The hydrological behaviour of urban streets: long‐term observations and modelling of runoff losses and rainfall–runoff transformation

Runoff on impervious surfaces (roads, roofs, etc.) raises a number of environmental and road safety‐related problems. The primary objective of this research effort is to improve our knowledge of the hydrological behaviour of impervious urban surfaces in order to better assess runoff on these surfaces and its subsequent consequences. This article will focus on two street stretches studied over a 38‐month period. Measurements of rainfall and runoff discharge on these stretches have made it possible to estimate runoff losses as well as to constitute a database for modelling purposes. On the basis of these data, two models have been used, one simple the other more detailed and physically based. For both models, runoff discharges at a 3‐min time step are well reproduced, although runoff coefficients and runoff losses are still poorly estimated. Detailed analyses of experimental data and model output, however, indicate that runoff losses could be quite high on such ‘impervious surfaces’ (between 30 and 40% of total rainfall, depending on the street stretch) and that these losses are mainly because of evaporation and infiltration inside the road structure. Copyright © 2011 John Wiley & Sons, Ltd.     

Predictors of urban variable source area: a cross‐sectional analysis of urbanized catchments in the United States

Many studies have empirically confirmed the relationship between urbanization and changes to the hydrologic cycle and degraded aquatic habitats. While much of the literature focuses on extent and configuration of impervious area as a causal determinant of degradation, in this article, I do not attribute causes of decreased watershed storage on impervious area a priori. Rather, adapting the concept of variable source area (VSA) and its relationship to incremental storage to the particular conditions of urbanized catchments, I develop a statistically robust linear regression‐based methodology to detect evidence of VSA‐dominant response. Using the physical and meteorological characteristics of the catchments as explanatory variables, I then use logistic regression to statistically analyze significant predictors of the VSA classification. I find that the strongest predictor of VSA‐type response is the percent of undeveloped area in the catchment. Characteristics of developed areas, including total impervious area, percent‐developed open space and the type of drainage infrastructure, do not add to the explanatory power of undeveloped land in predicting VSA‐type response. Within only developed areas, I find that total impervious area and percent‐developed open space both decrease the odds of a catchment exhibiting evidence of VSA‐type response and the effect of developed open space is more similar to that of total impervious area than undeveloped land in predicting VSA response. Different types of stormwater management infrastructure, including combined sewer systems and infiltration, retention and detention infrastructure are not found to have strong statistically significant effects on probability of VSA‐type response. VSA‐type response is also found to be stronger during the growing season than the dormant season. These findings are consistent across a national cross‐section of urbanized watersheds, a higher resolution dataset of Baltimore Metropolitan Area watersheds and a subsample of watersheds confirmed not to be served by (combined sewer systems). Copyright © 2016 John Wiley & Sons, Ltd.     

Effects of the catchment runoff coefficient on the performance of TOPMODEL in rainfall–runoff modelling

Effects of the catchment runoff coefficient on the performance of TOPMODEL in simulating catchment rainfall–runoff relationships are investigated in this paper, with an aim to improve TOPMODEL's simulation efficiency in catchments with a low runoff coefficient. Application of TOPMODEL in the semi‐arid Yihe catchment, with an area of 2623 km² in the Yellow River basin of China, produced a Nash–Sutcliffe model efficiency of about 80%. To investigate how the catchment runoff coefficient affects the performance of TOPMODEL, the whole observed discharge series of the Yihe catchment is multiplied with a larger‐than‐unity scale factor to obtain an amplified discharge series. Then TOPMODEL is used to simulate the amplified discharge series given the original rainfall and evaporation data. For a set of different scale factors, TOPMODEL efficiency is plotted against the corresponding catchment runoff coefficient and it is found that the efficiency of TOPMODEL increases with the increasing catchment runoff coefficient before reaching a peak (e.g. about 90%); after the peak, however, the efficiency of TOPMODEL decreases with the increasing catchment runoff coefficient. Based on this finding, an approach called the discharge amplification method is proposed to enhance the simulation efficiency of TOPMODEL in rainfall–runoff modelling in catchments with a low runoff coefficient. Copyright © 2004 John Wiley & Sons, Ltd.     

Distribution of surface imperviousness in small urban catchments predicts runoff peak flows and stream flashiness

Urban growth is a global phenomenon, and the associated impacts on hydrology from land development are expected to increase, especially in peri‐urban catchments. It is well understood that greater peak flows and higher stream flashiness are associated with increased surface imperviousness and storm location. However, the effect of the distribution of impervious areas on runoff peak flow response and stream flashiness of peri‐urban catchments has not been well studied. In this study, a new geometric index, Relative Nearness of Imperviousness to the Catchment Outlet (RNICO), is defined to correlate imperviousness distribution of peri‐urban catchments with runoff peak flows and stream flashiness. Study sites include 21 suburban catchments in New York representing a range of drainage area from 5 to 189 km² and average imperviousness from 10% to 48%. On the basis of RNICO, all development patterns are divided into 3 classes: upstream, centralized, and downstream. Results showed an obvious increase in runoff peak flows and decrease in time to peak when moving from upstream to centralized and downstream urbanization classes. This indicates that RNICO is an effective tool for classifying urban development patterns and for macroscale understanding of the hydrologic behavior of small peri‐urban catchments, despite the complexity of urban drainage systems. We also found that the impact of impervious distribution on runoff peak flows and stream flashiness decreases with catchment scale. For small catchments (A < 40 km²), RNICO was strongly correlated with the average (R² = .95) and maximum (R² = .91) gaged peak flows due to the relatively efficient subsurface routing through stormwater and sewer networks. Furthermore, the Richards–Baker stream flashiness index in small catchments was positively correlated with fractional impervious area (R² = .84) and RNICO (R² = .87). For large catchments (A > 40 km²), the impact of impervious surface distribution on peak flows and stream flashiness was negligible due to the complex drainage network and great variability in travel times. This study emphasizes the need for greater monitoring of discharge in small peri‐urban catchments to support flood prediction at the local scale.     

Automated rainfall simulator for variable rainfall on urban green areas

Rainfall simulators can enhance our understanding of the hydrologic processes affecting the total runoff to urban drainage systems. This knowledge can be used to improve urban drainage designs. In this study, a rainfall simulator is developed to simulate rainfall on urban green surfaces. The rainfall simulator is controlled by a microcomputer programmed to replicate the temporal variations in rainfall intensity of both historical and synthetic rainfall events with constant rainfall intensity on an area of 1 m². The performance of the rainfall simulator is tested under laboratory conditions with regard to spatial uniformity of the rainfall, the kinetic energy of the raindrops, and the ability to replicate historical and synthetic rainfall events with temporally varying intensity. The rainfall simulator is applied in the field to evaluate its functionality under field conditions and the influence of wind on simulated rainfall. Finally, a field study is carried out on the relationship between runoff, soil volumetric water content, and surface slope. Performance and field tests show that the simulated rainfall has a uniform spatial distribution, whereas the kinetic energy of the raindrops is slightly higher than that of other comparable rainfall simulators. The rainfall simulator performs best in low wind speed conditions. The simulator performs well in replicating historical and synthetic rainfall events by matching both intensity variations and accumulated rainfall depth. The field study shows good correlation between rainfall, runoff, infiltration, soil water content, and surface slope.     

Temporal patterns and controls on runoff magnitude and solution chemistry of urban catchments in the semiarid southwestern United States

Urban expansion and the scarcity of water supplies in arid and semiarid regions have increased the importance of urban runoff to localized water resources. However, urban catchment responses to precipitation are poorly understood in semiarid regions where intense rainfall often results in large runoff events during the short summer monsoon season. To evaluate how urban runoff quantity and quality respond to rainfall magnitude and timing, we collected stream stage data and runoff samples throughout the 2007 and 2008 summer monsoons from four ephemeral drainages in Tucson, Arizona. Antecedent rainfall explained 20% to 30% of discharge (mm) and runoff ratio in the least impervious (22%) catchment but was not statistically related to hydrologic responses at more impervious sites. Regression models indicated that rainfall depth, imperviousness and their combined effect control discharge and runoff ratios (p < 0.01, r² = 0.91 and 0.75, respectively). In contrast, runoff quality did not vary with imperviousness or catchment size. Rainfall depth and duration, time since antecedent rainfall and event and cumulative discharge controlled runoff hydrochemistry and resulted in five specific solute response patterns: (i) strong event and seasonal solute mobilization (solute flush), (ii) event chemostasis and strong seasonal flush, (iii) event chemostasis and weak seasonal flush, (iv) event and seasonal chemostasis and (v) late seasonal flush. Our results indicate that hydrologic responses of semiarid catchments are controlled by rainfall partitioning at the event scale, whereas wetting magnitude, frequency and timing alter solute stores readily available for transport and control temporal runoff quality. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling the hydrological response of mediterranean catchments,Prades, Catalonia. The use of distributed models as aids to hypothesis formulation

This paper attempts to extend the physical arguments underlying the distributed TOPMODEL concepts in an application to the strongly seasonal contributing area responses in two adjacent small mediterranean catchments in the Prades region of Catalonia, Spain. A perceptual model of hydrological response in these catchments is used to suggest possible modifications of the model in a hypothesis testing framework, including an attempt to modify the topographic index approach to reflect the expansion of the effective area of subsurface flow during the wetting-up sequence. It is found that slight improvements in modelling efficiency are possible but that different model parameter distributions are appropriate for different parts of the record. The model was much more successful for the catchment producing the higher runoff volumes. © 1997 John Wiley & Sons, Ltd.     

Error analysis for the evaluation of model performance: rainfall–runoff event time series data

This paper provides a procedure for evaluating model performance where model predictions and observations are given as time series data. The procedure focuses on the analysis of error time series by graphing them, summarizing them, and predicting their variability through available information (recalibration). We analysed two rainfall–runoff events from the R‐5 data set, and evaluated 12 distinct model simulation scenarios for these events, of which 10 were conducted with the quasi‐physically‐based rainfall–runoff model (QPBRRM) and two with the integrated hydrology model (InHM). The QPBRRM simulation scenarios differ in their representation of saturated hydraulic conductivity. Two InHM simulation scenarios differ with respect to the inclusion of the roads at R‐5. The two models, QPBRRM and InHM, differ strongly in the complexity and number of processes included. For all model simulations we found that errors could be predicted fairly well to very well, based on model output, or based on smooth functions of lagged rainfall data. The errors remaining after recalibration are much more alike in terms of variability than those without recalibration. In this paper, recalibration is not meant to fix models, but merely as a diagnostic tool that exhibits the magnitude and direction of model errors and indicates whether these model errors are related to model inputs such as rainfall. Copyright © 2004 John Wiley & Sons, Ltd.     

Comparison of genetic algorithms and shuffled complex evolution approach for calibrating distributed rainfall–runoff model

Three methods, Shuffled Complex Evolution (SCE), Simple Genetic Algorithm (SGA) and Micro‐Genetic Algorithm (µGA), are applied in parameter calibration of a grid‐based distributed rainfall–runoff model (GBDM) and compared by their performances. Ten and four historical storm events in the Yan‐Shui Creek catchment, Taiwan, provide the database for model calibration and verification, respectively. The study reveals that the SCE, SGA and µGA have close calibration results, and none of them are superior with respect to all the performance measures, i.e. the errors of time to peak, peak discharge and the total runoff volume, etc. The performances of the GBDM for the verification events are slightly worse than those in the calibration events, but still quite satisfactory. Among the three methods, the SCE seems to be more robust than the other two approaches because of the smallest influence of different initial random number seeds on calibrated model parameters, and has the best performance of verification with a relatively small number of calibration events. Copyright © 2009 John Wiley & Sons, Ltd.     

The role of hydrograph indices in parameter estimation of rainfall–runoff models

A reliable prediction of hydrologic models, among other things, requires a set of plausible parameters that correspond with physiographic properties of the basin. This study proposes a parameter estimation approach, which is based on extracting, through hydrograph diagnoses, information in the form of indices that carry intrinsic properties of a basin. This concept is demonstrated by introducing two indices that describe the shape of a streamflow hydrograph in an integrated manner. Nineteen mid‐size (223–4790 km²) perennial headwater basins with a long record of streamflow data were selected to evaluate the ability of these indices to capture basin response characteristics. An examination of the utility of the proposed indices in parameter estimation is conducted for a five‐parameter hydrologic model using data from the Leaf River, located in Fort Collins, Mississippi. It is shown that constraining the parameter estimation by selecting only those parameters that result in model output which maintains the indices as found in the historical data can improve the reliability of model predictions. These improvements were manifested in (a) improvement of the prediction of low and high flow, (b) improvement of the overall total biases, and (c) maintenance of the hydrograph's shape for both long‐term and short‐term predictions. Copyright © 2005 John Wiley & Sons, Ltd.     

Experimental study of water fluxes in a residential area: 2. Road infiltration,runoff and evaporation

Lack of accurate data has led some hydrologists and city planners to assume that urban infiltration is zero and runoff is 100% of the rainfall. These assumptions lead to an over estimation of road runoff volume and an underestimation of direct recharge to groundwater, which is already rising under some UK cities. This study investigates infiltration and runoff processes and quantifies the percentage of rainfall that contributes to storm drainage, and that which infiltrates through different types of road surface. Access tubes were installed for measuring soil water content using a neutron probe in three car parks, a road and a grass site at the Centre for Ecology and Hydrology, Crowmarsh Gifford, Wallingford. Storm drainage was recorded at the exit of the Thamesmead Estate in Crowmarsh Gifford, just before the drain joins the River Thames at Wallingford. Rainfall and water table depth were also recorded. Weekly measurements of soil moisture content indicated that the top 40 cm layer is not influenced by water‐table fluctuations and, therefore, positive changes in soil moisture could be attributed to infiltration of rainfall through the surface. Depending on the nature of the surface, subsurface layers, level of traffic, etc., between 6 and 9% of rainfall was found to infiltrate through the road surfaces studied. The storm drainage generated by road runoff revealed a flow pattern similar to that of the receiving watercourse (River Thames) and increased with the increase of infiltration and soil water content below the road surface. The ratio of runoff to rainfall was 0·7, 0·9 and 0·5 for annual, winter (October–March) and summer (April–September) respectively. As the results of the infiltration indicated that 6 to 9% of annual rainfall infiltrates through the road surface, this means that evaporation represents, 21–24% of annual rainfall, with more evaporation taking place during summer than winter. Copyright © 2003 John Wiley & Sons, Ltd.     

A statistical methodology for assessing the long‐term effects of antecedent drought conditions on stream runoff: applications to the Piedmont Province,southeastern United States

A method was developed to investigate the long‐term (months‐to‐years) effects (both magnitude and duration) of antecedent rainfall upon subsequent runoff coefficients (RCs) or runoff/rainfall ratios. The method was applied to a four‐state region (Georgia, South Carolina, North Carolina, and Virginia) within the southeastern Piedmont Province of the United States and incorporated a 59‐year data set of 19 United States Geological Survey stream gages and 57 National Climatic Data Center rain gages. The method was designed to facilitate statistical comparisons [Mann–Whitney rank sum tests] between various groups of normalized runoff coefficients (NRCs) representing 6–36 month periods which differed in terms of antecedent rainfall conditions. The results of this study show that under all subsequent rainfall conditions, with the exception of excess rainfall, a 1‐year period of antecedent drought lowered NRCs for at least 1 year following the drought. The principal finding of this study is that a year‐long drought period within the southeastern Piedmont Province lowers NRCs by ～25% during the following year when rainfall returns to normal. In most cases, RCs are significantly lower during the second year following a drought than they would be when anteceded by normal rainfall; however, the effects of drought wane during this period. This is a statistical and regional method that can be modified to other study areas; however, it cannot be used to predict storm‐event rainfall–runoff relationships for any specific basin. Copyright © 2010 John Wiley & Sons, Ltd.     

Semi‐distributed flood runoff model at the subcontinental scale for southwestern Iran

Rainfall–runoff modelling, as a surface hydrological process, on large‐scale data‐poor basins is currently a major topic of investigation that requires the model parameters be identified by using basin physical characteristics rather than calibration. This paper describes the application of the TOPMODEL framework accompanied by a kinematic wave model to the Karun River sub‐basins in southwestern Iran with just one conceptual parameter for calibration. ISLSCP1, HYDRO1K and Reynolds data sets are presented in a geographical information system and used as data sources for meteorological information, hydrological features and soil characteristics of the study area respectively. The results show that although the model developed can adequately predict flood runoff in the catchment with only one calibrated parameter, it is suggested that the effect of surface reservoirs be considered in the proposed model. Copyright © 2007 John Wiley & Sons, Ltd.     

Modelling the rainfall–runoff process of the Mara River basin using the Soil and Water Assessment Tool

The delicate balance between human utilization and sustaining its pristine biodiversity in the Mara River basin (MRB) is being threatened because of the expansion of agriculture, deforestation, human settlement, erosion and sedimentation and extreme flow events. This study assessed the applicability of the Soil and Water Assessment Tool (SWAT) model for long‐term rainfall–runoff simulation in MRB. The possibilities of combining/extending gage rainfall data with satellite rainfall estimates were investigated. Monthly satellite rainfall estimates not only overestimated but also lacked the variability of observed rainfall to substitute gage rainfall in model simulation. Uncertainties related to the quality and availability of input data were addressed. Sensitivity and uncertainty analysis was reported for alternative model components and hydrologic parameters used in SWAT. Mean sensitivity indices of SWAT parameters in MRB varied with and without observed discharge data. The manual assessment of individual parameters indicated heterogeneous response among sub‐basins of MRB. SWAT was calibrated and validated with 10 years of discharge data at Bomet (Nyangores River), Mulot (Amala River) and Mara Mines (Mara River) stations. Model performance varied from satisfactory at Mara Mines to fair at Bomet and weak at Mulot. The (Nash–Sutcliff efficiency, coefficient of determination) results of calibration and validation at Mara Mines were (0.68, 0.69) and (0.43, 0.44), respectively. Two years of moving time window and flow frequency analysis showed that SWAT performance in MRB heavily relied on quality and abundance of discharge data. Given the 5.5% area contribution of Amala sub‐basin as well as uncertainty and scarcity of input data, SWAT has the potential to simulate the rainfall runoff process in the MRB. Copyright © 2012 John Wiley & Sons, Ltd.     

A simple rainfall–runoff model based on hydrological units applied to the Teba catchment (south‐east Spain)

A hydrological model (YWB, yearly water balance) has been developed to model the daily rainfall–runoff relationship of the 202 km² Teba river catchment, located in semi‐arid south‐eastern Spain. The period of available data (1976–1993) includes some very rainy years with intensive storms (responsible for flooding parts of the town of Malaga) and also some very dry years. The YWB model is in essence a simple tank model in which the catchment is subdivided into a limited number of meaningful hydrological units. Instead of generating per unit surface runoff resulting from infiltration excess, runoff has been made the result of storage excess. Actual evapotranspiration is obtained by means of curves, included in the software, representing the relationship between the ratio of actual to potential evapotranspiration as a function of soil moisture content for three soil texture classes. The total runoff generated is split between base flow and surface runoff according to a given baseflow index. The two components are routed separately and subsequently joined. A large number of sequential years can be processed, and the results of each year are summarized by a water balance table and a daily based rainfall runoff time series. An attempt has been made to restrict the amount of input data to the minimum. Interactive manual calibration is advocated in order to allow better incorporation of field evidence and the experience of the model user. Field observations allowed for an approximate calibration at the hydrological unit level. Copyright © 2001 John Wiley & Sons, Ltd.     

Effect of rainfall uncertainty on the performance of physically based rainfall–runoff models

This paper analyses the effect of rain data uncertainty on the performance of two hydrological models with different spatial structures: a semidistributed and a fully distributed model. The study is performed on a small catchment of 19.6 km² located in the north‐west of Spain, where the arrival of low pressure fronts from the Atlantic Ocean causes highly variable rainfall events. The rainfall fields in this catchment during a series of storm events are estimated using rainfall point measurements. The uncertainty of the estimated fields is quantified using a conditional simulation technique. Discharge and rain data, including the uncertainty of the estimated rainfall fields, are then used to calibrate and validate both hydrological models following the generalized likelihood uncertainty estimation (GLUE) methodology. In the storm events analysed, the two models show similar performance. In all cases, results show that the calibrated distribution of the input parameters narrows when the rain uncertainty is included in the analysis. Otherwise, when rain uncertainty is not considered, the calibration of the input parameters must account for all uncertainty in the rainfall–runoff transformation process. Also, in both models, the uncertainty of the predicted discharges increase in similar magnitude when the uncertainty of rainfall input increase.     

Comparison of event‐specific rainfall–runoff responses and their controls in contrasting geographic areas

Numerous studies have examined the event‐specific hydrologic response of hillslopes and catchments to rainfall. Knowledge gaps, however, remain regarding the relative influence of different meteorological factors on hydrologic response, the predictability of hydrologic response from site characteristics, or even the best metrics to use to effectively capture the temporal variability of hydrologic response. This study aimed to address those knowledge gaps by focusing on 21 sites with contrasting climate, topography, geology, soil properties, and land cover. High‐frequency rainfall and discharge records were analysed, resulting in the delineation of over 1,600 rainfall–runoff events, which were described using a suite of hydrologic response metrics and meteorological factors. Univariate and multivariate statistical techniques were then applied to synthesize the information conveyed by the computed metrics and factors, notably measures of central tendency and variability, variation partitioning, partial correlations, and principal component analysis. Results showed that some response magnitude metrics generally reported in the literature (e.g., runoff ratio and area‐normalized peak discharge) did not vary significantly among sites. The temporal variability in site‐specific hydrologic response was often attributable to the joint influence of storage‐driven (e.g., total event rainfall and antecedent precipitation) and intensity‐driven (e.g., rainfall intensity and antecedent potential evapotranspiration) meteorological factors. Mean annual temperature and potential evapotranspiration at a given site appeared to be good predictors of hydrologic response timing (e.g., response lag and lag to peak). Response timing metrics, particularly those associated with response initiation, were also identified as the metrics most critical for capturing intrasite response variability. This study therefore contributes to the growing knowledge on event‐specific hydrologic response by highlighting the importance of response timing metrics and intensity‐driven meteorological factors, which are infrequently discussed in the literature. As few correlations were found between physiographic variables and response metrics, more data‐driven studies are recommended to further our understanding of landscape–hydrology interactions.     

Parameter uncertainty of the AWBM model when applied to an ungauged catchment

In this study, a quantitative assessment of uncertainty was made in connection with the calibration of Australian Water Balance Model (AWBM) for both gauged and ungauged catchment cases. For the gauged catchment, five different rainfall data sets, 23 different calibration data lengths and eight different optimization techniques were adopted. For the ungauged catchment case, the optimum parameter sets obtained from the nearest gauged catchment were transposed to the ungauged catchments, and two regional prediction equations were used to estimate runoff. Uncertainties were ascertained by comparing the observed and modelled runoffs by the AWBM on the basis of different combinations of methods, model parameters and input data. The main finding from this study was that the uncertainties in the AWBM modelling outputs could vary from ?1.3% to 70% owing to different input rainfall data, ?5.7% to 11% owing to different calibration data lengths and ?6% to 0.2% owing to different optimization techniques adopted in the calibration of the AWBM. The performance of the AWBM model was found to be dominated mainly by the selection of appropriate rainfall data followed by the selection of an appropriate calibration data length and optimization algorithm. Use of relatively short data length (e.g. 3 to 6 years) in the calibration was found to generate relatively poor results. Effects of different optimization techniques on the calibration were found to be minimal. The uncertainties reported here in relation to the calibration and runoff estimation by the AWBM model are relevant to the selected study catchments, which are likely to differ for other catchments. The methodology presented in this paper can be applied to other catchments in Australia and other countries using AWBM and similar rainfall–runoff models. Copyright © 2014 John Wiley & Sons, Ltd.     

Effectivity of dissolved SF6 tracer for clarification of rainfall–runoff processes in a forested headwater catchment

Understanding rainfall‐runoff processes is crucial for prevention and prediction of water‐related natural disasters. Sulfur hexafluoride (SF₆) is a potential tracer, but few researches have applied it for rainfall‐runoff process studies. We observed multiple tracers including SF₆ in spring water at 1‐ to 2‐hr intervals during rainstorm events to investigate the effectivity of SF₆ tracer in rainfall–runoff studies through the clarification of rainfall–runoff process. The target spring is a perennial spring in a forested headwater catchment with an area of 0.045 km² in Fukushima, Japan. The relationship between the SF₆ concentration in spring water and the spring discharge volume was negative trend; the SF₆ concentration in spring water becomes low as the spring discharge volume increases especially during rainstorms. The hydrograph separation using SF₆ and chloride ion tracers was applied for determining the contribution of principal sources on rainfall–runoff water. It suggested more than 60% contribution of bedrock groundwater at the rainfall peak and high percentage contribution continued even in the hydrograph recession phase. Based on observed low SF₆ concentration in groundwater after heavy rainfall, the replacement of groundwater near the spring with bedrock groundwater is indicated as a mechanism for water discharge with low SF₆ concentration during rainfall events. Consequently, rainstorm events play an important role as triggers in discharging water stored in the deeper subsurface area. In addition, SF₆ tracer is concluded as one of the strongest tracers for examining rainfall–runoff process studies. And, therefore, this study provided new insights into the dynamics of groundwater and its responses to rainfall in terms of SF₆ concentration variance in water in headwater regions.     

The simulation of runoff from small catchments in the permafrost zone by the SWAP model

The ability of a new version of SWAP physically based model, which describes the heat and water exchange processes in the soil-vegetation (snow cover)-near-surface atmosphere system and has been adapted to the permafrost conditions, to reproduce runoff formation at small watersheds in the permafrost zone. The procedure for the preparation of missing input data for model simulations is described. Model simulations were performed based on observational data collected within a decade (1969–1978) by the Kolyma Water Balance Station, located in a high-land continuous permafrost zone. The results of comparison of the modelled daily and annual runoff with data of appropriate measurements in a number of experimental watersheds in the basin of the Kontaktovyi Creek (Upper Kolyma) are analyzed.