Parameter estimation of hydrologic models using a likelihood function for censored and binary observations.
Explore this paper's citation graph
Summary
It is shown that censored observations make it possible to learn about model parameters, with an average decrease of 45% in parameter standard deviation from prior to posterior, and the inference substantially improves model predictions, providing higher Nash-Sutcliffe efficiency.
- Type
- article
- Published
- 2017-09-15
- Cited by
- 43
- References
- 43
- OpenAlex
- https://openalex.org/W28558280
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:37167901
Keywords
Humanities, Geography, Art
References
- An Analysis of Transformations
- Linking statistical bias description to multiobjective model calibration
- Using discharge data to reduce structural deficits in a hydrological model with a Bayesian inference approach and the implications for the prediction of critical source areas
- A Low Cost Calibration Method for Urban Drainage Models
- Visual Sensing for Urban Flood Monitoring
- A log‐sinh transformation for data normalization and variance stabilization
- Event based uncertainty assessment in urban drainage modelling, applying the GLUE methodology
- Bayesian calibration of computer models
- Parameterisation, calibration and validation of distributed hydrological models
- Applying global sensitivity analysis to the modelling of flow and water quality in sewers.
- Knowledge-Based System for SWMM Runoff Component Calibration
- Hydrological forecasting uncertainty assessment: Incoherence of the GLUE methodology
- Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling.
- A Markov Chain Monte Carlo Scheme for parameter estimation and inference in conceptual rainfall‐runoff modeling
- A partial ensemble Kalman filtering approach to enable use of range limited observations
- River flow forecasting through conceptual models part I — A discussion of principles☆
- Field validation of a new low-cost method for determining occurrence and duration of combined sewer overflows.
- Parameter estimation in distributed hydrological catchment modelling using automatic calibration with multiple objectives
- A model conditional processor to assess predictive uncertainty in flood forecasting
- Hydrological data monitoring for urban stormwater drainage systems
Cited by
- Information content of stream level class data for hydrological model calibration
- Comment on “Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?” by Mazzoleni et al. (2017)
- Storm event-based frequency analysis method
- A heuristic method for measurement site selection in sewer systems
- A robust and accurate surrogate method for monitoring the frequency and duration of combined sewer overflows
- Effects of Input Data Content on the Uncertainty of Simulating Water Resources
- Use of autonomous transmission line-type electromagnetic sensors for classification of dry and wet periods at sub-hourly time intervals
- Recent insights on uncertainties present in integrated catchment water quality modelling.
- The future of WRRF modelling - outlook and challenges.
- Scalable flood level trend monitoring with surveillance cameras using a deep convolutional neural network
- Uncertainty analysis in a large-scale water quality integrated catchment modelling study.
- The feasibility of using flap gates as constriction flow meters for estimating sanitary sewer overflows (SSO)
- Uncertainty analysis in integrated catchment modelling
- Urban drainage models for green areas: Structural differences and their effects on simulated runoff
- A new tool for automatic calibration of the Storm Water Management Model (SWMM)
- Public Surveillance and the Future of Urban Pluvial Flood Modelling
- The potential of proxy water level measurements for calibrating urban pluvial flood models.
- Rainfall regionalization and variability of extreme precipitation using artificial neural networks: a case study from western central Morocco
- Integrals over Gaussians under Linear Domain Constraints
- Das Internet der Dinge im städtischen Abwassersystem : Potenziale der LoRa-Technologie für reichweitenkritische Anwendungen im Untergrund
Related papers
No related papers recorded.