Effects of urban residential landscape composition on surface runoff generation

Abstract. A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall–runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, "Ernies" (control, fully forested) and "Lemon" (54% cleared) are in a zone of mean annual rainfall of 725 mm, while "Salmon" (control, fully forested) and "Wights" (100% cleared) are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall–runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i) immediately after clearing due to reduced evapotranspiration, and (ii) through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i) an upper zone unsaturated store, (ii) a transient stream zone store, (ii) a lower zone unsaturated store and (iv) a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and predicted monthly hydrographs. The observed and predicted monthly runoff for all catchments matched well with coefficients of determination (R2) ranging from 0.68 to 0.87. Predictions were relatively poor for: (i) the Ernies catchment (lowest rainfall, forested), and (ii) months with very high flows. Overall, the predicted mean annual streamflow was within ±8% of the observed values. Keywords: monthly streamflow, land use change, conceptual model, data-based approach, groundwater

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Spatio-temporal modeling of surface runoff in ungauged sub-catchments of Subarnarekha river basin using SWAT

MAUSAM ◽

10.54302/mausam.v72i3.1309 ◽

2021 ◽

Vol 72 (3) ◽

pp. 597-606

Author(s):

CHINMAYA PANDA ◽

DWARIKA MOHAN DAS ◽

B. C. SAHOO ◽

B. PANIGRAHI ◽

K. K. SINGH

Keyword(s):

Surface Runoff ◽

Assessment Tool ◽

Nutrient Loss ◽

Coefficient Of Determination ◽

Annual Rainfall ◽

Model Parameters ◽

Runoff Generation ◽

Temporal Modeling ◽

Spatio Temporal ◽

R Factors

In this present study, Soil and Water Assessment Tool (SWAT) embedded with ArcGIS interface has been used to simulate the surface runoff from the un-gauged sub-catchments in the upper catchment of Subarnarekha basin. Model calibration and validation were performed with the help of Sequential Uncertainty Fitting (SUFI-2) in-built in the SWAT-CUP package (SWAT Calibration Uncertainty Programs). The model was calibrated for a period from 1996 to 2008 with 3 years warm up period (1996-1998) and validated for a period of 5 years from 2009 to 2013. The model evaluation was performed by Nash - Sutcliffe coefficient (NSE), Coefficient of determination (R2) and Percentage Bias (PBIAS). The degree of uncertainty was evaluated by P and R factors. Basing upon the R2, NSE and PBIAS values respectively, of the order of 0.90, 0.90 and -12%, during calibration and 0.85, 0.83 and -15% during validation, substantiate performance of the model. All uncertainties of model parameters have been well taken by the P and R factors respectively, of the order of 0.95 and 0.77 during calibration and 0.82 and 0.87 during validation. The runoff generation from 19 sub-catchments of Adityapur catchment varies from 29.2-44.1% of the annual rainfall and average surface runoff simulated for the entire catchment is 545 mm. As the surface runoff generated in most of the sub-catchments amounts to above 30% of rainfall, it is recommended for adequate number of structural interventions at appropriate locations in the catchment to store the rainfall excess for providing irrigation, recharging groundwater and restricting the sediment and nutrient loss.

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Surface soil water dynamics in pastures in northern New South Wales. 2. Surface runoff

Australian Journal of Experimental Agriculture ◽

10.1071/ea03027 ◽

2004 ◽

Vol 44 (3) ◽

pp. 283 ◽

Cited By ~ 7

Author(s):

S. R. Murphy ◽

G. M. Lodge ◽

S. Harden

Keyword(s):

Soil Water ◽

Surface Runoff ◽

New South ◽

Ground Cover ◽

Simulation Modelling ◽

Runoff Generation ◽

Grazed Pastures ◽

South Wales ◽

Runoff Events

Surface runoff can represent a significant part of the hydrological balance of grazed pastures on the north-west slopes of New South Wales, and is influenced by a range of rainfall characteristic, soil property, and pasture conditions. Runoff plots were established on grazed pastures at 3 sites as part of the Sustainable Grazing Systems National Experiment (SGS NE). Pastures were either native (redgrass, wallaby grass and wire grass) or sown species (phalaris, subterranean clover and lucerne) and a range of grazing management treatments were imposed to manipulate pasture herbage mass, litter mass and ground cover. Rainfall and runoff events were recorded using automatic data loggers between January 1998 and September 2001. Stored soil water in the surface layer (0–22.5 cm) was monitored continuously using electrical resistance sensors and automatic loggers. Pasture herbage mass, litter mass and ground cover were estimated regularly to provide information useful in interpreting runoff generation processes.Total runoff ranged from 6.6 mm at Manilla (0.3% of rainfall) to 185 mm at Nundle (5.7% of rainfall) for different grazing treatments, with the largest runoff event being recorded at Nundle (46.7 mm). Combined site linear regression analyses showed that soil depth, rainfall depth and rainfall duration explained up to 30.3% of the variation in runoff depth. For individual sites, these same variables were also important, accounting for 13.3–33.6% of the variation in runoff depth. Continuous monitoring of stored soil water in relation to these runoff events indicated that the majority of these events were generated by saturation excess, with major events in winter contributing substantially to regional flooding. Long-term simulation modelling (1957–2001) using the SGS Pasture Model indicated that most runoff events were generated in summer, which concurred with the number of flood events recorded at Gunnedah, NSW, downstream of the SGS sites. However, floods also occurred frequently in winter, but the simulations generated few runoff events at that time of the year. These results have important implications for sustainability of grazed pastures and long-term simulation modelling of the hydrological balance of such systems, since runoff generation processes are likely to vary both spatially and temporally for different rainfall events.

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Investigating the effective factors influencing surface runoff generation in urban catchments – A review

10.5004/dwt.2019.24359 ◽

2019 ◽

Vol 164 ◽

pp. 276-292

Author(s):

Abdul Razaq Rezaei ◽

Zubaidah Binti Ismail ◽

Mohammad Hossein Niksokhan ◽

Abu Hanipah Ramli ◽

Lariyah Mohd Sidek ◽

...

Keyword(s):

Surface Runoff ◽

Runoff Generation ◽

Effective Factors ◽

Factors Influencing ◽

Urban Catchments

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Improving the representation of the prairie pothole dynamics in land surface models

10.5194/egusphere-egu2020-3713 ◽

2020 ◽

Author(s):

Mohamed I. Ahmed ◽

Amin Elshorbagy ◽

Alain Pietroniro

Keyword(s):

Surface Runoff ◽

Land Surface ◽

Flow Simulation ◽

Hydrologic Model ◽

Surface Model ◽

Prairie Pothole ◽

Runoff Generation ◽

Dem Resolution ◽

Physically Based ◽

Streamflow Simulation

The hydrography of the prairie basins is complicated by the existence of numerous land depressions, known as prairie potholes, which can retain a substantial amount of surface runoff. Consequently, the runoff production in the prairies follows a fill, spill, and merging mechanism, which results in a dynamic contributing area that makes the streamflow simulation challenging. Existing approaches to represent the potholes&#8217; dynamics, in different hydrological models, use either a lumped or a series of reservoirs that contribute flow after exceeding a certain storage threshold. These approaches are simplified and do not represent the actual dynamics of the potholes nor their spatial water extents. Consequently, these approaches may not be useful in capturing the potholes&#8217; complexities and may not be able to accurately simulate the complex prairie streamflow. This study advances towards more accurate and physically-based streamflow simulation in the prairies by implanting a physically-based runoff generation algorithm (Prairie Region Inundation MApping, PRIMA model) within the MESH land surface model, and is referred to as MESH-PRIMA. PRIMA is a recently developed hydrological routing model that can simulate the lateral movement of water over prairie landscape using topographic data provided via DEMs. In MESH-PRIMA, MESH handles the vertical water balance calculations, whereas PRIMA routes the water and determines the amount of water storage and surface runoff. The streamflow simulations of MESH-PRIMA (using different DEM resolution as a topographic input) and MESH with its existing conceptual pothole dynamics algorithm are tested on a number of pothole-dominated watersheds within Saskatchewan, Canada, and compared against observed flows. MESH-PRIMA provides improved streamflow and peak flow simulation, compared to that of MESH with its conceptual pothole algorithm, based on the metrics evaluated for the simulations. MESH-PRIMA shows potential for simulating the actual pothole water extents when compared against water areas obtained from remote sensing data. The use of different DEM resolution changes the resulting pothole water extent, especially for the small potholes as they are not detected in the coarse DEM. MESH-PRIMA can be considered as a hydraulic-hydrologic model that can be used for better understanding and accurate representation of the complex prairie hydrology.

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Surface Runoff Generation and Soil Loss Under Different Soil and Rainfall Properties in The Uluguru Mountains, Tanzania

Land Degradation and Development ◽

10.1002/ldr.2499 ◽

2016 ◽

Vol 28 (1) ◽

pp. 283-293 ◽

Cited By ~ 18

Author(s):

Tomohiro Nishigaki ◽

Soh Sugihara ◽

Method Kilasara ◽

Shinya Funakawa

Keyword(s):

Surface Runoff ◽

Soil Loss ◽

Runoff Generation ◽

Uluguru Mountains

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Assessment of Precipitation Error Propagation in Multi-Model Global Water Resources Reanalysis

10.5194/hess-2018-434 ◽

2018 ◽

Author(s):

Md Abul Ehsan Bhuiyan ◽

Efthymios I. Nikolopoulos ◽

Emmanouil N. Anagnostou ◽

Clement Albergel ◽

Emanuel Dutra ◽

...

Keyword(s):

Water Resources ◽

Surface Runoff ◽

Land Surface ◽

Runoff Generation ◽

Surface Exchange ◽

Hydrologic Modelling ◽

Study Region ◽

Precipitation Characteristics ◽

Model Structures ◽

Global Water

Abstract. This study focuses on the Iberian Peninsula and investigates the propagation of precipitation uncertainty, and its interaction with hydrologic modelling, in global water resources reanalysis. Analysis is based on ensemble hydrologic simulations for a period spanning 11 years (2000–2010). To simulate the hydrological variables of surface runoff, subsurface runoff, and evapotranspiration, we used four land surface models—JULES (Joint UK Land Environment Simulator), ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems), SURFEX (Surface Externalisée), and HTESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchange over Land)—and one global hydrological model, WaterGAP3 (Water–Global Assessment and Prognosis). Simulations were carried out for five precipitation products—CMORPH, PERSIANN, 3B42 (V7), ECMWF reanalysis, and a machine learning-based blended product. As reference, we used a ground-based observation-driven precipitation dataset, named SAFRAN, available at 5 km/1 h resolution. We present relative performances of hydrologic variables for the different multi-model/multi-forcing scenarios. Overall, results reveal the complexity of the interaction between precipitation characteristics and different modelling schemes and show that uncertainties in the model simulations are attributed to both uncertainty in precipitation forcing and the model structure. Surface runoff is strongly sensitive to precipitation uncertainty and the degree of sensitivity depends significantly on the runoff generation scheme of each model examined. Evapotranspiration fluxes are comparatively less sensitive for this study region. Finally, our results suggest that there is no single model/forcing combination that can outperform all others consistently for all variables examined and thus reinforce the fact that there are significant benefits in exploring different model structures as part of the overall modelling approaches used for water resources applications.

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The effect of the conditions of a landscape on its retention capacity

Slovak Journal of Civil Engineering ◽

10.2478/v10189-010-0005-5 ◽

2010 ◽

Vol 18 (2) ◽

pp. 1-12

Author(s):

K. Vrána ◽

T. Dostál ◽

P. Koudelka ◽

V. David ◽

K. Uuléřová

Keyword(s):

Surface Runoff ◽

Flood Control ◽

Considerable Effect ◽

Control Measures ◽

Flood Events ◽

Flood Wave ◽

Runoff Generation ◽

Retention Capacity ◽

Water Courses ◽

Basic Approaches

The effect of the conditions of a landscape on its retention capacityQuestions related to the occurrence, frequency, intensity, duration, characteristics and causes of floods have been discussed more in recent years. Two basic approaches to flood control often conflict. The first is based on the assumption of the considerable effect of a landscape's retention capacity, which can in fact prevent surface runoff generation and flood formation and can significantly transform flood wave. The second approach asserts that the retention capacity of a landscape is nearly negligible and that the only reliable flood protection can be provided by extending the technical structures of flood control measures mainly and directly on water courses. Two different approaches were applied to assess the effect of landscape conditions and revitalization measures on surface runoff and flood formation within a catchment and floodplain. The conclusion shows that the effect of landscape revitalization is very important, but mainly for low return periods of flood events, while for extreme events, the effect on landscapes and floodplains becomes less important and even negligible.

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Quantitative Assessment of Surface Runoff and Base Flow Response to Multiple Factors in Pengchongjian Small Watershed

Forests ◽

10.3390/f9090553 ◽

2018 ◽

Vol 9 (9) ◽

pp. 553 ◽

Cited By ~ 1

Author(s):

Lei Ouyang ◽

Shiyu Liu ◽

Jingping Ye ◽

Zheng Liu ◽

Fei Sheng ◽

...

Keyword(s):

Surface Runoff ◽

Climatic Factors ◽

Dynamic Change ◽

Vegetation Restoration ◽

Base Flow ◽

Small Watershed ◽

Runoff Generation ◽

Multiple Factors ◽

Precipitation Variation ◽

Annual Scale

Quantifying the impacts of multiple factors on surface runoff and base flow is essential for understanding the mechanism of hydrological response and local water resources management as well as preventing floods and droughts. Despite previous studies on quantitative impacts of multiple factors on runoff, there is still a need for assessment of the influence of these factors on both surface runoff and base flow in different temporal scales at the watershed level. The main objective of this paper was to quantify the influence of precipitation variation, evapotranspiration (ET) and vegetation restoration on surface runoff and base flow using empirical statistics and slope change ratio of cumulative quantities (SCRCQ) methods in Pengchongjian small watershed (116°25′48″–116°27′7″ E, 29°31′44″–29°32′56″ N, 2.9 km2), China. The results indicated that, the contribution rates of precipitation variation, ET and vegetation restoration to surface runoff were 42.1%, 28.5%, 29.4% in spring; 45.0%, 37.1%, 17.9% in summer; 30.1%, 29.4%, 40.5% in autumn; 16.7%, 35.1%, 48.2% in winter; and 35.0%, 38.7%, 26.3% in annual scale, respectively. For base flow they were 33.1%, 41.9%, 25.0% in spring; 39.3%, 51.9%, 8.8% in summer; 40.2%, 38.2%, 21.6% in autumn; 24.3%, 39.4%, 36.3% in winter; and 24.4%, 47.9%, 27.7% in annual scale, respectively. Overall, climatic factors, including precipitation and ET change, affect surface runoff generation the most, while ET affects the dynamic change of annual base flowthe most. This study highlights the importance of optimizing forest management to protect the water resource.

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Surface runoff connectivity across scales: revisiting three simulation studies

10.5194/egusphere-egu21-5004 ◽

2021 ◽

Author(s):

Daniel Caviedes-Voullième ◽

Ilhan Özgen-Xian ◽

Christoph Hinz

Keyword(s):

Water Balance ◽

Surface Runoff ◽

Spatial Scales ◽

Structural Connectivity ◽

Full Description ◽

Runoff Generation ◽

Catchment Scale ◽

Model Quality ◽

Spatiotemporal Model ◽

Hydrological Signatures

Surface runoff (dis)connectivity manifests across scales, spawning from different spatial flow patterns, which are dominated by both topography (structural connectivity) and hydrodynamics (dynamic connectivity). How the connectivity builds and evolves throughout rainfall events is integrated into observable hydrological signatures (namely, hydrographs and water balance).&#160;In this contribution we explore the connectivity properties of runoff generation processes across spatial scales. We revisit three case studies of runoff generation during rainfall, numerically simulated by solving shallow-water equations. This approach provides a full description of the hydrodynamic flow fields, allowing to study both the connectivity properties, as well as the domain-integrated hydrological signatures (namely, hydrographs) that build up in response to flow phenomena.&#160;We discuss and link the runoff generation processes arising from (i) runoff generation at the plot scale (20 m2 at cm resolution) with explicit microtopographies, (ii) runoff generation at the hillslope or first-order catchment scale with overland and (ephemeral) rill flows in the H&#252;hnerwasser experimental catchment (4000 m2 at m resolution), and (iii) runoff generation at the catchment scale in the Lower Triangle catchment (15 km2 at m resolution).The detailed study of runoff generation dynamics highlights the needs to use time-evolving connectivity metrics, which are particularly useful to understand spatiotemporal model output. We computed the number of disconnected flooded clusters (and Euler characteristic) as the main connectivity metric.The results of the three different systems suggest similar qualitative behaviours of connectivity across scales, from plot to catchment scales, and therefore also offer the possible use of connectivity to understand how fluxes are re-scaled across the landscape, and as a multiscale indicator of hydrological function. The relationship between the connectivity response at a given scale (e.g., plot) and the hydrological signature observed at the next larger scale (e.g., hillslope) may lead into a hierarchical relationship of connectivities and signatures, in which the time-continuous nature of the connectivity signal may give rise to non-linear and threshold behaviours in the larger scale signature.&#160;Additionally, in the context of assessing model quality, connectivity is a feature of the natural system which models (and modellers) should strive to ensure. In this sense, we argue that model formulations, meshing (including resolution/topology and preprocessing/smoothing of the terrain model) and parameterisations should be evaluated not only using integrated signatures (e.g., water balance, hydrographs) or point data (water depth, velocities) but also using (dis)connectivity metrics. In this way, it is possible to evaluate to which extent a model and its setup can simulate natural flow paths and landscape functions.

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