scholarly journals Toward an operational tool to simulate green roof hydrological impact at the basin scale: a new version of the distributed rainfall–runoff model Multi-Hydro

2016 ◽  
Vol 74 (8) ◽  
pp. 1845-1854 ◽  
Author(s):  
Pierre-Antoine Versini ◽  
Auguste Gires ◽  
Ioulia Tchinguirinskaia ◽  
Daniel Schertzer
Keyword(s):  
Positive Impact ◽  
Green Roof ◽  
Green Roofs ◽  
Peak Discharge ◽  
Rainfall Runoff ◽  
Runoff Volume ◽  
Basin Scale ◽  
Wide Range ◽  
Rainfall Runoff Model ◽  
Runoff Model

Currently widespread in new urban projects, green roofs have shown a positive impact on urban runoff at the building scale: decrease and slow-down of the peak discharge, and decrease of runoff volume. The present work aims to study their possible impact at the catchment scale, more compatible with stormwater management issues. For this purpose, a specific module dedicated to simulating the hydrological behaviour of a green roof has been developed in the distributed rainfall–runoff model (Multi-Hydro). It has been applied on a French urban catchment where most of the building roofs are flat and assumed to accept the implementation of a green roof. Catchment responses to several rainfall events covering a wide range of meteorological situations have been simulated. The simulation results show green roofs can significantly reduce runoff volume and the magnitude of peak discharge (up to 80%) depending on the rainfall event and initial saturation of the substrate. Additional tests have been made to assess the susceptibility of this response regarding both spatial distributions of green roofs and precipitation. It appears that the total area of greened roofs is more important than their locations. On the other hand, peak discharge reduction seems to be clearly dependent on spatial distribution of precipitation.

scholarly journals A comparison between natural forests and reforested lands in terms of runoff generation potential and hydrologic response (case study: Kasilian Watershed)

2012 ◽  
Vol 7 (No. 4) ◽  
pp. 166-173 ◽  
Author(s):  
E.H. Gholzom ◽  
V. Gholami
Keyword(s):  
Slope Aspect ◽  
Vegetation Density ◽  
Rainfall Runoff ◽  
Natural Forests ◽  
Runoff Generation ◽  
Mazandaran Province ◽  
Northern Iran ◽  
Runoff Volume ◽  
Rainfall Runoff Model ◽  
Runoff Model

Afforested lands are different from natural forests in terms of hydrologic conditions, runoff generation potential, and sediment generation rate. These differences emerge due to changes in soil structure and vegetation density, litter amount, trees heights, and so on. In this study, a comparison has been made between natural forests and afforested lands in Kasilian – a watershed located in Mazandaran province, Northern Iran. To achieve this purpose, harmonious units have been defined by overlay analysis of these layers in GIS environment: slope, aspect, Digital Elevation Model (DEM) and soil. Then, the location of couple plots was defined by field studies in the harmonious units. The plot locations were selected in a way that runoff generation was a function of tree species and tree conditions, assuming that rainfall intensity is equal in all areas. Initial loss and runoff volume were measured in even plots after rainfall. Then, the initial loss parameter in a rainfall-runoff model was applied to compare runoff volume and peak discharge in the afforested lands and natural forests. The rainfall-runoff model was presented using GIS and HEC-HMS model. The results showed that reforested lands have lower infiltration, lower initial loss, and higher runoff due to lower density, canopy, litter, and soil compaction. Furthermore, the runoff generation potential of reforested lands is several times higher than that of natural forests.

scholarly journals Hydrological modeling using Effective Rainfall routed by the Muskingum method (ERM)

2013 ◽  
Vol 15 (4) ◽  
pp. 1437-1455 ◽  
Author(s):  
M. Baymani-Nezhad ◽  
D. Han
Keyword(s):  
Hydrological Modeling ◽  
Effective Rainfall ◽  
Rainfall Runoff ◽  
Optimization Scheme ◽  
Calibration And Validation ◽  
Wide Range ◽  
Muskingum Method ◽  
Rainfall Runoff Model ◽  
Main Components ◽  
Runoff Model

This paper introduces a new rainfall runoff model called ERM (Effective Rainfall routed by Muskingum method), which has been developed based on the popular IHACRES model. The IHACRES model consists of two main components to transfer rainfall to effective rainfall and then to streamflow. The second component of the IHACRES model is a linear unit hydrograph which has been replaced by the classic and well-known Muskingum method in the ERM model. With the effective rainfall by the first component of the IHACRES model, the Muskingum method is used to estimate the quick flow and slow flow separately. Two different sets of input data (temperature or evapotranspiration, rainfall and observed streamflow) and genetic algorithm (GA) as an optimization scheme have been selected to compare the performance of IHACRES and ERM models in calibration and validation. By testing the models in three different catchments, it is found that the ERM model has better performance over the IHACRES model across all three catchments in both calibration and validation. Further studies are needed to apply the ERM on a wide range of catchments to find its strengths and weaknesses.

Towards a generic rainfall-runoff model for green roofs

2010 ◽  
Vol 62 (4) ◽  
pp. 898-905 ◽  
Author(s):  
H. Kasmin ◽  
V. R. Stovin ◽  
E. A. Hathway
Keyword(s):  
Green Roofs ◽  
Storm Event ◽  
Rainfall Runoff ◽  
Retention Capacity ◽  
Continuous Simulation ◽  
Moisture Storage ◽  
Substrate Moisture ◽  
Rainfall Runoff Model ◽  
Stormwater Retention ◽  
Runoff Model

A simple conceptual model for green roof hydrological processes is shown to reproduce monitored data, both during a storm event, and over a longer continuous simulation period. The model comprises a substrate moisture storage component and a transient storage component. Storage within the substrate represents the roof's overall stormwater retention capacity (or initial losses). Following a storm event the retention capacity is restored by evapotranspiration (ET). However, standard methods for quantifying ET do not exist. Monthly ET values are identified using four different approaches: analysis of storm event antecedent dry weather period and initial losses data; calibration of the ET parameter in a continuous simulation model; use of the Thornthwaite ET formula; and direct laboratory measurement of evaporation. There appears to be potential to adapt the Thornthwaite ET formula to provide monthly ET estimates from local temperature data. The development of a standardized laboratory test for ET will enable differences resulting from substrate characteristics to be quantified.

scholarly journals Inferring the flood frequency distribution for an ungauged basin using a spatially distributed rainfall-runoff model

2008 ◽  
Vol 5 (1) ◽  
pp. 1-26 ◽  
Author(s):  
G. Moretti ◽  
A. Montanari
Keyword(s):  
Frequency Distribution ◽  
River Flow ◽  
Spatial Scales ◽  
Flood Frequency ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Wide Range ◽  
Spatially Distributed ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract. The estimation of the peak river flow for ungauged river sections is a topical issue in applied hydrology. Spatially distributed rainfall-runoff models can be a useful tool to this end, since they are potentially able to simulate the river flow at any location of the watershed drainage network. However, it is not fully clear to what extent these models can provide reliable simulations over a wide range of spatial scales. This issue is investigated here by applying a spatially distributed, continuous simulation rainfall-runoff model to infer the flood frequency distribution of the Riarbero Torrent. This is an ungauged mountain creek located in northern Italy, whose drainage area is 17 km2. The results were checked by using estimates of the peak river flow obtained by applying a classical procedure based on hydrological similarity principles. The analysis highlights interesting perspectives for the application of spatially distributed models to ungauged catchments.

scholarly journals Assessment of an ensemble seasonal streamflow forecasting system for Australia

2017 ◽  
Vol 21 (12) ◽  
pp. 6007-6030 ◽  
Author(s):  
James C. Bennett ◽  
Quan J. Wang ◽  
David E. Robertson ◽  
Andrew Schepen ◽  
Ming Li ◽  
...  
Keyword(s):  
Error Model ◽  
Forecast Skill ◽  
Lead Times ◽  
Rainfall Runoff ◽  
Australian Continent ◽  
Wide Range ◽  
Streamflow Forecasts ◽  
Forecasting System ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract. Despite an increasing availability of skilful long-range streamflow forecasts, many water agencies still rely on simple resampled historical inflow sequences (stochastic scenarios) to plan operations over the coming year. We assess a recently developed forecasting system called forecast guided stochastic scenarios (FoGSS) as a skilful alternative to standard stochastic scenarios for the Australian continent. FoGSS uses climate forecasts from a coupled ocean–land–atmosphere prediction system, post-processed with the method of calibration, bridging and merging. Ensemble rainfall forecasts force a monthly rainfall–runoff model, while a staged hydrological error model quantifies and propagates hydrological forecast uncertainty through forecast lead times. FoGSS is able to generate ensemble streamflow forecasts in the form of monthly time series to a 12-month forecast horizon. FoGSS is tested on 63 Australian catchments that cover a wide range of climates, including 21 ephemeral rivers. In all perennial and many ephemeral catchments, FoGSS provides an effective alternative to resampled historical inflow sequences. FoGSS generally produces skilful forecasts at shorter lead times ( <  4 months), and transits to climatology-like forecasts at longer lead times. Forecasts are generally reliable and unbiased. However, FoGSS does not perform well in very dry catchments (catchments that experience zero flows more than half the time in some months), sometimes producing strongly negative forecast skill and poor reliability. We attempt to improve forecasts through the use of (i) ESP rainfall forcings, (ii) different rainfall–runoff models, and (iii) a Bayesian prior to encourage the error model to return climatology forecasts in months when the rainfall–runoff model performs poorly. Of these, the use of the prior offers the clearest benefit in very dry catchments, where it moderates strongly negative forecast skill and reduces bias in some instances. However, the prior does not remedy poor reliability in very dry catchments. Overall, FoGSS is an attractive alternative to historical inflow sequences in all but the driest catchments. We discuss ways in which forecast reliability in very dry catchments could be improved in future work.

scholarly journals The Impact of the Variability of Precipitation and Temperatures on the Efficiency of a Conceptual Rainfall-Runoff Model

2016 ◽  
Vol 24 (4) ◽  
pp. 1-7 ◽  
Author(s):  
P. Sleziak ◽  
J. Szolgay ◽  
K. Hlavčová ◽  
J. Parajka
Keyword(s):  
Hydrological Model ◽  
Differential Evolution Algorithm ◽  
Rainfall Runoff ◽  
University Of Technology ◽  
Wide Range ◽  
Evolution Algorithm ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
The Relationship ◽  
Runoff Model

AbstractThe main objective of the paper is to understand how the model’s efficiency and the selected climatic indicators are related. The hydrological model applied in this study is a conceptual rainfall-runoff model (the TUW model), which was developed at the Vienna University of Technology. This model was calibrated over three different periods between 1981-2010 in three groups of Austrian catchments (snow, runoff, and soil catchments), which represent a wide range of the hydroclimatic conditions of Austria. The model’s calibration was performed using a differential evolution algorithm (Deoptim). As an objective function, we used a combination of the Nash-Sutcliffe coefficient (NSE) and the logarithmic Nash-Sutcliffe coefficient (logNSE). The model’s efficiency was evaluated by Volume error (VE). Subsequently, we evaluated the relationship between the model’s efficiency (VE) and changes in the climatic indicators (precipitation ΔP, air temperature ΔT). The implications of findings are discussed in the conclusion.

scholarly journals Inferring the flood frequency distribution for an ungauged basin using a spatially distributed rainfall-runoff model

2008 ◽  
Vol 12 (4) ◽  
pp. 1141-1152 ◽  
Author(s):  
G. Moretti ◽  
A. Montanari
Keyword(s):  
Frequency Distribution ◽  
River Flow ◽  
Spatial Scales ◽  
Flood Frequency ◽  
Rainfall Runoff ◽  
River Flows ◽  
Wide Range ◽  
Spatially Distributed ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract. The estimation of the peak river flow for ungauged river sections is a topical issue in applied hydrology. Spatially distributed rainfall-runoff models can be a useful tool to this end, since they are potentially able to simulate the river flow at any location of the watershed drainage network. However, it is not fully clear to what extent these models can provide reliable simulations over a wide range of spatial scales. This issue is investigated here by applying a spatially distributed, continuous simulation rainfall-runoff model to infer the flood frequency distribution of the Riarbero River. This is an ungauged mountain creek located in northern Italy, whose drainage area is 17 km2. The hydrological model is first calibrated by using a 1-year record of hourly meteorological data and river flows observed at the outlet of the 1294 km2 wide Secchia River basin, of which the Riarbero is a tributary. The model is then validated by performing a 100-year long simulation of synthetic river flow data, which allowed us to compare the simulated and observed flood frequency distributions at the Secchia River outlet and the internal cross river section of Cavola Bridge, where the basin area is 337 km2. Finally, another simulation of hourly river flows was performed by referring to the outlet of the Riarbero River, therefore allowing us to estimate the related flood frequency distribution. The results were validated by using estimates of peak river flow obtained by applying hydrological similarity principles and a regional method. The results show that the flood flow estimated through the application of the distributed model is consistent with the estimate provided by the regional procedure as well as the behaviors of the river banks. Conversely, the method based on hydrological similarity delivers an estimate that seems to be not as reliable. The analysis highlights interesting perspectives for the application of spatially distributed models to ungauged catchments.

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