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Book ; Online: Remote Sensing of Regional Soil Moisture

Pause, Marion / Wöhling, Thomas / Schulz, Karsten / Jagdhuber, Thomas / Schrön, Martin / Wöhling, Thomas

2022

Keywords	History of engineering & technology ; instrument development ; hyperspectral ; spectroradiometry ; LiDAR ; soil ; regional soil moisture ; in situ network ; AMSR2 ; FY3B ; evaluation ; EVI ; SST ; disaggregation ; soil moisture ; DISPATCH ; Intermediate spatial resolution ; SMAP ; geostationary ; validation ; SEVIRI ; thermal infrared ; land surface temperature ; downscaling ; advanced scatterometer (ASCAT) ; soil moisture active passive (SMAP) ; random forest ; low-cost sensor ; AMSR-E ; the microwave polarization difference index ; surface soil moisture ; regional scale ; vegetation traits ; multi-sensor approach ; wetland ; environmental monitoring ; remote sensing ; geostatistics ; gap-filling ; mesonet ; ESA CCI SM ; ASTER imagery ; soil moisture content ; thermal inertia model ; serial dual-source model ; surface component temperature ; shadow impact ; multi-model coupling ; optimal solution method ; ESA CCI ; residual soil moisture ; evapotranspiration ; trend ; rainfall variability ; CHIRPS ; theta probe ; Sentinel-1A ; NDVI ; modified Dubois model ; Sentinel-1/2 ; Landsat-8 ; GF-1 ; vegetation water content ; Oh ; Dubois ; IEM ; WCM ; SSRT ; SAR ; LAI ; wheat ; Sentinel-1 ; support vector machine ; ordinary least square regression ; time series ; Mongolia ; MODIS ; relative soil moisture ; Chinese Loess Plateau ; ATI ; TVDI
Size	1 electronic resource (426 pages)
Publisher	MDPI - Multidisciplinary Digital Publishing Institute
Publishing place	Basel
Document type	Book ; Online
Note	English ; Open Access
HBZ-ID	HT021291365
ISBN	9783036529561 ; 303652956X
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: An in-depth analysis of Markov-Chain Monte Carlo ensemble samplers for inverse vadose zone modeling

Brunetti, Giuseppe / Šimůnek, Jiří / Wöhling, Thomas / Stumpp, Christine

Journal of Hydrology. 2023 Sept., v. 624 p.129822-

2023

Abstract: This study elucidates the behavior of Markov-Chains Monte Carlo ensemble samplers for vadose zone inverse modeling by performing an in-depth comparison of four algorithms that use Affine-Invariant (AI) moves or Differential Evolution (DE) strategies to ... ...

Abstract	This study elucidates the behavior of Markov-Chains Monte Carlo ensemble samplers for vadose zone inverse modeling by performing an in-depth comparison of four algorithms that use Affine-Invariant (AI) moves or Differential Evolution (DE) strategies to approximate the target density. Two Rosenbrock toy distributions, and one synthetic and one actual case study focusing on the inverse estimation of soil hydraulic parameters using HYDRUS-1D, are used to compare samplers in different dimensions d. The analysis reveals that an ensemble with N=d+1 chains evolved using DE-based strategies converges to the wrong stationary posterior, while AI does not suffer from this issue but exhibits delayed convergence. DE-based samplers regain their ergodic properties when using N≥2d chains. Increasing the number of chains above this threshold has only minor effects on the samplers’ performance, while initializing the ensemble in a high-likelihood region facilitates its convergence. AI strategies exhibit shorter autocorrelation times in the 7d synthetic vadose zone scenario, while DE-based samplers outperform them when the number of soil parameters increases to 16 in the actual scenario. All evaluation metrics degrade as d increases, thus suggesting that sampling strategies based only on interpolation between chains tend to become inefficient when the bulk of the posterior lays in increasingly small portions of the parameters’ space.
Keywords	Markov chain ; autocorrelation ; case studies ; soil ; vadose zone ; Markov-chain Monte Carlo ; Ensemble samplers ; Differential evolution ; Affine invariant
Language	English
Dates of publication	2023-09
Publishing place	Elsevier B.V.
Document type	Article ; Online
ZDB-ID	1473173-3
ISSN	1879-2707 ; 0022-1694
ISSN (online)	1879-2707
ISSN	0022-1694
DOI	10.1016/j.jhydrol.2023.129822
Database	NAL-Catalogue (AGRICOLA)

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Article: Natürliche und anthropogene Einflussfaktoren auf das hydrologische Regime des Wairau Plain Aquifer in Neuseeland. Natural and anthropogenic factors Controlling the hydrological regime of the Wairau Plain Aquifer, New Zealand

Wöhling, Thomas

Hydrologie und Wasserbewirtschaftung

2019 Volume 63, Issue 3, Page(s) 147

Language	German
Document type	Article
ZDB-ID	1467877-9
ISSN	0012-0235 ; 1439-1783
DOI	10.5675/hywa_2019.3_2
Database	Current Contents Nutrition, Environment, Agriculture

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Article ; Online: Robust Data Worth Analysis with Surrogate Models.

Gosses, Moritz / Wöhling, Thomas

Ground water

2021 Volume 59, Issue 5, Page(s) 728–744

Abstract: Highly detailed physically based groundwater models are often applied to make predictions of system states under unknown forcing. The required analysis of uncertainty is often unfeasible due to the high computational demand. We combine two possible ... ...

Abstract	Highly detailed physically based groundwater models are often applied to make predictions of system states under unknown forcing. The required analysis of uncertainty is often unfeasible due to the high computational demand. We combine two possible solution strategies: (1) the use of faster surrogate models; and (2) a robust data worth analysis combining quick first-order second-moment uncertainty quantification with null-space Monte Carlo techniques to account for parametric uncertainty. A structurally and parametrically simplified model and a proper orthogonal decomposition (POD) surrogate are investigated. Data worth estimations by both surrogates are compared against estimates by a complex MODFLOW benchmark model of an aquifer in New Zealand. Data worth is defined as the change in post-calibration predictive uncertainty of groundwater head, river-groundwater exchange flux, and drain flux data, compared to the calibrated model. It incorporates existing observations, potential new measurements of system states ("additional" data) as well as knowledge of model parameters ("parametric" data). The data worth analysis is extended to account for non-uniqueness of model parameters by null-space Monte Carlo sampling. Data worth estimates of the surrogates and the benchmark suggest good agreement for both surrogates in estimating worth of existing data. The structural simplification surrogate only partially reproduces the worth of "additional" data and is unable to estimate "parametric" data, while the POD model is in agreement with the complex benchmark for both "additional" and "parametric" data. The variance of the POD data worth estimates suggests the need to account for parameter non-uniqueness, like presented here, for robust results.
MeSH term(s)	Groundwater ; Models, Theoretical ; Monte Carlo Method ; Rivers ; Uncertainty
Language	English
Publishing date	2021-04-04
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	246212-6
ISSN	1745-6584 ; 0017-467X
ISSN (online)	1745-6584
ISSN	0017-467X
DOI	10.1111/gwat.13098
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Robust Data Worth Analysis with Surrogate Models

Gosses, Moritz / Wöhling, Thomas

Ground water. 2021 Sept., v. 59, no. 5

2021

Abstract	Highly detailed physically based groundwater models are often applied to make predictions of system states under unknown forcing. The required analysis of uncertainty is often unfeasible due to the high computational demand. We combine two possible solution strategies: (1) the use of faster surrogate models; and (2) a robust data worth analysis combining quick first‐order second‐moment uncertainty quantification with null‐space Monte Carlo techniques to account for parametric uncertainty. A structurally and parametrically simplified model and a proper orthogonal decomposition (POD) surrogate are investigated. Data worth estimations by both surrogates are compared against estimates by a complex MODFLOW benchmark model of an aquifer in New Zealand. Data worth is defined as the change in post‐calibration predictive uncertainty of groundwater head, river‐groundwater exchange flux, and drain flux data, compared to the calibrated model. It incorporates existing observations, potential new measurements of system states (“additional” data) as well as knowledge of model parameters (“parametric” data). The data worth analysis is extended to account for non‐uniqueness of model parameters by null‐space Monte Carlo sampling. Data worth estimates of the surrogates and the benchmark suggest good agreement for both surrogates in estimating worth of existing data. The structural simplification surrogate only partially reproduces the worth of “additional” data and is unable to estimate “parametric” data, while the POD model is in agreement with the complex benchmark for both “additional” and “parametric” data. The variance of the POD data worth estimates suggests the need to account for parameter non‐uniqueness, like presented here, for robust results.
Keywords	aquifers ; groundwater ; groundwater flow ; hydrologic models ; uncertainty ; variance ; New Zealand
Language	English
Dates of publication	2021-09
Size	p. 728-744.
Publishing place	Blackwell Publishing Ltd
Document type	Article
Note	JOURNAL ARTICLE
ZDB-ID	246212-6
ISSN	1745-6584 ; 0017-467X
ISSN (online)	1745-6584
ISSN	0017-467X
DOI	10.1111/gwat.13098
Database	NAL-Catalogue (AGRICOLA)

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Article: Lumped geohydrological modelling for long-term predictions of groundwater storage and depletion

Ejaz, Fahad / Wöhling, Thomas / Höge, Marvin / Nowak, Wolfgang

Journal of hydrology. 2022 Mar., v. 606

2022

Abstract: Excessive groundwater pumping exacerbates aquifer depletion and poses a major threat in regions all around the world that already suffer from overuse or climate change. In this situation, accurate and reliable predictions of long-term aquifer water ... ...

Abstract	Excessive groundwater pumping exacerbates aquifer depletion and poses a major threat in regions all around the world that already suffer from overuse or climate change. In this situation, accurate and reliable predictions of long-term aquifer water balances are key prerequisites to manage groundwater sustainably. Compared to spatially explicit numerical models, lumped hydrological models are computationally fast, lean on data requirement and more accessable for quantifying uncertainty. However, lumped hydrological models are mainly designed to simulate river discharge only, not aquifer storage. Consequently, calibration only includes stream flow data. In this study, we hypothesize that we can extend a lumped hydrological models (here HBV) towards a lumped geohydrological model (LGhM) by additional, designated terms for water budget and groundwater storage. The model building is inspired by the geometry and hydrogeological large-scale properties of the catchment’s aquifers. Underground flow routing resembles major groundwater flow paths. The model is calibrated and evaluated on both groundwater storage data and surface discharge data. We apply our LGhM to a MODFLOW-based virtual reality describing the unconfined Wairau Plain Aquifer, New Zealand. We consider and discuss specifically river-groundwater exchange processes, long-term forecast of aquifer storage dynamics, and groundwater depletion in a hypothetical, persistent drought. Our model evaluation shows very plausible predictive capabilities in 40-year forecasts with synthetic weather time series and several years of groundwater depletion in the extreme drought case.
Keywords	aquifers ; climate change ; computer simulation ; drought ; geometry ; groundwater ; groundwater flow ; model validation ; river flow ; stream flow ; time series analysis ; uncertainty ; water budget ; water shortages ; watersheds ; New Zealand
Language	English
Dates of publication	2022-03
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1473173-3
ISSN	1879-2707 ; 0022-1694
ISSN (online)	1879-2707
ISSN	0022-1694
DOI	10.1016/j.jhydrol.2021.127347
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Eigenmodels to forecast groundwater levels in unconfined river-fed aquifers during flow recession.

Wöhling, Thomas / Burbery, Lee

The Science of the total environment

2020 Volume 747, Page(s) 141220

Abstract: Low-land alluvial gravel aquifers are formed from, and tend to be recharged, by rivers. These interconnected river - groundwater systems can be highly dynamic with groundwater levels following the seasonality of the hydrological regime of the river. The ... ...

Abstract	Low-land alluvial gravel aquifers are formed from, and tend to be recharged, by rivers. These interconnected river - groundwater systems can be highly dynamic with groundwater levels following the seasonality of the hydrological regime of the river. The associated groundwater resources are regularly under stress during summer periods when abstractive demand is high and recharge is low. Predicting lead-times for critical groundwater levels allows for a more flexible and adaptive groundwater management. An eigenmodel approach is proposed here as a way of making such predictions, fast and efficiently. The eigenmodel is a mathematical concept that represents the hydraulic function of a groundwater aquifer as a set of conceptual linear reservoirs, arranged in-series. River recharge, land surface recharge, and groundwater abstraction for irrigation are considered as model forcings. The eigenmodel approach is demonstrated on three wells of the unconfined Wairau Aquifer in the Marlborough District of New Zealand, which are used for water resources management. Individual eigenmodels were calibrated to historic data and predictive uncertainty bounds were determined by Markov chain Monte Carlo sampling. Hindcasting of past recession periods showed a low predictive error of the models and a good coverage of the predictive uncertainty bounds. The main advantage of the approach is a 4-orders of magnitude higher computational efficiency compared to a numerical benchmark model. This allows for probabilistic simulation in operational forecasting of groundwater levels. The framework is implemented as a web application for 30-day operational forecasts that comprises automatic data downloads and model input generation, stochastic simulation, uncertainty estimation, visualization, and daily updates on a website.
Language	English
Publishing date	2020-07-29
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2020.141220
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Deriving transmission losses in ephemeral rivers using satellite imagery and machine learning

Ciacca, Antoine / Wilson, Scott / Kang, Jasmine / Wöhling, Thomas

eISSN: 1607-7938

2023

Abstract: Transmission losses are the loss in the flow volume of a river as water moves downstream. These losses provide crucial ecosystem services, particularly in ephemeral and intermittent river systems. Transmission losses can be quantified at many scales ... ...

Abstract	Transmission losses are the loss in the flow volume of a river as water moves downstream. These losses provide crucial ecosystem services, particularly in ephemeral and intermittent river systems. Transmission losses can be quantified at many scales using different measurement techniques. One of the most common methods is differential gauging of river flow at two locations. An alternative method for non-perennial rivers is to replace the downstream gauging location by visual assessments of the wetted river length on satellite images. The transmission losses are then calculated as the flow gauged at the upstream location divided by the wetted river length. We used this approach to estimate the transmission losses in the Selwyn River (Canterbury, New Zealand) using 147 satellite images collected between March 2020 and May 2021. The location of the river drying front was verified in the field on six occasions and seven differential gauging campaigns were conducted to ground-truth the losses estimated from the satellite images. The transmission loss point data obtained using the wetted river lengths and differential gauging campaigns were used to train an ensemble of random forest models to predict the continuous hourly time series of transmission losses and their uncertainties. Our results show that the Selwyn River transmission losses ranged between 0.25 and 0.65 <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow class="unit"><msup><mi mathvariant="normal">m</mi><mn mathvariant="normal">3</mn></msup><mspace width="0.125em" linebreak="nobreak"/><msup><mi mathvariant="normal">s</mi><mrow><mo>-</mo><mn mathvariant="normal">1</mn></mrow></msup><mspace linebreak="nobreak" width="0.125em"/><msup><mi mathvariant="normal">km</mi><mrow><mo>-</mo><mn ...<br />
Subject code	550 ; 333
Language	English
Publishing date	2023-02-09
Publishing country	de
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Deriving transmission losses in ephemeral rivers using satellite imagery and machine learning

Ciacca, Antoine / Wilson, Scott / Kang, Jasmine / Wöhling, Thomas

eISSN:

2023

Abstract	Transmission losses are the loss in the flow volume of a river as water moves downstream. These losses provide crucial ecosystem services, particularly in ephemeral and intermittent river systems. Transmission losses can be quantified at many scales using different measurement techniques. One of the most common methods is differential gauging of river flow at two locations. An alternative method for non-perennial rivers is to replace the downstream gauging location by visual assessments of the wetted river length on satellite images. The transmission losses are then calculated as the flow gauged at the upstream location divided by the wetted river length. We used this approach to estimate the transmission losses in the Selwyn River (Canterbury, New Zealand) using 147 satellite images collected between March 2020 and May 2021. The location of the river drying front was verified in the field on six occasions and seven differential gauging campaigns were conducted to ground-truth the losses estimated from the satellite images. The transmission loss point data obtained using the wetted river lengths and differential gauging campaigns were used to train an ensemble of random forest models to predict the continuous hourly time series of transmission losses and their uncertainties. Our results show that the Selwyn River transmission losses ranged between 0.25 and 0.65 <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow class="unit"><msup><mi mathvariant="normal">m</mi><mn mathvariant="normal">3</mn></msup><mspace width="0.125em" linebreak="nobreak"/><msup><mi mathvariant="normal">s</mi><mrow><mo>-</mo><mn mathvariant="normal">1</mn></mrow></msup><mspace linebreak="nobreak" width="0.125em"/><msup><mi mathvariant="normal">km</mi><mrow><mo>-</mo><mn ...<br />
Subject code	550 ; 333
Language	English
Publishing date	2023-02-09
Publishing country	de
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Soil hydraulic conductivity in the state of nonequilibrium

Vogel, Hans‐Jörg / Gerke, Horst H. / Mietrach, Robert / Zahl, René / Wöhling, Thomas

Vadose Zone Journal. 2023 Mar., v. 22, no. 2 p.e20238-

2023

Abstract: Hydraulic nonequilibrium in soil during water infiltration and drainage is a well‐known phenomenon. During infiltration, water initially invades easily accessible pores before it slowly redistributes towards some state of energetic minimum. In analogy, ... ...

Abstract	Hydraulic nonequilibrium in soil during water infiltration and drainage is a well‐known phenomenon. During infiltration, water initially invades easily accessible pores before it slowly redistributes towards some state of energetic minimum. In analogy, during drainage, easily drainable pores are emptied more rapidly than those blocked by bottlenecks. The consequence is that the water content is lagging behind the water potential and both state variables do not follow a unique water retention curve as typically assumed when applying Richards equation. Current models that account for nonequilibrium allow for the required decoupling of water content and water potential; however, they do not consider the consequences for the hydraulic conductivity. In this contribution, we present a physically based approach to estimate hydraulic conductivity during nonequilibrium, which depends on both water content and water potential during nonequilibrium conditions. This approach of a dynamic hydraulic conductivity function is demonstrated for an infiltration process into relatively dry soil and for a stepwise drainage and rewetting with decreasing and increasing water fluxes (i.e., multistep flux experiment). The new approach reproduces well‐known phenomena such as pressure overshoot and preferential flow across infiltration fronts using a unified concept for hydraulic conductivity. This was not possible with existing models assuming some fixed unsaturated conductivity function depending on either water content or water potential.
Keywords	drainage ; equations ; hydraulic conductivity ; preferential flow ; vadose zone ; water content ; water potential
Language	English
Dates of publication	2023-03
Publishing place	John Wiley & Sons, Ltd
Document type	Article ; Online
Note	JOURNAL ARTICLE
ZDB-ID	2088189-7
ISSN	1539-1663
ISSN	1539-1663
DOI	10.1002/vzj2.20238
Database	NAL-Catalogue (AGRICOLA)

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