Articles | Volume 13, issue 2
Development and technical paper 19 Feb 2020
Development and technical paper | 19 Feb 2020
Automated Monte Carlo-based quantification and updating of geological uncertainty with borehole data (AutoBEL v1.0)
Zhen Yin et al.
No articles found.
Adrian A. S. Barfod, Ingelise Møller, Anders V. Christiansen, Anne-Sophie Høyer, Júlio Hoffimann, Julien Straubhaar, and Jef Caers
Hydrol. Earth Syst. Sci., 22, 3351–3373,Short summary
Three-dimensional geological models are important to securing and managing groundwater. Such models describe the geological architecture, which is used for modeling the flow of groundwater. Common geological modeling approaches result in one model, which does not quantify the architectural uncertainty of the geology. We present a comparison of three different state-of-the-art stochastic multiple-point statistical methods for quantifying the geological uncertainty using real-world datasets.
Related subject area
HydrologyA distributed simple dynamical systems approach (dS2 v1.0) for computationally efficient hydrological modelling at high spatio-temporal resolutionSimulating second-generation herbaceous bioenergy crop yield using the global hydrological model H08 (v.bio1)KLT-IV v1.0: image velocimetry software for use with fixed and mobile platformsSimulating human impacts on global water resources using VIC-5The Ensemble Framework For Flash Flood Forecasting (EF5) v1.2: description and case studyML-SWAN-v1: a hybrid machine learning framework for the concentration prediction and discovery of transport pathways of surface water nutrientsThe latest improvements with SURFEX v8.0 of the Safran–Isba–Modcou hydrometeorological model for FranceA multirate mass transfer model to represent the interaction of multicomponent biogeochemical processes between surface water and hyporheic zones (SWAT-MRMT-R 1.0)The global water resources and use model WaterGAP v2.2d: Model description and evaluationMFIT 1.0.0: Multi-Flow Inversion of Tracer breakthrough curves in fractured and karst aquifersSimulator for Hydrologic Unstructured Domains (SHUD v1.0): numerical modeling of watershed hydrology with the finite volume methodHydroMix v1.0: a new Bayesian mixing framework for attributing uncertain hydrological sourcesShyft v4.8: A Framework for Uncertainty Assessment and Distributed Hydrologic Modelling for Operational HydrologyTIER version 1.0: an open-source Topographically InformEd Regression (TIER) model to estimate spatial meteorological fieldsglmGUI v1.0: an R-based graphical user interface and toolbox for GLM (General Lake Model) simulationsThe Canadian Hydrological Model (CHM) v1.0: a multi-scale, multi-extent, variable-complexity hydrological model – design and overviewWAYS v1: a hydrological model for root zone water storage simulation on a global scaleTOPMELT 1.0: a topography-based distribution function approach to snowmelt simulation for hydrological modelling at basin scaleMELPF version 1: Modeling Error Learning based Post-Processor Framework for Hydrologic Models Accuracy ImprovementBeo v1.0: numerical model of heat flow and low-temperature thermochronology in hydrothermal systemsA parallel workflow implementation for PEST version 13.6 in high-performance computing for WRF-Hydro version 5.0: a case study over the midwestern United Statesr.sim.terrain 1.0: a landscape evolution model with dynamic hydrologyThe probabilistic hydrological MARCSHYDRO (the MARkov Chain System) model: its structure and core version 0.2A Python-enhanced urban land surface model SuPy (SUEWS in Python, v2019.2): development, deployment and demonstrationThe multiscale routing model mRM v1.0: simple river routing at resolutions from 1 to 50 kmModular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v1.2: an open-source, extendable framework providing implementations of 46 conceptual hydrologic models as continuous state-space formulationsChallenges in developing a global gradient-based groundwater model (G3M v1.0) for the integration into a global hydrological modelDECIPHeR v1: Dynamic fluxEs and ConnectIvity for Predictions of HydRologyTerrainbento 1.0: a Python package for multi-model analysis in long-term drainage basin evolutionDiscrete k-nearest neighbor resampling for simulating multisite precipitation occurrence and model adaption to climate changeUsing observed river flow data to improve the hydrological functioning of the JULES land surface model (vn4.3) used for regional coupled modelling in Great Britain (UKC2)A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)V2Karst V1.1: a parsimonious large-scale integrated vegetation–recharge model to simulate the impact of climate and land cover change in karst regionsGSFLOW–GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systemsImprovements to the hydrological processes of the Town Energy Balance model (TEB-Veg, SURFEX v7.3) for urban modelling and impact assessmentSTORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate changeThe Land surface Data Toolkit (LDT v7.2) – a data fusion environment for land data assimilation systemsThe Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibilityDeveloping a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0EcH2O-iso 1.0: water isotopes and age tracking in a process-based, distributed ecohydrological modelEDDA 2.0: integrated simulation of debris flow initiation and dynamics considering two initiation mechanismsPCR-GLOBWB 2: a 5 arcmin global hydrological and water resources modelThe design, deployment, and testing of kriging models in GEOframe with SIK-0.9.8IPA (v1): a framework for agent-based modelling of soil water movementImproved regional-scale groundwater representation by the coupling of the mesoscale Hydrologic Model (mHM v5.7) to the groundwater model OpenGeoSys (OGS)The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological modelstran-SAS v1.0: a numerical model to compute catchment-scale hydrologic transport using StorAge Selection functionsContinuous state-space representation of a bucket-type rainfall-runoff model: a case study with the GR4 model using state-space GR4 (version 1.0)A hydrological emulator for global applications – HE v1.0.0Impacts of microtopographic snow redistribution and lateral subsurface processes on hydrologic and thermal states in an Arctic polygonal ground ecosystem: a case study using ELM-3D v1.0
Joost Buitink, Lieke A. Melsen, James W. Kirchner, and Adriaan J. Teuling
Geosci. Model Dev., 13, 6093–6110,Short summary
This paper presents a new distributed hydrological model: the distributed simple dynamical systems (dS2) model. The model is built with a focus on computational efficiency and is therefore able to simulate basins at high spatial and temporal resolution at a low computational cost. Despite the simplicity of the model concept, it is able to correctly simulate discharge in both small and mesoscale basins.
Zhipin Ai, Naota Hanasaki, Vera Heck, Tomoko Hasegawa, and Shinichiro Fujimori
Geosci. Model Dev., 13, 6077–6092,Short summary
Incorporating bioenergy crops into the well-established global hydrological models is seldom seen today. Here, we successfully enhance a state-of-the-art global hydrological model H08 to simulate bioenergy crop yield. We found that unconstrained irrigation more than doubled the yield under rainfed conditions while simultaneously reducing the water use efficiency by 32 % globally. Our enhanced model provides a new tool for the future assessment of bioenergy–water tradeoffs.
Matthew T. Perks
Geosci. Model Dev., 13, 6111–6130,Short summary
KLT-IV v1.0 offers a user-friendly graphical interface for the determination of river flow velocity and river discharge using videos acquired from both fixed and mobile remote sensing platforms. Platform motion can be accounted for using ground control points and/or stable features or a GPS device and inertial measurement unit sensor. Examples of the KLT-IV workflow are provided for two case studies where footage is acquired using unmanned aerial systems and fixed cameras.
Bram Droppers, Wietse H. P. Franssen, Michelle T. H. van Vliet, Bart Nijssen, and Fulco Ludwig
Geosci. Model Dev., 13, 5029–5052,Short summary
Our study aims to include both both societal and natural water requirements and uses into a hydrological model in order to enable worldwide assessments of sustainable water use. The model was extended to include irrigation, domestic, industrial, energy, and livestock water uses as well as minimum flow requirements for natural systems. Initial results showed competition for water resources between society and nature, especially with respect to groundwater withdrawals.
Zachary L. Flamig, Humberto Vergara, and Jonathan J. Gourley
Geosci. Model Dev., 13, 4943–4958,Short summary
The Ensemble Framework For Flash Flood Forecasting (EF5) is used in the US National Weather Service for operational monitoring and short-term forecasting of flash floods. This article describes the hydrologic models supported by the framework and evaluates their accuracy by comparing simulations of streamflow from 2001 to 2011 at 4 366 observation sites with catchments less than 1000 km2. Overall, the uncalibrated models reasonably simulate flash flooding events.
Benya Wang, Matthew R. Hipsey, and Carolyn Oldham
Geosci. Model Dev., 13, 4253–4270,Short summary
Surface water nutrients are essential to manage water quality, but it is hard to analyse trends. We developed a hybrid model and compared with other models for the prediction of six different nutrients. Our results showed that the hybrid model had significantly higher accuracy and lower prediction uncertainty for almost all nutrient species. The hybrid model provides a flexible method to combine data of varied resolution and quality and is accurate for the prediction of nutrient concentrations.
Patrick Le Moigne, François Besson, Eric Martin, Julien Boé, Aaron Boone, Bertrand Decharme, Pierre Etchevers, Stéphanie Faroux, Florence Habets, Matthieu Lafaysse, Delphine Leroux, and Fabienne Rousset-Regimbeau
Geosci. Model Dev., 13, 3925–3946,Short summary
The study describes how a hydrometeorological model, operational at Météo-France, has been improved. Particular emphasis is placed on the impact of climatic data, surface, and soil parametrizations on the model results. Model simulations and evaluations carried out on a variety of measurements of river flows and snow depths are presented. All improvements in climate, surface data, and model physics have a positive impact on system performance.
Yilin Fang, Xingyuan Chen, Jesus Gomez Velez, Xuesong Zhang, Zhuoran Duan, Glenn E. Hammond, Amy E. Goldman, Vanessa A. Garayburu-Caruso, and Emily B. Graham
Geosci. Model Dev., 13, 3553–3569,Short summary
Surface water quality along river corridors can be improved by the area of the stream bed and stream bank in which stream water mixes with shallow groundwater or hyporheic zones (HZs). These zones are ubiquitous and dominated by microorganisms that can process the dissolved nutrients exchanged at this interface of these zones. The modulation of surface water quality can be simulated by connecting the channel water and HZs through hyporheic exchanges using multirate mass transfer representation.
Hannes Müller Schmied, Denise Cáceres, Stephanie Eisner, Martina Flörke, Claudia Herbert, Christoph Niemann, Thedini Asali Peiris, Eklavyya Popat, Felix Theodor Portmann, Robert Reinecke, Maike Schumacher, Somayeh Shadkam, Camelia-Eliza Telteu, Tim Trautmann, and Petra Döll
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
In a globalized world with large flows of virtual water between river basins and international responsibilities for sustainable development of the Earth system and its inhabitants, quantitative estimates of water flows and storages and of water demand by humans are required. Global hydrological models as such as the WaterGAP model are developed to provide this information. Here we present a thorough description, evaluation and application of the most recent model version WaterGAP v2.2d.
Geosci. Model Dev., 13, 2905–2924,Short summary
Fractured and karst aquifers constitute important groundwater reservoirs worldwide but are particularly vulnerable to anthropogenic pollution. MFIT is a new GUI-based software for the analytical modeling of artificial tracer tests in such media. It integrates four transport models that are all capable of simulating complex (multimodal and/or heavy-tailed) tracer breakthrough curve responses and includes advanced tools for the automatic calibration and uncertainty analysis of model parameters.
Lele Shu, Paul A. Ullrich, and Christopher J. Duffy
Geosci. Model Dev., 13, 2743–2762,Short summary
Hydrologic modeling is an essential strategy for understanding and predicting natural flows. The paper introduces the design of Simulator for Hydrologic Unstructured Domains (SHUD), from the conceptual and mathematical description of hydrologic processes in a watershed to the model's computational structures. To demonstrate and validate the model performance, we employ three hydrologic experiments: the V-Catchment experiment, Vauclin's experiment, and a model study of the Cache Creek Watershed.
Harsh Beria, Joshua R. Larsen, Anthony Michelon, Natalie C. Ceperley, and Bettina Schaefli
Geosci. Model Dev., 13, 2433–2450,Short summary
We develop a Bayesian mixing model to address the issue of small sample sizes to describe different sources in hydrological mixing applications. Using composite likelihood functions, the model accounts for an often overlooked bias arising due to unweighted mixing. We test the model efficacy using a series of statistical benchmarking tests and demonstrate its real-life applicability by applying it to a Swiss Alpine catchment to obtain the proportion of groundwater recharged from rain vs. snow.
John F. Burkhart, Felix N. Matt, Sigbjørn Helset, Yisak Sultan Abdella, Ola Skavhaug, and Olga Silantyeva
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
We present a new hydrologic modeling framework for interactive development of inflow forecasts for hydropower production planning and other operational environments (e.g. flood forecasting, etc.). The software provides a Python user interface that gives an end user extensive control over the model configuration in realtime, during a simulation. This functionality allows extensive exploration of alternative weather scenarios or model setup options.
Andrew J. Newman and Martyn P. Clark
Geosci. Model Dev., 13, 1827–1843,Short summary
This paper introduces the Topographically InformEd Regression (TIER) model, which uses terrain attributes to turn observations of precipitation and temperature into spatial maps. TIER allows our understanding of complex atmospheric processes such as terrain-enhanced precipitation to be modeled in a very simple way. TIER lets users change the model so they can experiment with different ways of making maps. A key conclusion is that small changes in TIER will change the final map.
Thomas Bueche, Marko Wenk, Benjamin Poschlod, Filippo Giadrossich, Mario Pirastru, and Mark Vetter
Geosci. Model Dev., 13, 565–580,Short summary
The R-based graphical user interface glmGUI provides tools for pre- and postprocessing of General Lake Model (GLM) simulations. This includes an autocalibration, parameter sensitivity analysis, and several plot options. The model parameters can be analyzed and calibrated for the simulation output variables water temperature and lake level. The toolbox is tested for two sites (lake Ammersee, Germany, and lake Baratz, Italy).
Christopher B. Marsh, John W. Pomeroy, and Howard S. Wheater
Geosci. Model Dev., 13, 225–247,Short summary
The Canadian Hydrological Model (CHM) is a next-generation distributed model. Although designed to be applied generally, it has a focus for application where cold-region processes, such as snowpacks, play a role in hydrology. A key feature is that it uses a multi-scale surface representation, increasing efficiency. It also enables algorithm comparisons in a flexible structure. Model philosophy, design, and several cold-region-specific examples are described.
Ganquan Mao and Junguo Liu
Geosci. Model Dev., 12, 5267–5289,
Mattia Zaramella, Marco Borga, Davide Zoccatelli, and Luca Carturan
Geosci. Model Dev., 12, 5251–5265,Short summary
This paper presents TOPMELT, a parsimonious snowpack simulation model integrated into a basin-scale hydrological model. TOPMELT implements the full spatial distribution of clear-sky potential solar radiation by means of a statistical representation: this approach reduces computational burden, which is a key potential advantage when parameter sensitivity and uncertainty estimation procedures are carried out. The model is assessed by examining different resolutions of its domain.
Rui Wu, Lei Yang, Chao Chen, Sajjad Ahmad, Sergiu M. Dascalu, and Frederick C. Harris Jr.
Geosci. Model Dev., 12, 4115–4131,Short summary
The paper mainly has two contributions. First, a post-processor framework is proposed to improve hydrologic model accuracy. The key is to characterize possible connections between model inputs and errors. Based on results, it is also possible to replace the time-consuming model calibration step using our post-processor framework. Second, a window selection method is proposed to handle nonstationary data. A window size is chosen containing stable data using a measure named
DSproposed by us.
Geosci. Model Dev., 12, 4061–4073,Short summary
This paper presents a new model code that can be used to date the flow of hot fluids in the crust and the age of hot springs. It does so by modelling the thermal effects of fluid flow in the subsurface and by comparing the results with low-temperature thermochronology, which is a widely used method to quantify the temperature history of minerals and rocks. The model also demonstrates the effects of the depth and angle of permeable faults on temperatures of hot springs.
Jiali Wang, Cheng Wang, Vishwas Rao, Andrew Orr, Eugene Yan, and Rao Kotamarthi
Geosci. Model Dev., 12, 3523–3539,Short summary
WRF-Hydro needs to be calibrated to optimize its output with respect to observations. However, when applied to a relatively large domain, both WRF-Hydro simulations and calibrations require intensive computing resources and are best performed in parallel. This study ported an independent calibration tool (parameter estimation tool – PEST) to high-performance computing clusters and adapted it to work with WRF-Hydro. The results show significant speedup for model calibration.
Brendan Alexander Harmon, Helena Mitasova, Anna Petrasova, and Vaclav Petras
Geosci. Model Dev., 12, 2837–2854,Short summary
The numerical model, r.sim.terrain, simulates how overland flows of water and sediment shape topography over short periods of time. We tested the model by comparing runs of the simulation against a time series of airborne lidar surveys for our study landscape. Through these tests, we demonstrated that the model can simulate gully evolution including processes such as channel incision, channel widening, and the development of scour pits, rills, and depositional ridges.
Elena Shevnina and Andrey Silaev
Geosci. Model Dev., 12, 2767–2780,Short summary
The paper provides a theory and assumptions behind an advance of frequency analysis (AFA) approach in long-term hydrological forecasting. In this paper, a new core of the probabilistic hydrological model MARkov Chain System (MARCSHYDRO) was introduced, together with the code and an example of a climate-scale prediction of an exceedance probability curve of river runoff with low computational costs.
Ting Sun and Sue Grimmond
Geosci. Model Dev., 12, 2781–2795,Short summary
A Python-enhanced urban land surface model, SuPy (SUEWS in Python), is presented with its development (the SUEWS interface modification, F2PY configuration and Python frontend implementation), cross-platform deployment (PyPI, Python Package Index) and demonstration (online tutorials in Jupyter notebooks for users of different levels). SuPy represents a significant enhancement that supports existing and new model applications, reproducibility and enhanced functionality.
Stephan Thober, Matthias Cuntz, Matthias Kelbling, Rohini Kumar, Juliane Mai, and Luis Samaniego
Geosci. Model Dev., 12, 2501–2521,Short summary
We present a model that aggregates simulated runoff along a river (i.e. a routing model). The unique feature of the model is that it can be run at multiple resolutions without any modifications to the input data. The model internally (dis-)aggregates all input data to the resolution given by the user. The model performance does not depend on the chosen resolution. This allows efficient model calibration at coarse resolution and subsequent model application at fine resolution.
Wouter J. M. Knoben, Jim E. Freer, Keirnan J. A. Fowler, Murray C. Peel, and Ross A. Woods
Geosci. Model Dev., 12, 2463–2480,Short summary
Computer models are used to predict river flows. A good model should represent the river basin to which it is applied so that flow predictions are as realistic as possible. However, many different computer models exist, and selecting the most appropriate model for a given river basin is not always easy. This study combines computer code for 46 different hydrological models into a single coding framework so that models can be compared in an objective way and we can learn about model differences.
Robert Reinecke, Laura Foglia, Steffen Mehl, Tim Trautmann, Denise Cáceres, and Petra Döll
Geosci. Model Dev., 12, 2401–2418,Short summary
G³M is a new global groundwater model (http://globalgroundwatermodel.org) that simulates lateral and vertical flows as well as exchanges with surface water bodies like rivers, lakes, and wetlands for the whole globe except Antarctica and Greenland. The newly developed model framework enables an efficient integration into established global hydrological models. This paper presents the G³M concept and specific model design decisions together with first results under a naturalized equilibrium.
Gemma Coxon, Jim Freer, Rosanna Lane, Toby Dunne, Wouter J. M. Knoben, Nicholas J. K. Howden, Niall Quinn, Thorsten Wagener, and Ross Woods
Geosci. Model Dev., 12, 2285–2306,Short summary
DECIPHeR (Dynamic fluxEs and ConnectIvity for Predictions of Hydrology) is a new modelling framework that can be applied from small catchment to continental scales for complex river basins. This paper describes the modelling framework and its key components and demonstrates the model’s ability to be applied across a large model domain. This work highlights the potential for catchment- to continental-scale predictions of streamflow to support robust environmental management and policy decisions.
Katherine R. Barnhart, Rachel C. Glade, Charles M. Shobe, and Gregory E. Tucker
Geosci. Model Dev., 12, 1267–1297,Short summary
Terrainbento 1.0 is a Python package for modeling the evolution of the surface of the Earth over geologic time (e.g., thousands to millions of years). Despite many decades of effort by the geomorphology community, there is no one established governing equation for the evolution of topography. Terrainbento 1.0 thus provides 28 alternative models that support hypothesis testing and multi-model analysis in landscape evolution.
Taesam Lee and Vijay P. Singh
Geosci. Model Dev., 12, 1189–1207,Short summary
A simple novel technique for simulating multisite occurrence of precipitation is proposed. The proposed technique employs the nonparametric approaches k-nearest neighbor and genetic algorithms. We tested this technique in various ways and proved that this simple technique can be useful and comparable to the existing one.
Alberto Martínez-de la Torre, Eleanor M. Blyth, and Graham P. Weedon
Geosci. Model Dev., 12, 765–784,Short summary
Land–surface interactions with the atmosphere are key for weather and climate modelling studies, both in research and in the operational systems that provide scientific tools for decision makers. Regional assessments will be influenced by the characteristics of the land. We improved the representation of river flows in Great Britain by including a dependency on the terrain slope. This development will be reflected not only in river flows, but in the whole water cycle represented by the model.
Matthew R. Hipsey, Louise C. Bruce, Casper Boon, Brendan Busch, Cayelan C. Carey, David P. Hamilton, Paul C. Hanson, Jordan S. Read, Eduardo de Sousa, Michael Weber, and Luke A. Winslow
Geosci. Model Dev., 12, 473–523,Short summary
The General Lake Model (GLM) has been developed to undertake simulation of a diverse range of wetlands, lakes, and reservoirs. The model supports the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of lake sensors and researchers attempting to understand lake functioning and address questions about how lakes around the world vary in response to climate and land use change. The paper describes the science basis and application of the model.
Fanny Sarrazin, Andreas Hartmann, Francesca Pianosi, Rafael Rosolem, and Thorsten Wagener
Geosci. Model Dev., 11, 4933–4964,Short summary
We propose the first large-scale vegetation–recharge model for karst regions (V2Karst), which enables the analysis of the impact of changes in climate and land cover on karst groundwater recharge. We demonstrate the plausibility of V2Karst simulations against observations at FLUXNET sites and of controlling modelled processes using sensitivity analysis. We perform virtual experiments to further test the model and gain insight into its sensitivity to precipitation pattern and vegetation cover.
G.-H. Crystal Ng, Andrew D. Wickert, Lauren D. Somers, Leila Saberi, Collin Cronkite-Ratcliff, Richard G. Niswonger, and Jeffrey M. McKenzie
Geosci. Model Dev., 11, 4755–4777,Short summary
The profound importance of water has led to the development of increasingly complex hydrological models. However, implementing these models is usually time-consuming and requires specialized expertise, stymieing their widespread use to support science-driven decision-making. In response, we have developed GSFLOW–GRASS, a robust and comprehensive set of software tools that can be readily used to set up and execute GSFLOW, the U.S. Geological Survey's coupled groundwater–surface-water flow model.
Xenia Stavropulos-Laffaille, Katia Chancibault, Jean-Marc Brun, Aude Lemonsu, Valéry Masson, Aaron Boone, and Hervé Andrieu
Geosci. Model Dev., 11, 4175–4194,Short summary
Integrating vegetation in urban planning is promoted to counter steer potential impacts of climate and demographic changes. Assessing the multiple benefits of such strategies on the urban microclimate requires a detailed coupling of both the water and energy transfers in numerical tools. In this respect, the representation of water-related processes in the urban subsoil of the existing model TEB-Veg has been improved. The new model thus allows a better evaluation of urban adaptation strategies.
Michael Bliss Singer, Katerina Michaelides, and Daniel E. J. Hobley
Geosci. Model Dev., 11, 3713–3726,Short summary
For various applications, a regional or local characterization of rainfall is required, particularly at the watershed scale, where there is spatial heterogeneity. Furthermore, simple models are needed that can simulate various scenarios of climate change including changes in seasonal wetness and rainstorm intensity. To this end, we have developed the STOchastic Rainstorm Model (STORM). We explain its developments and data requirements, and illustrate how it simulates rainstorms over a basin.
Kristi R. Arsenault, Sujay V. Kumar, James V. Geiger, Shugong Wang, Eric Kemp, David M. Mocko, Hiroko Kato Beaudoing, Augusto Getirana, Mahdi Navari, Bailing Li, Jossy Jacob, Jerry Wegiel, and Christa D. Peters-Lidard
Geosci. Model Dev., 11, 3605–3621,Short summary
The Earth’s land surface hydrology and physics can be represented in highly sophisticated models known as land surface models. The Land surface Data Toolkit (LDT) software was developed to meet these models’ input processing needs. LDT supports a variety of land surface and hydrology models and prepares the inputs (e.g., meteorological data, satellite observations to be assimilated into a model), which can be used for inter-model studies and to initialize weather and climate forecasts.
Joseph J. Hamman, Bart Nijssen, Theodore J. Bohn, Diana R. Gergel, and Yixin Mao
Geosci. Model Dev., 11, 3481–3496,Short summary
Variable Infiltration Capacity (VIC) is a widely used hydrologic model. This paper documents the development of VIC version 5, which includes a reconfiguration of the model source code to support a wider range of modeling applications. It also represents a significant step forward for the VIC user community in terms of support for a range of modeling applications, reproducibility, and scientific robustness.
Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah L. Cloke, Davide Muraro, Christel Prudhomme, Elisabeth M. Stephens, Peter Salamon, and Florian Pappenberger
Geosci. Model Dev., 11, 3327–3346,Short summary
Global overviews of upcoming flood and drought events are key for many applications from agriculture to disaster risk reduction. Seasonal forecasts are designed to provide early indications of such events weeks or even months in advance. This paper introduces GloFAS-Seasonal, the first operational global-scale seasonal hydro-meteorological forecasting system producing openly available forecasts of high and low river flow out to 4 months ahead.
Sylvain Kuppel, Doerthe Tetzlaff, Marco P. Maneta, and Chris Soulsby
Geosci. Model Dev., 11, 3045–3069,Short summary
This paper presents a novel ecohydrological model in which both the fluxes of water and the relative concentration in stable isotopes (2H and 18O) can be simulated. Spatial heterogeneity, lateral transfers and plant-driven water use are incorporated. A thorough evaluation shows encouraging results using a wide range of in situ measurements from a Scottish catchment. The same modelling principles are then used to simulate how (and where) precipitation ages as water transits in the catchment.
Ping Shen, Limin Zhang, Hongxin Chen, and Ruilin Fan
Geosci. Model Dev., 11, 2841–2856,Short summary
A rainstorm can trigger numerous debris flows. A difficult task in debris flow risk assessment is to identify debris flow initiation locations and volumes. This paper presents a new model to solve this problem by physically simulating the initiation of debris flows by hillslope bed erosion and transformation from slope failures. The sediment from these two initiation mechanisms joins the flow mixture, and the volume of the flow mixture increases along the flow path due to additional bed erosion.
Edwin H. Sutanudjaja, Rens van Beek, Niko Wanders, Yoshihide Wada, Joyce H. C. Bosmans, Niels Drost, Ruud J. van der Ent, Inge E. M. de Graaf, Jannis M. Hoch, Kor de Jong, Derek Karssenberg, Patricia López López, Stefanie Peßenteiner, Oliver Schmitz, Menno W. Straatsma, Ekkamol Vannametee, Dominik Wisser, and Marc F. P. Bierkens
Geosci. Model Dev., 11, 2429–2453,Short summary
PCR-GLOBWB 2 is an integrated hydrology and water resource model that fully integrates water use simulation and consolidates all features that have been developed since PCR-GLOBWB 1 was introduced. PCR-GLOBWB 2 can have a global coverage at 5 arcmin resolution and supersedes PCR-GLOBWB 1, which has a resolution of 30 arcmin only. Comparing the 5 arcmin with 30 arcmin simulations using discharge data, we clearly find improvement in the model performance of the higher-resolution model.
Marialaura Bancheri, Francesco Serafin, Michele Bottazzi, Wuletawu Abera, Giuseppe Formetta, and Riccardo Rigon
Geosci. Model Dev., 11, 2189–2207,Short summary
This paper presents a new modeling package for the spatial interpolation of environmental variables. It includes 11 theoretical semivariogram models and four types of Kriging interpolations. To test the performances of the package, two applications are performed: the interpolation of 1 year of temperatures and a rainfall event. Both interpolations gave good results. In comparison with gstat, the SIK package proved to be a good alternative, regarding both the easiness of use and the accuracy.
Benjamin Mewes and Andreas H. Schumann
Geosci. Model Dev., 11, 2175–2187,
Miao Jing, Falk Heße, Rohini Kumar, Wenqing Wang, Thomas Fischer, Marc Walther, Matthias Zink, Alraune Zech, Luis Samaniego, Olaf Kolditz, and Sabine Attinger
Geosci. Model Dev., 11, 1989–2007,
Julian Koch, Mehmet Cüneyd Demirel, and Simon Stisen
Geosci. Model Dev., 11, 1873–1886,Short summary
Our work addresses a key challenge in earth system modelling: how to optimally exploit the information contained in satellite remote sensing observations in the calibration of such models. For this we thoroughly test a number of measures that quantify the fit between an observed and a simulated spatial pattern. We acknowledge the difficulties associated with such a comparison and suggest using measures that regard multiple aspects of spatial information, i.e. magnitude and variability.
Paolo Benettin and Enrico Bertuzzo
Geosci. Model Dev., 11, 1627–1639,Short summary
Solutes introduced in the environment are transported by water to streams and lakes. The tran-SAS package includes a set of codes to model this process for entire watersheds by using the concept of water residence times, i.e. the time that water takes to move through the landscape. Results show that the model is implemented efficiently and it can be used to simulate solute transport in a number of different conditions.
Léonard Santos, Guillaume Thirel, and Charles Perrin
Geosci. Model Dev., 11, 1591–1605,Short summary
Many rainfall–runoff models are based on stores. However, the differential equations that describe the stores' evolution are rarely presented in literature. This represents an issue when the temporal resolution changes. In this work, we propose and evaluate a state-space version of a simple rainfall–runoff model within a robust resolution scheme. The results show that the proposed model performs equally well or slightly better than the original one and is independent of the temporal resolution.
Yaling Liu, Mohamad Hejazi, Hongyi Li, Xuesong Zhang, and Guoyong Leng
Geosci. Model Dev., 11, 1077–1092,Short summary
This hydrologic emulator provides researchers with an easy way to investigate the variations in water budgets at any spatial scale of interest, with minimum requirements of effort, reasonable model predictability, and appealing computational efficiency. We expect it to have a profound influence on scientific endeavors in hydrological modeling and to excite the immediate interest of researchers working on climate impact assessments, uncertainty/sensitivity analysis, and integrated assessment.
Gautam Bisht, William J. Riley, Haruko M. Wainwright, Baptiste Dafflon, Fengming Yuan, and Vladimir E. Romanovsky
Geosci. Model Dev., 11, 61–76,Short summary
The land model integrated into the Energy Exascale Earth System Model was extended to include snow redistribution (SR) and lateral subsurface hydrologic and thermal processes. Simulation results at a polygonal tundra site near Barrow, Alaska, showed that inclusion of SR resulted in a better agreement with observations. Excluding lateral subsurface processes had a small impact on mean states but caused a large overestimation of spatial variability in soil moisture and temperature.
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We provide completely automated Bayesian evidential learning (AutoBEL) for geological uncertainty quantification. AutoBEL focuses on model falsification, global sensitivity analysis, and statistical learning for joint model uncertainty reduction by borehole data. Application shows fast and robust uncertainty reduction in geological models and predictions for large field cases, showing its applicability in subsurface applications, e.g., groundwater, oil, gas, and geothermal or mineral resources.
We provide completely automated Bayesian evidential learning (AutoBEL) for geological...