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.

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%.

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.

scholarly journals Computation of Runoff by SCS-CN Method from micro watersheds of Urmodi basin in Maharashtra state using RS and GIS

Agropedology ◽  
2019 ◽  
Vol 27 (2) ◽  
Author(s):  
S.B. Nandgude ◽  
◽  
G.S. Jadhav ◽  
S.S. Shinde ◽  
D.M. Mahale ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Water Conservation ◽  
Surface Runoff ◽  
Daily Rainfall ◽  
Curve Number ◽  
Rainfall Data ◽  
Land Use Land Cover ◽  
Daily Rainfall Data

Flood is a natural or manmade phenomenon and timely and accurate forecasting of flood is very important. However forecasting of flood is a difficult task due to influence of rainfall-runoff process which depends on various factors. Estimation of surface runoff in a watershed is based on the rate of precipitation and discharge at the outlet. In this study, runoff from micro watersheds of Urmodi basin in Maharashtra state was computed by Soil Conservation Service-Curve Number method using remote sensing and Geographic Information System (GIS) techniques. Various thematic maps such as soil map, land use/land cover, stream order, slope etc. were prepared using remote sensing and GIS. Daily rainfall data was used for determining runoff. Antecedent moisture conditions were determined from daily rainfall data and for different CNs with the help of combined land use land cover and hydrologic soil group map in GIS environment. Results showed that the highest runoff for Bharatgaon and Nagthane micro watersheds was 46.20 mm and 54 mm respectively. Total runoff depth for the year 2014 was computed as 215.05 mm for Bharatgaon micro watershed and 277.68 mm for Nagthane micro watershed. Different soil and water conservation measures and water harvesting structures were recommended to control soil erosion and to harness the surface runoff.

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 Recording Urban Land Dynamic and Its Effects during 2000–2019 at 15-m Resolution by Cloud Computing with Landsat Series

2020 ◽  
Vol 12 (15) ◽  
pp. 2451
Author(s):  
Yulin Dong ◽  
Zhibin Ren ◽  
Yao Fu ◽  
Zhenghong Miao ◽  
Ran Yang ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
High Resolution ◽  
Land Cover ◽  
Urban Development ◽  
Green Space ◽  
Urban Expansion ◽  
Sustainable Urban Development ◽  
Landsat Images ◽  
Land Types

Cities, the core of the global climate change and economic development, are high impact land cover land use change (LCLUC) hotspots. Comprehensive records of land cover land use dynamics in urban regions are essential for strategic climate change adaption and mitigation and sustainable urban development. This study aims to develop a Google Earth Engine (GEE) application for high-resolution (15-m) urban LCLUC mapping with a novel classification scheme using pan-sharpened Landsat images. With this approach, we quantified the annual LCLUC in Changchun, China, from 2000 to 2019, and detected the abrupt changes (turning points of LCLUC). Ancillary data on social-economic status were used to provide insights on potential drivers of LCLUC by examining their correlation with change rate. We also examined the impacts of LCLUC on environment, specifically air pollution. Using this approach, we can classify annual LCLUC in Changchun with high accuracy (all above 0.91). The change detection based on the high-resolution wall-to-wall maps show intensive urban expansion with the compromise of cropland from 2000 to 2019. We also found the growth of green space in urban regions as the result of green space development and management in recent years. The changing rate of different land types were the largest in the early years of the observation period. Turning points of land types were primarily observed in 2009 and 2010. Further analysis showed that economic and industry development and population migration collectively drove the urban expansion in Changchun. Increasing built-up areas could slow wind velocity and air exchange, and ultimately led to the accumulation of PM2.5. Our implement of pan-sharpened Landsat images facilitates the wall-to-wall mapping of temporal land dynamics at high spatial resolution. The primary use of GEE for mapping urban land makes it replicable and transferable by other users. This approach is a first crucial step towards understanding the drivers of change and supporting better decision-making for sustainable urban development and climate change mitigation.

scholarly journals Quantification and monetary valuation of urban ecosystem services in Munich, Germany

2015 ◽  
Vol 59 (3) ◽  
Author(s):  
Tim Aevermann ◽  
Jürgen Schmude
Keyword(s):  
Ecosystem Services ◽  
Land Cover ◽  
Urban Areas ◽  
Green Space ◽  
Local Population ◽  
Urban Green Space ◽  
Green Spaces ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Runoff Reduction

AbstractUrban green spaces provide ecosystem services that can be used by the local population. The valuation of these ecosystem services in urban areas gives information for stakeholders and decision-makers to improve urban planning processes. In addition, this information can be used to provide a better understanding of how urban green spaces should be managed. In this study, we quantify and monetize four ecosystem services (carbon sequestration and storage, air pollution removal, runoff reduction, groundwater recharge) provided by the urban green space of Schlosspark Nymphenburg in Munich, Germany. We classify four different land cover types (tree, grass/herbaceous, water, impervious) to calculate different amounts of ecosystem services according to the land cover type. In addition, we quantify the maintenance costs which this urban green space causes to the city of Munich. The interpretation, communication and risks of valuations studies are discussed.

scholarly journals Runoff changes in areas differing in land-use in the blanice river basin - application of the deterministic model

2009 ◽  
Vol 57 (3) ◽  
pp. 154-161 ◽  
Author(s):  
Michal Jeníček
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Deterministic Model ◽  
Initial Conditions ◽  
Hydrological Regime ◽  
Curve Number ◽  
Hydrologic Modelling ◽  
Lumped Model ◽  
Runoff Changes

Runoff changes in areas differing in land-use in the blanice river basin - application of the deterministic modelThe aim of this article is to present partial results of more extensive research which is focused on using different methods for runoff computation in areas differing in land use. With the help of the deterministic lumped model HEC-HMS (Hydrologic Engineering Center - Hydrologic Modelling System) several simulations of r noff changes by different basin conditions were carried out. The Blanice River basin in the Šumava Mts. was chosen as an experimental catchment in its closure profile in Podedvory (gauge station, area 209.6 km2). For assessment of land cover changes impact on hydrological regime four scenarios were carried out - 10, 20, 50 and 100-year 1-day probability precipitation in combination with different initial conditions (soil saturation). These scenarios were applied to the stage of the land cover in the year 1992 and 2000 (based on the CORINE Landcover database). The method SCS CN (Soil Conservation Service Curve Number) was applied as the main model technique.

scholarly journals A 30 m resolution dataset of China's urban impervious surface area and green space, 2000–2018

2021 ◽  
Vol 13 (1) ◽  
pp. 63-82
Author(s):  
Wenhui Kuang ◽  
Shu Zhang ◽  
Xiaoyong Li ◽  
Dengsheng Lu
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Green Space ◽  
Impervious Surface ◽  
Urban Land ◽  
Google Earth ◽  
Single Type ◽  
National Scale ◽  
Urban Impervious Surface ◽  
Urban Land Cover

Abstract. Accurate and timely maps of urban underlying land properties at the national scale are of significance in improving habitat environment and achieving sustainable development goals. Urban impervious surface (UIS) and urban green space (UGS) are two core components for characterizing urban underlying environments. However, the UIS and UGS are often mosaicked in the urban landscape with complex structures and composites. The “hard classification” or binary single type cannot be used effectively to delineate spatially explicit urban land surface property. Although six mainstream datasets on global or national urban land use and land cover products with a 30 m spatial resolution have been developed, they only provide the binary pattern or dynamic of a single urban land type, which cannot effectively delineate the quantitative components or structure of intra-urban land cover. Here we propose a new mapping strategy to acquire the multitemporal and fractional information of the essential urban land cover types at a national scale through synergizing the advantage of both big data processing and human interpretation with the aid of geoknowledge. Firstly, the vector polygons of urban boundaries in 2000, 2005, 2010, 2015 and 2018 were extracted from China's Land Use/cover Dataset (CLUD) derived from Landsat images. Secondly, the national settlement and vegetation percentages were retrieved using a sub-pixel decomposition method through a random forest algorithm using the Google Earth Engine (GEE) platform. Finally, the products of China's UIS and UGS fractions (CLUD-Urban) at a 30 m resolution were developed in 2000, 2005, 2010, 2015 and 2018. We also compared our products with six existing mainstream datasets in terms of quality and accuracy. The assessment results showed that the CLUD-Urban product has higher accuracies in urban-boundary and urban-expansion detection than other products and in addition that the accurate UIS and UGS fractions were developed in each period. The overall accuracy of urban boundaries in 2000–2018 are over 92.65 %; and the correlation coefficient (R) and root mean square errors (RMSEs) of UIS and UGS fractions are 0.91 and 0.10 (UIS) and 0.89 and 0.11 (UGS), respectively. Our result indicates that 71 % of pixels of urban land were mosaicked by the UIS and UGS within cities in 2018; a single UIS classification may highly increase the mapping uncertainty. The high spatial heterogeneity of urban underlying covers was exhibited with average fractions of 68.21 % for UIS and 22.30 % for UGS in 2018 at a national scale. The UIS and UGS increased unprecedentedly with annual rates of 1605.56 and 627.78 km2 yr−1 in 2000–2018, driven by fast urbanization. The CLUD-Urban mapping can fill the knowledge gap in understanding impacts of the UIS and UGS patterns on ecosystem services and habitat environments and is valuable for detecting the hotspots of waterlogging and improving urban greening for planning and management practices. The datasets can be downloaded from https://doi.org/10.5281/zenodo.4034161 (Kuang et al., 2020a).

scholarly journals POTENSI REDUKSI LIMPASAN PERMUKAAN DENGAN METODE SOIL CONSERVATION SERVICE - CURVE NUMBER DI KELURAHAN RAWA BUNTU

2021 ◽  
Vol 1 (2) ◽  
pp. 51
Author(s):  
Steffany Trifena ◽  
Dwi Prabowo
Keyword(s):  
Soil Conservation ◽  
Green Space ◽  
Curve Number ◽  
Soil Conservation Service ◽  
Rainfall Runoff ◽  
Total Rainfall ◽  
Runoff Reduction ◽  
Rainwater Runoff ◽  
Service Curve

<em><span lang="EN-US">Development in Rawa Buntu Subdistrict caused land use change and made green space  area  in  Rawa  Buntu  Subdistrict  decreased,  so  it  could  cause  flood.  This research  was  conducted  to  know  the  potential  of  rainwater  runoff  reduction  in each type of land cover in Rawa Buntu Subdistrict to serve as the basis for better planning in the future. The Soil Conservation Service - Curve Number (SCS-CN) method  is  used  to  calculate  the  total  rainfall  runoff  that  can  be  reduced  and  to know  the  role  of  green  space  in  reducing  rainwater  runoff.  The  result  of  the research shows that residential area dominates Rawa Buntu Subdistrict about 65% and  green  space  is  only  about  18%.  The  volume  of  rainfall  runoff  that  can  be reduced  each  month  on  AMC  I,  AMC  II  and  AMC  III  is  74,4MGal,  37,8MGal and  17,9MGal  with  green  space  contribution  of  27%,  31,2%  and  36,4%  of  the total rainfall runoff that can be reduced for each AMC condition.</span></em>

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. 

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