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View article: Multi-decadal streamflow projections for catchments in Brazil based on CMIP6 multi-model simulations and neural network embeddings for linear regression models
Multi-decadal streamflow projections for catchments in Brazil based on CMIP6 multi-model simulations and neural network embeddings for linear regression models Open
A linear regression model is developed to link anomalies of streamflow to anomalies of precipitation amounts and temperature with the goal of making multi-decadal streamflow projections based on CMIP6 multi-model simulations. Regression co…
View article: Multi-decadal Streamflow Projections for Catchments in Brazil based on CMIP6 Multi-model Simulations and Neural Network Embeddings for Linear Regression Models
Multi-decadal Streamflow Projections for Catchments in Brazil based on CMIP6 Multi-model Simulations and Neural Network Embeddings for Linear Regression Models Open
A linear regression model is developed to link anomalies of streamflow to anomalies of precipitation amounts and temperature with the goal of making multi-decadal streamflow projections based on CMIP6 multi-model simulations. Regression co…
View article: Design precipitation - new results for Norway
Design precipitation - new results for Norway Open
In August 2023, the extreme weather event “Hans” moved into Scandinavia from the southeast, bringing large amounts of rainfall. It led to large-scale floods, a number of landslides and forced evacuations across large parts of s…
View article: Areal reduction factors from gridded data products
Areal reduction factors from gridded data products Open
Areal reduction factors (ARFs) convert a point estimate of extreme precipitation to an estimate of extreme precipitation over a spatial domain, and are commonly used in flood risk estimation. The fixed-area approach to ARF estimation consi…
View article: Probabilistic prediction of the time to hard freeze using seasonal weather forecasts and survival time methods
Probabilistic prediction of the time to hard freeze using seasonal weather forecasts and survival time methods Open
Agricultural food production and natural ecological systems depend on a range of seasonal climate indicators that describe seasonal patterns in climatological conditions. This article proposes a probabilistic forecasting framework for pred…
View article: A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records
A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records Open
We present a Bayesian geostatistical model for mean annual runoff that incorporates simulations from a process-based hydrological model. The simulations are treated as a covariate and the regression coefficient is modeled as a spatial fiel…
View article: New runoffmap for Norway by combining a precipitation runoff model with geostatistical interpolation
New runoffmap for Norway by combining a precipitation runoff model with geostatistical interpolation Open
<p>We present a new runoff map for Norway for the reference period 1991-2020. A new framework combing precipitation runoff-modelling with geostatistical interpolation was used. The precipitation-runoff model WASMOD was used to simula…
View article: Estimating consistent rainfall design values for Norway using Bayesian inference and post-processing of posterior quantiles
Estimating consistent rainfall design values for Norway using Bayesian inference and post-processing of posterior quantiles Open
<p>The necessity of reliable rainfall statistics for the planning and design of infrastructure is growing as climate change leads to more frequent heavy rainfall events. These rainfall statistics are often displayed as Intensity-Dura…
View article: Probabilistic prediction of the time to hard freeze using seasonal weather forecasts and survival time methods
Probabilistic prediction of the time to hard freeze using seasonal weather forecasts and survival time methods Open
<p>In the agricultural sector there is a high interest for forecasts that&#160;predict relevant agroclimatic indicators related to heat accumulation and frost characteristics. The forecasts can simplify agricultural decisions rel…
View article: A Bayesian framework to derive consistent intensity-duration-frequency curves from multiple data sources&#160;
A Bayesian framework to derive consistent intensity-duration-frequency curves from multiple data sources  Open
<p>As a warming climate leads to more frequent heavy rainfall, the importance of accurate rainfall statistics is increasing. Rainfall statistics are often presented as intensity-duration-frequency (IDF) curves showing the&#160;ra…
View article: Probabilistic prediction of the time to hard freeze using seasonal weather forecasts and survival time methods
Probabilistic prediction of the time to hard freeze using seasonal weather forecasts and survival time methods Open
Agricultural food production and natural ecological systems depend on a range of seasonal climate indicators that describe seasonal patterns in climatological conditions. This paper proposes a probabilistic forecasting framework for predic…
View article: Reply on RC1
Reply on RC1 Open
We present a Bayesian geostatistical model for mean annual runoff that incorporates simulations from a process-based hydrological model by treating the simulations as a covariate in the statistical model. The regression coefficient of the …
View article: Reply on RC2
Reply on RC2 Open
Abstract. We present a Bayesian geostatistical model for mean annual runoff that incorporates simulations from a process-based hydrological model by treating the simulations as a covariate in the statistical model. The regression coefficie…
View article: A Two-Field Geostatistical Model Combining Point and Areal Observations—A Case Study of Annual Runoff Predictions in the Voss Area
A Two-Field Geostatistical Model Combining Point and Areal Observations—A Case Study of Annual Runoff Predictions in the Voss Area Open
We estimate annual runoff by using a Bayesian geostatistical model for interpolation of hydrological data of different spatial support: streamflow observations from catchments (areal data), and precipitation and evaporation data (point dat…
View article: A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records
A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records Open
We present a Bayesian geostatistical model for mean annual runoff that incorporates simulations from a process-based hydrological model by treating the simulations as a covariate in the statistical model. The regression coefficient of the …
View article: Estimating mean annual runoff by using a geostatistical spatially varying coefficient model that incorporates process-based simulations and short records
Estimating mean annual runoff by using a geostatistical spatially varying coefficient model that incorporates process-based simulations and short records Open
<p>In this work, we suggest a new framework for estimating mean annual runoff, which is a key water balance component. &#160;The framework consists of two steps: 1) A process-based hydrological model is used to simulate mean annu…
View article: Estimation of annual runoff by exploiting long-term spatial patterns and short records within a geostatistical framework
Estimation of annual runoff by exploiting long-term spatial patterns and short records within a geostatistical framework Open
In this article, we present a Bayesian geostatistical framework that is particularly suitable for interpolation of hydrological data when the available dataset is sparse and includes both long and short records of runoff. A key feature of …
View article: Using Bayesian geostatistical models to correct gridded hydrological products relative to the actually observed streamflow
Using Bayesian geostatistical models to correct gridded hydrological products relative to the actually observed streamflow Open
<p>Conceptual hydrological models are process-based models that are used to simulate flow indices based on physical or empirical relationships and input variables like precipitation, temperature and land use. For many applications th…
View article: A new Bayesian hierarchical geostatistical model based on two spatial fields with case studies with short records of annual runoff in Norway
A new Bayesian hierarchical geostatistical model based on two spatial fields with case studies with short records of annual runoff in Norway Open
<p>We present a new Bayesian geostatistical hierarchical model that is particularly suitable for interpolation of hydrological data when the available dataset has short records, for including overlapping catchments consistently and f…
View article: A geostatistical framework for estimating flow indices by exploitingshort records and long-term spatial averages – Application to annualand monthly runoff
A geostatistical framework for estimating flow indices by exploitingshort records and long-term spatial averages – Application to annualand monthly runoff Open
In this article, we present a Bayesian geostatistical framework that is particularly suitable for interpolation of hydrological data when the available dataset is sparse and includes missing values and short records of data. A key feature …
View article: A knowledge based spatial model for utilizing point and nested areal observations: A case study of annual runoff predictions in the Voss area
A knowledge based spatial model for utilizing point and nested areal observations: A case study of annual runoff predictions in the Voss area Open
In this study, annual runoff is estimated by using a Bayesian geostatistical model for interpolating hydrological data of different spatial support. That is, streamflow observations from catchments (areal data), and precipitation and evapo…
View article: A geostatistical two field model that combines point observations and nested areal observations, and quantifies long-term spatial variability -- A case study of annual runoff predictions in the Voss area
A geostatistical two field model that combines point observations and nested areal observations, and quantifies long-term spatial variability -- A case study of annual runoff predictions in the Voss area Open
In this study, annual runoff is estimated by using a Bayesian geostatistical model for interpolation of hydrological data of different spatial support. That is, streamflow observations from catchments (areal data), and precipitation and ev…
View article: A Bayesian Model for Area and Point Predictions - A Case Study of Predictions of Annual Precipitation and Runoff in the Voss Area.
A Bayesian Model for Area and Point Predictions - A Case Study of Predictions of Annual Precipitation and Runoff in the Voss Area. Open
In this work we perform predictions of annual precipitation and runoff by spatial interpolation. For this purpose, we utilise both point observations of precipitation and/or area observations of runoff from several years. We suggest a stat…