scholarly journals Statistical analysis and modelling of surface runoff from arable fields in central Europe

2013 ◽  
Vol 17 (10) ◽  
pp. 4121-4132 ◽  
Author(s):  
P. Fiener ◽  
K. Auerswald ◽  
F. Winter ◽  
M. Disse
Keyword(s):  
Statistical Model ◽  
Soil Properties ◽  
Surface Runoff ◽  
A Priori ◽  
Arable Land ◽  
Curve Number ◽  
Runoff Generation ◽  
Runoff Volume ◽  
Initial Abstraction ◽  
Arable Fields

Abstract. Surface runoff generation on arable fields is an important driver of flooding, on-site and off-site damages by erosion, and of nutrient and agrochemical transport. In general, three different processes generate surface runoff (Hortonian runoff, saturation excess runoff, and return of subsurface flow). Despite the developments in our understanding of these processes it remains difficult to predict which processes govern runoff generation during the course of an event or throughout the year, when soil and vegetation on arable land are passing many states. We analysed the results from 317 rainfall simulations on 209 soils from different landscapes with a resolution of 14 286 runoff measurements to determine temporal and spatial differences in variables governing surface runoff, and to derive and test a statistical model of surface runoff generation independent from an a priori selection of modelled process types. Measured runoff was related to 20 time-invariant soil properties, three variable soil properties, four rain properties, three land use properties and many derived variables describing interactions and curvilinear behaviour. In an iterative multiple regression procedure, six of these properties/variables best described initial abstraction and the hydrograph. To estimate initial abstraction, the percentages of stone cover above 10% and of sand content in the bulk soil were needed, while the hydrograph could be predicted best from rain depth exceeding initial abstraction, rainfall intensity, soil organic carbon content, and time since last tillage. Combining the multiple regressions to estimate initial abstraction and surface runoff allowed modelling of event-specific hydrographs without an a priori assumption of the underlying process. The statistical model described the measured data well and performed equally well during validation. In both cases, the model explained 71 and 58% of variability in accumulated runoff volume and instantaneous runoff rate (RSME: 5.2 mm and 0.23 mm min−1, respectively), while RMSE of runoff volume predicted by the curve number model was 50% higher (7.7 mm). Stone cover, if it exceeded 10%, was most important for the initial abstraction, while time since tillage was most important for the hydrograph. Time since tillage is not taken into account either in typical lumped hydrological models (e.g. SCS curve number approach) or in more mechanistic models using Horton, Green and Ampt, or Philip type approaches to address infiltration although tillage affects many physical and biological soil properties that subsequently and gradually change again. This finding should foster a discussion regarding our ability to predict surface runoff from arable land, which seemed to be dominated by agricultural operations that introduce man-made seasonality in soil hydraulic properties.

scholarly journals Statistical analysis and modelling of surface runoff from arable fields

2013 ◽  
Vol 10 (3) ◽  
pp. 3665-3692 ◽  
Author(s):  
P. Fiener ◽  
K. Auerswald ◽  
F. Winter ◽  
M. Disse
Keyword(s):  
Statistical Model ◽  
Soil Properties ◽  
Surface Runoff ◽  
A Priori ◽  
Arable Land ◽  
Organic Carbon Content ◽  
Runoff Generation ◽  
Initial Abstraction ◽  
Arable Fields ◽  
Generate Surface

Abstract. Surface runoff generation on arable fields is an important driver of (local) flooding, on-site and off-site damages by erosion, and of nutrient and agrochemical transport. In general, three different processes generate surface runoff (Hortonian runoff, saturation excess runoff, and return of subsurface flow). Despite the developments in our understanding of these processes it remains difficult to predict, which processes govern runoff generation during the course of an event or throughout the year, when soil and vegetation on arable land are passing many states. We analysed the results from 317 rainfall simulations with a resolution of 14286 runoff measurements to determine temporal and spatial differences in parameters governing surface runoff, and to derive and test a statistical model of surface runoff generation independent from an a priori selection of modelled processes types. Measured runoff was related to 20 time-invariant soil properties, three variable soil properties, four rain properties, three land use properties and many derived variables describing interactions and curvilinear behaviour. In an iterative multiple regression procedure, six of these properties/variables best described initial abstraction and the hydrograph. To estimate initial abstraction, a percentage of stone cover above 10% and of sand content in the bulk soil were needed, while the hydrograph could be predicted best from rain depth exceeding initial abstraction, rainfall intensity, soil organic carbon content, and time since last tillage. Combining the multiple regressions to estimate initial abstraction and surface runoff allowed modelling of event-specific hydrographs without an a priori assumption of the underlying process. The statistical model described the measured data well and performed equally well during validation. In both cases, the model explained 71 and 58% of variability in runoff volume and runoff rate (RSME: 5.2 mm and 0.23 mm min−1, respectively). Stone cover was most important for the initial abstraction while time since tillage was most important for the hydrograph. The latter variable is neither taken into account in typical lumped hydrological models (e.g. SCS CN approach) nor in more mechanistic models using Horton, Green and Ampt or Philips type approaches to address infiltration. This finding should foster a discussion regarding our ability to predict surface runoff from arable land, which seemed to be dominated by agricultural operations that introduce man-made seasonality in soil hydraulic properties.

Determination of SCS-CN initial abstraction ratio in a catchment prone to flash floods

2020 ◽  
Vol 15 (1) ◽  
pp. 112-123 ◽  
Author(s):  
Martin Caletka ◽  
Monika Šulc Michalková
Keyword(s):  
Surface Runoff ◽  
Soil Conservation ◽  
Curve Number ◽  
Flash Floods ◽  
Soil Conservation Service ◽  
Initial Abstraction ◽  
Service Curve ◽  
Scs Cn ◽  
Proper Setting

Abstract The soil conservation service - curve number method is a globally used approach to simulations of surface runoff for its simplicity and applicability. Nevertheless, relevant simulations require proper setting of the model's components. This work focuses on optimization of initial abstraction ratio λ in the Husí potok sub-catchments in Czech Republic. Due to favorable morphology, the watershed is prone to flash floods and accurate modeling of surface runoff is of high interest. The analysis was conducted using pairs of discharge and rainfall measurements. The results outline that the traditional value λ= 0.2 is too high in this watershed and should be reduced.

scholarly journals Surface-Runoff Characteristics under Simulated Rainfall Conditions

2014 ◽  
Vol 24 (1-2) ◽  
pp. 219-227
Author(s):  
P Das ◽  
K Mahmud ◽  
S Karmaker
Keyword(s):  
Surface Runoff ◽  
Sprinkler System ◽  
Runoff Generation ◽  
Runoff Simulation ◽  
Small Catchment ◽  
Rainfall Duration ◽  
Runoff Volume ◽  
Runoff Rate ◽  
Peak Runoff ◽  
Recession Constant

This paper describes a rainfall-runoff simulation study, conducted in a laboratory to investigate surface runoff characteristics, verify unit hydrograph assumption and investigate the nature of the recession constant. A hydrology bench consisting of a metallic tray with an over head sprinkler system was used for this study. The metallic tray with soil bed and a river network acted as a small catchment. The over head sprinkler system consisting of spray nozzles acted as rainfall simulator. Different rainfall intensities and durations were taken as the treatments for the experiments. Surface runoff volume was collected at 10 secondly pulses of time in each experiment. Collected data were then processed and analyzed to explain the results. Unit hydrographs were developed from the surface runoff hydrographs for different rainfall durations and intensities. Recession constant K was calculated from the recession limb of each surface runoff hydrograph by optimization. Investigations show that runoff volume, runoff generation rate and peak runoff rate increase with the increasing rainfall duration. However, the peak runoff rate per sec of effective rainfall decreases with the increasing rainfall duration. There is also an evidence of the effects of rainfall intensity on runoff characteristics but no specific trend is identified. This study also reveals that the assumption of linearity between runoff volume and hydrograph ordinates is partially valid with some error which may be attributed to the non-uniform distributions of rainfall. Nature of recession constant suggests that the recession hydrograph is not only a function of catchment characteristics but also depends on rainfall intensities.DOI: http://dx.doi.org/10.3329/pa.v24i1-2.19175 Progress. Agric. 24(1&2): 219 - 227, 2013

scholarly journals Modified NRCS Abstraction Method for Flood Hydrograph Generation

2020 ◽  
Author(s):  
Jaber Almedeij
Keyword(s):  
Surface Runoff ◽  
Water Retention ◽  
Potential Surface ◽  
Initial Moisture Content ◽  
Curve Number ◽  
Actual Surface ◽  
Time Of Concentration ◽  
Initial Abstraction ◽  
Flood Hydrograph ◽  
Selection Of

The NRCS abstraction method is based on two assumptions. The first is that the ratio of actual water retention after ponding to maximum potential retention after ponding is equal to the ratio of actual surface runoff to potential surface runoff. The second assumption is that the initial abstraction for the watershed is twenty percent of the maximum potential retention. This study shows that both assumptions violate continuity principles and proposes a modification that renders an elementary relationship accounting for all abstraction forms by dividing them into a variable and constant components. Consequently, the surface runoff computation becomes dependent on the soil initial moisture content and implicitly influenced by the initial abstraction, while retaining the advantage of the subjective selection of curve number from extensive database from which the NRCS method has gained popularity. A new time of concentration model is also proposed to extend the computation for flood hydrograph generation.

scholarly journals Integrating GIS-Based MCDA Techniques and the SCS-CN Method for Identifying Potential Zones for Rainwater Harvesting in a Semi-Arid Area

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 704
Author(s):  
Hussein Al-Ghobari ◽  
Ahmed Z. Dewidar
Keyword(s):  
Water Conservation ◽  
Surface Runoff ◽  
Rainwater Harvesting ◽  
Global Climate ◽  
Remote Sensing Data ◽  
Curve Number ◽  
Drainage Density ◽  
Promising Alternative ◽  
Thematic Layers ◽  
Scs Cn

An increasing scarcity of water, as well as rapid global climate change, requires more effective water conservation alternatives. One promising alternative is rainwater harvesting (RWH). Nevertheless, the evaluation of RWH potential together with the selection of appropriate sites for RWH structures is significantly difficult for the water managers. This study deals with this difficulty by identifying RWH potential areas and sites for RWH structures utilizing geospatial and multi-criteria decision analysis (MCDA) techniques. The conventional data and remote sensing data were employed to set up needed thematic layers using ArcGIS software. The soil conservation service curve number (SCS-CN) method was used to determine surface runoff, centered on which yearly runoff potential map was produced in the ArcGIS environment. Thematic layers such as drainage density, slope, land use/cover, and runoff were allotted appropriate weights to produced RWH potential areas and zones appropriate for RWH structures maps of the study location. Results analysis revealed that the outcomes of the spatial allocation of yearly surface runoff depth ranging from 83 to 295 mm. Moreover, RWH potential areas results showed that the study areas can be categorized into three RWH potential areas: (a) low suitability, (b) medium suitability, and (c) high suitability. Nearly 40% of the watershed zone falls within medium and high suitability RWH potential areas. It is deduced that the integrated MCDA and geospatial techniques provide a valuable and formidable resource for the strategizing of RWH within the study zones.

scholarly journals Estimating surface runoff and groundwater recharge in an urban catchment using a water balance approach

2021 ◽  
Vol 29 (7) ◽  
pp. 2411-2428
Author(s):  
Robin K. Weatherl ◽  
Maria J. Henao Salgado ◽  
Maximilian Ramgraber ◽  
Christian Moeck ◽  
Mario Schirmer
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Groundwater Recharge ◽  
Surface Runoff ◽  
Urban Areas ◽  
Water Cycle ◽  
Land Use Changes ◽  
Curve Number ◽  
Hydrograph Separation ◽  
Balance Approach

AbstractLand-use changes often have significant impact on the water cycle, including changing groundwater/surface-water interactions, modifying groundwater recharge zones, and increasing risk of contamination. Surface runoff in particular is significantly impacted by land cover. As surface runoff can act as a carrier for contaminants found at the surface, it is important to characterize runoff dynamics in anthropogenic environments. In this study, the relationship between surface runoff and groundwater recharge in urban areas is explored using a top-down water balance approach. Two empirical models were used to estimate runoff: (1) an updated, advanced method based on curve number, followed by (2) bivariate hydrograph separation. Modifications were added to each method in an attempt to better capture continuous soil-moisture processes and explicitly account for runoff from impervious surfaces. Differences between the resulting runoff estimates shed light on the complexity of the rainfall–runoff relationship, and highlight the importance of understanding soil-moisture dynamics and their control on hydro(geo)logical responses. These results were then used as input in a water balance to calculate groundwater recharge. Two approaches were used to assess the accuracy of these groundwater balance estimates: (1) comparison to calculations of groundwater recharge using the calibrated conceptual HBV Light model, and (2) comparison to groundwater recharge estimates from physically similar catchments in Switzerland that are found in the literature. In all cases, recharge is estimated at approximately 40–45% of annual precipitation. These conditions were found to closely echo those results from Swiss catchments of similar characteristics.

scholarly journals Initial abstraction ratio and Curve Number estimation using rainfall and runoff data from a tropical watershed

RBRH ◽  
2019 ◽  
Vol 24 ◽  
Author(s):  
Luiz Claudio Galvão do Valle Junior ◽  
Dulce Buchala Bicca Rodrigues ◽  
Paulo Tarso Sanches de Oliveira
Keyword(s):  
Conversion Factor ◽  
Poor Performance ◽  
Curve Number ◽  
Storm Events ◽  
Rainfall Runoff ◽  
Initial Abstraction ◽  
Rainfall Depth ◽  
Standard Value ◽  
Tropical Watershed ◽  
Runoff Events

ABSTRACT The Curve Number (CN) method is extensively used for predict surface runoff from storm events. However, remain some uncertainties in the method, such as in the use of an initial abstraction (λ) standard value of 0.2 and on the choice of the most suitable CN values. Here, we compute λ and CN values using rainfall and runoff data to a rural basin located in Midwestern Brazil. We used 30 observed rainfall-runoff events with rainfall depth greater than 25 mm to derive associated CN values using five statistical methods. We noted λ values ranging from 0.005 to 0.455, with a median of 0.045, suggesting the use of λ = 0.05 instead of 0.2. We found a S0.2 to S0.05 conversion factor of 2.865. We also found negative values of Nash-Sutcliffe Efficiency (to the estimated and observed runoff). Therefore, our findings indicated that the CN method was not suitable to estimate runoff in the studied basin. This poor performance suggests that the runoff mechanisms in the studied area are dominated by subsurface stormflow.

scholarly journals Natural and Managed Grasslands Productivity during Multiyear in Ex-Arable Lands (in the Context of Climate Change)

Agriculture ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215
Author(s):  
Liudmila Tripolskaja ◽  
Asta Kazlauskaite-Jadzevice ◽  
Virgilijus Baliuckas ◽  
Almantas Razukas
Keyword(s):  
Climate Change ◽  
Soil Properties ◽  
Dry Matter ◽  
Arable Land ◽  
Rainfall Amount ◽  
Rainfall Variation ◽  
Global Issue ◽  
Term Change ◽  
The Impact

Ex-arable land-use change is a global issue with significant implications for climate change and impact for phytocenosis productivity and soil quality. In temperate humid grassland, we examined the impact of climate variability and changes of soil properties on 23 years of grass productivity after conversion of ex-arable soil to abandoned land (AL), unfertilized, and fertilized managed grassland (MGunfert and MGfert, respectively). This study aimed to investigate the changes between phytocenosis dry matter (DM) yield and rainfall amount in May–June and changes of organic carbon (Corg) stocks in soil. It was found that from 1995 to 2019, rainfall in May–June tended to decrease. The more resistant to rainfall variation were plants recovered in AL. The average DM yield of MGfert was 3.0 times higher compared to that in the AL. The DM yields of AL and MG were also influenced by the long-term change of soil properties. Our results showed that Corg sequestration in AL was faster (0.455 Mg ha−1 year−1) than that in MGfert (0.321 Mg ha−1 year−1). These studies will be important in Arenosol for selecting the method for transforming low-productivity arable land into MG.

scholarly journals Seasonal Net Shortwave Radiation of Bare Arable Land in Poland and Israel According to Roughness and Atmospheric Irradiance

2021 ◽  
Vol 13 (10) ◽  
pp. 1897
Author(s):  
Jerzy Cierniewski ◽  
Jean-Louis Roujean ◽  
Jarosław Jasiewicz ◽  
Sławomir Królewicz
Keyword(s):  
Arable Land ◽  
Soil Tillage ◽  
Shortwave Radiation ◽  
Landsat 8 ◽  
Clear Sky ◽  
Spatial Coverage ◽  
Arable Fields ◽  
Model Equations ◽  
Earth’S Climate ◽  
Sky Conditions

Tillage of arable fields, using for instance a smoothing harrow, may increase the magnitude of albedo of such soil surfaces depending on the location, the sun’s illumination and atmospheric components. As these soil surfaces absorb less shortwave radiation compared to plowed soils, the result is an atmospheric cooling and a positive effect on the Earth’s climate. This paper is the follow-on of a previous study aimed at quantifying the seasonal dynamics of net shortwave radiation reflected by bare air-dried arable land areas located in contrasting environments, i.e. Poland and Israel. Soil tillage includes a plow, a disk harrow, and a smoothing harrow. Previous work concentrated on the estimate of net shortwave radiation under clear-sky theoretical scenarios, whereas the present study deals with a realistic atmosphere throughout the year 2014. This latter is characterized by the observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the Meteosat Second Generation (MSG). The variations of the net shortwave radiation for the selected bare arable land areas were assessed in combining observations from Landsat 8 images and digital maps of land use and soil, plus model equations that calculate the diurnal variations of the broadband blue-sky albedo with roughness inclusive. The daily amount of net shortwave radiation for air-dried bare arable land in Poland and Israel for the time their spatial coverage is the largest was found to be about 40–50% and 10% lower, respectively, in cloudy-sky conditions compared to clear-sky conditions.

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