Adaptive forecast of multi-month lake level elevations

The early and precise prediction of the water levels in lakes is a major concern for public authorities. Such predictions describe the evolution of the water levels and are essential for appropriate flood control measures. In this paper, a new ARMAX-type model is developed to predict, months in advance, the monthly fluctuations of the water level of Lake Erie. The predictive variables used in the model are the past monthly water levels of Lakes Erie, Superior, and Michigan–Huron along with the estimated response times between water flow entries and exits. Two scenarios are compared. The first scenario is based on the ordinary least squares (OLS) technique in order to identify the parameters of the ARMAX-type model, to filter measurement and model noises, using the ARMAX Kalman predictor (AKP), and to optimize predictions. In this scenario, the model parameters remain unchanged throughout the simulation. The second scenario is based on the mutually interactive state parameter (MISP) technique in order to readjust the parameters of the model at each time step and to filter measurement and modelling noises through the Kalman predictor. In this scenario, the parameters of the model change with time. The analysis shows that the MISP–AKP framework has a slightly higher Nash coefficient than the OLS–AKP framework for the first month. In subsequent months, however, the quality of the predictions based on the OLS–AKP technique improves significantly. This observation also applies to the persistence and extrapolation coefficients as well as to the sample autocorrelation functions for the residuals of the Lake Erie water level forecast. It was therefore decided to apply the MISP–AKP technique to obtain the first prediction of the Lake Erie level, and the OLS–AKP technique to compute subsequent predictions. Key words: adaptive, forecast, Kalman's filter, lake levels, MISP algorithm, Great Lakes.

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Optimal Operation of Floodwater Resources Utilization of Lakes in South-to-North Water Transfer Eastern Route Project

Sustainability ◽

10.3390/su13094857 ◽

2021 ◽

Vol 13 (9) ◽

pp. 4857

Author(s):

Zitong Yang ◽

Xianfeng Huang ◽

Jiao Liu ◽

Guohua Fang

Keyword(s):

Water Level ◽

Resource Utilization ◽

Flood Control ◽

Optimal Operation ◽

Water Transfer ◽

Water Levels ◽

Reservoir Storage ◽

Flood Season ◽

Hongze Lake ◽

North Water

In order to meet the demand of emergency water supply in the northern region without affecting normal water transfer, considering the use of the existing South-to-North Water Transfer eastern route project to explore the potential of floodwater resource utilization in the flood season of Hongze Lake and Luoma Lake in Jiangsu Province, this paper carried out relevant optimal operating research. First, the hydraulic linkages between the lakes were generalized, then the water resources allocation mode and the scale of existing projects were clarified. After that, the actual available amount of flood resources in the lakes was evaluated. The average annual available floodwater resources in 2003–2017 was 1.49 billion m3, and the maximum available capacity was 30.84 billion m3. Then, using the floodwater resource utilization method of multi period flood limited water levels, the research period was divided into the main flood season (15 July to 15 August) and the later flood season (16 August to 10 September, 11 September to 30 September) by the Systematic Clustering Analysis method. After the flood control calculation, the limited water level of Hongze Lake in the later flood season can be raised from 12.5 m to 13.0 m, and the capacity of reservoir storage can increase to 696 million m3. The limited water level of Luoma Lake can be raised from 22.5 m to 23.0 m (16 August to 10 September), 23.5 m (11 September to 30 September), and the capacity of reservoir storage can increase from 150 to 300 million m3. Finally, establishing the floodwater resource optimization model of the lake group with the goals of maximizing the floodwater transfer amount and minimizing the flood control risk rate, the optimal water allocation scheme is obtained through the optimization algorithm.

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Research and Application of Key Technologies for Dynamic Control of Reservoir Water Level in Flood Season

Water ◽

10.3390/w13243576 ◽

2021 ◽

Vol 13 (24) ◽

pp. 3576

Author(s):

Jun Zhang ◽

Yaowu Min ◽

Baofei Feng ◽

Weixin Duan

Keyword(s):

Water Supply ◽

Water Level ◽

Real Time ◽

Flood Control ◽

Dynamic Control ◽

Water Levels ◽

Reservoir Water ◽

Reservoir Water Level ◽

Danjiangkou Reservoir ◽

Flood Season

In today’s reservoir operation study, it is urgent to solve the issues on improving flood resource utilization, maximizing reservoir impoundment, and guaranteeing water supply through real-time regulation optimization under the premise of ensuring flood control safety and taking risks properly. Based on previous studies, the key real-time operation technologies for dynamic control of reservoir water levels in flood season are summarized. The Danjiangkou Reservoir was taken as an example, the division of flood stages, reservoir water level requirements for improving water supply guarantee, dynamic control indexes of reservoir water level for beneficial use in stages during the flood season, and flood control dispatching indexes are proposed. Moreover, a practicable real-time flood forecast operation scheme for Danjiangkou Reservoir was compiled. Its application in 2017 indicated that the established scheme can provide strong technical support to ensure the overall benefits of Danjiangkou Reservoir, including flood control, water supply, and power generation.

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Assimilation of Piezometric Data to Calibrate Parsimonious Daily Hydrological Models

Water ◽

10.3390/w13172342 ◽

2021 ◽

Vol 13 (17) ◽

pp. 2342

Author(s):

Axel Flinck ◽

Nathalie Folton ◽

Patrick Arnaud

Keyword(s):

Time Series ◽

River Flow ◽

Hydrological Model ◽

Water Levels ◽

Model Parameters ◽

Rainfall Time Series ◽

Time Step ◽

Processing Methods ◽

Analysis System ◽

Set Up

Low water levels are a seasonal phenomenon, which can be long, short, and more or less intense, affecting entire watercourses. This phenomenon has become a concern for many countries who seek better understanding of the processes that affect it and learn how to optimally manage water resources (pumping, irrigation). Consequently, a lumped rainfall model at daily time step (GR) has been defined, calibrated, and regionalised over French territories. The input data come from SAFRAN, the distributed mesoscale atmospheric analysis system, which provides daily solid and liquid precipitation and temperature data throughout the French territory. This model could be improved, in particular to more accurately simulate the hydrological response of watersheds interacting with groundwater. The idea is to use piezometric data from the ADES bank, available in France, and to use it for the calibration phase of the hydrological model. The analysis was carried out across ten French catchments that are representative of various hydrometeorological behaviours and are located in a diverse hydrogeological context. Each catchment must be represented by a piezometer that closely represents the main aquifer that interacts with the basin. This piezometer is located on part of the watershed that is most covered in terms of its drainage network, and closest to its outlet. Different signal processing methods are used to characterise the relationship between the fluctuation of river flow, piezometric levels and rainfall time series. Potential processing methods will be carried out in the temporal domain. To quantify groundwater table inertia and that of the catchment area, correlograms were calculated from daily chronicles of flows and piezometric levels. A cross-correlatory analysis was set up to see, in more detail, the correlations between the flow rates (especially base flows) and piezometric level time series. This type of analysis makes it possible to study relationships between various observations, and tests were carried out to take this information into account during the phase of the calibration of hydrological model parameters. These different analyses will hopefully help us to use piezometric data to consolidate the quality and robustness of the modelling.

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Assessing the impact of the development of an urban district on shallow groundwater using the integrated urban hydrological model URBS

10.5194/egusphere-egu2020-10436 ◽

2020 ◽

Author(s):

emmanuel berthier ◽

jérémie sage ◽

emmanuel dumont ◽

marie-laure mosini ◽

fabrice rodriguez ◽

...

Keyword(s):

Water Table ◽

Water Levels ◽

Integrated Modelling ◽

Model Parameters ◽

Good Representation ◽

Surprising Result ◽

Time Step ◽

Urban District ◽

The Impact ◽

Underground Constructions

The urbanisation leads to modifications in the water budget, not only at the surface but in groundwater as well. Few urban modelling studies deal with this topic, due to the lack of appropriate models. The URBS (Urban Runoff Branching Structure) model has been developed since several decades to simulate water transfers at the scale of an urban district. An integrated modelling approach is deliberately adopted to account for the numerous elements that influence urban hydrology: the spatial distribution of the sealed surfaces, interactions between the urban soil and water networks or underground, sustainable drainage systems&#8230;. In URBS, the spatial discretization of a catchment is based on Urban Hydrologic Elements (UHE) constituted by cadastral parcels and the adjacent streets, connected to the drainage network. URBS is able to perform continuous and long-period simulations (typically several years) of water fluxes in urban districts for small time-steps (typically few-minutes), with rainfall and potential evapotranspiration as input data.The URBS model is adopted to study the hydrological impact of the Moulon district layout, a 200 ha development operation of the Paris-Saclay Cluster (currently underway). The project should result in an increase of sealed surfaces from 14% to 35% and a densification of underground constructions such as networks and basements. A shallow unconfined aquifer extends on the whole area. The fluctuations of ground-water levels have been monitored at an hourly time-step with 8 piezometers since 2012. Water-table levels exhibit significant variations, with near-saturation levels during winter and several meters depths during summer, although the piezometers do not all exhibit the same dynamics.A calibration of the URBS model is first conducted for a 2-year period using only piezometric data and no flowrate data. The calibration is solely performed for the parameters influencing the soil compartment: soil permeability and parameters of the sewer infiltration process. Model performances are rather satisfactory with good representation of the observed levels for several piezometers, despite some difficulties for two piezometers exhibiting atypical variations. Once the URBS model is calibrated for the initial situation, simulations are conducted for the project layout (accounting for land-use modification and underground constructions) so as to evaluate the hydrological impacts of the development. Simulation results suggest that an increase of water table levels might be expected after the development of the district (this somehow surprising result may partly originate from the decrease of evapotranspiration fluxes associated with the increased of sealed surfaces).The analysis of these first simulations also suggests that large uncertainties might be expected regarding the water levels computed by URBS. A simplified uncertainty analysis (based on Monte-Carlo simulations) is thus conducted to evaluate and distinguish uncertainties associated with model parameters and the total uncertainties in model outputs. While the results clearly evidence the importance of total uncertainties (although the uncertainties due to the model parameters remain low), they also confirm that groundwater depths could be reduced by the construction of the Moulon district.

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Assimilation of probabilistic flood maps from SAR data into a coupled hydrologic–hydraulic forecasting model: a proof of concept

Hydrology and Earth System Sciences ◽

10.5194/hess-25-4081-2021 ◽

2021 ◽

Vol 25 (7) ◽

pp. 4081-4097

Author(s):

Concetta Di Mauro ◽

Renaud Hostache ◽

Patrick Matgen ◽

Ramona Pelich ◽

Marco Chini ◽

...

Keyword(s):

Standard Method ◽

Initial Conditions ◽

Model Simulation ◽

Water Levels ◽

Forecasting Model ◽

Model Parameters ◽

Time Step ◽

Sar Data ◽

Assimilation Time ◽

Flood Maps

Abstract. Coupled hydrologic and hydraulic models represent powerful tools for simulating streamflow and water levels along the riverbed and in the floodplain. However, input data, model parameters, initial conditions, and model structure represent sources of uncertainty that affect the reliability and accuracy of flood forecasts. Assimilation of satellite-based synthetic aperture radar (SAR) observations into a flood forecasting model is generally used to reduce such uncertainties. In this context, we have evaluated how sequential assimilation of flood extent derived from SAR data can help improve flood forecasts. In particular, we carried out twin experiments based on a synthetically generated dataset with controlled uncertainty. To this end, two assimilation methods are explored and compared: the sequential importance sampling method (standard method) and its enhanced method where a tempering coefficient is used to inflate the posterior probability (adapted method) and reduce degeneracy. The experimental results show that the assimilation of SAR probabilistic flood maps significantly improves the predictions of streamflow and water elevation, thereby confirming the effectiveness of the data assimilation framework. In addition, the assimilation method significantly reduces the spatially averaged root mean square error of water levels with respect to the case without assimilation. The critical success index of predicted flood extent maps is significantly increased by the assimilation. While the standard method proves to be more accurate in estimating the water levels and streamflow at the assimilation time step, the adapted method enables a more persistent improvement of the forecasts. However, although the use of a tempering coefficient reduces the degeneracy problem, the accuracy of model simulation is lower than that of the standard method at the assimilation time step.

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SLOPE STABILITY ASSESSMENT OF THE UPSTREAM SLOPE OF THE DRY MOUNTAIN FLOOD CONTROL RESERVOIR DURING THE FLOOD

Problems of Water supply Sewerage and Hydraulic ◽

10.32347/2524-0021.2021.37.4-12 ◽

2021 ◽

pp. 4-12

Author(s):

Svitlana Velychko ◽

Olena Dupliak ◽

Tetiana Kurbanova

Keyword(s):

Slope Stability ◽

Water Level ◽

Flood Control ◽

Limit Equilibrium ◽

High Water ◽

Limit Equilibrium Method ◽

Water Levels ◽

The Body ◽

Stability Assessment ◽

Upstream Slope

The flood control is one of the priority goal for successful economic activity on the areas that are periodically suffer from floods. Such areas are the mountainous regions of the Ukrainian Carpathian Mountains. Floods on the mountain rivers are repeated several times each year, and are characterized by the sudden water level rise with almost the same rapid decrease of the water level. Active flood protection measures include dry mountain flood control reservoirs, the principle of which is to transform part of the flood runoff and to accumulate water for the short time in the the artificial reservoir, with followed rapid emptying to the minimum level. The complex hydraulic regime is formed in the body of the dam which forms the flood control reservoir during the flood, that is different from the operation of the water permanent reservoir. The design of the flood control structures is car-ried out in accordance with Ukrainian building codes for the construction of the water reservoirs with constant water level, and require testing the stability of the downstream slope for the maximum water levels under steady state seepage conditions and assessment the upstream slope stability during the water level decreasing from the maximum level calculated in the steady state condition, these calculations do not correspond to the real seepage processes in the body of the dam of the dry flood control reservoir. Therefore, the purpose of this work is to determine the necessary boundary conditions of the flood control reservoir operation and upstream slope stability assessment by the limit equilibrium method. In the article the operation of the dry mountain flood control reservoir was analysed and found that the dam was characterized by two states: dry reservoir with water minimum water level and variable position of the seepage curve in the core and the upstream prism during the flood. The main factors influencing the upstream slope stability are the physical and mechanical properties of the soil, the laying of the slope, the period of time when the high-water level is maintained and the intensity of water level dropping. The upstream slope stability was evaluated by the Morgenstern & Price and Ordinary methods on the Slope/w software package. After the first 25 hours of the flood (period of high-water levels and the next water level dropping) the Safety Factor evaluated by limit equilibrium methods began to decrease, and reached the minimum value during the greatest seepage curve gradients at the time between 45 and 50 hours. Slope stability calculations by the limit equilibrium method were compared with the results of calculations performed by the SRM method, the values of the Safety Factor and the way of their change during the flood evaluated by Ordinary and SRM methods almost coincide, which indicates the reliability of the results obtained by different methods of slope stability analysis

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Groundwater modelling for time periods of up to hundreds of thousands of years.

10.5194/egusphere-egu2020-5177 ◽

2020 ◽

Author(s):

Gerrit H. de Rooij ◽

Thomas Mueller

Keyword(s):

Surface Water ◽

Water Level ◽

Coastal Plain ◽

Land Surface ◽

Hydraulic Head ◽

Water Levels ◽

Analytical Models ◽

Time Interval ◽

Mountain Range ◽

Time Step

Occasionally, there is an interest in groundwater flows over many millennia. The input parameter requirement of numerical groundwater flow models and their calculation times limit their usefulness for such studies.Analytical models require considerable simplifications of the properties and geometry of aquifers and of the forcings. On the other hand, they do not appear to have an inherent limitation on the duration of the simulated period. The simplest models have explicit solutions, meaning that the hydraulic head at a given time and location can be calculated directly, without the need to incrementally iterate through the entire preceding time period like their numerical counterparts.We developed an analytical solution for a simple aquifer geometry: a strip aquifer between a no flow boundary and a body of surface water with a prescribed water level. This simplicity permitted flexible forcings: The non-uniform initial hydraulic head in the aquifer is arbitrary and the surface water level can vary arbitrarily with time. Aquifer recharge must be uniform in space but can also vary arbitrarily with time.We also developed a modification that verifies after prescribed and constant time intervals if the hydraulic head is such that the land surface is covered with water. This excess water then infiltrates in areas where the groundwater level is below the surface and the remainder is discharged into the surface water. The hydraulic head across the aquifer is modified accordingly and used as the initial condition for the next time interval. This modification models the development of a river network during dry periods. The increased flexibility of the model comes at the price of the need to go through the entire simulation period one time step at a time. For very long time records, these intervals will typically be one year.Given the uncertainty of the aquifer parameters and the forcings, the models are expected to be used in a stochastic framework. We are therefore working on a shell that accepts multiple values for each parameter as well as multiple scenarios of surface water levels and groundwater recharge rates, along with an estimate of their probabilities. The shell will generate all possible resulting combinations, the number of which can easily exceed 10000, then runs the model for each combination, and computes statistics of the average hydraulic head and the aquifer discharge into the surface water at user-specified times.A case study will tell if this endeavor is viable. We will model the aquifer below the mountain range north of Salalah in Oman, which separates the desert of the Arabian Peninsula from the coastal plain at its southern shore. Rainfall estimates from the isotopic composition of stalactites in the area indicate distinct dry and wet periods in the past 300 000 years. In combination with estimated sea level fluctuations over that period, this provides an interesting combination of forcings. We examine the dynamics of the total amount of water stored in the aquifer, and of the outflow of water from the aquifer into the coastal plain.

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Towards automatic calibration of 2-D flood propagation models

Hydrology and Earth System Sciences ◽

10.5194/hess-14-911-2010 ◽

2010 ◽

Vol 14 (6) ◽

pp. 911-924 ◽

Cited By ~ 24

Author(s):

P. Fabio ◽

G. T. Aronica ◽

H. Apel

Keyword(s):

Model Calibration ◽

Degrees Of Freedom ◽

Flood Control ◽

Flood Hazard ◽

Element Model ◽

Water Levels ◽

Control Measures ◽

Automatic Calibration ◽

Calibration Data ◽

Model Setup

Abstract. Hydraulic models for flood propagation description are an essential tool in many fields and are used, for example, for flood hazard and risk assessments, evaluation of flood control measures, etc. Nowadays there are many models of different complexity regarding the mathematical foundation and spatial dimensions available, and most of them are comparatively easy to operate due to sophisticated tools for model setup and control. However, the calibration of these models is still underdeveloped in contrast to other models like e.g. hydrological models or models used in ecosystem analysis. This has two primary reasons: first, lack of relevant data against which the models can be calibrated, because flood events are very rarely monitored due to the disturbances inflicted by them and the lack of appropriate measuring equipment in place. Second, 2-D models are computationally very demanding and therefore the use of available sophisticated automatic calibration procedures is restricted in many cases. This study takes a well documented flood event in August 2002 at the Mulde River in Germany as an example and investigates the most appropriate calibration strategy for a simplified 2-D hyperbolic finite element model. The model independent optimiser PEST, that enables automatic calibrations without changing model code, is used and the model is calibrated against over 380 surveyed maximum water levels. The application of the parallel version of the optimiser showed that (a) it is possible to use automatic calibration in combination of 2-D hydraulic model, and (b) equifinality of model parameterisation can also be caused by a too large number of degrees of freedom in the calibration data in contrast to a too simple model setup. In order to improve model calibration and reduce equifinality, a method was developed to identify calibration data, resp. model setup with likely errors that obstruct model calibration.

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Analytical approach for determining the mean water level profile in an estuary with substantial fresh water discharge

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-12-8381-2015 ◽

2015 ◽

Vol 12 (8) ◽

pp. 8381-8417 ◽

Cited By ~ 3

Author(s):

H. Cai ◽

H. H. G. Savenije ◽

C. Jiang ◽

L. Zhao ◽

Q. Yang

Keyword(s):

Water Level ◽

Fresh Water ◽

Flood Control ◽

Analytical Approach ◽

Water Discharge ◽

Water Levels ◽

Wide Range ◽

Mean Water Level ◽

The Mean ◽

Fresh Water Discharge

Abstract. Although modestly, the mean water level in estuaries rises in landward direction induced by a combination of the salinity gradient, the tidal asymmetry, and the backwater effect. The water level slope is increased by the fresh water discharge. However, the interactions between tide and river flow and their individual contributions to the rise of the mean water level along the estuary are not yet completely understood. In this study, we adopt an analytical approach to describe the tidal wave propagation under the influence of fresh water discharge, in which the friction term is approximated by a Chebyshev polynomials approach. The analytical model is used to quantify the contributions made by tide, river, and tide–river interaction to the water level slope along the estuary. Subsequently, the method is applied to the Yangtze estuary under a wide range of river discharge conditions and the influence of tidal amplitude and fresh water discharge on the longitudinal variation of mean water level is explored. The proposed method is particularly useful for accurately predicting water levels and the frequency of extreme high water, relevant for water management and flood control.

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Machine Learning-Based Water Level Prediction in Lake Erie

Water ◽

10.3390/w12102654 ◽

2020 ◽

Vol 12 (10) ◽

pp. 2654

Author(s):

Qi Wang ◽

Song Wang

Keyword(s):

Machine Learning ◽

Water Level ◽

Lake Erie ◽

Water Resource Management ◽

Predictive Accuracy ◽

Meteorological Data ◽

Water Levels ◽

Paper Machine ◽

K Nearest Neighbor ◽

Time Saving

Predicting water levels of Lake Erie is important in water resource management as well as navigation since water level significantly impacts cargo transport options as well as personal choices of recreational activities. In this paper, machine learning (ML) algorithms including Gaussian process (GP), multiple linear regression (MLR), multilayer perceptron (MLP), M5P model tree, random forest (RF), and k-nearest neighbor (KNN) are applied to predict the water level in Lake Erie. From 2002 to 2014, meteorological data and one-day-ahead observed water level are the independent variables, and the daily water level is the dependent variable. The predictive results show that MLR and M5P have the highest accuracy regarding root mean square error (RMSE) and mean absolute error (MAE). The performance of ML models has also been compared against the performance of the process-based advanced hydrologic prediction system (AHPS), and the results indicate that ML models are superior in predictive accuracy compared to AHPS. Together with their time-saving advantage, this study shows that ML models, especially MLR and M5P, can be used for forecasting Lake Erie water levels and informing future water resources management.

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