scholarly journals Formulation of Parsimonious Urban Flash Flood Predictive Model with Inferential Statistics

Mathematics ◽  
2022 ◽  
Vol 10 (2) ◽  
pp. 175
Author(s):  
Lloyd Ling ◽  
Sai Hin Lai ◽  
Zulkifli Yusop ◽  
Ren Jie Chin ◽  
Joan Lucille Ling
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Flash Flood ◽  
Curve Number ◽  
Runoff Coefficient ◽  
Rainfall Runoff ◽  
Inferential Statistics ◽  
Moisture Condition ◽  
Antecedent Moisture ◽  
Runoff Model

The curve number (CN) rainfall–runoff model is widely adopted. However, it had been reported to repeatedly fail in consistently predicting runoff results worldwide. Unlike the existing antecedent moisture condition concept, this study preserved its parsimonious model structure for calibration according to different ground saturation conditions under guidance from inferential statistics. The existing CN model was not statistically significant without calibration. The calibrated model did not rely on the return period data and included rainfall depths less than 25.4 mm to formulate statistically significant urban runoff predictive models, and it derived CN directly. Contrarily, the linear regression runoff model and the asymptotic fitting method failed to model hydrological conditions when runoff coefficient was greater than 50%. Although the land-use and land cover remained the same throughout this study, the calculated CN value of this urban watershed increased from 93.35 to 96.50 as the watershed became more saturated. On average, a 3.4% increase in CN value would affect runoff by 44% (178,000 m3). This proves that the CN value cannot be selected according to the land-use and land cover of the watershed only. Urban flash flood modelling should be formulated with rainfall–runoff data pairs with a runoff coefficient > 50%.

scholarly journals Impacts of Land Use and Land Cover Changes on Peak Discharge and Flow Volume in Kakia and Esamburmbur Sub-Catchments of Narok Town, Kenya

Hydrology ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 82
Author(s):  
Etienne Umukiza ◽  
James M. Raude ◽  
Simon M. Wandera ◽  
Andrea Petroselli ◽  
John M. Gathenya
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Curve Number ◽  
Peak Discharge ◽  
Land Use Land Cover ◽  
Flow Volume ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Event Based ◽  
Runoff Model

Due to population growth and an expanding economy, land use/land cover (LULC) change is continuously intensifying and its effects on floods in Kakia and Esamburmbur sub-catchments in Narok town, Kenya, are increasing. This study was carried out in order to evaluate the influence of LULC changes on peak discharge and flow volume in the aforementioned areas. The Event-Based Approach for Small and Ungauged Basins (EBA4SUB) rainfall–runoff model was used to evaluate the peak discharge and flow volume under different assumed scenarios of LULC that were projected starting from a diachronic analysis of satellite images of 1985 and 2019. EBA4SUB simulation demonstrated how the configuration and composition of LULC affect peak discharge and flow volume in the selected catchments. The results showed that the peak discharge and flow volume are affected by the variation of the Curve Number (CN) value that is dependent on the assumed LULC scenario. The evaluated peak discharge and flow volume for the assumed LULC scenarios can be used by local Municipal bodies to mitigate floods.

scholarly journals Rainfall-Runoff Modeling Using NRCS-CN method and GIS approach

2020 ◽  
Author(s):  
Rekha Verma ◽  
Azhar Husain ◽  
Mohammed Sharif
Keyword(s):  
Hydrological Modeling ◽  
Curve Number ◽  
Geographical Information ◽  
Rainfall Runoff ◽  
Moisture Condition ◽  
Natural Resource Conservation ◽  
Antecedent Moisture ◽  
Natural Resource Conservation Service ◽  
Runoff Modeling ◽  
Runoff Depth

Rainfall-Runoff modeling is a hydrological modeling which is extremely important for water resources planning, development, and management. In this paper, Natural Resource Conservation Service-Curve Number (NRCS-CN) method along with Geographical Information System (GIS) approach was used to evaluate the runoff resulting from the rainfall of four stations, namely, Bilodra, Kathlal, Navavas and Rellawada of Sabarmati River basin. The rainfall data were taken for 10 years (2005-2014). The curve number which is the function of land use, soil and antecedent moisture condition (AMC) was generated in GIS platform. The CN value generated for AMC- I, II and III were 57.29, 75.39 and 87.77 respectively. Using NRCS-CN method, runoff depth was calculated for all the four stations. The runoff depth calculated with respect to the rainfall for Bilodra, Kathlal, Navavas and Rellawada shows a good correlation of 0.96. The computed runoff was compared with the observed runoff which depicted a good correlation of 0.73, 0.70, 0.76 and 0.65 for the four stations. This method results in speedy and precise estimation of runoff from a watershed.

Investigating land use and land cover changes in Dublin, Ireland using Satellite Imagery: A comparative analysis

2020 ◽  
Author(s):  
Bidroha Basu ◽  
Arunima Sarkar Basu ◽  
Srikanta Sannigrahi ◽  
Francesco Pilla
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Population Growth ◽  
Satellite Imagery ◽  
Rainfall Runoff ◽  
Lulc Changes ◽  
The Past ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Over Time

<p>Over the past few decades, there has been over increasing pressure on land due to population growth, urbanization, agriculture expansion and industrialization. The change in land use and land cover (LULC) pattern are highly dependent on human intervention. Deforestation pattern has started due to growth of suburbs, cities, and industrial land. The alarming rate in change of LULC pattern was on a rising trend since 1990s and has been increasing over time. This study focuses on analyzing the changes in LULC pattern in Dublin, Ireland over the past two decades using remotely sensed LANDSAT satellite imagery data, and quantify the effect of LULC change in streamflow simulation in watershed at Dublin by using rainfall-runoff model. Benefit of using remotely sensed image to investigate LULC changes include availability of high-resolution spatial data at free of cost, images captured at high temporal resolution to monitor the changes in LULC during both seasonal and yearly timescale and readily availability of data. The potential classification of landforms has been done by performing both supervised as well as unsupervised classification. The results obtained from the classified images have been compared to google earth images to understand the accuracy of the image classification. The change in LULC can be characterized by changes in building density and urban/artificial area (build up areas increase due to population growth), changes in vegetation area as well as vegetation health, changes in waterbodies and barren land. Furthermore, a set of indices such as vegetation index, building index, water index and drought index were estimated, and their changes were monitored over time. Results of this analysis can be used to understand the driving factors affecting the changes in LULC and to develop mathematical models to predict future changes in landforms. Soil Water Assessment Tool (SWAT) based rainfall-runoff model were used to simulate the changes in runoff due to the LULC changes in watershed over two decades. The developed framework is highly replicable because of the used LANDSAT data and can be applied to generate essential information for conservation and management of green/forest lands, as well as changes in water availability and water stress in the assessed area.</p>

scholarly journals The Hydrologic Role of Urban Green Space in Mitigating Flooding (Luohe, China)

2018 ◽  
Vol 10 (10) ◽  
pp. 3584 ◽  
Author(s):  
Tian Bai ◽  
Audrey Mayer ◽  
William Shuster ◽  
Guohang Tian
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Green Space ◽  
Curve Number ◽  
Central China ◽  
Design Storm ◽  
Antecedent Moisture ◽  
Runoff Reduction ◽  
Urban Catchments ◽  
Infiltration Excess

Even if urban catchments are adequately drained by sewer infrastructures, flooding hotspots develop where ongoing development and poor coordination among utilities conspire with land use and land cover, drainage, and rainfall. We combined spatially explicit land use/land cover data from Luohe City (central China) with soil hydrology (as measured, green space hydraulic conductivity), topography, and observed chronic flooding to analyze the relationships between spatial patterns in pervious surface and flooding. When compared to spatial–structural metrics of land use/cover where flooding was commonly observed, we found that some areas expected to remain dry (given soil and elevation characteristics) still experienced localized flooding, indicating hotspots with overwhelmed sewer infrastructure and a lack of pervious surfaces to effectively infiltrate and drain rainfall. Next, we used curve numbers to represent the composite hydrology of different land use/covers within both chronic flooding and dry (non-flooding) circles of 750 m diameter, and local design storms to determine the anticipated average proportion of runoff. We found that dry circles were more permeable (curve number (mean ± std. error) = 74 ± 2, n = 25) than wetter, flooded circles (curve number = 87 ± 1). Given design storm forcing (20, 50, 100 years’ recurrence interval, and maximum anticipated storm depths), dry points would produce runoff of 26 to 35 percent rainfall, and wet points of 52 to 61 percent of applied rainfall. However, we estimate by simulation that runoff reduction benefits would decline once infiltration-excess (Hortonian) runoff mechanisms activate for storms with precipitation rates in excess of an average of 21 mm/h, contingent on antecedent moisture conditions. Our spatial metrics indicate that larger amounts and patches of dispersed green space mitigate flooding risk, while aggregating buildings (roofs) and green space into larger, separate areas exacerbates risk.

Estimation of Rainfall Runoff using SCS-CN Method with RS and GIS Techniques for Mandavi Basin in YSR Kadapa District of Andhra Pradesh, India

2018 ◽  
Vol 2 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Siddi Raju R. ◽  
Sudarsana Raju G. ◽  
Rajasekhar M.
Keyword(s):  
Curve Number ◽  
Crystalline Rock ◽  
Geographical Information ◽  
Annual Rainfall ◽  
Rainfall Runoff ◽  
Moisture Condition ◽  
Gis Techniques ◽  
Antecedent Moisture ◽  
Rs And Gis ◽  
Wet Condition

The study aims to estimate the surface runoff in the semi-arid crystalline rock terrain of Mandavi basin using Remote Sensing (RS) and Geographical Information System (GIS) techniques. The rainfall is the only source of water in this basin drains off and little amount percolates into the ground. The study area experiences rigorous groundwater scarcity despite having high rainfall -runoff. Consequently, integrated RS and GIS techniques are used for estimation of the runoff. The weighted curve number (CN) is resolute based on AMC-II (Antecedent Moisture Condition) with the combination of HSGs (hydrologic soil groups) and LU/LC (land use and land cover) categories. The outcomes of study showed 52.292 (CNII) of normal condition, 31.506(CNI) of dry condition and 71.583 (CNIII) of wet condition. The ungauged watershed exhibits an annual average of rainfall, runoff, runoff volume and runoff coefficients for 20 years are 688.82 mm, 478.06 mm, 699.75 m3 and 0.69, respectively. The annual rainfall-runoff relationship during 1995 to 2014 is indicating the overall increase in runoff with the rainfall in the study area.

scholarly journals Gis Based SCS - CN Method For Estimating Runoff In Kundahpalam Watershed, Nilgries District, Tamilnadu

2015 ◽  
Vol 19 (1) ◽  
pp. 59-64 ◽  
Author(s):  
Viji Raja
Keyword(s):  
Land Use ◽  
Curve Number ◽  
Annual Runoff ◽  
Annual Rainfall ◽  
Land Use Pattern ◽  
Moisture Condition ◽  
Antecedent Moisture ◽  
Average Annual Runoff ◽  
Distributed Hydrological Models ◽  
Scs Cn

<p>Divination and determination of catchment surface runoff are the most important contestable process of hydrology. Soil Conservation Service - Curve Number (SCS – CN) method is employed to estimate the runoff. It is one of the physical based and spatially distributed hydrological models. In this model, the curve number is a primary factor used for runoff calculation. The selection of curve number is based on the land use pattern and HSG (Hydrological Soil Group) present in the study area. Since the spatial distribution of CN estimation by the conventional way is very difficult and time consuming, the GIS (Geographic Information System) based CN method is generated for Kundapallam watershed. With the combination of land use and HSG the estimated composite CN for AMC (Antecedent Moisture Condition) I, AMC II and AMC III for the entire watershed was about 48, 68 and 83 respectively. The average annual runoff depth estimated by SCS-CN method for the average annual rainfall of 173.5 mm was found to be 72.5 mm. The obtained results were comparable to measured runoff in the watershed.</p><p> </p><p><strong>Resumen</strong></p>La predicción y la determinación del caudal de escorrentía de una cuenca son procesos de amplio debate en la hidrología. El método coeficiente de escurrimiento, del Servicio de Conservación de Suelos (SCS-CN, inglés) fue utilizado en este trabajo para estimar la escorrentía. Este es uno de los modelos hidrológicos basados en conceptos físicos y distribución espacial. En este modelo el coeficiente de escurrimiento es un factor de relevancia para el cálculo de la escorrentía. La selección del coeficiente de escurrimiento está basada en los patrones del uso de la tierra y del Grupo de Suelos Hidrológicos (HSG, inglés) relativos a esta área de estudio. Debido a que la estimación del coeficiente de escurrimiento en la distribución espacial es compleja, para la cuenca Kundapallam se implementó un método a partir de un Sistema de Información Geográfica (GIS, inglés), y basado en el coeficiente de escurrimiento. Con la combinación del uso de suelos y el HSG, la estimación compuesta del coeficiente de escurrimiento para el Antecedente de Condición de Humedad AMCI, AMCII y AMCIII para toda la cuenca fue de 48, 68 y 83. El promedio anual de escorrentía profunda estimada por el método SCS-CN con una media anual de lluvia de 173,5 mm fue de 72,5 mm. Los resultados fueron comparados con la escorrentía medida en la cuenca.

scholarly journals ANÁLISE DAS CARACTERÍSTICAS HIDROLÓGICAS DE TRÊS SUB-BACIAS DO RIO CARAPÁ (CANINDEYÚ, PARAGUAI) EM FUNÇÃO DAS MUDANÇAS DA COBERTURA VEGETAL

FLORESTA ◽  
2011 ◽  
Vol 41 (2) ◽  
Author(s):  
César Daniel Riveros Reys ◽  
Nivaldo Eduardo Rizzi ◽  
Hideo Araki
Keyword(s):  
Land Use ◽  
River Basin ◽  
Forest Cover ◽  
Plant Cover ◽  
Curve Number ◽  
Response Analysis ◽  
Runoff Coefficient ◽  
Antecedent Moisture ◽  
History Of ◽  
Multitemporal Analysis

O objetivo deste trabalho foi analisar o comportamento hidrológico em três sub-bacias da bacia hidrográfica do rio Carapá, localizadas no Departamento de Canindeyú, Paraguai em 1985, 1999 e 2007, através de análise multitemporal do uso do solo e análise da resposta hidrológica pelo método de Curva Número com ênfase no parâmetro de Coeficiente de escoamento superficial (CE). A metodologia de estudo foi dividida em duas etapas: classificação dos usos do solo e análise das mudanças da vegetação nativa e análise das classes geradas com adição de tipologias de solos para gerar os parâmetros hidrológicos nas três condições de umidade antecedente: normal (NII), seco (NI) e próximo da saturação (NIII). Os resultados indicaram diminuição da cobertura florestal nas três sub-bacias. Das três, o coeficiente de escoamento superficial nas três situações de umidade antecedente da sub-bacia 49 no período de 1985 e 1999 foi a mais alta (NI=6,42; NII=30,88; NIII=57,86) e a que indica maior possibilidade de degradação. No período de 2007, o coeficiente de escoamento superficial nas três situações de umidade antecedente da sub-bacia 01 foi a mais alta (NI=17,03; NII=45,18; NIII=69,32), indicando maior possibilidade de degradação na sub-bacia por conta da ação da erosão hídrica.Palavras-chave: Bacia hidrográfica; análise multitemporal; curva número; escoamento superficial. AbstractAnalysis of hydrologic characteristics of three sub-basins of Carapa River basin (Canindeyú, Paraguay) in relation to changes of plant cover. The objective of this study was to analyze the hydrological behavior in three sub-basins of the river basin, Carapa, located in the Department of Canindeyú, Paraguay in 1985, 1999 and 2007 through multitemporal analysis of land use and hydrologic response analysis method Curve Number with emphasis on parameter runoff coefficient (EC). The methodology was divided into two steps: classification of land use and analysis of changes in vegetation and analysis of the generated classes with the addition of soil types to generate the hydrological parameters in the three antecedent moisture conditions: normal (NII) cleaning (NI) and close to saturation (NIII). The results showed decrease in forest cover in the three sub-basins. From the three parameters, the runoff coefficient in three different moisture history of the sub-basin 49 between 1985 and 1999 was the highest (NI = 6.42, NII = 30.88, NIII = 57.86) and indicates a higher possibility of degradation. During 2007, the runoff coefficient in three different moisture history of the sub-basin 01 was the highest (NI = 17.03, NII = 45.18, NIII = 69.32), indicating a greater possibility of degradation the sub-basin due to the action of water erosion.Keywords: Hydrographic basin; multitemporal analysis; curve number; runoff. 

scholarly journals Application of a continuous Rainfall-Runoff model to the basin of Kosynthos river using the hydrological software HEC-HMS

2014 ◽  
Vol 16 (1) ◽  
pp. 188-203 ◽  
Keyword(s):  
Soil Conservation ◽  
Curve Number ◽  
Hydrologic Model ◽  
Army Corps ◽  
Soil Conservation Service ◽  
Rainfall Runoff ◽  
Runoff Hydrograph ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Continuous Rainfall

<div> <h1 style="text-align: justify;"><span style="font-size:11px;"><span style="font-family:arial,helvetica,sans-serif;">In this paper, the application of a continuous rainfall-runoff model to the basin of Kosynthos River (district of Xanthi, Thrace, northeastern Greece), as well as the comparison of the computational runoff results with field discharge measurements are presented. The rainfall losses are estimated by the widely known Soil Conservation Service-Curve Number model, while the transformation of rainfall excess into direct runoff hydrograph is made by using the dimensionless unit hydrograph of Soil Conservation Service. The baseflow is computed by applying an exponential recession model. The routing of the total runoff hydrograph from the outlet of a sub-basin to the outlet of the whole basin is achieved by the Muskingum-Cunge model. The application of this complex hydrologic model was elaborated with the HEC-HMS 3.5 Hydrologic Modeling System of the U.S. Army Corps of Engineers. The results of the comparison between computed and measured discharge values are very satisfactory.</span></span></h1> </div> <p>&nbsp;</p>

ANN-SCS-based hybrid model in conjunction with GCM to evaluate the impact of climate change on the flow scenario of the River Subansiri

2019 ◽  
Vol 11 (4) ◽  
pp. 1150-1164
Author(s):  
Swapnali Barman ◽  
Rajib Kumar Bhattacharjya
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Hybrid Model ◽  
Curve Number ◽  
Future Trend ◽  
Land Use Land Cover ◽  
Ann Model ◽  
Non Linear ◽  
The Future ◽  
The Impact

Abstract The River Subansiri, one of the largest tributaries of the Brahmaputra, makes a significant contribution towards the discharge at its confluence with the Brahmaputra. This study aims to investigate an appropriate model to predict the future flow scenario of the river Subansiri. Two models have been developed. The first model is an artificial neural network (ANN)-based rainfall-runoff model where rainfall has been considered as the input. The future rainfall of the basin is calculated using a multiple non-linear regression-based statistical downscaling technique. The proposed second model is a hybrid model developed using ANN and the Soil Conservation Service (SCS) curve number (CN) method. In this model, both rainfall and land use/land cover have been incorporated as the inputs. The ANN models were run using time series analysis and the method selected is the non-linear autoregressive model with exogenous inputs. Using Sen's slope values, the future trend of rainfall and runoff over the basin have been analyzed. The results showed that the hybrid model outperformed the simple ANN model. The ANN-SCS-based hybrid model has been run for different land use/land cover scenarios to study the future flow scenario of the River Subansiri.

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