Rainstorm Characteristics Research Articles

Global Rainstorm Temporal Variation from 1979 to 2016 Based on the Perspective of Land-Ocean Differentiation

Based on the ERA-Interim precipitation data from 1979 to 2016, this paper uses a variety of statistical methods to diagnose the multi-attribute time series characteristics of global rainstorms and its response to ENSO from the perspective of land-ocean differentiation. The results showed as follows. (1) The global, global land and global ocean rainstorm and their contribution rates showed an increasing trend from 1979 to 2016. The global, global land and global ocean total rainfall showed an decreasing trend. The global land total rainfall showed a distinct sectional change pattern, which first increased from 1979 to 2006 and then decreased from 2007 to 2016. The comparison between the rainstorm and the total rainfall in global land and ocean showed that the rainstorm tended to increase in both ocean and land regions from 1979 to 2016, while the weak intensity rainfall tends to decrease in the globe. (2) The results of MK mutation test showed that the global, global land and global ocean rainstorm changed abruptly in the year of 2006, 1999 and 2008, respectively, without passing the 0.05 significance level test. The global, global land and global ocean total rainfall changed abruptly in the year of 1998, 2014 and 1994, respectively, and passed the test of 0.05 significance level. The rainstorm contribution rates of global, global land and global ocean changed abruptly in the year of 2006, 2003 and 2007, respectively. Only global land rainstorm and global ocean rainstorm passed the 0.05 significance level test. The year of abruptly change of global rainstorm and total rainfall were consistent with the year of ENSO warm event or the year of transition from cold event to warm event. (3) The global land and ocean rainstorm and total rainfall did not change consistently on multiple time scales from 1979 to 2016, but showed inverse phase or forward and lag phase correlation. Fourthly, compared with ENSO, global land (ocean) rainstorm changed earlier (lag) in high energy spectral region. Compared with ENSO changes in low energy spectral region, global land rainstorm changes were consistent or ahead of time, while global ocean rainstorm changes were mainly ahead of time compared with ENSO changes.

Dynamic spatial-temporal precipitation distribution models for short-duration rainstorms in Shenzhen, China based on machine learning

Abstract Short-duration rainstorm, the main cause of urban waterlogging and mountain torrents, is characterized by sudden, intense, and highly destructive rainfall. Understanding the dynamic temporal and spatial distribution patterns of short-duration rainstorm can help to predict their development processes. In this study, the dynamic temporal and spatial distribution models of various types of short-duration rainstorm events were established by using machine learning (ML) method based on the rainfall data of the recent decade in a Chinese coastal megacity, Shenzhen. The dynamic characteristics of these rainstorm events were extracted by using ML method in conjunction with the Locally Linear Embedding algorithm, which shows a potential capability to predict the developmental trend of a heavy rainstorm before it occurs. Based on the method put forward in the current study, characteristic rainfall process models consistent with the local temporal and spatial distribution characteristics of rainstorms can be designed, which is important to understand the risks of the rainstorms and consequently helpful for the assessment of urban flood insurance, the scientific design of drainage systems and the forecasting and warning of urban waterlogging.

Spatiotemporal Changes of Urban Rainstorm-Related Micro-Blogging Activities in Response to Rainstorms: A Case Study in Beijing, China

Natural disasters cause significant casualties and losses in urban areas every year. Further, the frequency and intensity of natural disasters have increased significantly over the past couple of decades in the context of global climate change. Understanding how urban dwellers learn about and response to a natural hazard is of great significance as more and more people migrate to cities. Social media has become one of the most essential communication platforms in the virtual space for users to share their knowledge, information, and opinions about almost everything in the physical world. Geo-tagged posts published on different social media platforms contain a huge amount of information that can help us to better understand the dynamics of collective geo-tagged human activities. In this study, we investigated the spatiotemporal distribution patterns of the collective geo-tagged human activities in Beijing when it was afflicted by the “6-22” rainstorm. We used a variety of machine learning and statistical methods to examine the correlations between rainstorm-related microblogs and the rainstorm characteristics at a fine spatial and a fine temporal scale across Beijing. We also studied factors that could be used to explain the changes of the rainstorm-related blogging activities. Our results show that the human response to a disaster is very consistent, though with certain time lags, in the virtual and physical spaces at both the grid and city scales. Such a consistency varies significantly across our study area.

Assessing sub-daily rainstorm variability and its effects on flood processes in the Yangtze River Delta region

ABSTRACTTaking a representative catchment of the Yangtze River Delta region as the study area, this research evaluated sub-daily rainstorm variability and its potential effects on flood processes based on an integrated approach of the HEC-HMS model and design storm hyetographs. The results show that the intensities of rainfall on sub-daily scale are getting more extreme. The annual maximum 1-, 2- and 3-hour rainstorms followed significant upward trends with increases of 0.32, 0.43 and 0.44 mm per year, respectively, while the annual maximum 6-, 12- and 24-h events had non-significant rising trends. The detected significant trends in short-duration rainstorms were then used to redesign storm hyetographs to drive the HEC-HMS model, the results show that these changes in short-duration rainstorm characteristics would increase the flood peak discharge and flood volume. These findings indicate that regional flood control capabilities must be improved to manage the adverse impacts of rainfall variation under changing environments.

Simulation of rainfall runoff based on flood season stage

The staging simulation model is based on the flood season staging, which considering the weather system genesis and rainstorm characteristics. Moreover, the physical mechanism of rainfall runoff can be comprehensively considered, and the physical meaning of the parameter can be better reflected in different stages. In this paper, the Tingxia basins in the humid and semi-humid areas are selected, which the flood season can be divided into in plum rains period and the typhoon period, then the staged simulation model is constructed by the staged rate. Some statistical indicators are introduced to evaluate the effectiveness of the staging rainfall-runoff model in improving simulation accuracy, the simulation results are ideal, and the accuracy is improved.

Lateral transport of soil total carbon with slope runoff and interflow: Effects of rainstorm characteristics under simulated rainfall

In order to study the characteristics of soil total carbon (TC) transport with slope runoff and interflow during rainstorms in the Zhejiang-Fujian hilly region, China. Slope gradients (5, 8, 15, 25°) and rainfall intensities (60, 90, 150 mm·h−1) were selected as the variable factors for artificially simulated rainfall experiments. Runoff samples were collected every 3 min to measure the volume and TC mass concentration, then we calculated the TC loss rates and loss gross amount. The results showed that the overall trend of TC mass concentration in slope runoff presented a high initial value that gradually decreased with the increase of rainfall duration and finally tended to be stable, and it mean mass concentration was relatively highest at all the 15° conditions. The TC loss rates presented a stability at a certain value after gradually increasing over time at gentle slopes while it led to an increasing trend when the slope was steeper, yet these trends weren't obvious at 150 mm·h−1 condition. The initial TC mass concentration was low at beginning in interflow which rose rapidly to the peak and finally continued to drop to a stable level. The shape of TC loss rate curves was similar to mass concentration curves. For both slope runoff and interflow, the slope gradient had little effect on TC mass concentration. The TC loss gross amount in the runoff (slope runoff + interflow) increased with the increase of slope gradients or rainfall intensities, which reached the maximum value at the 25°, 150 mm·h−1 condition, namely, 12.56 g, though the increase rates of TC transport decreased. The TC loss gross amount with slope runoff showed a trend of increasing first and then decreasing with increasing slope gradients, which all reached the maximum at 8° conditions, however it showed a continued rising trend as slope gradients increased in interflow. TC at 15° and 25° conditions mainly lost with the interflow, though at other slope gradients it mainly transported with the slope runoff. Similarly, the more gentle the slope gradients, the greater the proportion of the slope runoff volume in total runoff. The regression analysis showed at identical conditions, the influence of rainfall intensity on TC loss was larger than slope gradient in slope runoff while the slope gradient had a greater influence on TC loss in interflow. Correlation analysis showed that there was a significant correlation between the runoff volume and the TC loss gross amount in slope runoff and interflow (P < 0.01). There was a linear correlation between runoff volume and TC loss in slope runoff (R2 = 0.95), and power function fits the relationship between TC loss in interflow and runoff volume better (R2 = 0.66). The results provided a calculation method for estimating TC loss in runoff from bare land of weathered granite parent soil in the Zhejiang-Fujian hilly region of China.

Monsoon Rainstorm Characteristics for Varying Inter-event Intervals at a Site on West Coast of India

Continuous hourly rainfall records from a site on the western coast of India were examined to ascertain the effects of the inter-event interval (IET) considered for the segregation of the individual rainstorms from the continuous datasets. The maximum 24-h rainfall displayed high variability though the number of rainy days, the total rainfall volume and the maximum hourly intensity all were within one standard deviation from the mean in most of the years. The reduction in number of independent rainstorms was very steep up to IET of 7 h, moderate from 7 to 20 h, and very gradual beyond the value of IET greater than 20 h. Wetter years required higher separation between rainstorms for statistical independence and consequently recorded fewer number of rainstorms for a particular separation period. The duration of segregated rainstorms as well as their total volume of rainfall in rainstorm displayed high variability, whereas the average rainfall intensity of the rainstorms varied in a somewhat haphazard fashion, possibly due to non-correlated variation of the duration and total rainfall. Like these characteristics, the temporal distribution of rainfall in a rainstorm was also observed to be severely affected by the choice of the IET.

Development of a Stochastic Storm Generator Using High-Resolution Precipitation Records

Abstract.Sophisticated field and watershed scale environmental models for runoff, erosion control, environmental, and global-change investigations require detailed continuous temporal and spatial inputs of precipitation to drive the hydrologic processes. For accurate estimates of these processes, the resolution of the input data must allow the representation of the variability of precipitation as it represents a major source of variability in the model outputs. Currently, the use of stochastic weather generators is widespread to generate continuous series of meteorological data at gauged and ungauged locations. These weather simulators are designed to replicate the statistical properties of real weather data at monthly or daily time resolutions. However, daily values of precipitation do not represent the variability of storm parameters within a day, which is assumed to significantly influence the predictions of environmental or agricultural models where processes are sensitive to sub-daily values. This research proposes a parsimonious stochastic storm generator based on 5-min time resolution and correlated non-normal Monte Carlo-based numerical simulation. The model considers correlated non-normal random rainstorm characteristics such as time between storms, duration, and amount of precipitation, as well as the storm intensity structure. The accuracy of the model was verified by comparing the generated rainfall with rainfall data from a randomly selected 5-min weather station in North Carolina. Current results have shown that the proposed storm generator can capture the essential statistical features of rainstorms as well as their patterns followed by their intensities, preserving the first four moments of monthly storm events, good annual extreme event correspondence, and the correlation structure within each storm. Finally, as the proposed model depends on statistical properties at a site, this may allow the use of the synthetic storms in ungauged locations provided relevant information from a regional analysis is available. Keywords: Monte Carlo, Stochastic storm generator, Storm distribution.

Utilization of a C-band Polarimetric Radar for Severe Rainfall Event Analysis in Complex Terrain over Eastern China

Polarimetric radar measurements and products perform as the cornerstones of modern severe weather warning and nowcast systems. Two radar quantitative precipitation estimation (QPE) frameworks, one based on a radar-gauge feedback mechanism and the other based on standard rain drop size distribution (DSD)-derived rainfall retrieval relationships, are both evaluated and investigated through an extreme severe convective rainfall event that occurred on 23 June 2015 in the mountainous region over eastern China, using the first routinely operational C-band polarimetric radar in China. Complex rainstorm characteristics, as indicated by polarimetric radar observables, are also presented to account for the severe rainfall field center located in the gap between gauge stations. Our results show that (i) the improvements of the gauge-feedback-derived radar QPE estimator can be attributed to the attenuation correction technique and dynamically adjusted Z–R relationships, but it greatly relies on the gauge measurement accuracy. (ii) A DSD-derived radar QPE estimator based on the specific differential phase (KDP) performs best among all rainfall estimators, and the interaction between the mesocyclone and the windward slope of the mountainous terrain can account for its apparent overestimation. (iii) The rainstorm is mainly dominated by small-sized and moderate-sized raindrops, with the mean volume diameter being less than 2 mm, but its KDP column (KDP &gt; 3°·km−1) has a liquid water content that is higher than 2.4815 g·m−3, and a high raindrop concentration (Nw) with log10(Nw) exceeding 5.1 mm−1m−3. In addition, small hailstones falling and melting are also found in this event, which further aggregates Nw upon the severe rainfall center in the gap between gauge stations.

Infiltration-excess runoff properties of dryland floodplain soil types under simulated rainfall conditions

The study estimated infiltration-excess runoff properties of three floodplain soil-types under aquifer water management at Anglo American Kolomela Iron Ore mine in Postmasburg, Northern Cape Province of South Africa. Rainstorm regimes of amounts 60 (high), 30 (medium), and 15 (low) mm with respective intensities of 1.61, 0.52, and 0.27 mm min−1 were simulated on 1 m2 plot with 1% slope. Infiltration-excess runoff properties were affected by a rainstorm, but not soil-type. When combined with rainstorm, soil-type affected accumulative run-off rates. High rainstorm had different (p ≤ 0.05) accumulative runoff rates (0.1–0.61 mm min−1) and increased with clay content. Different response times of 4, 10, and 17 min for respective high, medium, and low rainstorms were quickest on higher clay plus silt content and bulk-density under high and lower rainstorms, respectively. Lower rainstorms had similar effects on accumulative runoff rates (0.01–0.05 mm min−1), total runoff yield (0.59–18 mm), and runoff coefficients (4.29–18%). Under the high rainstorm, total runoff yields (11.4–25.8 mm) and runoff coefficients (19–42.9%) were different and increased with clay plus fine-silt content. Although simulated rainstorms had constant intensities, results showed high rainstorms to be of primal influence on infiltration-excess runoff. Clay plus silt content and bulk-density influenced infiltration-runoff properties for respective high and lower rainstorms. Apart from rainstorm characteristics, surface clay plus silt content and bulk-density are important for harnessing surface runoff in floodplains for aquifer recharge.

Synoptic-Scale Control over Modern Rainfall and Flood Patterns in the Levant Drylands with Implications for Past Climates

Abstract Rainfall in the Levant drylands is scarce but can potentially generate high-magnitude flash floods. Rainstorms are caused by distinct synoptic-scale circulation patterns: Mediterranean cyclone (MC), active Red Sea trough (ARST), and subtropical jet stream (STJ) disturbances, also termed tropical plumes (TPs). The unique spatiotemporal characteristics of rainstorms and floods for each circulation pattern were identified. Meteorological reanalyses, quantitative precipitation estimates from weather radars, hydrological data, and indicators of geomorphic changes from remote sensing imagery were used to characterize the chain of hydrometeorological processes leading to distinct flood patterns in the region. Significant differences in the hydrometeorology of these three flood-producing synoptic systems were identified: MC storms draw moisture from the Mediterranean and generate moderate rainfall in the northern part of the region. ARST and TP storms transfer large amounts of moisture from the south, which is converted to rainfall in the hyperarid southernmost parts of the Levant. ARST rainfall is local and intense, whereas TP rainfall is widespread and prolonged due to high precipitation efficiency and large-scale forcing. Thus, TP rainfall generates high-magnitude floods in the largest catchments; integration of numerous basins leads to sediment feeding from the south into the Dead Sea, exhibited in large sediment plumes. Anecdotal observations of the channel with the largest catchment in the region (Nahal HaArava) indicate that TP floods account for noticeable geomorphic changes in the channel. It provides insights into past intervals of increased flash flood frequency characterized by episodes of marked hydrogeomorphic work; such an increase is especially expected during intervals of southerly situated and southwesterly oriented STJs.

Multivariate frequency analysis of urban rainfall characteristics using three-dimensional copulas

Urban runoff is a major cause of urban flooding and is difficult to monitor in the long term. In contrast, long term continuous rainfall data are generally available for any given region. As a result, it has become customary to use design rainfall depth as a proxy for runoff in urban hydrological analyses, with an assumption of the same frequency for runoff and rainfall. However, this approach has lack of overall coordination and cannot fully reflect the variability of rainfall characteristics. To address this issue, this study presents a three-dimensional copula-based multivariate frequency analysis of rainfall characteristics based on a long term (1961-2012) rainfall data from Guangzhou, China. Firstly, continuous rainfall data were divided into individual rainfall events using the rainfall intensity method. Then the characteristic variables of rainfall (design rainfall depth, DRD; total rainfall depth, TRD; peak rainfall depth, PRD) were sampled using the annual maximum method. Finally, a copula method was used to develop the multivariate joint probability distribution and the conditional probability distribution of rainfall characteristics. The results showed that the copula-based method is easy to implement and can better reflect urban rainstorm characteristics. It can serve a scientific reference for urban flood control and drainage planning.

Assessing Changes in Rainstorms in Beijing During the Last 50 Years

Abstract: With global warming, rainstorms and other extreme weather events are occurring frequently, leading to urban waterlogging disasters. A study on spatiotemporal variation characteristics of rainstorms in urban areas can provide scientific support for the design of urban drainage facilities to mitigate the damage of urban flooding disasters. Drawing on daily rainfall data from 20 meteorological stations during 1960–2010, this study analyzed change trends for annual rainstorms in Beijing, using the Mann-Kendall approach and cumulative departure curve as methodology. The results show that annual days of rainstorms in Beijing decreased non-significantly, but the precipitation of rainstorms and annual maximum daily precipitation declined significantly. The frequency of rainstorms generally decreased from southeast to northwest, with the greatest decrease occurring in the southeast plain areas. The results of this study contribute to the understanding of rainstorm risk in Beijing.

Analysis of Durative Rainstorm Characteristics Occurred in the Ambient Area of Qinghai-Xizang Plateau

Analysis of Durative Rainstorm Characteristics Occurred in the Ambient Area of Qinghai-Xizang Plateau

Correlating check dam sedimentation and rainstorm characteristics on the Loess Plateau, China

On the Loess Plateau, China, check dams are necessary for soil and water conservation. In this study, the relationships between check dam sedimentation and storm characteristics were investigated, and rainstorm events for an area of data scarcity were reconstructed using optimal regression models. Four typical check dams of the Loess Plateau (the Shipanmao, Hualiang, No. 3 Guandigou, and No. 4 Guandigou dams) were selected for case studies. Soil profiles behind the four dams were divided into 21, 25, 31, and 31 layers, respectively. The one-to-one link between sediment layers and corresponding storm characteristics were considered based on the peak fallout of 137Cs and on the principle that higher flow corresponds to higher sediment deposition volume. Analysis showed that the layered sediment volume (V) was closely related to rainfall erosivity (R), and to the maximum rainfall intensity over 30min (I30). A statistically significant power regression model between V and R was observed, along with an exponential regression model between V and I30. Based on the power regression model between V and R, a new approach was developed in order to reconstruct rainfall erosivity in rainfall data-scarcity areas. Different hysteresis patterns (counterclockwise, clockwise, and hybrid) at the single storm scale were observed between V and R for the Shipanmao dam deposition wedge (depositional area behind a dam), and these impacted differently on the scale reconstruction results. However, the distance between the reconstructed dams and the known dams had an even stronger influence. The scale method developed in this study was shown to perform well and was able to reconstruct rainstorm events for adjacent regions with similar climatic and geomorphological conditions. Furthermore, the results of this study have improved our understanding of single rainstorm dynamics and soil erosion mechanisms on the Loess Plateau.

Selective organic carbon losses from soils by sheet erosion and main controls

AbstractAlthough the impact of sheet erosion on the selective transportation of mineral soil particles has been widely investigated, little is yet known about the specific mechanisms of organic carbon (OC) erosion, which constitutes an important link in the global carbon cycle. The present study was conducted to quantify the impact of sheet erosion on OC losses from soils. Erosion plots with the lengths of 1‐ and 5‐m were installed at different topographic positions along a hillslope in a mountainous South African region. A total of 32 rainfall events from a three years period (November 2010 up to February 2013), were studied and evaluated for runoff (R), particulate and dissolved organic carbon (POCL and DOCL). In comparison to the 0–0·05 m bulk soil, the sediments from the 1‐m plots were enriched in OC by a factor 2·6 and those from the 5‐m long plots by a factor of 2·2, respectively. These findings suggest a preferential erosion of OC. In addition, total organic carbon losses (TOCL) were incurred mainly in particulate form (~94%) and the increase in TOCL from 14·09 ± 0·68 g C m−1 yr−1 on 1‐m plots to 50·03 ± 2·89 g C m−1 yr−1 on 5‐m plots illustrated an increase in sheet erosion efficiency with increasing slope length. Both TOCL and sediment enrichment in OC correspondingly increased with a decrease in soil basal grass cover. The characteristics of rainstorms had no significant impact on the selectivity of OC erosion. The results accrued in this study investigating the links between sheet erosion and OC losses, are expected to be of future value in the generation of carbon specific erosion models, which can further help to inform and improve climate change mitigation measures. Copyright © 2016 John Wiley &amp; Sons, Ltd.

Better knowledge with more gauges? Investigation of the spatiotemporal characteristics of precipitation variations over the Greater Beijing Region

ABSTRACTUsing the hourly precipitation observations from 118 gauge stations and a weather radar in the Greater Beijing Region (GBR) during 2008–2012, we investigate the spatiotemporal characteristics of precipitation and discuss the appropriate observational approach for capturing variability of precipitation over this region. In general, the south central and northeastern GBR receives more intense precipitation than other parts. The diurnal cycle of precipitation amount (PA) peaks in the evening and decreases till noon, whereas precipitation intensity (PI) and precipitation frequency (PF) both have two peaks. The stronger peaks of PI and PF occur in the evening whereas the weaker ones appear in the early nighttime and in the afternoon. Remarkable spatial heterogeneity also exists in the diurnal patterns of PA, PI and PF over the GBR. Rainstorms extracted from radar data feature in short duration (11.4 h in average) and highly localized patterns (4.31–20.58/1.85–9.10 km in major/minor radius direction). The estimated diurnal cycles of PA, PI and PF are found to depend on the gauge density in a sensitivity analysis, where a gauge density ratio of 0.6 (corresponding to 30 gauges in total with a representative area of 239.5 km2 per gauge) is identified as adequate to capture the temporal characteristics of precipitation in the plain area of GBR. However, such a gauge density ratio (i.e. 0.6) is incapable for resolving the spatial characteristics of precipitation in GBR. As such, different instruments (e.g. gauge network, weather radar, etc.) and multiple data sources are suggested to be jointly utilized to better capture the characteristics of rainstorms in GBR.

Changing pattern of heavy rainstorms in the Indus basin of India under global warming scenarios

Estimation of extremely high rainfall (point or areal) is one of the major components of design storm derivation. The estimation of Probable Maximum Precipitation (PMP) involves selection of heavy rainstorms and its maximization for the moisture content during the rainstorm period. These heavy rainstorms are nothing but the widespread heavy rainfall exceeding a certain threshold value. The present study examines the characteristics of heavy rainstorms in the Indus basin selected from present climate and future scenarios simulated by the regional climate model. Such information on heavy rainfall forms the basis for the hydrologic design projects and also for the water management of a river basin. Emphasis is given to severe rainstorms of 1-day duration covering an area of at least 40,000 km 2 with spatial average rainfall of at least 5cm. This analysis also provides the information on the temporal changes in the storm factors such as shape, orientation, and movement, and shows that the model can well simulate the rainstorm pattern in terms of its intensity, orientation, and shape of the rainstorm, but overestimates the frequency of such heavy rainstorms. The future scenario indicates increase in rainfall intensity at the center of the rainstorm with decreasing areal spread. Decrease in the frequency of rainstorms is projected under the global warming conditions.

Spatially distributed simulation of water balance and sediment transport in an agricultural field

Runoff and sediment transport are distinctively three-dimensional (3D) processes and occur through overland, tillage layer and subsurface pathways. The objective was to quantify water balance and sediment concentrations in runoff waters and to assess sediment loads via surface runoff and drainflow in a clayey, subsurface drained field section using the FLUSH model. The model can simulate field scale two-dimensional overland flow and 3D unsaturated and saturated subsurface flow, including preferential flow in macropores. The erosive processes, comprised of hydraulic and raindrop splash erosion, occur in the overland domain while suspended sediment is conveyed from the field surface to subsurface drains via preferential transport in macropores in the subsurface domain. The study site, located in southern Finland, is a clayey, subsurface drained field section with an area of 12ha and an average slope of 2.8%. The growing seasons and the following autumns of two years with distinctly different rainstorm characteristics were modelled. The simulated sediment loads via tillage layer runoff and drainflow were 85 and 117kgha−1, respectively in 1988, and 63 and 189kgha−1 in 1984. Despite the high precipitation in October 1984 (143mm), erosion in the field area was low due to minimal surface runoff and consequently minimal hydraulic erosion. The suspended sediment at the site was generated by raindrop impacts and the eroded material was transported to the open ditch through tillage layer flow and subsurface drainflow. The model was able to reproduce the measured sediment concentrations in the main open ditch into which both tillage layer runoff and drainflow are discharged from the field. Spatially distributed erosion simulations facilitate the detection of net erosion and deposition locations in the field and could be used to design intensive measurement campaigns and guide erosion control practices in the future.

Hortonian runoff closure relations for geomorphologic response units: evaluation against field data

Abstract. This paper presents an evaluation of the closure relation for Hortonian runoff, proposed in Vannametee et al. (2012), that incorporates a scaling component to explicitly account for the process heterogeneity and scale effects in runoff generation for the real-world case studies. We applied the closure relation, which was embedded in an event-based lumped rainfall–runoff model, to a 15 km2 catchment in the French Alps. The catchment was disaggregated into a number of landform units, referred to as Geomorphologic Response Units (GRUs), to each of which the closure relation was applied. The scaling component in the closure relation was identified using the empirical relations between rainstorm characteristics, geometry, and local-scale measurable properties of the GRUs. Evaluation of the closure relation performance against the observed discharge shows that the hydrograph and discharge volume were quite satisfactorily simulated even without calibration. Performance of the closure relation can be mainly attributed to the use of scaling component, as it is shown that our closure relation outperforms a benchmark closure relation that lacks this scaling component. The discharge prediction is significantly improved when the closure relation is calibrated against the observed discharge, resulting in local-scale GRU-properties optimal for the predictions. Calibration was done by changing one local-scale observable, i.e. hydraulic conductivity (Ks), using a single pre-factor for the entire catchment. It is shown that the calibrated Ks values are somewhat comparable to the observed Ks values at a local scale in the study catchment. These results suggest that, in the absence of discharge observations, reasonable estimates of catchment-scale runoff responses can possibly be achieved with the observations at the sub-GRU (i.e. plot) scale. Our study provides a platform for the future development of low-dimensional, semi-distributed, physically based discharge models in ungauged catchments.