Applicability of open rainfall data to event-scale urban rainfall-runoff modelling

Niemi, Tero; Warsta, Lassi; Taka, Maija; Hickman, Brandon; Pulkkinen, Seppo; Krebs, Gerald; Moisseev, Dmitri; Koivusalo, Harri; Kokkonen, Teemu

doi:10.1016/j.jhydrol.2017.01.056

Cited by 24 publications

(19 citation statements)

References 44 publications

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“…In the literature, one can find a considerable amount of papers dedicated to this subject e.g., [3,[14][15][16]. Despite of all the challenges and limitations related to radar measurements of rainfall, the radar estimates are frequently used in the rainfall-runoff modeling (e.g., [8,9,19,[51][52][53]).…”

Section: Radar Rainfall Estimatesmentioning

confidence: 99%

Inter-Comparison of Rain-Gauge, Radar, and Satellite (IMERG GPM) Precipitation Estimates Performance for Rainfall-Runoff Modeling in a Mountainous Catchment in Poland

Gilewski

Nawalany

2018

Water

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Precipitation is one of the essential variables in rainfall-runoff modeling. For hydrological purposes, the most commonly used data sources of precipitation are rain gauges and weather radars. Recently, multi-satellite precipitation estimates have gained importance thanks to the emergence of Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG GPM), a successor of a very successful Tropical Rainfall Measuring Mission (TRMM) mission which has been providing high-quality precipitation estimates for almost two decades. Hydrological modeling of mountainous catchment requires reliable precipitation inputs in both time and space as the hydrological response of such a catchment is very quick. This paper presents an inter-comparison of event-based rainfall-runoff simulations using precipitation data originating from three different sources. For semi-distributed modeling of discharge in the mountainous river, the Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS) is applied. The model was calibrated and validated for the period 2014–2016 using measurement data from the Upper Skawa catchment a small mountainous catchment in southern Poland. The performance of the model was assessed using the Nash–Sutcliffe efficiency coefficient (NSE), Pearson’s correlation coefficient (r), Percent bias (PBias) and Relative peak flow difference (rPFD). The results show that for the event-based modeling adjusted radar rainfall estimates and IMERG GPM satellite precipitation estimates are the most reliable precipitation data sources. For each source of the precipitation data the model was calibrated separately as the spatial and temporal distributions of rainfall significantly impact the estimated values of model parameters. It has been found that the applied Soil Conservation Service (SCS) Curve Number loss method performs best for flood events having a unimodal time distribution. The analysis of the simulation time-steps indicates that time aggregation of precipitation data from 1 to 2 h (not exceeding the response time of the catchment) provide a significant improvement of flow simulation results for all the models while further aggregation, up to 4 h, seems to be valuable only for model based on rain gauge precipitation data.

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Section: Radar Rainfall Estimatesmentioning

confidence: 99%

Inter-Comparison of Rain-Gauge, Radar, and Satellite (IMERG GPM) Precipitation Estimates Performance for Rainfall-Runoff Modeling in a Mountainous Catchment in Poland

Gilewski

Nawalany

2018

Water

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“…Changes in soil cover have been addressed in several studies on the effects of urbanization (Suriya & Mudgal, 2012;Zope et al, 2016;Niemi et al, 2017), evolution of anthropogenic occupation in watersheds (Fang et al, 2012;Sanyal et al, 2014;Rodriguez-Lloveras et al, 2015;Napoli et al, 2017;Welde & Gebremariam, 2017), and influence of vegetation cover (Marques et al, 2007;Mu et al, 2015;Zhang et al, 2015;Silva et al, 2016;Yu et al, 2016) on the balance between the elements of the hydrological cycle. However, few studies have sought to investigate the effects of the seasonality of agricultural soil use on runoff Engenharia Agrícola, Jaboticabal, v.39, n.5, p.592-599, sep./oct.…”

Section: Introductionmentioning

confidence: 99%

Seasonal Dynamics of Agricultural Soil Cover in Runoff Generation

et al. 2019

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Seasonal changes in agricultural soil use due to agroclimatic conditions affect the water cycle in watersheds. This study aimed to understand the temporal variation of runoff inherent to the seasonal occupation dynamics of the agricultural soil in the basin that drains the upper valley of the Marrecas River, upstream of the urban perimeter of Francisco Beltrão, PR. The effects of runoff were verified through flow peaks simulated by the HEC-HMS model in twelve monthly soil use scenarios, under seven precipitation return periods. The results indicated a strong relationship between bare soil and flow peaks, temporally delimiting April and March as the largest runoff generators and January and August as the smallest ones. The ratio quantified by rates of increase in flow peaks ranging from 0.78 to 1.64 m 3 s −1 per km 2 of bare soil. In addition, the survey of historical precipitation data also warns of the generation of large runoff volumes in October. Therefore, the strong correlation between the increase in flow peaks and occupation by bare soil can be quantified with good precision, but it is also necessary to consider historical precipitation records to understand the temporal distribution of runoff and flood risks.

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“…The aim of the research was to study means of assessing multifunctionality during the landscape architectural design process. A widely used SWMM model was parameterized for assessing the impacts of SUDS scenarios with respect to the water quantity criterion [44][45][46][47][48][49]. Likewise, data-driven ANFIS model was used for assessing the impacts of SUDS scenarios with consideration of the water quality criterion [52].…”

Section: Discussionmentioning

confidence: 99%

“…This study models the current state and the three designed SUDS scenarios using the stormwater management model (SWMM) (EPA, Washington, DC, USA [44]) to assess the impact of SUDS on water quantity and quality. SWMM [44][45][46][47][48][49] is a widely used tool for single event and long-term simulations of different water balance components, such as surface runoff, flood volume, discharge, and losses in urban areas. Losses refer to water lost from the system in the form of evaporation and infiltration.…”

Section: Water Quantity and Quality Assessment Through Modelingmentioning

confidence: 99%

Can We Really Have It All?—Designing Multifunctionality with Sustainable Urban Drainage System Elements

et al. 2019

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Multifunctionality is seen as one of the key benefits delivered by sustainable urban drainage systems (SUDS). It has been promoted by both scientific research and practical guidelines. However, interrelations between different benefits are vaguely defined, thus highlighting a lack of knowledge on ways they could be promoted in the actual design process. In this research, multifunctionality has been studied with the help of scenario analysis. Three stormwater scenarios involving different range of SUDS elements have been designed for the case area of Kirstinpuisto in the city of Turku, Finland. Thereafter, the alternative design scenarios have been assessed with four criteria related to multifunctionality (water quantity, water quality, amenity, and biodiversity). The results showed that multifunctionality could be analyzed in the design phase itself, and thus provided knowingly. However, assessing amenity and biodiversity values is more complex and in addition, we still lack proper methods. As the four criteria have mutual interconnections, multifunctionality should be considered during the landscape architectural design, or else we could likely lose some benefits related to multifunctionality. This reinforces emerging understanding that an interdisciplinary approach is needed to combine ecological comprehension together with the system thinking into SUDS design, locating them not as individual elements or as a part of the treatment train, but in connection with wider social ecological framework of urban landscape.

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Applicability of open rainfall data to event-scale urban rainfall-runoff modelling

Cited by 24 publications

References 44 publications

Inter-Comparison of Rain-Gauge, Radar, and Satellite (IMERG GPM) Precipitation Estimates Performance for Rainfall-Runoff Modeling in a Mountainous Catchment in Poland

Inter-Comparison of Rain-Gauge, Radar, and Satellite (IMERG GPM) Precipitation Estimates Performance for Rainfall-Runoff Modeling in a Mountainous Catchment in Poland

Seasonal Dynamics of Agricultural Soil Cover in Runoff Generation

Can We Really Have It All?—Designing Multifunctionality with Sustainable Urban Drainage System Elements

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