, these values were much greater than the amount of sediments collected for the early simulation runs, which might be explained primarily by the settling of loess when subject to heavy rainfall. But as rainfall continued and rills further developed, the misestimations made by LS and SfM remarkably dropped, i.e., from −17.8% to 4.9% and from −18.1% to 4.3%, respectively. These findings suggest a generally higher accuracy of SfM in quantifying rill erosion with more fluctuating soil surface than in interrill erosion measurement.

Water-Saving Soil Conservation Measures Should Be Used in Northern China: Evidence from Runoff Plot Data

Most of the current studies on soil conservation measures mainly focus on their soil control effect, neglecting their impact on water quantity. In the present study, the latest seven years (2014–2020) of monitored data from 22 runoff plots in the upstream catchment of the Miyun Reservoir, Beijing were used to evaluate the effects of slope, rainfall, and soil conservation measures on soil and water loss, and some implications were given in this water-scarce region. Excluding the impact of soil conservation measures, soil loss increased with the slope gradient and slope length. Runoff and soil loss were greatly affected by the rainfall amount and maximum 30-min rainfall intensity on the bare and cultivated slopes, or by rainfall amount and rainfall duration on almost all of the plots with soil conservation measures. The results indicated that the bare soil suffered the most severe soil loss, with a mean annual soil loss rate (SLR) of 4325 t km−2 year−1, followed by the cultivated lands without any measure, with an annual SLR of above 3205 t km−2 year−1. Contour tillage cannot effectively control soil loss on steep slopes. The vegetation measures and terrace, level bench, and fish scale pits, as well as their combinations, can decrease runoff by above 86% and decrease soil loss by 95%, respectively. Water-saving measures should be implemented in the study region. The measures, such as vegetation coverage, terracing, contour tillage, etc., should be carefully implemented on slopes. Bare and cultivated lands should further be implemented with soil conservation measures in this and similar regions in the world.

Convective precipitation trends in the Spanish Mediterranean region

This paper aims to analyse the distribution and temporal evolution of convective precipitation in the Mediterranean region of Spain. To accomplish this goal, we used 148 sets of 5-min rainfall rate data from the 1989–2015 period. The selected regions were the Júcar Hydrographic Confederation (CHJ) and the Internal Basins of Catalonia (CIC), which cover most of the autonomous communities of Catalonia and the Valencian Community (east Spain). The average 5-min intensity threshold of 35 mm/h and the β parameter, defined as the ratio between convective precipitation versus total precipitation in any period, were used to characterise convective precipitation. Convective episodes were categorised as “very convective”, “moderately convective”, and “slightly convective” based on the β value. After quality control, the series of 129 stations were clustered into homogeneous precipitation zones that also include β as one of the variables of characterisation. The results show that convective precipitation can contribute to total annual precipitation by up to 16% on average, but it is generated by a very small percentage of convective events (between 3% and 6% across all the stations) in comparison with the total number of rainfall episodes. In this sense, moderately convective events are the most common, with a predominantly unimodal monthly distribution of β, with summer the most convective season. Trends show a significant increase in precipitation, convective precipitation, and convective episodes in the CHJ. On the other hand, a positive trend of convective events is predominant in the CIC region, despite an overall precipitation decrease in the analysed period. These results are relevant given that extreme daily rainfall does not show a positive or significant trend, and they are in line with the impact of climate change on increased atmospheric instability and water vapour in the atmosphere. They highlight the need to work with sub-daily precipitation series in the case of the Mediterranean, which is mainly affected by flash floods.

Key drivers of pyrogenic carbon redistribution during a simulated rainfall event

Abstract. Pyrogenic carbon (PyC) is produced by the incomplete combustion of vegetation during wildfires and is a major and persistent pool of the global carbon (C) cycle. However, its redistribution in the landscape after fires remains largely unknown. Therefore, we conducted rainfall simulation experiments on 0.25 m2 plots with two distinct Swiss forest soils (Cambisol (clay loam) and Luvisol (sandy silt)). We applied PyC produced from wood (Picea abies) labeled under FACE conditions and C4 grass (Miscanthus sinensis) to the soil surface to study PyC redistribution by runoff and splash and the vertical mobility of PyC in a 10 cm unsaturated soil column based on the differences in δ13C of soils and PyC. We assessed the effect of soil texture, slope angle and PyC characteristics (feedstock and particle size) on the mobility of PyC during 30 min of intense rainfall (102 mm h−1). Our results highlight that PyC is highly mobile. Surface runoff transported between 0.2 % and 36.0 % of the total added PyC. Erosion by splash further redistributed 10.3 % to 25.3 % of the added PyC. Soil type had a substantial impact on the redistribution of PyC by both runoff and splash: on average, we recovered 10.5 % of the added PyC in runoff and splashed material for the clay-rich Cambisol and 61.3 % of the added PyC for the sandy silt Luvisol combined. PyC feedstock had a clear but contrasting effect on PyC redistribution: relocation in the runoff and splashed material was greater for wood PyC (43.4 % of total added PyC) than grass PyC (28.4 %). However, more wood PyC (11.5 %; fraction of organic C derived from the PyC) remained where it was initially applied compared to grass PyC (7.4 %). The results further suggest that the effect of PyC characteristics on its mobility can be highly variable and depend not only on the material from which it was derived, but also on other factors (e.g., particle size, porosity, density). In particular, the mobility of PyC was almost twice as large for fine-grained PyC (< 63 µm) than for coarse PyC (63 µm–2 mm). Vertical mobility of PyC up to 10 cm depth was greater in the clay-rich, well-aggregated Cambisol but limited in the physically instable Luvisol, likely due to quick aggregate breakdown and surface sealing. The addition of PyC to the surface of the studied soils further induced changes in the export of native soil organic carbon (nSOC) after the 30 min rainfall event. Our study shows that large quantities of PyC can be redistributed by water erosion over short timescales and that the mobility of PyC depends to a great extent on the response of soils to rainfall. Moreover, the addition and redistribution of PyC affects the export of nSOC and thus the C budget of fire-affected soils and catchments.

Evaluation of Rainfall Erosivity Factor Estimation Using Machine and Deep Learning Models

Rainfall erosivity factor (R-factor) is one of the Universal Soil Loss Equation (USLE) input parameters that account for impacts of rainfall intensity in estimating soil loss. Although many studies have calculated the R-factor using various empirical methods or the USLE method, these methods are time-consuming and require specialized knowledge for the user. The purpose of this study is to develop machine learning models to predict the R-factor faster and more accurately than the previous methods. For this, this study calculated R-factor using 1-min interval rainfall data for improved accuracy of the target value. First, the monthly R-factors were calculated using the USLE calculation method to identify the characteristics of monthly rainfall-runoff induced erosion. In turn, machine learning models were developed to predict the R-factor using the monthly R-factors calculated at 50 sites in Korea as target values. The machine learning algorithms used for this study were Decision Tree, K-Nearest Neighbors, Multilayer Perceptron, Random Forest, Gradient Boosting, eXtreme Gradient Boost, and Deep Neural Network. As a result of the validation with 20% randomly selected data, the Deep Neural Network (DNN), among seven models, showed the greatest prediction accuracy results. The DNN developed in this study was tested for six sites in Korea to demonstrate trained model performance with Nash–Sutcliffe Efficiency (NSE) and the coefficient of determination (R2) of 0.87. This means that our findings show that DNN can be efficiently used to estimate monthly R-factor at the desired site with much less effort and time with total monthly precipitation, maximum daily precipitation, and maximum hourly precipitation data. It will be used not only to calculate soil erosion risk but also to establish soil conservation plans and identify areas at risk of soil disasters by calculating rainfall erosivity factors.

Effects of slope length on soil erosion of Karst slope under different rainfall conditions

Based on the runoff and sediment yield data from 59 erosive rainfall plots with different slope lengths (5, 10, 15, 20, 25 m) in Shiqiao small watershed of Guizhou Province from 2012 to 2014, we analyzed the relationship between runoff and sediment yield and slope length under diffe-rent rainfall conditions. The results showed that, with the increases of slope length, the runoff yield of slope showed a 'V-shape' pattern, the sediment yield of slope increased first and then decreased. According to rainfall amount, rainfall duration, and average rainfall intensity, the 59 erosive rainfall in the study area could be divided into three types, including type A with short duration, heavy rain intensity and small rainfall, type B with medium duration, light rain intensity and medium rainfall, and type C with long duration, medium rain intensity and large rainfall. The relationships between runoff and sediment yield and slope length were different under different rainfall patterns. There was about 20 m critical slope length of sediment yield under type A and B. The sediment yield gradually increased with the increases of slope length under type C. There was a good cubic function relationship between slope length and runoff and sediment yield under different rainfall patterns. The variable amplitude of runoff and sediment yield was different among different slope lengths. Except the slope length of 15-20 m, the variable amplitude of runoff and sediment yield under type C was relatively large. The variation amplitude of sediment yield was significantly higher than that under other rainfall patterns. The total runoff yield under different rainfall patterns was type A>B>C. The sediment yield under type B was the smallest, that of type A at the slope length of 20 m was the largest and that of type C at other slope lengths was the largest. The correlation between compound rainfall factors and runoff and sediment yield was better than that of single rainfall factor under type A (common rainfall type in the study area). Rainfall amount (P), the pro-duct of rainfall duration and maximum 30 min rainfall intensity (TI30), product of rainfall duration and average rainfall intensity (TI), product of rainfall amount and rainfall duration (PT) were significantly correlated with the runoff and sediment yield. Among those factors, P and TI had the strongest correlation with runoff. Further, the relationship between them and runoff under different slope lengths could be expressed by linear equation and S-curve. There was a good cubic function relationship between the sediment yield and its corresponding rainfall factors under different slope lengths.

Multifractal Properties of Temporal Rainfall Series in Peninsular Malaysia

Studies on the investigation of scale-invariance of rainfall are still in the early development stage in the humid tropical regions. In order to further enhance understanding of the rainfall variability across a range of temporal scales in these regions, this study aims to investigate and characterize rainfall in a multifractal framework from areas in Peninsular Malaysia. It is done by studying the scaling of the statistical properties of rainfall. Data set consisting of 15 min rainfall observations from 56 rain gauge stations were adopted and the stations were grouped into four regions to identify the possibility that the multifractal properties of rainfall could depend on the geographical locations and local climatology. The results show that the temporal structure of rainfall in Peninsular Malaysia displays a multifractal behaviour for scales ranging from 15 min to about 3 days. The multifractal parameters that described the scaling properties of rainfall in terms of intermittency and multifractality revealed to be different for each region in the peninsula, particularly between the west and east coasts. The rainfall process for east coast was characterized by less intermittent rain with the rainfall fluctuations displaying a strong degree of multifractality. While for the west coast which consists of northwest, west and southwest regions, they exhibited a similar distribution of rainfall occurrences which is very intermittent and unsmoothed. Rainfall fluctuations, however, were spikier in northwest regions than in the west and southwest regions.

An Operational Multi-Radar Multi-Sensor QPE System in Taiwan

AbstractOver the last two decades, the Central Weather Bureau of Taiwan and the U.S. National Severe Storms Laboratory have been involved in a research and development collaboration to improve the monitoring and prediction of river flooding, flash floods, debris flows, and severe storms for Taiwan. The collaboration resulted in the Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system. The QPESUMS system integrates observations from multiple mixed-band weather radars, rain gauges, and numerical weather prediction model fields to produce high-resolution (1 km) and rapid-update (10 min) rainfall and severe storm monitoring and prediction products. The rainfall products are widely used by government agencies and emergency managers in Taiwan for flood and mudslide warnings as well as for water resource management. The 3D reflectivity mosaic and QPE products are also used in high-resolution radar data assimilation and for the verification of numerical weather prediction model forecasts. The system facilitated collaborations with academic communities for research and development of radar applications, including quantitative precipitation estimation and nowcasting. This paper provides an overview of the operational QPE capabilities in the Taiwan QPESUMS system.

Evaluation of the efficiency of the rainfall simulator to achieve a regional model of erosion (case study: Toroq watershed in the east north of Iran)

The purpose of this study was to obtain the regional model of erosion according to the specific climatic, adaptive, and other conditions of the Toroq watershed located in the east north of Khorasan Razavi province. To conduct this research, first, the homogeneous units were prepared using slope maps, lithology, land use, and erosion forms in a Geographic Information System environment. Then, to optimize the number of homogeneous units, the cluster analysis method was used in Statistical Product and Service Solutions (SPSS) software. The diagnostic analysis confirmed the accuracy of cluster analysis inhomogeneous regions. Field operations were carried out in homogeneous units with the establishment of a rainfall simulator and also the application of 30-min rainfall intensity with a return period of 10 years. Also, the collected soil samples were analyzed in the laboratory. After performing statistical analyses in the SPSS environment, the variables affecting erosion were determined and prioritized. Then, through the use of multivariate linear regression and step-by-step and interpolation methods, the equations for estimating the amount of erosion were determined. Finally, the multivariate linear model of plot erosion was prepared using the step-by-step method using two variables of plot slope and land use. The model was selected for estimating erosion after examining different validation methods based on less RE and less RMSE, higher R, low significance coefficient (Sig < 0.05), and also fewer inputs.

Characterization of standardized heavy rainfall profiles for Barcelona city: clustering, rain amounts and intensity peaks

Standardized heavy rainfall profiles may contribute to a best knowledge concerning flash floods, ground erosion and runoff. Taking advantage of the rain rate gauges network of Barcelona city and applying a short integration time of 5 min, the heavy rainfall records with amounts above 25 mm and longer than 60 min have been selected along 15 years, being detected 499 records corresponding to 67 episodes. The amount distribution of these records are analysed at time deciles. By grouping these standardized rainfall profiles according to their similarity by means of the average linkage clustering algorithm, 10 clusters are derived, each one of them characterized by different time evolution of rainfall. The representative standardized rainfall profiles for every one of the clusters, together with maximum 5-min rain amounts and rainfall amounts characterizing them, permit to distinguish rainfall patterns. In addition, the extreme heavy rainfalls which may lead to flash floods are identified, as also their respective synoptic situations. In short, this analysis offers a description of heavy rainfall patterns in Barcelona city, complementing previous papers on the normalized intensity curves and 5-min intensity return periods. These heavy rainfall analyses would be very useful when designing drainage and sewerage systems in urban areas as Barcelona, where flash floods may be expected due to episodes of notable rainfall amount and intensity. The imperviousness density of the soil and an appropriate sewerage structure should be adapted to mitigate the effects of these copious and intense episodes.