Simon Stisen

Geological Survey of Denmark and Greenland · Department of Hydrology

Large samples of hydrometeorological time series and catchment attributes are critical for improving the understanding of complex hydrological processes, hydrological model development and performance benchmarking. CAMELS (Catchment Attributes and Meteorological time series for Large Samples) datasets have been developed in several countries and re...

Accurate streamflow estimation is essential for effective water resource management and adapting to extreme events in the face of changing climate conditions. Hydrological models have been the conventional approach for streamflow interpolation and extrapolation in time and space for the past few decades. However, their large-scale applications have...

This study provides the first inter-comparison of different state-of-the-art approaches and frameworks that share a commonality in their utilization of satellite remote-sensing data to quantify irrigation at a regional scale. The compared approaches vary in their reliance on either soil moisture or evapotranspiration data or their joint utilization...

Optimization of spatially consistent parameter fields is believed to increase the robustness of parameter estimation and its transferability to ungauged basins. The current paper extends previous multi‐objective and transferability studies by exploring the value of both multi‐basin and spatial pattern calibration of distributed hydrologic models as...

Accurate streamflow estimation is essential for effective water resources management and adapting to extreme events in the face of changing climate conditions. Hydrological models have been the conventional approach for streamflow inter/extrapolation in time and space for the past decades. However, their large-scale applications have encountered ch...

Temporal drain flow dynamics and understanding of their underlying controlling factors are important for water resource management in tile-drained agricultural areas. The use of physics-based water flow models to understand tile drained systems is common. These models are complex, with large parameter sets and require high computational effort. The...

Optimization of spatially consistent parameter fields is believed to increase the robustness of parameter estimation and its transferability to ungauged basins. The current paper extends previous multi-objective and transferability studies by exploring the value of both multi-basin and spatial pattern calibration of distributed hydrologic models as...

Even though irrigation is the largest direct anthropogenic interference in the natural terrestrial water cycle, limited knowledge of the amount of water applied for irrigation exists. Quantification of irrigation via evapotranspiration (ET) or soil moisture residuals between remote-sensing models and hydrological models, with the latter acting as b...

The substantial climate change mitigation potential of restoring peatlands through rewetting and intensifying agriculture to reduce greenhouse gas (GHG) emissions is largely recognized. The green deal in Denmark aims at restoring 100 000 ha of peatlands by 2030. This area corresponds to more than half of the Danish peatland, with an expected reduct...

This study provides the first inter-comparison of different state-of-the-art approaches and frameworks that share a commonality in their utilization of satellite remote sensing data to quantify irrigation at a regional scale. The compared approaches vary in their reliance on either soil moisture or evapotranspiration data, or their joint utilizatio...

Study region: Denmark Study focus: Tile drainage, widespread across agricultural areas in Denmark, significantly impacts the hydrological cycle. Tile drain flow dynamics and their spatial patterns are crucial for water managers to address water quality and quantity issues. However, these processes are challenging to simulate accurately. In this stu...

Lake Urmia, located in northwest Iran, was among the world's largest hypersaline lakes but has now experienced a 7 m decrease in water level, from 1278 m to 1271 over 1996 to 2019. There is doubt as to whether the pixel-based analysis (PBA) approach's answer to the lake's drying is a natural process or a result of human intervention. Here, a non-pa...

Canopy interception loss is a key process in forest hydrology and the role of interception loss in relation to the forest water budgets and future impact of afforestation on water resources is important to quantify. Based on high frequency in situ monitoring, the effect of species‐ and leaf‐cover‐specific canopy structure metrics for interception l...

The substantial climate change mitigation potential of restoring peatlands, through rewetting and extensifying agriculture to reduce greenhouse gas (GHG) emissions is largely recognized. The green deal in Denmark aims at restoring 100,000 ha peatlands by 2030. This area corresponds to more than half of the Danish peatland, with an expected reductio...

Citation: Henriksen, H.J.; Schneider, R.; Koch, J.; Ondracek, M.; Troldborg, L.; Seidenfaden, I.K.; Kragh, S.J.; Bøgh, E.; Stisen, S. A New Digital Twin for Climate Change Adaptation, Water Management, and Disaster Risk Reduction (HIP Digital Twin). Abstract: The paper analyzes the national DK-model hydrological information and prediction (HIP) sys...

There is an urgent demand for assessments of climate change impacts on the hydrological cycle at high spatial resolutions. In particular, the impacts on shallow groundwater levels, which can lead to both flooding and drought, have major implications for agriculture, adaptation, and urban planning. Predicting such hydrological impacts is typically p...

The paper analyses the national DK-model Hydrological Information and Prediction (HIP) system and HIP portal viewed as a ‘Digital Twin’ and how the introduction of real-time dynamic updating of the DK-model HIP simulations can give room for plug-in sub-models with real-time boundary conditions made available from a HIP portal. The possible feedback...

The paper analyses the national DK-model Hydrological Information and Prediction (HIP) system and HIP portal viewed as a ‘Digital Twin’ and how the introduction of real-time dynamic updating of the DK-model HIP simulations can give room for plug-in sub-models with real-time boundary conditions made available from a HIP portal. The possible feedback...

Various methods are available for assessing uncertainties in climate impact studies. Among such methods, model weighting by expert elicitation is a practical way to provide a weighted ensemble of models for specific real-world impacts. The aim is to decrease the influence of improbable models in the results and easing the decision-making process. I...

Even though irrigation is the largest direct anthropogenic interference with the terrestrial water cycle, limited knowledge on the amount of water applied for irrigation exist. Quantification of irrigation via evapotranspiration (ET) or soil moisture residuals between remote sensing models and hydrological models, with the latter acting as baseline...

This paper presents the first study assessing the climate change impact on groundwater levels of the Zagreb alluvial aquifer in Croatia by coupling climate projections under RCP8.5 for the period 2040-2070 with local scale groundwater flow modelling. As a novelty in groundwater modelling of climate change impacts, this study utilizes an ensemble of...

Groundwater models require parameter optimization based on the minimization of objective functions describing, for example, the residual between observed and simulated groundwater head. At larger scales, constraining these models requires large datasets of groundwater head observations. These observations are typically only available from databases...

Soil moisture estimates at high spatial and temporal resolution are of great value for optimizing water and agricultural management. To fill the gap between local ground observations and coarse spatial resolution remote sensing products, we use Soil Moisture Active Passive (SMAP) and Sentinel-1 data together with a unique data set of ground-based s...

The region studied is the 137.000 km² North China Plain (NCP). A region with high population density and a major agricultural production leading to unsustainable exploitation of groundwater resources. Previous modeling studies in the region have utilized simplified representations of model boundary fluxes, both regarding lateral inflows from surfac...

Study region The study investigates six different geological regions covering 42,111 km or 98% of Denmark. Study focus Climate change impacts on spatial changes and uncertainties of water balance and groundwater levels are still not well understood, especially, the effect from hydrogeology and geomorphological setting on impact response. In this s...

There is an urgent demand for assessments of climate change impact on the hydrological cycle at high spatialresolution. In particular, the impacts on shallow groundwater levels, which can lead to both flooding and drought, havemajor implications for agriculture, adaptation and urban planning. Predicting such hydrological impacts is typicallyperform...

Spatial pattern-based performance evaluation and uncertainty analysis of a distributed hydrological model Graphical Abstract Abstract Advancement in data acquisition techniques (e.g., satellites) has provided enormous opportunities to improve the predictions of distributed hydrological models by incorporating new types of information. Moreover, suc...

Study region Densu River Basin in Ghana, West Africa. Study focus This paper reviews aquifers and groundwater resources in the Densu River Basin based on several past studies which adopted hydrochemical, numerical modelling, geostatistical techniques, and several other conventional methods with particular focus on the hydrogeological and hydrochem...

Groundwater recharge quantification is essential for sustainable groundwater resources management, but typically limited to local and regional scale estimates. A high-resolution (1 km × 1 km) dataset consisting of long-term average actual evapotranspiration, effective precipitation, a groundwater recharge coefficient, and the resulting groundwater...

Spatial pattern-oriented evaluations of distributed hydrological models have contributed towards an improved realism of hydrological simulations. This advancement has been supported by the broad range of readily available satellite-based datasets of key hydrological variables, such as evapotranspiration (ET). At larger scale, spatial patterns of ET...

About half of the Danish agricultural land is drained artificially. Those drains, mostly in the form of tile drains, have a significant effect on the hydrological cycle. Consequently, the drainage system must also be represented in hydrological models that are used to simulate, for example, the transport and retention of chemicals. However, represe...

Hydrological process knowledge has advanced significantly during the past six decades. During the same period catchment models have undergone major developments including simple black box models, lumped conceptual models, hydrological response unit models, spatially distributed process-based models and, recently, the emergence of machine learning h...

Spatial pattern-oriented evaluations of distributed hydrological models have contributed towards an improved realism of hydrological simulations. This advancement was supported by the broad range of readily available satellite-based datasets of key hydrological variables, such as evap-otranspiration (ET). At larger scale, spatial patterns of ET are...

Soil moisture estimates at high spatial and temporal resolution are of great value for optimizing water and agricultural management. To fill the gap between local ground observations and coarse spatial resolution remote sensing products we use SMAP and Sentinel-1 data together with a unique dataset of ground based soil moisture estimates by cosmic...

Hydrological models have traditionally been calibrated and evaluated against point-scale observations, such as streamflow, emphasizing the temporal, but not necessarily the spatial component of a model. The main goal of this study is to improve the spatial pattern performance of simulated actual evapotranspiration (AET), a key variable in the land-...

Detailed knowledge of the uppermost water table representing the shallow groundwater system is critical in order to address societal challenges that relate to the mitigation and adaptation to climate change and enhancing climate resilience in general. Machine learning (ML) allows for high resolution modeling of the water table depth beyond the capa...

Spatial patterns in long-term average evapotranspiration (ET) represent a unique source of information for evaluating the spatial pattern performance of distributed hydrological models on a river basin to continental scale. This kind of model evaluation is getting increased attention, acknowledging the shortcomings of traditional aggregated or time...

This study aims to improve the standard water balance evapotranspiration (WB ET) estimate, which is typically used as benchmark data for catchment-scale ET estimation, by accounting for net intercatchment groundwater flow in the ET calculation. Using the modified WB ET approach, we examine errors and shortcomings associated with the long-term annua...

Due to increasing water demands globally, freshwater ecosystems are under constant pressure. Groundwater resources, as the main source of accessible freshwater, are crucially important for irrigation worldwide. Over-abstraction of groundwater leads to declines in groundwater levels; consequently, the groundwater inflow to streams decreases. The red...

Irrigation is the greatest human interference with the terrestrial water cycle. Detailed knowledge on irrigation is required to better manage water resources and to increase water use efficiency (WUE). This study applies a framework to quantify net irrigation at monthly timescale at a spatial resolution of 1 km² providing high spatial and temporal...

Udvikling af landsdækkende modelberegninger af terrænnære hydrologiske forhold i 100m grid ved anvendelse af DK-modellen: Dokumentationsrapport vedr. modelleverancer til Hydrologisk Informations- og Prognosesystem. Udarbejdet som en del af DEN FÆLLESOFFENTLIGE DIGITALISERINGSSTRATEGI 2016-2020 INITIATIVET FÆLLES DATA OM TERRÆN, KLIMA OG VAND. Rapp...

Udvikling af landsdækkende modelberegninger af terrænnære hydrologiske forhold i 100m grid ved anvendelse af DK-modellen: Sammenfatningsrapport vedr. modelleverancer til Hydrologisk Informations- og Prognosesystem. Udarbejdet som en del af DEN FÆLLESOFFENTLIGE DIGITALISERINGSSTRATEGI 2016-2020 INITIATIVET FÆLLES DATA OM TERRÆN, KLIMA OG VAND

Missing rainfall data are a major limitation for distributed hydrological modeling and climate studies. Practitioners need reliable approaches that can be employed on a daily basis, often with too limited data in space to feed complex predictive models. In this study we compare different automatic approaches for missing data imputation including ge...

Abstract. Groundwater models require parameter optimization based on the minimization of objective functions describing, for example, the residual between observed and simulated groundwater head. At larger scales, constraining these models requires large datasets of groundwater head observations, due to the size of the inverse problem. These observ...

Although the complexity of physically-based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensi...

Although the complexity of physically based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensi...

The need for regional-scale integrated hydrological models for the purpose of water resource management is increasing. Distributed physically based coupled surface-subsurface models are usually complex and contain a large amount of spatio-temporal information that leads to a relatively long forward runtime. One of the main challenges with regard to...

The management of water resources needs robust methods to efficiently reduce nitrate loads. Knowledge on where natural denitrification takes place in the subsurface is thereby essential. Nitrate is naturally reduced in anoxic environments and high-resolution information of the redox interface, that is, the depth of the uppermost reduced zone is cru...

Formålet med projektet er at udvikle nye metoder til bedre beregning af det terrænnære grundvandsspejl og vandstand i vandløbene. Dette muliggør anvendelse i risikovurderinger forbundet med vand på terræn og oversvømmelser fra vandløb og grundvand. Metodeudviklingen er afgrænset til to oplande i hhv. Øst- og Vestdanmark: Storå og Odense Å der er ke...

Hydrologic models are conventionally constrained and evaluated using point measurements of streamflow, which represent an aggregated catchment measure. As a consequence of this single objective focus, model parametrization and model parameter sensitivity typically do not reflect other aspects of catchment behavior. Specifically for distributed mode...

Hydrologic models are conventionally constrained and evaluated using point measurements of streamflow, which represents an aggregated catchment measure. As a consequence of this single objective focus, model parametrization and model parameter sensitivity are typically not reflecting other aspects of catchment behavior. Specifically for distributed...

Spatially distributed hydrological models are traditionally calibrated and evaluated against few spatially aggregated observations such as river discharge. This model evaluation approach does not enable an assessment of the model predictive capabilities of other hydrological states and fluxes nor does it give any insight into the model ability to m...

The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial perf...

Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibra...

Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land–atmosphere interface, obtained from two different...

Developing new metricsfor spatial pattern comparison of observed and simulated variables has been planned as major part of the first work package (WP1) of the SPACE project. This goal was achieved by developing SPAtial EFficiency metric (SPAEF) described below. For that first we have extensively investigated the current state-of-art spatial compari...

The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling 10 community has a large and well tested toolbox of metrics to evaluate temporal model performance. On the contrary, spati...