Rainfall Depth Research Articles

Spatial heterogeneity of controlling factors’ impact on urban pluvial flooding in Cincinnati, US

Urban pluvial flooding has become a common threat for urban areas. Intensified rainfall, increasing imperviousness, and insufficient drainage capacity contribute to the increase of pluvial flood risk. The strategy of risk mitigation relies on the understanding of these controlling factors of urban pluvial flooding. However, spatial heterogeneity of the impacts of controlling factors has received limited attention. This study analyzes how topography, rainfall, impervious surfaces affect urban pluvial flooding and how the effects vary in space. A case study in the city of Cincinnati, US based on four storm events in recent years is conducted. The impact of topography is measured by a depression-based empirical parameter, Topographic Control Index (TCI), which is generated based on depression ponding volume, contributing area, and upstream slope. Rainfall depth estimated from kriging interpolation method is used to measure how the rainfall affect the urban pluvial flooding. The impervious area ratio of the contributing area of each depression as well as that of observed flooded locations are calculated to analyze the influence of impervious area. The results showed that TCI value and rainfall intensity are spatially correlated with the presence of flooded locations, and flooded locations can be classified into two types: rainfall control or topography control. The imperviousness of land surface does not show a significant correlation with pluvial flood due to the relatively small spatial variation of impervious area in a well-developed city. The framework in this study could identify the spatial distribution of dominant controlling factors for pluvial flooding, which is critical for the effective planning of mitigation measures.

Rainfall–streamflow relationships for three chalk escarpment springs (Oxfordshire, United Kingdom): effective rainfall and groundwater recharge area computational issues

Abstract Flow responses to rainfall are investigated for three small chalk springs located within about 30 km of each other. A high degree of synchronicity is shown for the spring hydrographs, which exhibit a lag of about 50 days relative to a much larger local reference catchment. Rainfall–streamflow models with six or fewer parameters, calibrated using free-to-download software, account for about 75% of the variance in daily streamflow for the reference catchment, and between about 76 and 85% for the chalk springs. Several modelling issues are discussed related to computation of the daily effective rainfall that forms the input to a Unit Hydrograph part of the model. Descriptions are given of how and why, when the recharge area used for a spring is far too small, the modelling software generates physically unrealistic effective rainfall depths much greater than the rainfall, without affecting model-fit to streamflow or the calibrated values of model parameters (except one). Reasons are suggested why it can be pragmatically acceptable for computed effective rainfall to occasionally exceed the corresponding recorded rainfall by small amounts. Wider implications of the modelling results are outlined and some suggestions for further work are made.

Sensitivity analysis of using unreliable rain gauge stations for evaluating the accuracy of radar rainfall estimates

Providing reliable rainfall information through the integration of all possible data sources such as rain gauge and radar can make a valuable contribution to the development of the lahar flow warning system. However, the reliability of radar rainfall (R) data still needs to be evaluated based on ground rainfall (G) given the estimated value of radar rainfall depth is not so precise compared to ground rainfall. The selection of which ground rainfall data can be used as an evaluation reference is based on the assessment of the variance analysis. Through the Scheffe test, the unreliable rain gauge stations can be known. The use of unreliable rain gauge stations for evaluating the accuracy of radar rainfall estimates affecting the parameter values of radar rainfall and ground rainfall conformity. This paper discusses sensitivity analysis of using unreliable rain gauge stations for evaluating the accuracy of radar rainfall estimates. Based on the Scheffe test, several scenarios are set to assess the change of conformity parameter values. The conformity between radar rainfall and ground rainfall are evaluated by using Log (G/R), FSE, and RMSE index. A number of 10-minute rainfall intensity data during 2016-2018 from 21 automatic rain gauge and X-band MP radar stations in the Merapi volcano region are used in the analysis. The result show that the less unreliable rain gauge stations used to assess the radar rainfall accuracy, the better the conformity parameter values.

Modeling the kinetics of manure-borne fecal indicator removal in runoff.

Several manure-borne microorganism removal models have been developed to provide accurate estimations of the number of microorganisms removed from manure or manured soils undergoing rainfall. It has been commonly assumed that these models perform equally well when used to simulate microbe removal in runoff from manures of different consistency and levels of weathering. The objectives of this work were (a) to observe kinetics of the removal of Escherichia coli and enterococci with runoff for two different manure consistencies and three manure weathering durations, and (b) to compare performance of the log-linear, Vadas-Kleinman-Sharpley, and Bradford-Shijven models in simulation of the observed kinetics. Liquid and solid dairy manure were applied to grassed soil boxes that received simulated rainfall immediately after application and subsequently at 1 and 2 wk. Runoff samples were collected for 1 h at increasing time intervals during each event. Only the effective rainfall depth at the start of runoff was significantly affected by manure consistency (p=.033), whereas other parameters were not (p>.05). Substantial differences in microorganism removal kinetics during the initial, 1-, and 2-wk rainfall events were manifested by the significant (p<.05) effect of the degree of manure weathering in about 70% of cases. The log-linear model produced the largest fitting error especially during the initial rainfall event. The Vadas-Kleinman-Sharpley model and the Bradford-Schijven model were comparable in accuracy for all events. The latter model was slightly more accurate, and the former model had better expressed dependencies of parameter values on manure weathering. Ignoring manure weathering may lead to incorrect parameterization of manure removal models.

A simple method for sizing modular green–blue roof systems for design storm peak discharge reduction

Typical green roof systems are used to improve downstream water quality and reduce long-term total runoff. However, they perform poorly at peak discharge reduction during large design storm events. This performance can be significantly improved by the addition of storage a layer (blue roof) underneath a green roof system. This paper presents a simple design methodology for designing modular green–blue roof systems to reduce this peak discharge. In particular, the methodology can be used for the preliminary design of the blue roof module’s outflow control sizing. It is then shown how the resulting design can be incorporated into a standard hydrologic modeling system for a more detailed analysis. Results of an example design show that the addition of just 3.8 cm (1.5 in) of storage can result in a 38.6% reduction in peak discharge for a rainfall depth of 17.2 cm (6.78 in) compared to a green roof without underlying storage. Increasing the storage depth to 7.6 cm (3 in) for the same storm resulted in a 78.2% reduction of peak discharge.

Advanced hydrological streamflow simulation in a watershed using adjusted radar-rainfall estimates as meteorological input data

Among the input data of the watershed model for simulating changes of flowrate in the watershed, weather input data, especially input data related to rainfall, are the most important. Therefore, it is important to ensure the accuracy of rainfall input data to increase the accuracy of the watershed model results. Securing rainfall measurements with finer spatial and temporal resolutions is important in predicting flowrate variations at a sub-catchment, especially as they relate to global and local climate changes in weather conditions such as rainfall depth, rainfall intensity, etc. In this study, adjusted radar-rainfall estimates were suggested as alternative input data for watershed modeling. Through a statistical analysis of the representativeness of a ground rainfall measurement (10 km × 10 km grid), the necessity of radar-rainfall estimates (2 km × 2 km grid) was identified. By applying calibration factors to initial radar-rainfall estimates and comparing adjusted radar-rainfall estimates with ground rainfall measurements, it was proven that adjusted radar-rainfall estimates could be used as input data for watershed simulations (NSE > 0.92; n = 12). Adjusted radar-rainfall estimates and ground rainfall measurements were used as input data of the Soil and Water Assessment Tool model to predict flowrate variations at the outlets of a tributary and the entire watershed. As a result, the accuracies of the simulation results were improved for the outlets of a tributary and the entire watershed (NSE: 0.33 to 0.48 and 0.19 to 0.55, respectively). To obtain more reliable rainfall data, radar images easily accessible to users were applied, and the accuracy of the data was increased by applying simple equations to numerical data extracted from radar image processing. Additionally, the applicability of the adjusted radar-rainfall estimates was demonstrated by comparing the modeling results using the suggested rainfall data and existing ground-based rainfall data. The suggested methodologies are expected to contribute to more accurately predict the possibility of flood disasters in other regions and countries lacking infrastructure related to rainfall measurements and to establish appropriate countermeasures.

Climate change impacts on the water and groundwater resources of the Lake Tana Basin, Ethiopia

AbstractClimate change impacts on the water cycle can severely affect regions that rely on groundwater to meet their water demands in the mid- to long-term. In the Lake Tana basin, Ethiopia, discharge regimes are dominated by groundwater. We assess the impacts of climate change on the groundwater contribution to streamflow (GWQ) and other major water balance components in two tributary catchments of Lake Tana. Based on an ensemble of 35 bias-corrected regional climate models and a hydrologic catchment model, likely changes under two representative concentration pathways (RCP4.5 and 8.5) are assessed. No or only slight changes in rainfall depth are expected, but the number of rainy days is expected to decrease. Compared to the baseline average, GWQ is projected to decrease whereas surface runoff is projected to increase. Hence, rainfall trends alone are not revealing future water availability and may even be misleading, if regions rely heavily on groundwater.

Establishment of Design Hyetographs of 24-hour Duration Using a Bivariate Gumbel-Hougaard Copula

Yang, X.; Wang, J.; Weng, S.G.; Hou, M.; Zhang, X.Y., and Wang, T.S., 2020. Establishment of Design Hyetographs of 24-hour duration using a bivariate Gumbel-Hougaard copula. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 166–171. Coconut Creek (Florida), ISSN 0749-0208.Design hyetograph with a given return period and selected combinations of rainfall depth, peak intensity and duration, is widely used in engineering design. Recent hydrologic studies on multivariate stochastic analysis of extreme rainfall event have shown that these variables related to design hyetograph are partially correlated, and that copulas perform well for multivariate problems. Therefore, the main aim of the study is to develop a new method using Gumbel-Hougaard copula to construct design hyetograph. Firstly fixing the rainfall duration and rainfall return period, then the pairs total rainfall depth-the corresponding peak can be determined using a specified conditional risk probability, finally the dimensionless hyetograph is scaled to fit the specified design total rainfall depth and the corresponding peak. Shenzhen (China) was chosen for case study, and T-year (50-yr, 100-yr, 200-yr) design hyetographs of 24 h duration were discussed. The proposed method provides an effective rule to optimize the choices for the design hyetograph variables.

20-Years of hindsight into hydrological dynamics of a mountain forest catchment in the Central Spanish Pyrenees

Mediterranean mountain forests play a significant role in hydrological regulation. In this study, hydrological dynamics was examined at different temporal scales in a small mountain forest catchment in the Central Spanish Pyrenees (San Salvador), based on a 20-year dataset (1999–2019). Mean annual runoff coefficient is 0.21, and ranged from 0.02 to 0.58. The catchment has a bi-modal hydrological behavior with two hydrological periods: a dry-period between July and December, and a wet-period between January and June. During the study period, only 108 floods were recorded, suggesting a low responsiveness of the catchment, with a high variable response. Spearman correlation analysis and stepwise multivariate regression suggest that the hydrological response in the San Salvador catchment is mainly depending on water table, with antecedent moisture conditions and rainfall depth as secondary factors. Seasonal differences were also observed: during dry season, the response was mainly related to rainfall depth and rainfall intensity; in contrast in wet season, the response was mainly related to antecedent conditions (previous rainfall and base flow). Thus, the already challenging water resources management in the Mediterranean basin is magnified by the key function of forests as natural modulators of water cycle. Consequently, the study of natural forested catchments is needed and long-datasets have to be analysed to understand the role of natural Mediterranean forest in the hydrological dynamics and its evolution and adaptation in a context of Global Change.

Flash-Flood Potential Assessment by Integrating the Remote Sensing Data and GIS with Reference to Adam Area, Western Saudi Arabia

Heavy rainstorms are common occurrences in the Western mountainous region of Saudi Arabia that results in hazardous floods damaging the infrastructure and development plans. Severe rainstorms and heavy showers cause instant flash floods that result in major damage of properties and loss of human lives. Therefore, it becomes crucial during the development planning that floods are accurately analyzed. For the calculation and spatial mapping of flood features, an integrated remote sensing and GIS methodology has been formed. This new methodology makes use of various landscape, metrological, geological, and land use datasets in a GIS environment by employing the technique of Curve Number (CN) of flood modeling for unrestricted dry catchments. The prediction of rainfall depths for 50 and 100-years are 73.6 and 82.3 mm respectively. 4.3679 and 8.0605 million cubic meters are the flood volumes for 50- and 100-year return periods. Moreover, the flood’s statistical data like the depth and volume of runoff is added in GIS layers’ attribute tables so that all results are collected in the same environment. The application of advanced methodology aids in providing exact estimations and digital results. Moreover, it is economical and can be re-operated in different circumstances as well.

Water and thermal regime of extensive green roof test beds planted with sedum cuttings and sedum carpets

Implementation of green roofs could help to reduce rapid runoff and help cities to mitigate heat islands. The aim of the study is to assess the water and temperature regimes of four experimental green roof test beds having different growing media and plant coverage during the vegetation season 2018. Experiments were conducted in four test beds (1 × 1 m) established on a flat roof. Two types of growing media were used. The first (A) was a substrate composed of crushed spongolite, crushed expanded clay, and peat. The second (B) was a coarser substrate, composed of crushed expanded clay, crushed bricks, peat, and compost. Two test beds, hereafter designated ACu and BCu, were filled with substrates A and B respectively and planted with a mixture of Sedum spp. cuttings with approximately 10% coverage. The substrate thickness was 6 cm. Two other test beds, designated ACa and BCa, were filled to a depth of 4 cm with A and B growing media, respectively, and planted with a carpet of Sedum spp. with approximate coverage of 100%. The experiment was conducted over one growing season. Continuous monitoring of substrate temperature, water content, and outflow was conducted on each test bed. The lowest runoff coefficient was observed in test bed ACu, while the highest runoff occurred in test bed BCu, with twice the amount of outflow as ACu. The total runoff coefficient of ACa was more than one-third higher than that of ACu. The lowest maximum substrate temperature on the hottest day of the season was observed in bed ACa with a temperature of 40.6 °C, while the highest temperature was seen in bed BCu, 7.9 °C higher. The analysis of the rainfall-runoff relationship calculated for individual rainfall events demonstrated that runoff coefficients depended on initial water content, rainfall intensity, rainfall depth, substrate type, and vegetation cover. Beds planted with sedum carpets and having more extensive vegetation coverage were superior at moderating extremes of temperature.

Effective rainfall estimates for St. Augustinegrass lawns under varying irrigation programs

AbstractPrediction of effective rainfall, rainfall which contributes to the plant available water content, for lawns remains a challenge despite its critical role in accurately estimating a soil water balance and irrigation water requirement. The objective of this research was to validate simple runoff models for estimating effective rainfall on St. Augustinegrass [Stenotaphrum secundatum (Walter) Kuntze ‘Raleigh’] turf managed under varying irrigation strategies. A field experiment was conducted at Texas A&amp;M Urban Landscape Runoff Facility in College Station, TX, USA. Effective rainfall during the irrigation season was approximately 16% of measured rainfall but varied with rainfall depth and irrigation management. Methods which accounted for initial abstraction and subsequent rainfall independently were more accurate than simple coefficient models which only accounted for runoff as a percentage of daily rainfall depth. In general, St. Augustinegrass lawns can abstract 12.5 mm of water before rainfall becomes ineffective (runs off). These findings suggest accurate estimates of effective rainfall can be achieved using readily‐available methods such as the SCS Curve Number model with adjustments for irrigation management strategy. Implementing more accurate effective rainfall estimates may reduce irrigation applied without decreasing turf quality.

A geospatial approach for estimating hydrological connectivity of impervious surfaces

Recent studies have reported that connected impervious areas – those impervious surfaces that contribute directly to runoff in a storm network or stream – are a better indicator of hydrologic response, stream alteration, and water quality than total impervious area. However, most methods for quantifying connected impervious areas require major assumptions regarding the definition of ‘connection’, potentially over-simplifying the role of variable climates, slope gradients, soils conditions, and heterogeneous flow paths on impervious surface connectivity. This study presents a new conceptual model and method for estimating hydrologically connected impervious areas (HCIA) that explicitly considers the effect of landscape and storm variability. The model separates impervious surfaces into two categories: directly or physically connected (Aphys) and variably connected (Avar) (impervious that drains to pervious). Of these categories, we investigated the sensitivity of Avar connectivity to varying soil conditions, slope gradients, rainfall properties, and hillslope geometry using PySWMM (a python interface for SWMM5). Simulations spanned a large parameter space with varying soil, slope, rainfall properties and geometries (i.e., relationships between the impervious and downslope pervious areas). PySWMM simulations were used to train and test a regression tree that predicts infiltration and connectivity of runoff from Avar surfaces, which provides excellent fidelity with PySWMM outcomes. To enable use of these methods in practice, we developed an ArcGIS tool that (1) delineates subcatchments; (2) extracts the impervious surface categories Aphys and Avar; (3) applies the regression tree algorithm to predict the fraction of incident rainfall that produces runoff across Avar; and (4) summarizes the resulting HCIA by subcatchment. Analysis of the regression feature importance shows that, in general, Avar connectivity is highly sensitive to the soil type, rainfall depth, area fraction, and antecedent soil moisture conditions of the downslope pervious area. We find that temporally varying parameters (e.g., rainfall and antecedent soil moisture) control Avar connectivity in areas with low permeability soils, while spatial flow path variability (e.g., relative quantity of disconnecting pervious area) controls Avar connectivity in areas with highly permeable soils. The methods developed in this study can be used to identify impervious surface connectivity more accurately in urban watersheds, representing an important step forward for incorporating spatial heterogeneity in stormwater modeling and planning.

The effect of storm movement on infiltration, runoff and soil erosion in a semi‐arid catchment

AbstractRainfall characteristics are key factors influencing infiltration and runoff generation in catchment hydrology, particularly for arid and semiarid catchments. Although the effect of storm movement on rainfall‐runoff processes has been evaluated and emphasized since the 1960s, the effect on the infiltration process has barely been considered. In this study, a physically based distributed hydrological model (InHM) was applied to a typical semi‐arid catchment (Shejiagou, 4.26 km2) located in the Loess Plateau, China, to investigate the effect of storm movement on infiltration, runoff and soil erosion at the catchment scale. Simulations of 84 scenarios of storm movement were conducted, including storms moving across the catchment in both the upstream and downstream directions along the main channel, while in each direction considering four storm moving speeds, three rainfall depths and two storm ranges. The simulation results showed that, on both the hillslopes facing downstream (facing south) and in the main channel, the duration of the overland flow process under the upstream‐moving storms was longer than that under the downstream‐moving storms. Thus, the duration and volume of infiltration under upstream‐moving storms were larger in these areas. For the Shejiagou catchment, as there are more hillslopes facing downstream, more infiltration occurred under the upstream‐moving storms than the downstream‐moving storms. Therefore, downstream‐moving storms generated up to 69% larger total runoff and up to 351% more soil loss in the catchment than upstream‐moving storms. The difference in infiltration between the storms moving upstream and downstream decreased as the storm moving speed increased. The relative difference in total runoff and sediment yield between the storms moving upstream and downstream decreased with increasing rainfall depth and storm speed. The results of this study revealed that the infiltration differences under moving storms largely influenced the total runoff and sediment yield at the catchment scale, which is of importance in runoff prediction and flood management. The infiltration differences may be a potential factor leading to different groundwater, vegetation cover and ecology conditions for the different sides of the hillslopes.

Effects of watershed char and climate variables on annual runoff in different climatic zones in China

The complex interactions between climate and watershed characteristics lead to diverse annual runoff responses. Understanding the mechanism by which different climatic and watershed factors affect annual runoff is helpful in understanding the resulting changes in the hydrological process. In this study, the characteristics of 73 watersheds were analyzed. The basins were divided into three categories according to their climatic regions: temperate continental climate (n = 7); temperate monsoon climate(n = 36); and subtropical monsoon climate(n = 30). Correlation analysis, linear regression, and path analysis were used to quantify the effects of selected watershed characteristics and meteorological conditions on long-term runoff. Results showed that the average annual runoff coefficient was strongly correlated with basin area, showing a scale effect. The average annual runoff depth was strongly positively correlated with precipitation for the all watersheds. As the drought index (DI, the ratio of annual evaporation capacity to annual precipitation) increased, the annual runoff depth decreased logarithmically. The average annual rainfall and runoff depth of watersheds in the subtropical monsoon climate zone were significantly higher than those in other climatic zones, and there was no significant difference in potential evaporation between the temperate monsoon climate and subtropical monsoon climate zones. With increases in both the drought index (Ep/P) and moisture index (E/P), the vegetation distribution in the basin showed an increasing trend in farmland area and decreasing trend in forest area. Path analysis showed that rainfall had a positive effect on annual average runoff depth (ranging from 31 to 62%) while actual evapotranspiration had a negative impact (ranging from 17 to 47%). For all basins, a negative effect (13–25%) of basin area on runoff depth was observed, while forestland area had a positive effect (7–39%) on runoff depth. This study further quantified the effects of climatic and geographical factors on the long-term water balance in different climatic regions.

DETERMINANT PLUVIOMETRIC CHARACTERISTICS OF SEDIMENT TRANSPORT IN A CATCHMENT WITH THINNED VEGETATION IN THE TROPICAL SEMIARID

ABSTRACT Knowing determinant factors of erosive process is essential to adopt soil conservationist and loss-mitigation measures. Therefore, the objective of this work was to assess the correlation between rainfall characteristics and sediment transport in the Semiarid region of Brazil. The study was conducted at the Iguatu Experimental Basin in the state of Ceará, Brazil, in a watershed with area of 1.15 ha. The vegetation was thinned by removal of plants with diameters below 10 cm, and the area remained with an arboreous cover of 60%. The following variables were evaluated from 2012 to 2016: rainfall depth (mm), rainfall duration (hours), maximum rainfall intensity in 5, 10, 15, 20, 30, 45, and 60 minutes (mm h-1), mean rainfall intensity (mm h-1), rainfall depth in the previous 5 days (mm), runoff depth (mm), and transported sediment (kg ha-1). The records showed 158 rainfall events, 27 with surface runoff and 24 with sediment transport. The correlations were investigated by multivariate analysis of principal components (PC). The model explained 84% of total variance with four PC-PC1, PC2, PC3, and PC4 were formed, respectively, for disaggregating power of rainfall on soil particles, represented by the rainfall intensities; soil water content; runoff depth and sediment transport; and rainfall duration and interval between rainfalls. The highest factorial weight was found for the maximum intensity in 20 minutes, indicating the need for further hydrological studies focused on this variable at basin scale in areas of the Semiarid region of Brazil subjected to thinning of the vegetation.

Full-Year Evaluation of Nonmeteorological Echo Removal with Dual-Polarization Fuzzy Logic for Two C-Band Radars in a Temperate Climate

AbstractThe Royal Netherlands Meteorological Institute (KNMI) operates two dual-polarization C-band weather radars in simultaneous transmission and reception (STAR; i.e., horizontally and vertically polarized pulses are transmitted simultaneously) mode, providing 2D radar rainfall products. Despite the application of Doppler and speckle filtering, remaining nonmeteorological echoes (especially sea clutter) mainly due to anomalous propagation still pose a problem. This calls for additional filtering algorithms, which can be realized by means of polarimetry. Here we explore the effectiveness of the open-source wradlib fuzzy echo classification and clutter identification based on polarimetric moments. Based on our study, this has recently been extended with the depolarization ratio and clutter phase alignment as new decision variables. Optimal values for weights of the different membership functions and threshold are determined employing a 4-h calibration dataset from one radar. The method is applied to a full year of volumetric data from the two radars in the Dutch temperate climate. The verification focuses on the presence of remaining nonmeteorological echoes by mapping the number of exceedances of radar reflectivity factors for given thresholds. Moreover, accumulated rainfall maps are obtained to detect unrealistically large rainfall depths. The results are compared to those for which no further filtering has been applied. Verification against rain gauge data reveals that only a little precipitation is removed. Because the fuzzy logic algorithm removes many nonmeteorological echoes, the practice to composite data from both radars in logarithmic space to hide these echoes is abandoned and replaced by linearly averaging reflectivities.

A Nonparametric Stochastic Approach for Disaggregation of Daily to Hourly Rainfall Using 3-Day Rainfall Patterns

As infrastructure and populations are highly condensed in megacities, urban flood management has become a significant issue because of the potentially severe loss of lives and properties. In the megacities, rainfall from the catchment must be discharged throughout the stormwater pipe networks of which the travel time is less than one hour because of the high impervious rate. For a more accurate calculation of runoff from the urban catchment, hourly or even sub-hourly (minute) rainfall data must be applied. However, the available data often fail to meet the hydrologic system requirements. Many studies have been conducted to disaggregate time-series data while preserving distributional statistics from observed data. The K-nearest neighbor resampling (KNNR) method is a useful application of the nonparametric disaggregation technique. However, it is not easy to apply in the disaggregation of daily rainfall data into hourly while preserving statistical properties and boundary continuity. Therefore, in this study, three-day rainfall patterns were proposed to improve reproducible ability of statistics. Disaggregated rainfall was resampled only from a group having the same three-day rainfall patterns. To show the applicability of the proposed disaggregation method, probability distribution and L-moment statistics were compared. The proposed KNNR method with three-day rainfall patterns reproduced better the characteristics of rainfall event such as event duration, inter-event time, and toral amount of rainfall event. To calculate runoff from urban catchment, rainfall event is more important than hourly rainfall depth itself. Therefore, the proposed stochastic disaggregation method is useful to hydrologic analysis, particularly in rainfall disaggregation.

Trade-off between soil moisture and species diversity in semi-arid steppes in the Loess Plateau of China

Effectively balancing soil moisture and biodiversity restoration remains a contentious issue for managers and researchers in the Loess Plateau region of China, even after many years of restoration efforts. We conducted a regional study on the trade-off between soil moisture and species diversity using spatial grid sampling in a semi-arid steppe (200-300 mm annual precipitation) in the northwest Loess Plateau. Results reveal that only soil moisture between 20 and 60 cm depth was significantly correlated with diversity indexes. Root-mean-square deviation (RSMD, the index of the soil water-biodiversity relationship) increased by monotonous linear trends with soil moisture in 20-60 cm depth. The linear relationship for Shannon Wiener diversity index (SD) was stronger than for species richness index (SR). When soil moisture in 20-60 cm depth was lower than 6–8%, RSMD often was less than zero, representing the trade-off relationship. However, synergism was more common as the soil moisture increased beyond 6–8%. The overall trends and the soil moisture threshold (6–8%) did not differ significantly between sites with different vegetation cover and aspect, though there were differences in the relative ratio of trade-off and synergism samples. Comparing results from sampling at different scales in the Loess Plateau suggests 6–8% soil moisture in 200-300 mm precipitation gradient, consistent with 370 mm rainfall depth in 250-550 mm precipitation gradient, might be a scale-independent threshold driving the soil moisture-biodiversity relationship from trade-off to synergism in the region.

How does increasing impervious surfaces affect urban flooding in response to climate variability?

Total impervious area (TIA) is one of the most common measures for predicting runoff yield in hydrologic studies and regulating urbanization in land use policy. Directly connected impervious area (DCIA), a subset of TIA, represents the hydraulic connection between development and underground sewer systems. Which indicator to use in runoff prediction has been subject to debate. The effectiveness of TIA and DCIA in the face of climate variability also remains unclear. The present study empirically assessed the impacts of TIA and DCIA on urban runoff in three metropolitan statistical areas (MSAs) in the U.S. state of Texas. The total monthly runoff depths of 92 watersheds and peak flows of 43 watersheds were computed using streamflow monitored by the U.S. Geological Survey from 2010 to 2017. A series of ordinal logit regression models were developed to determine which imperviousness indicator better predicted probable runoff yield. Additionally, an average marginal effect analysis was performed to investigate how TIA and DCIA responded to changing precipitation depths. The results demonstrate that DCIA outperformed TIA in runoff depth prediction, whereas TIA predicted peak flow better than DCIA. However, for far-above-average runoff, the contribution of DCIA to runoff depth was far greater than that of TIA, but no difference was found for peak flow. The effectiveness of TIA and DCIA also varied by total and 24-hour peak depths of monthly precipitation. After reaching their maximum capacity, both TIA and DCIA became less effective in predicting runoff and did not correlate with rainfall depth in extremely wet months. Meanwhile, the control of TIA and DCIA for runoff volume reduction was most effective for monthly rainfall of a 5% to 10% probability of exceedance in all MSAs, whereas that of peak flow reduction was most effective if the 24-hour peak storm in a month had a 2% to 5% probability of exceedance. The findings of this study demonstrate the hydrologic significance of regulating DCIA over TIA for high-risk runoff under certain rainfall depths and return periods. The study expands the current knowledge of urban hydrology for effective stormwater management and mitigation of future flooding risk.