The session will give time to both laboratory and field monitoring studies, preferably quantitative, and based on novel measurement and modelling techniques. We invite pioneering research that includes hydrological information in local and regional hazard assessment. Moreover, we welcome studies that incorporate hydrological process knowledge in the geotechnical analysis and modelling setting the next step to improve landslide hazard analysis.
A large number of micropollutants and their transformation products veterinary and human pharmaceuticals, personal care products, pesticides and biocides, chlorinated compounds, heavy metals, emerging contaminants such as PFASs pose a risk for soil, groundwater and surface water.
The large diversity of compounds and of their sources makes the quantification of their occurrence in the terrestrial and aquatic environment across space and time a challenging task. Effective strategies to protect water resources from micropollutants are still lacking because the basic processes that contribute to their persistence and mobility in the aquatic environments are poorly understood. Innovative experimental studies in conjunction with modeling are urgently needed to fill these knowledge gaps to asses risks and develop remediation schemes.
This session invites contributions that improve our quantitative understanding of the sources and pathways, mass fluxes, the fate and transport of micropollutants in the soil-groundwater-river continuum. Topics cover: - Novel sampling and monitoring concepts and devices - New analytical methods for micropollutants such as non-target screening - Experimental studies and modelling approaches to quantify diffuse and point source inputs - Novel monitoring approaches such as non-target screening as tools for improving processes understanding and source identification such as industries - Comparative fate studies on parent compounds and transformation products - Diffuse sources and re- emerging chemicals - Biogeochemical interactions and impact on micropollutant behaviour.
Land use and climate change as well as legal requirements e. Sources and pathways of nutrients and pollutants have to be characterized to understand and manage the impacts of their enrichment in river systems. Additionally, water quality assessment needs to cover the chemical and ecological status to link the hydrological view to aquatic ecology. Models can help to optimize monitoring schemes. Moreover, model-based water quality calculations are affected by errors in input data, model errors, inappropriate model complexity and insufficient process knowledge or implementation.
Therefore there is a strong need for advances in water quality models and to quantify and reduce uncertainties in water quality predictions. Additionally, models should be capable of representing changing land use and climate conditions, which is a prerequisite to meet the increasing needs for decision making. This session aims to bring scientist together who work on experimental as well as on modelling studies to improve the prediction and management of water quality constituents with the focus on nutrients, organic matter, algae or sediments at the catchment scale.
Contributions are welcome that cover the following issues: - Experimental and modelling studies on the identification of sources, hot spots and pathways of nutrients and pollutants at the catchment scale - New approaches to develop efficient water quality monitoring schemes - Innovative monitoring strategies that support both process investigation and model performance - Advanced modelling tools integrating catchment as well as in-stream processes - Observational and modelling studies at catchment scale that relate and quantify water quality changes to changes in land use and climate - Measurements and modelling of abiotic and biotic interaction and feedback involved in the transport and fate of nutrients and pollutants at the catchment scale - Catchment management: pollution reduction measures, stakeholder involvement, scenario analysis for catchment management.
Agriculture intensification causes worldwide increase of rivers, lakes and groundwater aquifers pollution. Pollutants may originate from various sources related to different types of agriculture activities including cultivation, aquaculture, livestock and dairy farms and related food-processing industries, and partitioning their respective contribution to water bodies remains challenging. Degradation of water quality is associated with both macronutrients and micro-pollutants originating from the inefficient use of chemical and organic fertilizers, and transport and persistence of pesticides and antibiotics.
Therefore, identification of spatial and seasonal variations of pollutant sources and loads at the catchment scale is critical for better understanding human and environmental impacts of agro-contaminants, and eventually improving land management practices to protect water quality. This session is focused on the use of hydro geo chemical and stable isotope tracers in quantifying agro-contaminant sources and transport but other related studies are also welcome. Join us! Active poster sessions: a poster walk-through is organized at , poster authors will have 1—2 minutes to present their poster.
Historical and contemporary mining activities generate significant volumes of contaminated waste that can have wide-ranging implications, including potential lethal and sub-lethal effects on aquatic biota, adverse effects on surface waters used for drinking water and irrigation, and overall degradation of water bodies used for recreation and other purposes. Contaminants are dispersed in river catchments by a variety of physical, chemical and biological pathways and processes.
Submissions from a variety of subfields are welcome, including research into mine water treatment and mine waste remediation practices. We also welcome submissions that focus on a variety of contaminant types including, but not limited to, metals, metalloids, rare earth elements and sulfate. Bayesian approaches have become increasingly popular in water quality modelling, thanks to their ability to handle uncertainty comprehensively data, model structure and parameter uncertainty and as flexible statistical and data mining tools.
Furthermore, graphical Bayesian Belief Networks can be powerful decision support tools that make it relatively easy for stakeholders to engage in the model building process. The aim of this session is to review the state-of-the-art in this field and compare software and procedural choices in order to consolidate and set new directions for the emerging community of Bayesian water quality modellers.
Surface water quality deterioration is typically assessed and managed at the catchment scale. Management decisions rely on process knowledge and understanding of cause-effect relationships to be effective. However, the dynamics of solute and particulate concentrations integrate a multitude of hydrological and biogeochemical processes interacting at different temporal and spatial scales, which are difficult to assess using local field experiments. Hence, time series of water quality observed at the outlet of catchments can be highly beneficial to understand these processes.
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Recent advances in this field have used concentration-discharge relationships to infer the interplay between hydrological and biogeochemical controls, both in the terrestrial part of catchments and in the river network. Long-term time series of nutrient input-output relationships help understand nutrients legacy effects and catchments response times. High-frequency observations allow understanding the fine structure of concentration dynamics, including flowpath contributions during runoff events and ecological controls on diel cycles.
When multiple catchments are monitored, it is possible to relate metrics from concentration time series to catchment descriptors. This session aims to bring together studies using data-driven analysis of river concentration time series to infer solute and particulate export mechanisms. We strongly encourage studies that use findings from data-driven analysis to build conceptual and process-based models.
Presentations of the following topics are invited: - Interpretation of C-Q relationships - Long-term changes of nutrient inputs, outputs and apparent nutrient travel times - Co-variance of solute and particulate concentrations and their ecohydrological controls - Instream processes and river network effects on solute concentrations - Utilizing time series of compound-specific isotopic fingerprints - Time series analysis of emerging contaminants such as pesticides or micropollutants.
Snow and ice can capture and store contaminants both local and global in origin. The decrease in glacier cover, snow cover and sea ice in response to climate affects cycling of airborne impurities in polar and alpine environments, accelerating and enhancing their release. In this context snow and ice act as a secondary source for numerous organic and inorganic atmospheric contaminants that were deposited on their surface during recent decades, including persistent organic pollutants, radioactive species, microplastics, pesticides, and heavy metals.
The release of contaminants from snow and ice to glacier forefields, rivers and seas might pose a hazard to these ecosystems and to human health, particularly under accelerated melt conditions. Identification and assessment of this hazard relies, for each contaminant class, on the understanding of processes that control their accumulation, release and downstream transport.
The physical and chemical forms in which contaminants are removed from the atmosphere and hydrosphere may further affect their interactions with mineral substances and biota. Existing studies suggest that the contaminant release process is not linear, and that interactions between meltwater, supraglacial debris and glacial microbiology may be crucial in the accumulation and transport of contaminants in glacier catchments. For example, evidence is mounting that cryoconite can efficiently accumulate radionuclides from anthropogenic sources to potentially hazardous levels in glaciers around the world.
At the same time, the high biological activity present in cryoconite could enhance the degradation of organic pollutants, with important implications for remediation. A portion of contaminants released from glaciers may also be stored in their proglacial zones as shown by the very high concentrations of radionuclides found by several recent studies. The effects of contaminant transport on the pro-glacial environment and downstream communities remain uncertain, but improved understanding of the impacts of contaminants in land ice, sea ice, and snow is clearly warranted.
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The session aims to contribute to the development of this emerging and interdisciplinary field, welcoming presentations from across cryospheric, hydrological, and biogeochemical sciences, and other research areas. Hydrological extremes droughts and floods , have major impacts on society and ecosystems and are expected to increase in frequency and severity with climate change. Although both at the extreme end of the hydrological spectrum, floods and droughts are governed by different processes, which means that they operate on different spatial and temporal scales and that different analysis methods and indices are needed to characterise them.
But there are also many similarities and links between the two extremes that are increasingly being studied. This general session on hydrological extremes aims to bring together the two communities in order to learn from the similarities and differences between flood and drought research. We aim to increase the understanding of the governing processes of both hydrological extremes, find robust ways of modelling and analysing floods and droughts, assess the influence of global change including climate change, land use change, and other anthropogenic influences on floods and droughts, and study the socio-economic and environmental impacts of hydrological extremes.
We welcome submissions of insightful studies of floods or droughts, and especially encourage abstracts that cover both extremes. Excellent submissions of early-career researchers that are deemed important contributions to the session topics will be classified as solicited talks, as a "label of excellence". The space-time dynamics of floods are controlled by atmospheric, catchment, river system and anthropogenic processes and their interactions. The natural oscillatory behaviour of floods between flood-rich and flood-poor periods superimpose with anthropogenic climate change and human interventions in river morphology and land uses.
In addition, flood risk is further shaped by continuous changes in exposure and vulnerability. Despite more frequent exploratory analyses of the changes in spatio-temporal dynamics of flood hazard and risk, it remains unclear how and why these changes are occurring. The scope of this session is to report when, where, how detection and why attribution changes in the space-time dynamics of floods occur.
Of particular interest is what drivers are responsible for observed changes. Presentations on the impact of climate variability and change, land use changes and morphologic changes in streams, as well as on the role of pre-flood catchment conditions in shaping flood hazard and risk are welcome. Furthermore, contributions on the impact of socio-economic and structural factors on past and future risk changes are invited.
The session will further stimulate scientific discussion on flood change detection and attribution. Specifically, the following topics are of interest for this session: - Decadal oscillations in rainfall and floods - Process-informed extreme value statistics - Interactions between spatial rainfall and catchment conditions shaping flood patterns - Detection and attribution of flood hazard changes: atmospheric drivers, land use controls and river training, among others - Changes in flood risk: urbanisation of flood prone areas, implementation of risk mitigation measures, changes of economic, societal and technological drivers, flood vulnerability, among others.
Catchments are systems that often consist of an organized architecture of typical patterns of topography, soils, vegetation and flow networks. These patterns are largely the geomorphic, and biologic response to temporally and spatially variable environmental conditions or human interference. This organization of catchment components controls the storage and release of water and nutrients.
We present experimental and modeling studies that analyze the role of catchment storage, catchment mixing and hyporheic exchange fluxes and determine how they control hydrologic and hydrochemical catchment response in time and space.
Estimates of water availability and flooding risks remain one of the central scientific and societal challenges of the 21st century. The complexity of this challenge arises particularly from transient boundary conditions: Increasing atmospheric greenhouse gas concentrations lead to global warming and an intensification of the water cycle and finally to shifts in the temporal and spatial distribution of precipitation and terrestrial water availability.
Likewise, large-scale land use changes impact and alter regional atmospheric circulation, thereby local precipitation characteristics and again terrestrial water availability. Also the feedbacks between the interlinked terrestrial and atmospheric processes on different spatial and temporal scales are still poorly understood.
We especially welcome contributions on the development of novel methods and methodologies to quantify hydrological change. Further aspects of this topic comprise particularly: - Robustness of hydrological impact assessments based on scenarios using downscaled climate model — hydrology model modelling chains. In the current context of global change, assessing the impact of climate variability and changes on hydrological systems and water resources is increasingly crucial for society to better-adapt to future shifts in water resources as well as extreme conditions floods and droughts.
Internal climate modes of variability e. ENSO, NAO, AMO and their impact on the continent are not properly reproduced in the current global climate models, leading to large underestimations of decadal climate and hydroclimatic variability at the global scale. At the same time, hydrological response strongly depends on catchment properties, whose interactions with climate variability are little understood at the decadal timescales. These factors altogether reduce significantly our ability to understand long-term hydrological variability and to improve projection and reconstruction of future and past hydrological changes on which improvement of adaption scenarios depends.
We welcome abstracts capturing recent insights for understanding past or future impacts of large-scale climate variability on hydrological systems and water resources as well as newly developed projection and reconstruction scenarios. Results from model intercomparison studies are encouraged. Global, continental and other large scale hydrological research is very important in many different contexts. Examples include increasing understanding of the climate system and water cycle, assessment of water resources in a changing environment, hydrological forecasting and water resource management.
HESS - Socio-hydrological modelling: a review asking "why, what and how?"
We invite contributions from across the atmospheric, meteorological and hydrological communities. Large samples of catchments can provide insights into hydrological processes that cannot be obtained from small samples. This session aims to showcase recent data- and model-based efforts on large-sample hydrology, which advance the characterisation, understanding and modelling of hydrological diversity. We welcome abstracts from a wide range of fields, including catchment hydrology, land-surface modelling, eco-hydrology, groundwater hydrology and hydrometeorology, which seek to explore: 1.
Landscape characterisation - hydrological processes are shaped by the interplay of landscape attributes such as topography, climate, vegetation, soil, geology: how to better understand this interplay using available data sets? Generalisation from the catchment to continental scale: how can we use large samples of catchments to refine process understanding and modelling at the regional to global scale? Hydrological similarity and catchment classification, including across borders 4.
Quantification and synthesis of data quality and uncertainty, including across borders 5. Identification and characterisation of dominant hydrological processes with limited data: how far can we get using hydrological signatures? Human intervention and land cover changes: how to characterise and account for these processes in large-sample studies? Revisiting hypotheses testing: testing the generality of existing hypotheses particularly those originally formulated on small samples of catchments using large samples We encourage abstracts addressing any of these challenges, in particular those aiming at reducing geographical gaps i.
Our invited speaker for is Vazken Andreassian. In addition to this session, we will organise a splinter meeting to discuss and coordinate the production of large-sample data sets. The session and the splinter meeting will be organised in the framework of the Panta Rhei Working Group on large-sample hydrology.
Since early work on the assessment of global, continental and regional-scale water balance components, many studies use different approaches including global models, remote sensing, observation data or combination of these. They attempted to estimate the amount of water that evapotranspires, runs-off into the Ocean or is retained in water storages on the terrestrial part of the Earth.
However, previous estimates in literature e. Contributions could focus on any of the water balance components or in an integrative manner, for either Land, Ocean or both. Assessments of uncertainty of water balance components are highly welcome. Geodesy is becoming increasingly important for observing the hydrological cycle and its effects on solid Earth shape. Signals in geodetic data have revealed water's influence on other geophysical processes including earthquakes, volcanos, land subsidence, mountain uplift, and other aspects of long- and short-term vertical land motion.
GPS and InSAR measurements, for example, respectively provide high temporal and spatial resolution to study natural hydrologically-related deformation and monitor anthropogenic groundwater extraction and recharge, and GRACE is helping to track changes in the global terrestrial water storage. Signals of loading from changes in surface and groundwater storage are seen from basin to continental scale. A wide range of processes in the earth system directly affect geodetic observations. Changes in regional sea level and ocean circulation are observed by altimetry and gravimetry.
Mass changes in the ice sheets and glaciers are detectable by both geometrical and gravimetric techniques. And other novel applications of geodetic techniques are emerging in many fields. In addition, individual sensor recordings are often affected by high-frequency variability caused by, e.
This session invites a wide array of contributions which showcase the use of geodesy for Earth science and climate applications. Since the use of geodetic techniques is not always straightforward, we encourage authors to think of creative ways to make their findings, data and software more readily accessible to other communities in hydrology, ocean, cryospheric, atmospheric and climate sciences.
With author consent, highlights from the oral and poster session will be tweeted with a dedicated hashtag during the conference in order to increase the impact of the session. Hydroinformatics has emerged over the last decade to become a recognised and established field of independent research within the hydrological sciences. Hydroinformatics is concerned with the development and hydrological application of mathematical modelling, information technology, high-performance computing, systems science and computational intelligence tools. It provides the computer-based decision-support systems that are now entering more and more into the offices of consulting engineers, water authorities and government agencies.
Tools for capturing data, on both a mega-scale and a milli-scale, are immense and still emerging. As a result we have to face the challenges of Big Data: large data sets, both in size and complexity. Methods and technologies for data handling, visualization and knowledge acquisition are more and more often referred to as Data Science. The aim of this session is to provide an active forum in which to demonstrate and discuss the integration and appropriate application of emergent computational technologies in a hydrological modelling context.
Topics of interest are expected to cover a broad spectrum of theoretical and practical activities that would be of interest to hydro-scientists and water-engineers. Applications could belong to any area of hydrology or water resources: rainfall-runoff modelling, flow forecasting, sedimentation modelling, analysis of meteorological and hydrologic data sets, linkages between numerical weather prediction and hydrologic models, model calibration, model uncertainty, optimisation of water resources, etc.
Many environmental and hydrological problems are spatial or temporal, or both in nature. Spatio-temporal analysis allows identifying and explaining large-scale anomalies which are useful for understanding hydrological characteristics and subsequently predicting hydrological events. Temporal information is sometimes limited; spatial information, on the other hand has increased in recent years due technological advances including the availability of remote sensing data. This development has motivated new research efforts to include data in model representation and analysis.
Geostatistics is the discipline that investigates the statistics of spatially extended variables. Spatio-temporal analysis is at the forefront of geostatistical research these days, and its impact is expected to increase in the future. This trend will be driven by increasing needs to advance risk assessment and management strategies for extreme events such as floods and droughts, and to support both short and long-term water management planning. The session is targeted at both hydrologists and statisticians interested in the spatial and temporal analysis of hydrological events, extremes, and related hazards, and it aims to provide a forum for researchers from a variety of fields to effectively communicate their research.
Given the broad scope of this session, the topics of interest include the following non-exclusive list of subjects: 1. New and innovative geostatistical applications in spatial modeling, spatio-temporal modeling, spatial reasoning and data mining. Spatio-temporal dynamics of natural events e. Generalization and optimization of spatial models including monitoring networks optimization. Applications of copulas on the identification of spatio-temporal relationships. Spatial analysis and predictions using Gaussian and non-Gaussian models. Spatial and spatio-temporal covariance application revealing links between hydrological variables and extremes.
Prediction on regions of unobserved or limited data where gridded and point simulated data from physical-based models is available. Generalized extreme value distributions used to model extremes for spatial event analysis. Geostatistical characterization of uncertainties. Bayesian Geostatistical Analysis. Citizen Observatories, crowdsourcing, and innovative sensing techniques are used increasingly in water resources monitoring, especially when dealing with natural hazards.
In this way new knowledge for monitoring, modelling, and management of water resources and their related hazards is obtained. This session is dedicated to multidisciplinary contributions, especially those that are focused on the demonstration of the benefit of the use of Citizen Observatories, crowdsourcing, and innovative sensing techniques for monitoring, modelling, and management of water resources. The research presented might focus on, but not limited to, innovative applications of Citizen Observatories, crowdsourcing, innovative and remote sensing techniques for i water resources monitoring; ii hazard, exposure, vulnerability and risk mapping; iii development of disaster management and risk reduction strategies.
Research studies might also focus on the development of technology, modelling tools, and digital platforms within research projects. The session aims to serve a diverse community of research scientists, practitioners, end users, and decision makers. Submissions that look into issues related to the benefits and impacts of innovative sensing on studies of climate change, anthropogenic pressure, as well as ecological and social interactions are highly desired. Early stage researchers are strongly encouraged to present their research.
This session aims to bring together researchers working with big data sets generated from monitoring networks, extensive observational campaigns and detailed modeling efforts across various fields of geosciences. Topics of this session will include the identification and handling of specific problems arising from the need to analyze such large-scale data sets, together with methodological approaches towards semi or fully automated inference of relevant patterns in time and space aided by computer science-inspired techniques. Many situations occur in Geosciences where one wants to obtain an accurate description of the present, past or future state of a particular system.
Examples are prediction of weather and climate, assimilation of observations, or inversion of seismic signals for probing the interior of the planet. One important aspect is the identification of the errors affecting the various sources of information used in the estimation process, and the quantification of the ensuing uncertainty on the final estimate.
The session is devoted to the theoretical and numerical aspects of that broad class of problems. A large number of topics are dealt with in the various papers to be presented: algorithms for assimilation of observations, and associated mathematical aspects particularly, but not only, in the context of the atmosphere and the ocean , predictability of geophysical flows, with stress on the impact of initial and model errors, inverse problems of different kinds, and also new aspects at the crossing between data assimilation and data-driven methods.
Applications to specific physical problems are presented. This interdisciplinary session welcomes contributions on novel conceptual approaches and methods for the analysis of observational as well as model time series and associated uncertainties from all geoscientific disciplines. Methods to be discussed include, but are not limited to: - linear and nonlinear methods of time series analysis - time-frequency methods - predictive approaches - statistical inference for nonlinear time series - nonlinear statistical decomposition and related techniques for multivariate and spatio-temporal data - nonlinear correlation analysis and synchronisation - surrogate data techniques - filtering approaches and nonlinear methods of noise reduction We particularly encourage submissions addressing the problem of uncertainty of geoscientific time series and its treatment in the context of statistical and dynamical analysis, including: - representation of time series with uncertain dating in particular paleoclimatic records from ice cores, sediments, speleothems etc.
Drought and water scarcity are important issues in many regions of the Earth, requiring innovative hydro-meteorological monitoring, modelling and forecasting tools to evaluate the complex impacts on the availability and quality of water resources. While drought describes a natural hazard, water scarcity is related to long-term unsustainable use of water resources and associated socio-economic aspects. Both phenomena are, however, closely linked, with the complex interrelationship requiring careful attention.
While an increase in the severity and frequency of droughts can lead to water scarcity situations, particularly in regions that are already water stressed, overexploitation of available water resources can exacerbate the consequences of droughts. In the worst case, this can lead to long-term environmental and socio-economic impacts. Particular attention should, therefore, be paid to the feedbacks between these two phenomena, including the potential impacts of climate change.
It is therefore necessary to improve both monitoring and sub-seasonal to seasonal forecasting for droughts and water availability, and to develop innovative indicators and methodologies that translate the information provided into effective drought early warning and risk management. These include, but are not limited to, precipitation, snow cover, soil moisture, streamflow, groundwater levels and extreme temperatures.
The development and implementation of drought indicators meaningful to decision making processes, and ways of presenting and explaining them to water managers, policy makers and other stakeholders, are further issues to be addressed. Particularly welcome are applications and real-world case studies in regions subject to significant water stress, where the importance of drought warning, supported through state-of-the-art monitoring and forecasting of water resources availability is likely to become more important in the future.
Many water management sectors are already having to cope with extreme weather events, climate variability and change. For this purpose, climate services provide science-based and user-specific information on possible impacts. Such information can be based on weather forecasts or on climate projections. Modeled time series of total population for different values of the tested parameters. All subplots correspond to one tested parameter, the separate lines represent model outcome for a given parameter. It is not just the timing and the magnitude We have performed a sensitivity analysis in order to assess of the population time series that is affected when parameters alternate realities that the socio-hydrologic model can gen- are varied.
It appears that the model is able to simulate three erate and to identify sensitive parameters of the model. Ta- different modes of a socio-hydrologic system, i. Figure 12 shows the vari- different parametric perturbations. In most cases, the param- ation in one outcome, variable, namely population, as a result eter selections lead to outcomes that are relatively close to of the variation of parameters one at a time.
Each subfigure the best fit with reality, i. However, perturbations with several pa- the 15 parameters is varied within the ranges prescribed in rameters e. It shows that not all parameters have a significant www. Sensitivity index Si for all parameters, indicating the sensitivity of population N , irrigated area A, storage S, wetland storage W and environmental awareness E to the parameter selection. Figure 13 shows the sensitivity index of all system model The sensitivity analysis shows that the model results are outputs population, irrigated area, storage, wetland storage in some cases strongly affected by parameter selection.
It This means that the modeling framework may provide equifi- shows that wetland storage W and environmental awareness nal representations of a socio-hydrological reality. The value E are sensitive to only a few parameters. This is to be ex- of field data in such cases cannot be overemphasized. An- pected since only a few of the model equations are connected other interesting finding of the sensitivity analysis is the to W and E.
The parameters that have the largest influence discovery of three system modes that the model can repli- are the wetland leakage rate, the wetland recharge thresh- cate. This means that the framework allows the flexibility old and the wetland danger threshold. Population N, irrigated to model diverse socio-hydrological realities. This highlights area A and storage S are sensitive to more parameters. The how socio-hydrologic modeling might be used to simulate population outcome is highly sensitive to maximum effec- other coupled human—water systems.
These parame- The development of the model presented in this paper, in- ters limit the growth potential of the population. When this cluding the performed sensitivity analysis, shows the poten- is increased or decreased, it significantly affects the irriga- tial of using socio-hydrologic modeling to explain observed tion potential, the growth and the speed of saturation of the dynamics in human—water coupled systems. Our model basin. For example, with a larger natural population growth is fundamentally sound conceptually, and is in line with rate, it is likely that the carrying capacity of the system will other socio-hydrologic models e.
Finally, Fig. One of the modes is the optimal and most realistic of the outcomes, 4 Conclusions which is similar to Fig. The other mode is one of apparent This paper presents a socio-hydrologic modeling framework unbounded growth. When the natural population growth is that has contributed new insights into the drivers of the co- high, the population and the irrigated area start to grow ex- evolution in the Murrumbidgee River basin.
We used a sim- ponentially. As this development makes the society less re- ple coupled model that attempted to mimic the human—water silient to droughts, the storage is increased as well. However, system. A series of simplifying but plausible assumptions the modeled time frame is too short to investigate whether were made e. The third ecosystem health, environmental awareness to configure the mode is that of no growth.
This happens when the maxi- model to be able to mimic human—water interactions at a mum effective irrigated area is low and very little potential generic level. Clearly, such a parsimonious but rudimentary for agricultural development exists. The incentive for people model cannot match the fine reality in the Murrumbidgee, to migrate and further develop the MRB is then low. Fig- which is far more complex. Nonetheless, the model has suf- ure 14 shows how the three modes of population, irrigated ficient degrees of freedom and is mathematically complex.
For all three, the It is possibly because of this that the model development modes occur for similar parameter selections. The modes for and implementation brought out key elements that control Hydrol. Three model modes for population, irrigated area, water storage, wetland storage and environmental awareness: realistic solid , increasing dashed and declining dash-dot.
It is the balance of these productive exploitative also in other similar river basins. We therefore encourage the and restorative environmental forces that has contributed use of our presented approach to other river basins to be able to the emergent dynamics, as shown in in Fig. The to eventually arrive at generic socio-hydrologic concepts. The rest of the dynamics was Liu et al. In spite Fig.
It also has many similarities to a more generic for- of the details and the specificity of the model to the Mur- mulation proposed by Elshafei et al. The first was evolution playing an important role. The exploitation of land and water re- sources. The second was environmental awareness, which sources led to environmental degradation, which eventually restricted basin production in order to restore the function- began to act as a constraint, through the intervention of hu- ing of ecosystem services to certain extent.
Both technology www. Such an analy- environment were modeled in broad terms. Any further ad- sis would explore various co-evolutionary trajectories initi- vance of socio-hydrologic modeling would therefore require ated by different conditions under different forcings in the considerable research to quantify them in acceptable ways co-evolutionary space of population, growth, migration, wa- for the purposes of modeling.
The other two key factors ter use, ecosystem health and environmental awareness. De- were external: climate as reflected in the water inflows pending on socio-hydrological characteristics, different tra- and external socio-economic conditions as reflected in the jectories might be identified by parts of the co-evolutionary world food prices. Therefore the specificity of any socio- space that these trajectories take the system to in the long hydrologic system, and the differences between several dif- run.
Such an extended analysis might even reveal socio- ferent systems, may be said to arise from the climatic and hydrological characteristics that result in chaotic system dy- socio-economic externalities, and the socio-economic and namics, where co-evolutionary trajectories that are initially political milieus that govern the evolution of technology and close to each other lead to diverse socio-hydrological out- environmental awareness in each of these places. A richer set of dominant modes The sensitivity study with the model showed that the might then be revealed, each depending on the type of forc- model is sensitive to perturbations of certain parameter val- ings, initial and boundary conditions and socio-hydrological ues.
This revealed interesting sensitivities of model outcomes characteristics. This is exciting because the presented socio- to selected parameters and shed light on how the socio- hydrologic modeling framework can then be used to replicate hydrologic model might be used and improved.
Our results and understand alternate socio-hydrological realities. How- showed that the mode of a socio-hydrological system func- ever, this is left for future research. It used constitutive recharge threshold. For the sake of simplicity, we considered relations that may also be explicitly derived based on indi- these values as static, but one can argue that these might also vidual decision making see, for example, Lyon and Pande, vary in time and space.
HS1.1 – Innovative sensors and monitoring in hydrology
These parameters were the main fac- For example, it modeled human migration patterns tors that restricted or boosted system development. It models technological innovation and adoption as a socio-hydrologic modeling studies. The sensitivity study also function of aggregate production at basin scale based on the revealed the insensitivity of model outcomes to other param- assumption that technology and wealth are intrinsic to system eters and hence revealed the possibility of equifinal mod- dynamics see, for example, Romer, ; Eicher, on els that are equally capable of representing observed socio- endogenous technological change.
The model also incorpo- hydrological patterns. Thus the sensitivity analysis revealed rated changing values and norms of a society by introducing some important implications for robust socio-hydrological environmental awareness as another co-evolutionary variable model identification and parameter selection. As a consequence, the model saw the We used a simplified Sobol method for our sensitivity co-evolution of human—water systems as a competition be- analysis.
A detailed sensitivity analysis may be required to better Finally, the modeling framework presented here is the first understand the system dynamics if it is sensitive to perturba- spatially explicit socio-hydrological model that has the ca- tions of parameter combinations as well. We would also like pacity to replicate observed patterns of population migration to emphasize on the need of studying the stability of socio- and growth, technological adoption and aggregate produc- hydrologic models.
As these models consist of coupled non- tion at basin scale. We thus conjecture that the models of this linear differential equations, further studying of the stabil- type are capable of mimicking dominant controls on the tra- ity and sensitivity might shed additional light on how socio- jectory of co-evolution of diverse coupled human—water sys- hydrologic models might be applied to different area.
This tems since they can incorporate such layers of complexity. Nonetheless our sensitivity analysis However, the model presented in this paper focused exclu- revealed the capacity of the model to represent three domi- sively on surface water utilization for agriculture and food nant modes of behavior under the same socio-hydro-climatic production.
The situation may be different in groundwater forcing. Application of ings, and initial and boundary conditions. However, the pa- models such as these, suitably adapted to these different rameters would be kept fixed in this case, for example, fixed contexts, may help bring out fundamental differences in the at the parameter values found reasonable to represent the emergent dynamics that may result.
In this paper we show Hydrol. We hypothesize that this approach, human-water systems, Hydrol. Di Baldassarre, G. DWR: Water distribution operations in irrigation areas and districts Acknowledgements. Data Elshafei, Y. THMvE is grateful for the , We also thank Seline van der Woude from Delft 28, doi University of Technology for her help with the sensitivity analysis.
Fedotov, S. We are also thankful to the three doi Understanding catchment behavior through stepwise model concept improvement, Water Resour. Gerten doi Forrester, J. Gleick, P. Change, 3, 1—7, Arkesteijn, L. November, Crutzen, P. World Dynamics Model, Automatica, 10, —, Jakeman, A. Water Resour. Roderick, M. Planetary boundaries:exploring the safe Hamilton, S. Noah land surface model over transition zones during the warm Liu, Y. Savenije, H. Maneta, M. Sivapalan, M. Pande, S.
Hypothesis Testing in Hydrology: Why Falsification of Models is Still a Great Idea
Iturbe, I. Song, X. Vitousek, P. Zalasiewicz, J. Related Papers. By Timos Karpouzoglou. Modelling stream flow and quantifying blue water using a modified STREAM model for a heterogeneous, highly utilized and data-scarce river basin in Africa. By Pieter van der Zaag. Simulating past changes in the balance between water demand and availability and assessing their main drivers at the river basin scale. By Denis Ruelland.
Environmental and Hydrological Systems Modelling
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