Antecedent Moisture Conditions Research Articles

Capturing the transient hydrological response in sandy soils during a rare cloudburst associated with shallow slope failures; a case study in the Atlantic Highlands, New Jersey, USA

A cloudburst on 7 August 2018 in the coastal bluffs of the Atlantic Highlands, New Jersey, induced flooding, erosion and multiple shallow slope failures that adversely affected the surrounding hillside residential area. Historically, short-duration deluges are rare in the New York Bay region, with only eight cloudbursts of greater magnitude documented since 1948. The coastal bluffs consist of a variably thick, sandy surficial material overlying flat-lying, mostly non-indurated Cretaceous and Tertiary sediments, including some low-permeability glauconitic units. The bluffs have been affected by both historical deep-seated and shallow landslide movement, the latter typically related to heavy, relatively long-duration rainfall associated with tropical cyclones and nor'easters. The shallow hydrological response during the rare cloudburst was captured at two hydrological monitoring sites and yielded insights into rapidly changing moisture conditions resulting in slope failure. Additional information is provided on historical cloudbursts that have affected the region, antecedent moisture conditions, and documented landslide types and processes. Supplementary material: A USGS ScienceBase data release of the time-series monitoring data that accompanies the publication of this paper is available at https://doi.org/10.5066/P9A601HC

Identifying rainfall threshold of flash flood using entropy decision approach and hydrological model method

Flash flood disaster, with strong suddenness and tremendous destructiveness, is one of the most severe natural disasters in China that seriously threaten the lives and property safety of people and social development. Owing to the complex terrain and limited rainfall and runoff monitoring gauges, it is arduous to effectively prevent and control flash flood disasters in small-sized and medium-sized hilly watersheds. Identifying rainfall threshold, critical discharge and warning periods for flash flood, is critical in disaster prevention in such regions. This study adopted two approaches, the entropy-based decision approach and the hydrological model approach in calculating rainfall thresholds under different antecedent moisture condition (AMC). In particular, the entropy-based decision approach was improved, by using the Frank copula to calculate the multivariate joint distribution of the cumulative rainfall and the corresponding peak discharge. These two approaches were validated in a typical basin, located in the Pearl River Delta in South China that is characterized by frequently heavy rainfall and floods in the monsoon. Results showed that both approaches have the ability to quantify rainfall thresholds. Relatively, the Bayesian method exhibited higher rainfall thresholds, comparing to the other methods. In particular, for AMC I, the utility-entropy risk function method (with λ = 1) exhibited the best-applied practicable forecast lead time of 2.0 h; as for AMC II, the two methods showed the same forecast lead time of 1.5 h, and for AMC III, the hydrological model-based approach showed an optimal forecast lead time of 6.0 h. Meanwhile, the entropy-based approach exhibited the same performance as hydrological modeling approaches, indicating that this method is practicable in flood forecasting. The results would be helpful for floods prevention and mitigation in such small-sized and medium-sized hilly watersheds.

A simulation of the rainfall-runoff process using artificial neural network and HEC-HMS model in forest lands

Simulation of the runoff-rainfall process in forest lands is essential for forest land management. In this research, a hydrologic modelling system (HEC-HMS) and artificial neural network (ANN) were applied to simulate the rainfall-runoff process (RRP) in forest lands of Kasilian watershed with an area of 68 square kilometres. The HMS model was performed using the secondary data of rainfall and discharge at the climatology and hydrometric stations, the Soil Conservation Service (SCS) for simulating a flow hydrograph, the curve number (CN) method for runoff estimation, and lag time method for flow routing. Further, a multilayer perceptron (MLP) network was used for simulating the rainfall-runoff process. HEC-HMS model was used to optimize the initial loss (IL) values in the rainfall-runoff process as an input. IL reflects the conditions of vegetation, soil infiltration, and antecedent moisture condition (AMC) in soil. Then, IL values and also incremental rainfall were applied as inputs into ANN to simulate the runoff values. The comparison of the results of simulating the RRP in two scenarios, using IL and without IL, showed that the IL parameter has a high effect in increasing the simulation performance of the rainfall-runoff process. Moreover, ANN predictions were more precise in comparison with those of the HMS model. Further, forest lands can significantly increase IL values and decrease runoff generation.

Hydrological analysis of the September 2014 torrential floods of the Danube tributaries in the Eastern Serbia

Torrential flood as a rainfall precipitation driven natural hazard occurs in the watershed that responds within several hours due to a rugged topography. The extraordinary torrential flood event from September 15 2014 in the Eastern Serbia with its severe consequences, widespread material damages and casualties, draw an attention of the Serbian public and is a topic of this work. The combined method of Soil Conservation Service and synthetic unit triangular hydrograph is used to calculate the effective rainfall and peak discharges in five affected watersheds (Podvrska, Velika Kamenica, Slatinska, Zamna, and Mala Kamenica) in order to define the extremeness of this event. Special attention is given to the determination of the lag time defining the unit hydrograph and the curve numbers of the studied watersheds on the base of land use and hydrological class of soils with regard to geology, considering antecedent soil moisture conditions. Taking into account the high curve number (due to the high share of soils with an unfavorable hydrological conditions and high share of agriculture areas in land use), the shortest time to peak (due to the highest mean slope of river bed), the highest specific maximal discharge on subject date (4.58 m3s−1 km−2) as well as sediment transport data, the highest priority for erosion and torrential flood control works is attributed to the Mala Kamenica watershed. The results of this work may be a significant contribution to the flood risk assessment on a watershed level in this part of Eastern Serbia that should always start with reviewing and analyzing the historical torrential flood events.

Long-term and event-scale sub-daily streamflow and sediment simulation in a small forested catchment

ABSTRACT In small catchments, the time interval most commonly used for simulation – daily or monthly – may not be sufficient to accurately capture the time distribution of hydrological processes. In this paper, the Soil and Water Assessment Tool (SWAT) was used to perform an hourly long-term streamflow and sediment load simulation in the small (4.8 km2) and forested Aixola catchment (northern Spain). From this simulation, 10 runoff events were tested; the most satisfactory results for streamflow were obtained under wet antecedent conditions. However, simulated sediment load was underestimated during the peaks and remained high towards the end of the event. Furthermore, the influence of the precipitation time step (1–4 h, daily) was not relevant in the streamflow simulation but does influence the sediment simulation. The best results were achieved with the daily step simulations obtained at an hourly time step. This paper shows that sub-daily modelling improves water and especially sediment yield results; however, improvements are still needed in timing-related routines.

Stream Water Chemistry in Mixed-Conifer Headwater Basins: Role of Water Sources, Seasonality, Watershed Characteristics, and Disturbances

Understanding the transport of dissolved organic carbon (DOC) and nitrogen (N) as water flows through headwater basins is important for predicting downstream water quality. With increased recognition of climatic impact on nutrient transport, more studies are needed in headwater basins experiencing a Mediterranean-type climate, such as those of the Sierra Nevada, California. We analyzed water samples collected over 5 years from eight low-order and mixed-conifer watersheds to elucidate the temporal variation of water chemistry and evaluate their responses to prolonged drought and low-intensity forest thinning. We observed higher stream DOC concentrations in October compared to other months within water years prior to drought and thinning, suggesting the importance of antecedent moisture conditions on seasonal C export. In unthinned watersheds, stream DOC concentrations were lower (62%) and DOC aromaticity was higher (68 and 92%, depending on the index used) during drought compared to non-drought years. In thinned watersheds during drought years, stream water had higher DOC concentrations (66–94% in three consecutive years following thinning) and dissolved inorganic N (24%, in the third year following thinning) compared to unthinned watersheds during drought. Additionally, lower stream DOC concentrations were found in watersheds with higher elevations and lower drainage densities in the year with near-average precipitation; however, these correlations were not significant in years with greater or extremely low precipitation. Taken together, our results suggest that stream concentrations of DOC and dissolved N in Mediterranean headwater basins are extremely variable over time due to the high temporal climatic variabilities and periodic management practices.

Managing the effects of extreme sub-daily rainfall and flash floods-a practitioner's perspective.

Extreme sub-daily rainfall affects flooding in the UK and urban pollution management. Water utilities in the UK need to understand the characteristics of this rainfall, and how it may change in the future in order to plan for and manage these impacts. There is also significant interest from infrastructure owners and urban authorities exposed to flood risk from short-period, intense rainfall events. This paper describes how UK flood risk guidance incorporates allowances for climate change and how recent research using convection-permitting climate models is helping to inform this guidance. The guidance documents are used by engineers and scientists in the modelling of sewer networks, smaller river catchments and urban drainage areas and provide values to 'uplift' rainfall event data used as model inputs to reflect climate change model projections. With an increasing focus on continuous simulation modelling using time series rainfall, research into adjusting time series data to reflect future rainfall characteristics in convection-permitting climate models is discussed. Other knowledge gaps for practitioners discussed are the potential changing shape (profile) of future rainfall events and future changes in antecedent wetness conditions. The author explains the challenge of developing simple and effective guidance for practitioners from the complex scientific output. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Can a superabsorbent polymer help remediate compaction in frigid, semiarid soils? – a laboratory evaluation on soil physical processes

Superabsorbent polymers (SAPs) absorb more water than their mass. When applied to frigid, semiarid soils, they may modify physical processes and amplify winter freezing-thawing effects for remediating compaction. If so, SAPs may be an effective amendment in reclamation projects. Laboratory tests evaluated SAPs influences on setting antecedent soil moisture and mechanical conditions prior to freezing-thawing. This was done by evaluating evaporation characteristics, water retention, and Atterberg limits on five soil series of differing textures as affected by SAP application rates (0, 40, 80, and 200 mg SAP kg−1 dry soil). Then, soil columns with and without freeze-thaw cycles were evaluated for each SAP rate to determine if SAP amplified freezing-thawing to remediate compaction. This was done by observing changes in soil bulk density, peak penetration resistance, and saturated hydraulic conductivity (Ksat) as indicators of compaction. Results demonstrated that increasing SAP rates significantly decreased evaporative water losses, increased water retention, and increased the liquid limit. In a field setting, these trends would set antecedent soil conditions that favor the remediation of compaction during subsequent winter freeze-thaw cycles. Results also demonstrated that SAP significantly affected the freezing-thawing process on some indicators of soil compaction. Increases in SAP rates significantly decreased peak penetration resistance, had mixed effects on Ksat, but no effect on bulk density. This suggests particle rearrangement is occurring internally (i.e., aggregation) even though changes in bulk density are not evident. Application of SAP appears to have potential for amplifying the remediation of soil compaction during winter in frigid, semiarid environments.

Measuring and modeling event-based environmental flows: An assessment of HEC-RAS 2D rain-on-grid simulations

There is an immediate need to use available modeling tools to quantify environmental flows targets where changing climate and human activity has altered hydroecologically important streamflow regimes. A model performance assessment was undertaken using observed data collected from five nested gauging sites in a mixed land use watershed of the central US. An integrated modeling approach was used to couple The Soil and Water Assessment Tool (SWAT version 2012), and The Hydrologic Engineering Center's River Analysis System (HEC-RAS version 5.0.7). SWAT was used to generate effective rainfall needed to run HEC-RAS rain-on-grid two-dimensional hydrodynamic simulations. Model calibration results showed the potential usefulness of coupling SWAT and HEC-RAS using an integrated modeling approach. For example, PBIAS of 8.3%, NSE value of 0.84, and coefficient of determination (R2) value of 0.80 at a highly urbanized monitoring site used for model calibration. Split-site validation results showed PBIAS values that ranged from 10.4 to 33.8%, NSE values that ranged from 0.33 to 0.92, and R2 values that ranged from 0.86 to 0.97. Results showed that 2D rain-on-grid HEC-RAS simulations can produce realistic simulations of stage hydrograph response when: (1) areal effective precipitation is used for 2D HEC-RAS rain-on-grid forcing's, (2) HEC-RAS is calibrated to observed data during the event of interest, (3) there are not substantial sources of backwatering from outside the models geometric data, and (4) during saturated antecedent soil moisture conditions surface DEM's adequately describe overland flow paths. This model performance assessment is among the first, if not the first, to show calibration and validation results associated with 2D HEC-RAS rain-on-grid simulations at a watershed scale. Results highlight the need for time-varying roughness coefficients to account for soil moisture conditions, and point to the efficacy of using a SWAT/HEC-RAS integrated modeling approach to generate event-based environmental flows information.

Modeling the response of soil moisture to climate variability in the Mediterranean region

Abstract. Future climate scenarios for the Mediterranean region indicate a possible decrease in annual precipitation associated with an intensification of extreme rainfall events in the coming years. A major challenge in this region is to evaluate the impacts of changing precipitation patterns on extreme hydrological events such as droughts and floods. For this, it is important to understand the impact of climate change on soil moisture since it is a proxy for agricultural droughts, and the antecedent soil moisture condition plays a key role on runoff generation. This study focuses on 10 sites, located in southern France, with available soil moisture, temperature, and precipitation observations for a 10-year time period. Soil moisture is simulated at each site at the hourly time step using a model of soil water content. The sensitivity of the simulated soil moisture to different changes in precipitation and temperature is evaluated by simulating the soil moisture response to temperature and precipitation scenarios generated using a delta change method for temperature and a stochastic model (the Neyman–Scott rectangular pulse model) for precipitation. Results show that soil moisture is more impacted by changes in precipitation intermittence than precipitation intensity and temperature. Overall, increased temperature and precipitation intensity associated with more intermittent precipitation leads to decreased soil moisture and an increase in the annual number of days with dry soil moisture conditions. In particular, a temperature increase of +4 ∘C combined with a decrease of annual rainfall between 10 % and 20 %, corresponding to the current available climate scenarios for the Mediterranean, lead to a lengthening of the drought period from June to October with an average of +28 d of soil moisture drought per year.

Soil carbon dynamics during drying vs. rewetting: Importance of antecedent moisture conditions

Soil moisture influences soil carbon dynamics, including microbial growth and respiration. The response of such ‘soil respiration’ to moisture changes is generally assumed to be linear and reversible, i.e. to depend only on the current moisture state. Current models thus do not account for antecedent soil moisture conditions when determining soil respiration or the available substrate pool. We conducted a laboratory incubation to determine how the antecedent conditions of drought and flood influenced soil organic matter (SOM) chemistry, bioavailability, and respiration. We sampled soils from an upland coastal forest, Beaver Creek, WA USA, and subjected them to drying and rewetting treatments. For the drying treatment, field moist soils were saturated and then dried to 75, 50, 35, and 5% saturation. In the rewetting treatment, field moist soils were air-dried and then rewet to 35, 50, 75, and 100% saturation. We measured respiration and water extractable organic carbon (WEOC) concentrations and used 1H-NMR and FT-ICR-MS to characterize the WEOC pool across the treatments. The drying vs. wetting treatment strongly influenced SOM bioavailability, as rewet soils (with antecedent drought) had greater WEOC concentrations and respiration fluxes compared to the drying soils (with antecedent flood). In addition, air-dry soils had the highest WEOC concentrations, and the NMR-resolved peaks showed a strong contribution of protein groups in these soils. Both NMR and FT-ICR-MS analyses indicated increased contribution of complex aromatic groups/molecules in the rewet soils, compared to the drying soils. We suggest that drying introduced organic matter into the WEOC pool via desorption of aromatic molecules and/or by microbial cell lysis, and this stimulated microbial mineralization rates. Our work indicates that even short-term shifts in antecedent moisture conditions can strongly influence soil C dynamics at the core scale. The predictive uncertainties in current soil models may be reduced by a more accurate representation of soil water and C persistence that includes a mechanistic and quantitative understanding of the impact of antecedent moisture conditions.

Surface runoff estimation of Sind river basin using integrated SCS-CN and GIS techniques

Rainfall and runoff are the significant hydrologic component in the water resources assessment. Numerous methods are available to estimate runoff from rainfall; however, the SCS-CN method remains the most popular and frequently used method as runoff curve number (CN) is a crucial factor of the SCS-CN method and depends on land use/land cover (LULC), soil type, and antecedent soil moisture (AMC). Besides this, various parameters, such as Hydrological Soil Characteristics (HSG), precipitation (P), Potential Maximum Retention (PMR), Antecedent Moisture Condition (AMC), Weighted Curve Number (WCN), are the mandatory inputs to the SCS-CN model. In the results, the daily runoff from the Sind river basin for ten years, i.e., 2005 to 2014, has been used. As a result, the average annual surface runoff calculated for the Sind river basin is 133.71 mm. The total average volume of runoff is 35.04 × 10 8 m 3, representing 17.21% of the total average annual rainfall.

A COMPARATIVE ASSESSMENT OF DIFFERENT LOSS METHODS AVAILABLE IN MIKE HYDRO RIVER-UHM

Hydrologic modelling studies usually involve data series with a large temporal scale, especially in Romania, focusing on a long-term impact analysis. Nevertheless, event-based runoff models are essential tools for short-term purposes such as flash flood forecasting. Suitable methods or models must be considered in order to ensure the validity of such research based on parameter calibration to a particular area. Therefore, a comparative analysis of methods must be conducted first, in order to determine the optimal ones that can be used for future data prediction. The aim of the present study is to apply and validate the MIKE HYDRO River modeling system - the UHM module, through a comparative analysis of the SCS, Generalized SCS and Proportional Loss methods available, to a small-sized mountainous watershed, where no research has been conducted in this field. To this end, three spring rainfall events were chosen, but with different antecedent moisture conditions, in order to examine how well the chosen methods can reproduce the available observations in such circumstances. The SCS method yielded the highest quality performance, but the Proportional Loss method has also proven effective under these conditions.

Landscape‐Scale Plant Water Content and Carbon Flux Behavior Following Moisture Pulses: From Dryland to Mesic Environments

AbstractRain pulses followed by interstorm drying periods are the fundamental units of water input into ecosystems on subweekly time scales. It is essential to understand landscape‐scale vegetation responses on these unit time scales as they may describe sensitivity of landscape water, carbon, and energy cycles to shifts in rainfall intensity and frequency, even if the average seasonal precipitation remains unchanged. Because pulse investigations are primarily carried out in drylands, little is known about the characteristics and extent of ecosystem plant pulse responses across the broader range of climates and biomes. Using satellite‐based plant water content (from vegetation optical depth) and plant carbon uptake observations from eddy covariance towers across the continental United States climate gradient (dry to humid), we characterize large‐scale plant carbon and water uptake responses to rain pulses during spring and summer months. We find that while all ecosystems in the study region show discernable plant water content and carbon flux responses to rain pulses, drier ecosystems exhibit more frequent and longer duration responses. Unlike mesic environments, drylands show significantly different responses under varying antecedent soil moisture and pulse magnitude conditions; the largest water and carbon uptakes follow large pulses on initially wet soils. We detect soil moisture thresholds primarily in drylands, which can partly explain dryland vegetation's different responses under dry and wet conditions. We conclude that vegetation responds to individual pulses of water availability across all climates and therefore a range of ecosystems are sensitive to rainfall distributions beyond simple seasonal precipitation totals.

Assessment of climate change impact on the Gomti River basin in India under different RCP scenarios

Climate change can adversely affect the elements of water balance in river basins. This paper studies the effects of climate change on hydro-climatological components of the Gomti River basin using SWAT hydrological model. Model performance has been evaluated through sensitivity analysis, calibration, and validation. During calibration and validation time period, the Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2) values were obtained as 0.86, 0.87, and 0.79, 0.83, respectively. From the sensitivity analysis, it was found that SCS runoff curve number for antecedent moisture condition II (CN2) is the most sensitive parameter, followed by saturated hydraulic conductivity (SOL_K) and then available water capacity of the soil layer (SOL_AWC) etc. To assess the future climate change effects on hydrological variables, MIROC-ESM, MIROC-ESM-CHEM, MIROC_MIROC5, and MOHC_HADGEM2_ES Global Climate Models (GCMs) under RCP 4.5 and RCP 8.5 were applied in the calibrated SWAT model. The following trends were observed after applying the scenarios—the temperature is rising under RCP 4.5 (8.5) scenarios, near-century by + 0.24% (+ 0.65), mid-century by + 2.8% (+ 4.62), and end-century by + 5.25% (+ 10.98), respectively. Precipitation is declining under RCP 4.5 (8.5) by − 29.17% (− 29.65%), − 28.69% (− 28.88%), and − 23.82% (− 20.11%), respectively. Evapotranspiration under RCP 4.5 (RCP 8.5) is increasing by + 3.62% (+ 3.95%), + 4.30% (+ 5.38%), and + 5.49% (+ 6.03%), respectively. Consequently, streamflow under RCP 4.5 (RCP 8.5) is declining by − 31.27% (− 23.99%), − 27.45% (− 28.96%), and − 24.30% (− 18.03%), respectively in near, mid, and end century. The findings will be beneficial for managing future water resources in the Gomti River basin.

A dynamic prediction model for time‐to‐peak

AbstractA simplified empirical equation is developed for widespread prediction of dynamic catchment response time. This model allows for time‐to‐peak prediction to evolve from static, lumped models, thereby providing a single value for any storm within a given catchment, using a single set of input parameters, that can be applied to a dynamic model, thus accounting for the variability between storm sizes and catchment moisture conditions. These dynamic prediction methods are translated to North America for the first time. This allows the concepts and prediction methods for catchment response time prediction previously established for the United Kingdom (UK), to be translated to a simple empirical equation for use in North America, through the use of selected study areas in Canada and the United States. This reconfigured model is statistically successful in both the UK and North America and allows for a straightforward implementation of dynamic time‐to‐peak prediction. Further, the reconfigured model introduces the use of a runoff coefficient (Rc) to encompass historical catchment wetness, increasing the ease of incorporating antecedent moisture condition into predictions.

Processes in the Unsaturated Zone by Reliable Soil Water Content Estimation: Indications for Soil Water Management from a Sandy Soil Experimental Field in Central Italy

Reliable soil moisture data are essential for achieving sustainable water management. In this framework, the performance of devices to estimate the volumetric moisture content by means dielectric properties of soil/water system is of increasing interest. The present work evaluates the performance of the PR2/6 soil moisture profile probe with implications on the understanding of processes involving the unsaturated zone. The calibration at the laboratory scale and the validation in an experimental field in Central Italy highlight that although the shape of the moisture profile is the same, there are essential differences between soil moisture values obtained by the calibrated equation and those obtained by the manufacturer one. These differences are up to 10 percentage points for fine-grained soils containing iron oxides. Inaccurate estimates of soil moisture content do not help with understanding the soil water dynamic, especially after rainy periods. The sum of antecedent soil moisture conditions (the Antecedent Soil moisture Index (ASI)) and rainfall related to different stormflow can be used to define the threshold value above which the runoff significantly increases. Without an accurate calibration process, the ASI index is overestimated, thereby affecting the threshold evaluation. Further studies on other types of materials and in different climatic conditions are needed to implement an effective monitoring network useful to manage the soil water and to support the validation of remote sensing data and hydrological soil models.

Emission of Greenhouse Gases From Water Tracks Draining Arctic Hillslopes

AbstractExperimental and ambient warming of Arctic tundra results in emissions of greenhouse gases to the atmosphere, contributing to a positive feedback to climate warming. Estimates of gas emissions from lakes and terrestrial tundra confirm the significance of aquatic fluxes in greenhouse gas budgets, whereas few estimates describe emissions from fluvial networks. We measured dissolved gas concentrations and estimated emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) from water tracks, vegetated depressions that hydrologically connect hillslope soils to lakes and streams. Concentrations of trace gases generally increased as ground thaw deepened through the growing season, indicating active production of greenhouse gases in thawed soils. Wet antecedent conditions were correlated with a decline in CO2 and CH4 concentrations. Dissolved N2O in excess of atmospheric equilibrium occurred in drier water tracks, but on average water tracks took up N2O from the atmosphere at low rates. Estimated CO2 emission rates for water tracks were among the highest observed for Arctic aquatic ecosystems, whereas CH4 emissions were of similar magnitude to streams. Despite occupying less than 1% of total catchment area, surface waters within water tracks were an estimated source of up to 53–85% of total CH4 emissions from their catchments and offset the terrestrial C sink by 5–9% during the growing season. Water tracks are abundant features of tundra landscapes that contain warmer soils and incur deeper thaw than adjacent terrestrial ecosystems and as such might contribute to ongoing and accelerating release of greenhouse gases from permafrost soils to the atmosphere.

Application of the SCS–CN Method to the Hancheon Basin on the Volcanic Jeju Island, Korea

This study investigates three issues regarding the application of the SCS–CN (Soil Conservation Service–Curve Number) method to a basin on the volcanic Jeju Island, Korea. The first issue is the possible relation between the initial abstraction and the maximum potential retention. The second is the determination of the maximum potential retention, which is also closely related to the estimation of CN. The third issue is the effect of the antecedent soil moisture condition (AMC) on the initial abstraction, maximum potential retention and CN. All of these issues are dealt with based on the analysis of several rainfall events observed in the Hancheon basin, a typical basin on Jeju Island. In summary, the results are that, firstly, estimates of initial abstraction, ratio λ, maximum potential retention, and CN were all found to be consistent with the SCS–CN model structure. That is, CN and the maximum potential retention showed a strong negative correlation, and the ratio λ and the maximum potential retention also showed a rather weak negative correlation. On the other hand, a significant positive correlation was found between CN and the ratio λ. Second, in the case where the accumulated number of days is four or five, the effect of antecedent precipitation amount is clear. The antecedent five-day rainfall amount for the AMC-III condition is higher than 400 mm, compared to the AMC-I condition of less than 100 mm. Third, an inverse proportional relationship is found between the AMC and the maximum potential retention. On the other hand, a clear linear proportional relation is found between the AMC and CN. Finally, the maximum potential retention for the Hancheon basin is around 200 mm, with the corresponding CN being around 65. The ratio between the initial abstraction and the maximum potential retention is around 0.3. Even though these results are derived by analyzing a limited number of rainfall events, they are believed to properly consider the soil characteristics of Jeju Island.

Study on the applicability of the SCS-CN-based models to simulate floods in the semi-arid watersheds of northern Algeria

Algeria has experienced catastrophic floods over the second half of the twentieth century, causing many deaths and extensive material damage. This study was conducted to find a suitable event-based rainfall-runoff (RR) model for semi-arid conditions, where continuous data are not available in all regional basins. The study compared, based on data availability, the SCS-CN model based on the antecedent moisture conditions (AMC) and four modified SCS-CN models incorporating antecedent moisture amounts (AMA) in order to find the best model to reproduce the flood hydrographs in two catchments. The modified models were predominant over the SCS-CN method. Nonetheless, the Singh et al. (Water Resour Manag 29:4111–4127, 2015. https://doi.org/10.1007/s11269-015-1048-1 ) model (M4) and the Verma et al. (Environ Earth Sci 76:736, 2017a. https://doi.org/10.1007/s12665-017-7062-2 ) model (M5) were superior and demonstrated more stable structures. Coupled with the Hayami routing model, the models showed promising results and were able to reproduce the observed hydrographs’ shape. However, it was impossible to choose the preferred model since they each excelled as to a criterion. Therefore, the corresponding outputs were combined using the simple average (SA) method and the weighted average (WA) method. We found that the WA method showed better results in the two catchments and allowed a more accurate prediction according to the performance criteria.