Real-Time Operation of River-Reservoir Systems During Flood Conditions Using Optimization-Simulation Model with One- and Two-Dimensional Modeling

abstract: Flooding is a critical issue around the world, and the absence of comprehension of watershed hydrologic reaction results in lack of lead-time for flood forecasting and expensive harm to property and life. It happens when water flows due to extreme rainfall storm, dam breach or snowmelt exceeds the capacity of river system reservoirs and channels. The objective of this research was to develop a methodology for determining a time series operation for releases through control gates of river-reservoir systems during flooding events in a real-time using one- and/or two-dimensional modeling of flows through river-reservoir systems. The optimization-simulation methodology interfaces several simulation-software coupled together with an optimization model solved by genetic algorithm coded in MATLAB. These software include the U.S. Army Corps of Engineers HEC-RAS linked the genetic algorithm in MATLAB to come up with an optimization-simulation model for time series gate openings to control downstream elevations. The model involves using the one- and two-dimensional ability in HEC-RAS to perform hydrodynamic routing with high-resolution raster Digital Elevation Models. Also, the model uses both real-time gridded- and gaged-rainfall data in addition to a model for forecasting future rainfall-data. This new model has been developed to manage reservoir release schedules before, during, and after an extraordinary rainfall event that could cause extreme flooding. Further to observe and control downstream water surface elevations to avoid exceedance of threshold of flood levels in target cells in the downstream area of study, and to minimize the damage and direct effects in both the up and downstream. The application of the complete optimization-simulation model was applied to a portion of the Cumberland River System in Nashville, Tennessee for the flooding event of May 2010. The objective of this application is to demonstrate the applicability of the model for minimizing flood damages for an actual flood event in real-time on an actual river basin. The purpose of the application in a real-time framework would be to minimize the flood damages at Nashville, Tennessee by keeping the flood stages under the 100-year flood stage. This application also compared the three unsteady flow simulation scenarios: one-dimensional, two-dimensional and combined one- and two-dimensional unsteady flow.Dissertation/ThesisDoctoral Dissertation Civil, Environmental and Sustainable Engineering 201

Applying Optimization to Support Adaptive Water Management of Rivers

ABSTRACT: Adaptive water management is a promising management paradigm for rivers that addresses the uncertainty of decision consequences. However, its implementation into current practice is still a challenge. An optimization assessment can be framed within the adaptive management cycle allowing the definition of environmental flows (e-flows) in a suitable format for decision making. In this study, we demonstrate its suitability to mediate the incorporation of e-flows into diversion management planning, fostering the realization of an adaptive management approach. We used the case study of the Pas River, Northern Spain, as the setting for the optimization of surface water diversion. We considered e-flow requirements for three key river biological groups to reflect conditions that promote ecological conservation. By drawing from hydrological scenarios (i.e., dry, normal, and wet), our assessment showed that the overall target water demand can be met, whereas the daily volume of water available for diversion was not constant throughout the year. These results suggest that current the decision making needs to consider the seasonal time frame as the reference temporal scale for objectives adjustment and monitoring. The approach can be transferred to other study areas and can inform decision makers that aim to engage with all the stages of the adaptive water management cycle

Developing SWMMCALPY : an automated, genetic approach to calibrating the storm water management model

Parameter calibration is considered a crucial, albeit arduous, step for reliable performance of the Storm Water Management Model (SWMM) that engineers often undertake manually. This research presents an open-source, automated calibration routine that returns a calibrated model input file to the user. The routine first represents the catchment network as a directed graph object using the NetworkX python package for flexibility in handling real-world observed data availability. Once the calibratable subset of the system is identified, a multi-objective, genetic algorithm (modified Non-dominated Sorting Genetic Algorithm II: NSGA-II) estimates the Pareto front for the objective functions within the feasible performance space. The solutions on this Pareto front represent the optimized parameter sets for matching simulated and observed catchment behavior. A specific solution among this Pareto set can be chosen by assigning weights to the objective functions. This solution is then returned to the user, completing a fully automated process that requires minimal user input and does not require intervention or selections during calibration.Civil, Architectural, and Environmental Engineerin

Structural Best Management Practices (BMPs) and hydrological effects modelling using swat for urban watershed

Orientador: Prof. Dr. Cristovao V.S. FernandesDissertação (mestrado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia de Recursos Hídricos e Ambiental. Defesa : Curitiba, 15/03/2019Inclui referências: p. 128-141Resumo: As Best Management Practices (BMPs) têm sido usadas como solução para mitigação de condições de pós-desenvolvimento em bacias urbanas e rurais. Estes dispositivos regulam vazões e volumes, além de capturar poluentes do escoamento superficial usando vários mecanismos. Estes dispositivos têm sido estudados e seu uso disseminado em vários países. Concomitantemente, o melhoramento de modelos de transporte e destinação de constituintes para investigar os efeitos, algoritmos para otimizar a busca por locais ótimos de instalação e facilitação da avaliação de entradas e saídas trouxe à luz vários desafios no que tange a modelagem dos fenômenos, incluindo a seleção de escalas de dimensão e tempo adequadas à representação dos fenômenos. A revisão de literatura demonstra uma fronteira clara entre usar inputs massivos de dados e computação exaustiva em modelos para descrição detalhada dos processos ou a adoção de abordagens mais simplificadas que capturem áreas maiores a custos menores de levantamento de dados. Neste estudo o Soil and Water Assessment Tool (SWAT) é utilizado como solução harmônica para modelagem em bacias com usos do solo mistos. Para vencer os desafios acima citados, BMPs são tratadas como zonas de recarga, isto é, zonas com Números de Curva (CN) menores. A localização destes dispositivos no modelo é realizada utilizando critérios consolidados de viabilidade através de ferramentas já desenvolvidas. Quatro cenários de redução percentual são utilizados para avaliação das melhoras de fluxo nas escalas da Hydrological Response Unit (HRU), subbacia e curso do rio(reach): 10%, 30%, 50% e 70%. As mudanças foram avaliadas na escala diária e anual, usando aplicações desenvolvidas em Python para automatizar a parametrização do modelo e a entrada e saída de dados. O estudo foi bem-sucedido em conceber a geração de múltiplos cenários, assim como em produzir ferramentas que auxiliem a entrada e saída de dados. Os resultados demonstram que a criação de zonas de recarga é mais eficaz em regiões onde há mais capacidade de retenção do solo. Do contrário, a redução do escoamento superficial tende a chegar em um limite, a partir do qual não há mais roteamento do escoamento superficial. Em HRUs e subbacias onde as condições de solo são favoráveis, a dinâmica de roteamento superficial e subsuperficial é modificada, fazendo com que a recarga dos aquíferos aumente e as recessões sejam mais lentas. Em geral, não são visíveis efeitos na escala da subbacia e no curso principal do rio, uma vez que muito do escoamento superficial é roteado como escoamento lateral ou fluo de subsuperfície. Além disso, a superposição dos efeitos para o resto da bacia é muito pequena na escala diária. Palavras-chave: SWAT. Bacias Urbanas. Python. Best Management Practices Hidrologia.Abstract: Best Management Practice (BMP) devices have been employed as a solution for both agricultural and urban watershed post-development effect mitigation. These devices regulate flow and capture runoff pollutants using various mechanisms. Such devices have been studied and its use disseminated in several countries. Concurrently, the enhancement of pollutant fate and transport models to assess the effects, search for optimal locations and facilitate inputs has brought to light several challenges concerning the modelling of physical phenomena, especially the one related to selecting time and size scales for adequate representation. The literature revision demonstrates that a clear boundary between using massive data inputs and computation-exhaustive models for thorough process description or more simplified approaches that capture larger areas at a more affordable data cost has limited the comprehension and description of BMP hydrological processes at the subbasin and watershed scale. In this study, SWAT is used a harmonic solution for modelling mixed land-use watersheds. To overcome the challenges stated, BMPs are treated as recharge - lower Curve Number (CN) zones, in feasible scenarios generated using an pre-built-tool and consolidated feasibility topographic, hydrological and space-distribution features. Four scenarios were generated: 10, 30, 50 70% CN reductions were tested and evaluated at the daily HRU/subbasin and subbasin yearly average scales, using developed applications for automating the parameter change and Input/output operations. The study was successful in automating the BMP scenario generation and multiple scenario generation as well as output data analysis. Results show that the creation of recharge zones is more effective at regions where more soil storage is available. Otherwise, runoff reduction tends to reach a limit. In HRUs and subbasins where soil conditions are favorable, the entire soil water and groundwater flow dynamics is modified, causing aquifer recharge to increase on average and recessions to be slower. Generally, no effects can be noticed at the subbasin o reach scale, as much of the runoff is also routed either as lateral flow or groundwater flow. The superposition of such effects to the rest of the watershed results in small differences at the daily scale. Keywords: SWAT. Urban watersheds. Python. Best Management Practices. Hydrology

Flood Forecasting Using Machine Learning Methods

This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Wate

Calibrating Shenandoah Watershed SWAT Model Using A Nonlinear Groundwater Algorithm

This study contributes to a project with the Interstate Commission on the Potomac River Basin to build a model of the Potomac watershed using the Soil Water Assessment Tool (SWAT). The 2,937 mi2 Shenandoah watershed represents about 40% of the Potomac Basin by area. The model subdivides the Shenandoah watershed into 28 subwatersheds and 489 hydrologic response units. SWAT's linear-reservoir groundwater algorithm is modified into a new non-linear method. Modeled flows are compared to observations (dating from 1996 to 2006) at 15 USGS stream gages. The model is auto-calibrated using the Parameter Estimation Software (PEST), experimenting with options to improve model performance. The best model results are obtained by applying ordinal weights to the observation groups, decreasing from headwaters to outlet, and pre-calibrating the roughness coefficients using empirical equations. The calibrated model will contribute to understanding hydrological processes and predicting the effects of land use and climate change in the watershed

Rainfall-Runoff Processes in Tropical Urban Environments

Ph.DDOCTOR OF PHILOSOPH

Advanced techniques for solving groundwater and surface water problems in the context of inverse methods and climate change.

[ES] El tema de la investigación se centra en técnicas avanzadas para manejar problemas de aguas subterráneas y superficiales relacionados con métodos inversos y cambio climático. Los filtros de Kalman, con especial atención en Ensemble Smoother with Multiple Data Assimilation (ES-MDA), se analizan y mejoran para la solución de diferentes tipos de problemas inversos. En particular, la principal novedad es la aplicación de estos métodos para la identificación de series temporales. La primera parte de la tesis, luego de la descripción del método, presenta el desarrollo de un software escrito en Python para la aplicación de la metodología propuesta. El software cuenta con un flujo de trabajo flexible que puede adaptarse fácilmente para implementar diferentes variantes del filtro de Kalman y ser aplicado para la solución de varios tipos de problemas. Un paquete de herramientas proporciona varias funcionalidades que permiten de configurar el algoritmo de acuerdo con el problema específico analizado. La primera aplicación se refiere a la solución del problema inverso de flujo en ríos. Este es un procedimiento inverso destinado a estimar el flujo de entrada a un sistema hidráulico en función de información recopilada abajo. El procedimiento se prueba mediante dos ejemplos sintéticos y un estudio de caso real; se investiga el impacto de los tamaños de los conjuntos y la aplicación de técnicas de localización e inflación de covarianzas. Los resultados muestran la capacidad del método propuesto de resolver este tipo de problemas; el rendimiento de ES-MDA mejora, especialmente para tamaños de conjuntos pequeños, cuando se aplican técnicas de inflación y localización de covarianza. La segunda aplicación en el campo de las aguas superficiales se refiere a la calibración de un modelo hidrológico-hidráulico que simula los mecanismos de formación de eventos de inundación. ES-MDA se acopla al modelo numérico de forma paralela para la estimación de los coeficientes de rugosidad e infiltración en base al conocimiento de un hidrograma de flujo en una sección del dominio. Los resultados de dos casos sintéticos y un estudio de caso real demuestran la capacidad del método propuesto para calibrar el modelo hidrológico-hidráulico con un tiempo computacional razonable. En el campo de aguas subterráneas, ES-MDA se aplica por primera vez para identificar simultáneamente la ubicación de la fuente y el historial de liberación de un contaminante en un acuífero a partir de datos de concentración detectados en diferentes puntos del dominio. Se realizaron numerosas pruebas para evaluar la influencia de la distribución espacial y temporal de los datos de concentración, el número del conjunto y el uso de técnicas de localización e inflación; además, se presenta un nuevo procedimiento para realizar una localización iterativa espacio-temporal. La metodología se valida mediante un ejemplo analítico y un estudio de caso que utiliza datos obtenidos en el laboratorio mediante una caja de arena. ES-MDA conduce a una buena estimación de los parámetros investigados; una red de monitoreo bien diseñada y la aplicación de correcciones de covarianza mejoran el rendimiento del método y ayudan a mitigar el posible problema de no unicidad de la solución. Otro propósito de la tesis es investigar el efecto del cambio climático en las aguas subterráneas. Se presenta un modelo simplificado que describe la respuesta de los niveles de agua subterránea a las variables meteorológicas hasta 2100. Es un enfoque estadístico sencillo basado en las correlaciones entre los niveles de agua subterránea y dos índices de sequía que dependen de los datos de precipitación y temperatura. El método se utiliza para evaluar el impacto del cambio climático en los recursos de agua subterránea en un área de estudio ubicada en el norte de Italia utilizando datos históricos y de modelos climáticos regionales. Los resultados m[CA] El tema de la investigació se centra en tècniques avançades per a manejar problemes d'aigües subterrànies i superficials relacionats amb mètodes inversos i canvi climàtic. Els filtres de Kalman, amb especial atenció en Ensemble Smoother with Multiple Data Assimilation (ES-MDA), s'analitzen i milloren per a la solució de diferents tipus de problemes inversos. En particular, la principal novetat és l'aplicació d'aquests mètodes per a la identificació de sèries temporals. La primera part de la tesi presenta el desenvolupament d'un programari escrit en Python per l'aplicació de la metodologia presentada. El programari compta amb un flux de treball flexible que pot adaptar-se fàcilment per a implementar diferents variants del filtre de Kalman i ser aplicat per a la solució de diversos tipus de problemes. Un paquet complementar d'eines proporciona diverses funcionalitats que permeten de configurar l'algorisme d'acord amb el problema específic analitzat. La primera aplicació es un nou enfocament per la solució del problema invers de flux en rius. Aquest és un procediment invers destinat a estimar el flux d'entrada a un sistema hidràulic en funció d'informació recopilada aigües avall. El procediment es prova mitjançant dos exemples sintètics i un estudi de cas real; s'investiga l'impacte de les grandàries dels conjunts i l'aplicació de tècniques de localització i inflació de covariàncies. Els resultats mostren la capacitat del mètode proposat de resoldre aquest tipus de problemes; el rendiment de ES-MDA millora, especialment per a grandàries de conjunts xicotets, quan s'apliquen tècniques d'inflació i localització de covariància. La segona aplicació en el camp de les aigües superficials es refereix al calibratge d'un model hidrològic-hidràulic que simula els mecanismes de formació d'esdeveniments d'inundació a partir de sollicitació hidrometeorológicas i la seua posterior propagació. ES-MDA s'acobla al model numèric de manera paral·lela per l'estimació dels coeficients de rugositat i infiltració sobre la base del coneixement d'un hidrograma de flux en una secció del domini. Els resultats de dos casos sintètics i un estudi de cas real demostren la capacitat del mètode proposat per calibrar el model hidrològic-hidràulic amb un temps computacional raonable. En el camp d'aigües subterrànies, ES-MDA s'aplica per primera vegada per identificar simultàniament la ubicació de la font i l'historial d'alliberament d'un contaminant en un aqüífer a partir d'un conjunt de dades de concentració detectats en diferents punts del domini. Es van realitzar nombroses proves per avaluar la influència de la distribució espacial i temporal de les dades de concentració, el número del conjunt i l'ús de tècniques de localització i inflació; a més, es presenta un nou procediment per realitzar una localització iterativa espaciotemporal. La metodologia es valguda mitjançant un exemple analític i un estudi de cas per al qual s'utilitzen dades obtingudes en el laboratori mitjançant una caixa d'arena. ES-MDA condueix a una bona reconstrucció dels paràmetres investigats; una xarxa de monitoratge ben dissenyada i l'aplicació de correccions de covariància milloren el rendiment del mètode i ajuden a mitigar el possible problema de no unicitat de la solució. Un altre propòsit de la tesi és investigar l'efecte del canvi climàtic en les aigües subterrànies. Es presenta un model simplificat que descriu la resposta dels nivells d'aigua subterrània a les variables meteorològiques fins a 2100. És un enfocament estadístic senzill basat en les correlacions entre els nivells d'aigua subterrània i dos índexs de sequera que depenen de les dades de precipitació i temperatura. El mètode s'utilitza per a avaluar l'impacte del canvi climàtic en els recursos d'aigua subterrània en una àrea d'estudi situada en el nord d'Itàlia utilitzant dades històriques i de models climàtics regionals.[EN] This work focuses on the investigation of advanced techniques to handle groundwater and surface water problems in the framework of inverse methods and climate change. The Ensemble Kalman filter methods, with particular attention to the Ensemble Smoother with Multiple Data Assimilation (ES-MDA), are extensively analyzed and improved for the solution of different types of inverse problems. In particular, the main novelty is the application of these methods for the identification of time series function. In the first part of the thesis, after the description of the ES-MDA method, the development of a Python software package for the application of the proposed methodology is presented. It is designed with a flexible workflow that can be easily adapted to implement different variants of the Ensemble Kalman filter and to be applied for the solution of various types of inverse problems. A complemented tool package provides several functionalities that allow to setup the algorithm configuration suiting the specific analyzed problem. The first novelty application of the ES-MDA method aimed at solving the reverse flow routing problem. The objective of the inverse procedure is the estimation of an unknown inflow hydrograph to a hydraulic system on the basis of information collected downstream and a given forward routing model that relates inflow hydrograph and downstream observations. The procedure is tested by means of two synthetic examples and a real case study; the impact of ensemble sizes and the application of covariance localization and inflation techniques are also investigated. The tests show the capability of the proposed method to solve this type of problem; the performance of ES-MDA improves, especially for small ensemble sizes, when covariance localization and inflation techniques are applied. The second application, in the context of surface water, concerns the calibration of a hydrological-hydraulic model that simulates rainfall-runoff processes. The ES-MDA is coupled with the numerical model by parallel way for the estimation of roughness and infiltration coefficients based on the knowledge of a discharge hydrograph at the basin outlet. The results of two synthetic tests and a real case study demonstrate the capability of the proposed method to calibrate the hydrological-hydraulic model with a reasonable computational time. In the groundwater field, ES-MDA is applied for the first time to simultaneously identify the source location and the release history of a contaminant spill in an aquifer from a sparse set of concentration data collected in few points of the aquifer. The impacts of the concentration sampling scheme, the ensemble size and the use of covariance localization and covariance inflation techniques are tested; furthermore, a new procedure to perform a spatiotemporal iterative localization is presented. The methodology is tested by means of an analytical example and a study case that uses real data collected in a laboratory sandbox. ES-MDA leads to a good estimation of the investigated parameters; a well-designed monitoring network and the use of covariance corrections improve the performance of the method and help to minimize ill-posedness and equifinality. A part of the thesis investigates the impact of climate change on the groundwater availability. A surrogate model that describes the response of groundwater levels to meteorological variables up to 2100 is presented. It is a simple statistical approach based on the correlations between groundwater levels and two drought indices that depend on precipitation and temperature data. The presented method is used to evaluate the impact of climate change on groundwater resources in a study area located in Northern Italy using historical and regional climate model data. The results denote a progressive increase of groundwater droughts in the investigated area.Todaro, V. (2021). Advanced techniques for solving groundwater and surface water problems in the context of inverse methods and climate change [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/166439TESI

Integrated High-Resolution Modeling for Operational Hydrologic Forecasting

Current advances in Earth-sensing technologies, physically-based modeling, and computational processing, offer the promise of a major revolution in hydrologic forecasting—with profound implications for the management of water resources and protection from related disasters. However, access to the necessary capabilities for managing information from heterogeneous sources, and for its deployment in robust-enough modeling engines, remains the province of large governmental agencies. Moreover, even within this type of centralized operations, success is still challenged by the sheer computational complexity associated with overcoming uncertainty in the estimation of parameters and initial conditions in large-scale or high-resolution models. In this dissertation we seek to facilitate the access to hydrometeorological data products from various U.S. agencies and to advanced watershed modeling tools through the implementation of a lightweight GIS-based software package. Accessible data products currently include gauge, radar, and satellite precipitation; stream discharge; distributed soil moisture and snow cover; and multi-resolution weather forecasts. Additionally, we introduce a suite of open-source methods aimed at the efficient parameterization and initialization of complex geophysical models in contexts of high uncertainty, scarce information, and limited computational resources. The developed products in this suite include: 1) model calibration based on state of the art ensemble evolutionary Pareto optimization, 2) automatic parameter estimation boosted through the incorporation of expert criteria, 3) data assimilation that hybridizes particle smoothing and variational strategies, 4) model state compression by means of optimized clustering, 5) high-dimensional stochastic approximation of watershed conditions through a novel lightweight Gaussian graphical model, and 6) simultaneous estimation of model parameters and states for hydrologic forecasting applications. Each of these methods was tested using established distributed physically-based hydrologic modeling engines (VIC and the DHSVM) that were applied to watersheds in the U.S. of different sizes—from a small highly-instrumented catchment in Pennsylvania, to the basin of the Blue River in Oklahoma. A series of experiments was able to demonstrate statistically-significant improvements in the predictive accuracy of the proposed methods in contrast with traditional approaches. Taken together, these accessible and efficient tools can therefore be integrated within various model-based workflows for complex operational applications in water resources and beyond