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Runoff Prediction in Ungauged Basins
Predicting water runoff in ungauged water catchment areas is vital to practical applications such as the design of drainage infrastructure and flooding defences, runoff forecasting, and for catchment management tasks such as water allocation and climate impact analysis. This full colour book offers an impressive synthesis of decades of international research, forming a holistic approach to catchment hydrology and providing a one-stop resource for hydrologists in both developed and developing countries. Topics include data for runoff regionalisation, the prediction of runoff hydrographs, flow duration curves, flow paths and residence times, annual and seasonal runoff, and floods. Illustrated with many case studies and including a final chapter on recommendations for researchers and practitioners, this book is written by expert authors involved in the prestigious IAHS PUB initiative. It is a key resource for academic researchers and professionals in the fields of hydrology, hydrogeology, ecology, geography, soil science, and environmental and civil engineering.
eBook
Regulation characteristics of underlying surface on runoff regime metrics and their spatial differences in typical urban communities across China
The regulation and spatial differences of urban runoffs are of great concern in contemporary hydrological research. However, owing to a shortage of basic data sources and restrictions on urban hydrological simulation functions, simulating and investigating the regulation mechanism behind rainfall-runoff processes remain significantly challenging. In this study, the Time Variant Gain Model (TVGM), a hydrological nonlinear system model, was extrapolated to the hydrodynamic model of an urban drainage network system by integrating it with the widely used Stormwater Management Model (SWMM) to adequately simulate urban runoff events while considering various underlying surfaces and runoff routing modes, such as surface, drainage network and river runoff, in urban regions (i.e., TVGM-SWMM). Moreover, runoff events were characterized using the following four runoff regime metrics: runoff coefficient, capture ratio of annual runoff volume, standardized flood timescale, and the ratio of occurrence time differences between flow and rainfall peak to event duration (peak flow delay time). The characteristics and spatial differences of urban runoff regulations were investigated, and the key impact factors and their relative contributions were identified using multivariate statistical analyses. Four communities were selected as our study areas, consisting of communities from Beijing, Shenzhen, Wuhan, and Chongqing. Our results showed that the TVGM-SWMM performed considerably better than SWMM alone. The comprehensive simulation accuracy of 60% of the events (12/20) improved by 486%, with the bias improving the most, followed by the efficiency coefficient. Barring the runoff coefficient, significant spatial differences were identified at the patch scale for the runoff regime metrics, with differences of 0.43, 0.22, and 0.16 (
p
<0.05). The key impact factors were the pipe length (
r
=0.51) in the drainage network system and the forest area ratios (
r
=0.56), sponge measures (
r
=0.52), grassland (
r
=0.48), and impervious surface (
r
=0.46) in the underlying surfaces. The contributions of the drainage network system and the underlying surfaces were 4.27% and 37.83%, respectively. Regulation in the Beijing community, dominated by grassland regulation, delayed and reduced the peak flow and total runoff volume. In the Shenzhen community, sharp and thin runoff events were mainly generated by impervious surfaces and were not adequately regulated. Forest regulation was the dominant regulation type in the Wuhan community, which reduced the total runoff volume and delayed the peak flow. Waterbody regulation was the primary regulation type in the Chongqing community, which reduced the total runoff volume and peak flow. This study aims to introduce a comprehensive theoretical and technical assessment of the hydrological effects of urbanization and the performance of sponge city construction and provide a reference for urban hydrological model improvements in China.
Journal Article
Surface and subsurface runoff generation processes in a poorly gauged tropical coastal catchment : a study from Nicaragua : dissertation
Hydrological research in humid tropics is particularly challenging because of highly variable hydrological conditions and high socio-economic stresses caused by rapid population increase, as is the case of Nicaragua. The objective of this research is to understand the surface and subsurface runoff generation processes in a poorly gauged coastal catchment in Nicaragua under variable humid tropical conditions. Specifically, it focuses on identifying geomorphological and hydro-climatic controls on catchment response at different spatio-temporal scales and studies the link between hydrological processes and ecosystem conditions.
Book
Using Graywater and Stormwater to Enhance Local Water Supplies
Chronic and episodic water shortages are becoming common in many regions of the United States, and population growth in water-scarce regions further compounds the challenges. Increasingly, alternative water sources such as graywater-untreated wastewater that does not include water from the toilet but generally includes water from bathroom sinks, showers, bathtubs, clothes washers, and laundry sinks- and stormwater-water from rainfall or snow that can be measured downstream in a pipe, culvert, or stream shortly after the precipitation event-are being viewed as resources to supplement scarce water supplies rather than as waste to be discharged as rapidly as possible. Graywater and stormwater can serve a range of non-potable uses, including irrigation, toilet flushing, washing, and cooling, although treatment may be needed. Stormwater may also be used to recharge groundwater, which may ultimately be tapped for potable use. In addition to providing additional sources of local water supply, harvesting stormwater has many potential benefits, including energy savings, pollution prevention, and reducing the impacts of urban development on urban streams. Similarly, the reuse of graywater can enhance water supply reliability and extend the capacity of existing wastewater systems in growing cities.
Despite the benefits of using local alternative water sources to address water demands, many questions remain that have limited the broader application of graywater and stormwater capture and use. In particular, limited information is available on the costs, benefits, and risks of these projects, and beyond the simplest applications many state and local public health agencies have not developed regulatory frameworks for full use of these local water resources.
To address these issues, Using Graywater and Stormwater to Enhance Local Water Supplies analyzes the risks, costs, and benefits on various uses of graywater and stormwater. This report examines technical, economic, regulatory, and social issues associated with graywater and stormwater capture for a range of uses, including non-potable urban uses, irrigation, and groundwater recharge. Using Graywater and Stormwater to Enhance Local Water Supplies considers the quality and suitability of water for reuse, treatment and storage technologies, and human health and environmental risks of water reuse. The findings and recommendations of this report will be valuable for water managers, citizens of states under a current drought, and local and state health and environmental agencies.
eBook
Using plants for stormwater management : a green infrastructure guide for the Gulf South
The subtropical climate of the Gulf South supports a varied abundance of flora, and this diversity is sustained by the ample amount of rainwater that characterizes the region. Managing rainwater in a planned environment and mitigating its effect on human habitation can test the skills of even the most seasoned landscape architect or designer. That challenge has never been more acute as increased human demand for natural resources compels professionals and home gardeners alike to seek out sustainable ecological solutions. In this guidebook, Dana Nunez Brown details ways to manage each drop of rainwater where it falls, using a cost-effective and environmentally sensitive approach. Under natural conditions, rainfall primarily percolates into the ground and flows as groundwater until it is absorbed by trees and other vegetation, after which it is evaporated into the atmosphere and the cycle starts anew. Brown identifies plants and techniques that leverage this natural process in order to filter, clean, and slow runoff, a practice known as Low Impact Development. Using Plants for Stormwater Management presents the native ecological communities and plant species of the Gulf South in easy-to-follow sections and diagrams. Information ranging from the productiveness of root structures and the compatibility of plants with local soils to the optimal elevation of specific vegetation and the average dimensions of foliage is represented by graphic icons for quick and easy identification. An accessible and essential resource, this book gives both novices and experts the know-how to harness rainfall and create beautiful, ecologically functioning landscapes. -- Provided by publisher.
Book
Comprehensive Review: Advancements in Rainfall-Runoff Modelling for Flood Mitigation
Runoff plays an essential part in the hydrological cycle, as it regulates the quantity of water which flows into streams and returns surplus water into the oceans. Runoff modelling may assist in understanding, controlling, and monitoring the quality and amount of water resources. The aim of this article is to discuss various categories of rainfall–runoff models, recent developments, and challenges of rainfall–runoff models in flood prediction in the modern era. Rainfall–runoff models are classified into conceptual, empirical, and physical process-based models depending upon the framework and spatial processing of their algorithms. Well-known runoff models which belong to these categories include the Soil Conservation Service Curve Number (SCS-CN) model, Storm Water Management model (SWMM), Hydrologiska Byråns Vattenbalansavdelning (HBV) model, Soil and Water Assessment Tool (SWAT) model, and the Variable Infiltration Capacity (VIC) model, etc. In addition, the data-driven models such as Adaptive Neuro Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN), Deep Neural Network (DNN), and Support Vector Machine (SVM) have proven to be better performance solutions in runoff modelling and flood prediction in recent decades. The data-driven models detect the best relationship based on the input data series and the output in order to model the runoff process. Finally, the strengths and downsides of the outlined models in terms of understanding variation in runoff modelling and flood prediction were discussed. The findings of this comprehensive study suggested that hybrid models for runoff modeling and flood prediction should be developed by combining the strengths of traditional models and machine learning methods. This article suggests future research initiatives that could help with filling existing gaps in rainfall–runoff research and will also assist hydrological scientists in selecting appropriate rainfall–runoff models for flood prediction and mitigation based on their benefits and drawbacks.
Journal Article
Benchmarking data-driven rainfall–runoff models in Great Britain: a comparison of long short-term memory (LSTM)-based models with four lumped conceptual models
Long short-term memory (LSTM) models are recurrent neural networks from the field of deep learning (DL) which have shown promise for time series modelling, especially in conditions when data are abundant. Previous studies have demonstrated the applicability of LSTM-based models for rainfall–runoff modelling; however, LSTMs have not been tested on catchments in Great Britain (GB). Moreover, opportunities exist to use spatial and seasonal patterns in model performances to improve our understanding of hydrological processes and to examine the advantages and disadvantages of LSTM-based models for hydrological simulation. By training two LSTM architectures across a large sample of 669 catchments in GB, we demonstrate that the LSTM and the Entity Aware LSTM (EA LSTM) models simulate discharge with median Nash–Sutcliffe efficiency (NSE) scores of 0.88 and 0.86 respectively. We find that the LSTM-based models outperform a suite of benchmark conceptual models, suggesting an opportunity to use additional data to refine conceptual models. In summary, the LSTM-based models show the largest performance improvements in the north-east of Scotland and in south-east of England. The south-east of England remained difficult to model, however, in part due to the inability of the LSTMs configured in this study to learn groundwater processes, human abstractions and complex percolation properties from the hydro-meteorological variables typically employed for hydrological modelling.
Journal Article