scholarly journals Upscaling land-use effects on water partitioning and water ages using tracer-aided ecohydrological models

2020 ◽  
Author(s):  
Aaron A. Smith ◽  
Doerthe Tetzlaff ◽  
Lukas Kleine ◽  
Marco Maneta ◽  
Chris Soulsby
Keyword(s):  
Land Use ◽  
Large Scale ◽  
Overland Flow ◽  
Spatial Scales ◽  
Water Flux ◽  
Model Performance ◽  
Spatial And Temporal Scales ◽  
Groundwater Movement ◽  
Ne Germany ◽  
Water Partitioning

Abstract. Quantifying how vegetation mediates water partitioning at different spatial and temporal scales in complex, managed catchments is fundamental for long-term sustainable land and water management. Estimations from ecohydrological models conceptualizing how vegetation regulates the inter-relationships between catchment water storage dynamics, evapotranspiration losses, and recharge/runoff fluxes are needed to assess water availability for a range of ecosystem services; and evaluate how these might change under increasing extreme events, such as droughts. Currently, the feedback mechanisms between water and mosaics of different vegetation/land cover are not well understood across spatial scales and the effects of scale on the skill of ecohydrological models needs to be clarified. We used the tracer-aided ecohydrological model EcH2O-iso in an intensively monitored 66 km2 mixed land-use catchment in NE Germany to quantify water flux-storage-age interactions at four model-grid resolutions (250, 500, 750, and 1000 m). This used a fusion of field (including precipitation, soil water, groundwater, and stream isotopes) and remote sensed data in the calibration. Multi-criteria calibration across the catchment at each resolution revealed some differences in the estimation of fluxes, storages, and water ages. Larger grid-resolutions were unable to replicate observed streamflow and distributed isotope dynamics in the way smaller pixels could. However, using isotope data in the calibration still helped in constraining the estimation of fluxes, storage and water ages at coarser resolutions. Despite using the same data and parameterisation for calibration at different grid resolutions, the modelled proportion of fluxes differed slightly at each resolution, with coarse models simulating higher evapotranspiration, lower relative transpiration, increased overland flow, and slower groundwater movement. Although the coarser resolutions also revealed higher uncertainty and lower overall model performance, the overall results were broadly consistent. The study shows that tracers provide effective calibration constraints on larger resolution ecohydrological modelling and help understand the influence of grid-resolution on the simulation of vegetation-soil interactions. This is essential in interpreting associated uncertainty in estimating land-use influence on large-scale blue (ground and surface water) and green (vegetation and evaporated water) fluxes, particularly for future environmental change.

scholarly journals Quantifying the effects of land use and model scale on water partitioning and water ages using tracer-aided ecohydrological models

2021 ◽  
Vol 25 (4) ◽  
pp. 2239-2259
Author(s):  
Aaron Smith ◽  
Doerthe Tetzlaff ◽  
Lukas Kleine ◽  
Marco Maneta ◽  
Chris Soulsby
Keyword(s):  
Land Use ◽  
Large Scale ◽  
Overland Flow ◽  
Spatial Scales ◽  
Water Flux ◽  
Model Performance ◽  
Remote Sensing Data ◽  
Spatial And Temporal Scales ◽  
Water Partitioning ◽  
Northeastern Germany

Abstract. Quantifying how vegetation mediates water partitioning at different spatial and temporal scales in complex, managed catchments is fundamental for long-term sustainable land and water management. Estimations from ecohydrological models conceptualising how vegetation regulates the interrelationships between evapotranspiration losses, catchment water storage dynamics, and recharge and runoff fluxes are needed to assess water availability for a range of ecosystem services and evaluate how these might change under increasing extreme events, such as droughts. Currently, the feedback mechanisms between water and mosaics of different vegetation and land cover are not well understood across spatial scales, and the effects of different scales on the skill of ecohydrological models needs to be clarified. We used the tracer-aided ecohydrological model EcH2O-iso in an intensively monitored 66 km2 mixed land use catchment in northeastern Germany to quantify water flux–storage–age interactions at four model grid resolutions (250, 500, 750, and 1000 m). This used a fusion of field (including precipitation, soil water, groundwater, and stream isotopes) and remote sensing data in the calibration. Multicriteria calibration across the catchment at each resolution revealed some differences in the estimation of fluxes, storages, and water ages. In general, model sensitivity decreased and uncertainty increased with coarser model resolutions. Larger grids were unable to replicate observed streamflow and distributed isotope dynamics in the way smaller pixels could. However, using isotope data in the calibration still helped constrain the estimation of fluxes, storage, and water ages at coarser resolutions. Despite using the same data and parameterisation for calibration at different grid resolutions, the modelled proportion of fluxes differed slightly at each resolution, with coarse models simulating higher evapotranspiration, lower relative transpiration, increased overland flow, and slower groundwater movement. Although the coarser resolutions also revealed higher uncertainty and lower overall model performance, the overall results were broadly similar. The study shows that tracers provide effective calibration constraints on larger resolution ecohydrological modelling and help us understand the influence of grid resolution on the simulation of vegetation–soil interactions. This is essential in interpreting associated uncertainty in estimating land use influence on large-scale “blue” (ground and surface water) and “green” (vegetation and evaporated water) fluxes, particularly for future environmental change.

scholarly journals Comparison of generalized non-data-driven lake and reservoir routing models for global-scale hydrologic forecasting of reservoir outflow at diurnal time steps

2020 ◽  
Vol 24 (5) ◽  
pp. 2711-2729 ◽  
Author(s):  
Joseph L. Gutenson ◽  
Ahmad A. Tavakoly ◽  
Mark D. Wahl ◽  
Michael L. Follum
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Model Performance ◽  
Global Scale ◽  
Army Corps ◽  
Time Step ◽  
Large Spatial Scale ◽  
Reservoir Routing ◽  
Routing Methods ◽  
Improved Model

Abstract. Large-scale hydrologic forecasts should account for attenuation through lakes and reservoirs when flow regulation is present. Globally generalized methods for approximating outflow are required but must contend with operational complexity and a dearth of information on dam characteristics at global spatial scales. There is currently no consensus on the best approach for approximating reservoir release rates in large spatial scale hydrologic forecasting, particularly at diurnal time steps. This research compares two parsimonious reservoir routing methods at daily steps: Döll et al. (2003) and Hanasaki et al. (2006). These reservoir routing methods have been previously implemented in large-scale hydrologic modeling applications and have been typically evaluated seasonally. These routing methods are compared across 60 reservoirs operated by the U.S. Army Corps of Engineers. The authors vary empirical coefficients for both reservoir routing methods as part of a sensitivity analysis. The method proposed by Döll et al. (2003) outperformed that presented by Hanasaki et al. (2006) at a daily time step and improved model skill over most run-of-the-river conditions. The temporal resolution of the model influences model performances. The optimal model coefficients varied across the reservoirs in this study and model performance fluctuates between wet years and dry years, and for different configurations such as dams in series. Overall, the method proposed by Döll et al. (2003) could enhance large-scale hydrologic forecasting, but can be subject to instability under certain conditions.

scholarly journals E-DATA: A Comprehensive Field Campaign to Investigate Evaporation Enhanced by Advection in the Hyper-Arid Altiplano

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 745 ◽  
Author(s):  
Francisco Suárez ◽  
Felipe Lobos ◽  
Alberto de la Fuente ◽  
Jordi Vilà-Guerau de Arellano ◽  
Ana Prieto ◽  
...  
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Open Water ◽  
Water Evaporation ◽  
Distributed Temperature Sensing ◽  
Field Campaign ◽  
Spatial And Temporal Scales ◽  
Airborne Measurements ◽  
Dry Air ◽  
Evaporation Dynamics

In the endorheic basins of the Altiplano, water is crucial for sustaining unique ecological habitats. Here, the wetlands act as highly localized evaporative environments, and little is known about the processes that control evaporation. Understanding evaporation in the Altiplano is challenging because these environments are immersed in a complex topography surrounded by desert and are affected by atmospheric circulations at various spatial scales. Also, these environments may be subject to evaporation enhancement events as the result of dry air advection. To better characterize evaporation processes in the Altiplano, the novel Evaporation caused by Dry Air Transport over the Atacama Desert (E-DATA) field campaign was designed and tested at the Salar del Huasco, Chile. The E-DATA combines surface and airborne measurements to understand the evaporation dynamics over heterogeneous surfaces, with the main emphasis on the open water evaporation. The weather and research forecasting model was used for planning the instruments installation strategy to understand how large-scale air flow affects evaporation. Instrumentation deployed included: meteorological stations, eddy covariance systems, scintillometers, radiosondes and an unmanned aerial vehicle, and fiber-optic distributed temperature sensing. Additional water quality and CO2 fluxes measurements were carried out to identify the link between meteorological conditions and the biochemical dynamics of Salar del Huasco. Our first results show that, in the study site, evaporation is driven by processes occurring at multiple spatial and temporal scales and that, even in the case of available water and energy, evaporation is triggered by mechanical turbulence induced by wind.

Resource selection in a high-altitude rangeland equid, the kiang (Equus kiang): influence of forage abundance and quality at multiple spatial scales

2014 ◽  
Vol 92 (3) ◽  
pp. 239-249 ◽  
Author(s):  
Antoine St-Louis ◽  
Steeve D. Côté
Keyword(s):  
High Altitude ◽  
Resource Selection ◽  
Large Scale ◽  
Plant Biomass ◽  
Spatial Scales ◽  
Plant Quality ◽  
The Tibetan Plateau ◽  
Higher Plant ◽  
Feeding Site ◽  
Spatial And Temporal Scales

Herbivores foraging in arid and seasonal environments often face choices between plant patches varying in abundance and nutritional quality at several spatial and temporal scales. Because of their noncompartmented digestive system, equids typically rely on abundant forage to meet their nutrient requirements. In forage-limited environments, therefore, scarcity of food resources represents a challenge for wild equids. We investigated hierarchical resource-selection patterns of kiangs (Equus kiang Moorcroft, 1841), a wild equid inhabiting the high-altitude steppes of the Tibetan Plateau, hypothesizing that vegetation abundance would be the main factor driving resource selection at a large scale and that plant quality would influence resource selection at finer scales. We investigated resource-selection patterns at three spatial levels (habitat, feeding site, and plant (vegetation groups, i.e., grasses, sedges, forbs, and shrubs)) during summer and fall. At the habitat level, kiangs selected both mesic and xeric habitats in summer and only xeric habitats (plains) during fall. At the feeding-site level, feeding sites had higher plant biomass and percentage of green foliage than random sites in the same habitats. At the plant level, grasses were selected over forbs and shrubs, and sedges were used in proportion to their availability during all seasons. Our results indicate that resource-selection patterns in kiangs vary across scales and that both forage abundance and quality play a role in resource selection. Plant quality appeared more important than hypothesized, possibly to increase daily nutrient intake in forage-limited and highly seasonal high-altitude rangelands.

scholarly journals The impact of local surface changes in Borneo on atmospheric composition at wider spatial scales: coastal processes, land-use change and air quality

2011 ◽  
Vol 366 (1582) ◽  
pp. 3210-3224 ◽  
Author(s):  
J. A. Pyle ◽  
N. J. Warwick ◽  
N. R. P. Harris ◽  
Mohd Radzi Abas ◽  
A. T. Archibald ◽  
...  
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Land Use Change ◽  
Spatial Scales ◽  
Model Performance ◽  
Atmospheric Composition ◽  
Model Studies ◽  
Uncertainty Model ◽  
Emission Changes ◽  
The Impact

We present results from the OP3 campaign in Sabah during 2008 that allow us to study the impact of local emission changes over Borneo on atmospheric composition at the regional and wider scale. OP3 constituent data provide an important constraint on model performance. Treatment of boundary layer processes is highlighted as an important area of model uncertainty. Model studies of land-use change confirm earlier work, indicating that further changes to intensive oil palm agriculture in South East Asia, and the tropics in general, could have important impacts on air quality, with the biggest factor being the concomitant changes in NO x emissions. With the model scenarios used here, local increases in ozone of around 50 per cent could occur. We also report measurements of short-lived brominated compounds around Sabah suggesting that oceanic (and, especially, coastal) emission sources dominate locally. The concentration of bromine in short-lived halocarbons measured at the surface during OP3 amounted to about 7 ppt, setting an upper limit on the amount of these species that can reach the lower stratosphere.

Tactical Predictions of Shoreline Oiling Probability via Machine Learning Models and Satellite-Derived Surface Oil Analysis Products

2014 ◽  
Vol 2014 (1) ◽  
pp. 660-672
Author(s):  
Zachary Nixon
Keyword(s):  
Machine Learning ◽  
Spatial Scales ◽  
Information Service ◽  
Habitat Type ◽  
Model Performance ◽  
Boosted Regression Trees ◽  
Oil Analysis ◽  
Spatial Indices ◽  
Spatial And Temporal Scales ◽  
Trajectory Models

ABSTRACT For significant oil spills in remote areas with complex shoreline geometry, apportioning Shoreline Cleanup Assessment Technique (SCAT) survey effort is a complicated and difficult task. Aerial surveys are often used to select shoreline areas for ground survey after an initial prioritization based upon anecdotal reports or trajectory models, but aerial observers may have difficulty locating cryptic surface shoreline oiling in vegetated or other complex environments. In dynamic beach environments, stranded shoreline oiling may be rapidly buried, making aerial observation difficult. A machine learning-based model is presented for estimating shoreline oiling probabilities via satellite-derived surface oil analysis products, wind summary data, and shoreline habitat type and geometry data. These inputs are increasingly available at spatial and temporal scales sufficient for tactical use, enabling model predictions to be generated within hours after satellite remote sensing products are available. The model was constructed using SCAT data from the Deepwater Horizon oil spill, satellite-derived surface oil analysis products generated during the spill by NOAA's National Environmental Satellite, Data, and Information Service (NESDIS) using a variety of satellite platforms of opportunity, and available shoreline geometry, character, and other preexisting data. The model involves the generation of set of spatial indices of relative over-water proximity of surface oil slicks based upon the satellite-derived analysis products. The model then uses boosted regression trees (BRT), a flexible and relatively recently developed modeling methodology, to generate calibrated estimates of probability of subsequent shoreline oiling based upon these indices, wind climatological data over the time period of interest, and other shoreline data. The model can be implemented via data preparation in any Geographic Information System (GIS) software coupled with the open-source statistical computing language, R. The model is entirely probabilistic and makes no attempt to reproduce the physics of oil moving through the environment, as do trajectory models. It is best used in concert with such models to make estimates at different spatial scales, or when time and data requirements make implementation of fine-scale trajectory modeling impractical for tactical use. The details of model development implementation and assessments of model performance and limitations are presented.

scholarly journals Editorial: SESMO Special Issues

2021 ◽  
Vol 2 ◽  
pp. 18040
Author(s):  
Tony Jakeman ◽  
Ioannis Athanasiadis ◽  
Serena Hamilton
Keyword(s):  
Land Use ◽  
Large Scale ◽  
Best Practice ◽  
Spatial Scales ◽  
Open Access Journal ◽  
Environmental Research ◽  
Special Issue ◽  
Environmental Systems ◽  
Challenges And Opportunities ◽  
Institute Of Technology

As the journal nears the end of its second official year, we are pleased to start accepting submissions to our first two Special Issues. The first Special Issue is on Resilience of complex coupled Socio-Technical-Environmental systems through the modeling lens with guest editors Tatiana Filatova, Tina Comes (4TU Resilience Engineering Centre), Christoph Hoelscher (ETH Zurich) and Juliet Mian (Resilence Shift). This Special Issue aims to bring together cutting-edge research and international practice to offer insights into the latest scientific modelling methods, gaps, challenges and opportunities and best practice examples relating to operationalising resilience across a range of socio-technical-environmental applications. The second Special Issue is on Large-scale behavioural models of land use change with guest editors Calum Brown (Karlsruhe Institute of Technology), Tatiana Filatova (University of Twente), Birgit Müller (Helmholtz Centre for Environmental Research – UFZ), and Derek Robinson (University of Waterloo). This Special Issue is focussed on better understanding and modelling of temporal or spatial scales in land use dynamics.   We invite new proposals for Special Issues that fit within SESMO’s aims and scope. Our Special Issues are cohesive collections of articles focussed on a specific contemporary theme related to socio-environmental systems modelling. The Special Issue can build on previous work and research gaps, but can also explore new and emerging terrain relevant to our aims. Although the conceptualisation of a Special Issue may be initiated in a conference or workshop, it is critical that such a proposal also builds on the original dialogue. Articles should also be canvassed from across the globe. SESMO is an open access journal with no article processing or publication charges for authors. If you have a topic to propose, please contact us to discuss further.

scholarly journals Analysis and Reduction of Systematic Errors through a Seamless Approach to Modeling Weather and Climate

2010 ◽  
Vol 23 (22) ◽  
pp. 5933-5957 ◽  
Author(s):  
G. M. Martin ◽  
S. F. Milton ◽  
C. A. Senior ◽  
M. E. Brooks ◽  
S. Ineson ◽  
...  
Keyword(s):  
Time Scales ◽  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Spatial Scales ◽  
Full Range ◽  
Model Development ◽  
Model Performance ◽  
Systematic Errors ◽  
Wide Range

Abstract The reduction of systematic errors is a continuing challenge for model development. Feedbacks and compensating errors in climate models often make finding the source of a systematic error difficult. In this paper, it is shown how model development can benefit from the use of the same model across a range of temporal and spatial scales. Two particular systematic errors are examined: tropical circulation and precipitation distribution, and summer land surface temperature and moisture biases over Northern Hemisphere continental regions. Each of these errors affects the model performance on time scales ranging from a few days to several decades. In both cases, the characteristics of the long-time-scale errors are found to develop during the first few days of simulation, before any large-scale feedbacks have taken place. The ability to compare the model diagnostics from the first few days of a forecast, initialized from a realistic atmospheric state, directly with observations has allowed physical deficiencies in the physical parameterizations to be identified that, when corrected, lead to improvements across the full range of time scales. This study highlights the benefits of a seamless prediction system across a wide range of time scales.

scholarly journals Land use and landscape pattern impacts on water quality at multiple spatial scales in a subtropical large river

2021 ◽  
Author(s):  
Xiao Shu ◽  
Weibo Wang ◽  
Mingyong Zhu ◽  
Jilei Xu ◽  
Xiang Tan ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
River Water ◽  
Total Nitrogen ◽  
Landscape Pattern ◽  
Spatial Scales ◽  
Dry Season ◽  
Wet Season ◽  
Spatial And Temporal Scales ◽  
Multiple Spatial Scales

Abstract The coupling between land use/landscape pattern and water quality in river system varies across different spatial and temporal scales. It is important to understand the association between water quality and land use/landscape pattern across different spatial and temporal scales for the protection of water resources. Here, we measured seasonal water quality at 12 sub-basins in the upper reaches of the Han River (UHR) between 2010 and 2018. We conducted factor analysis and redundancy analysis to determine the links between land use and water quality at multiple spatial scales and to identify the main factors influencing water quality. We found that the concentration of nutrients, including total nitrogen, total phosphorus, nitrate-N, and ammonium-N were higher during the wet season than the dry season. Total nitrogen was identified as the main driver of nutrient pollution of UHR, whereas total phosphorus was identified as another potential nutrient pollutant. We also found that water quality parameters had a stronger related to land use types over the wet season than the dry season. Croplands and urban lands increased phosphorus concentrations of river water, whereas forest and grass lands decreased the nitrogen concentrations of river water at the sub-basins scale. Land use at riparian zone scales better explained variations in water quality than land use at sub-basin scales. The explained variations in landscape metrics were generally higher over the dry season compared to that over the wet season. The largest patch index and Shannon's diversity index were the main predictors of river water quality in UHR.

scholarly journals The application of science to the management of Atlantic salmon (Salmo salar): integration across scales

1998 ◽  
Vol 55 (S1) ◽  
pp. 303-311 ◽  
Author(s):  
John D Armstrong ◽  
James WA Grant ◽  
Harvey L Forsgren ◽  
Kurt D Fausch ◽  
Richard M DeGraaf ◽  
...  
Keyword(s):  
Atlantic Salmon ◽  
Life Histories ◽  
Large Scale ◽  
Scale Effects ◽  
Spatial Scales ◽  
Small Scale ◽  
Spatial And Temporal Scales ◽  
Management Plans ◽  
Broad Scale ◽  
The Way

The need for integration across spatial and temporal scales in applying science to the management of Atlantic salmon is considered. The factors that are currently believed to affect the production of anadromous adult Atlantic salmon (synthesized from recent reviews) are arranged in a hierarchy in which any given process overrides those processes at lower levels. There is not a good correlation between levels in the process hierarchy and levels in hierarchies of scale. This demonstrates the importance of integrating across scales in identifying the optimum foci for targeting management action. It is not possible to generalize on the need for integration across scales within management plans. This is because of the complex ecology of salmon, the broad range of characteristics of the systems of which they are a part, and the fact that both local scale and broad scale management can have broad scale effects. Many uncertainties remain regarding the large-scale components of the ecology of salmon, the way that small-scale mechanisms interact with life histories, and the way that different factors interact to limit production of fish. When more is understood of these processes, it is likely that generalized rules might be developed to predict the management requirements for stream systems. In the meantime, it is essential that there is good integration among managers working at different scales and it is important that management systems operating at all spatial scales include high-calibre expertise to compensate for the present paucity of general rules.

Sign in / Sign up

Export Citation Format

Share Document