On doing large-scale hydrology with Lions: Realising the value of perceptual models and knowledge accumulation
08 May 2020-
TL;DR: In this article, the authors use shared perceptual models as ways to capture, debate and test our experience with different hydrologic systems and improve knowledge accumulation in hydrology by more strongly focusing on knowledge extraction from available historical articles.
Abstract: Moving the study domain in hydrology to larger and larger regions leaves us with significant knowledge gaps because we are unable to observe the hydrology of many parts of the world, while in-depth hydrologic studies cover only a fraction of our landscape. On medieval maps, knowledge gaps were shown as images of lions. How do we best acknowledge and reduce these gaps in hydrology, i.e. our hydrologic lions? The accumulation of knowledge has been postulated as the fundamental mark of scientific advancement by some philosophers of science. In hydrology, knowledge accumulation has been somewhat fragmented, left as a pursuit for (often brilliant) individuals rather than emphasised as a necessary focus for the research community. Our knowledge of a region’s hydrology originates from available observations. However, the ability of observations to reliably characterise hydrological phenomena is limited, and large areas of the globe lack detailed observations. In this commentary we propose two strategies to rectify these deficiencies. First, the use of shared perceptual models as ways to capture, debate and test our experience with different hydrologic systems. Second, improved knowledge accumulation in hydrology by more strongly focusing on knowledge extraction from available historical articles. This effort should include the addition of meta-data to tag hydrologic journal articles and by developing a related hydrological database that would enable searching, organizing and analysing previous studies in a hydrologically meaningful manner.
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01 Dec 2012
Abstract: We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5 degrees x 0.5 degrees spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 +/- 7 J x 10(18) yr(-1)), H (164 +/- 15 J x 10(18) yr(-1)), and GPP (119 +/- 6 Pg C yr(-1)) were similar to independent estimates. Our global TER estimate (96 +/- 6 Pg C yr(-1)) was likely underestimated by 5-10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.
948 citations
382 citations
01 Apr 2017
TL;DR: In this article, the authors investigated the physical controls on spatial patterns of pan-European flow signatures, taking advantage of large open datasets for catchment classification and comparative hydrology, and found that a 15 to 33% improvement in regression model skills when combined with catchment classifications versus simply using all catchments at once.
Abstract: . This study contributes to better understanding the physical controls on spatial patterns of pan-European flow signatures – taking advantage of large open datasets for catchment classification and comparative hydrology. Similarities in 16 flow signatures and 35 catchment descriptors were explored for 35 215 catchments and 1366 river gauges across Europe. Correlation analyses and stepwise regressions were used to identify the best explanatory variables for each signature. Catchments were clustered and analyzed for similarities in flow signature values, physiography and the combination of the two. We found the following. (i) A 15 to 33 % (depending on the classification used) improvement in regression model skills when combined with catchment classification versus simply using all catchments at once. (ii) Twelve out of 16 flow signatures were mainly controlled by climatic characteristics, especially those related to average and high flows. For the baseflow index, geology was more important and topography was the main control for the flashiness of flow. For most of the flow signatures, the second most important descriptor is generally land cover (mean flow, high flows, runoff coefficient, ET, variability of reversals). (iii) Using a classification and regression tree (CART), we further show that Europe can be divided into 10 classes with both similar flow signatures and physiography. The most dominant separation found was between energy-limited and moisture-limited catchments. The CART analyses also separated different explanatory variables for the same class of catchments. For example, the damped peak response for one class was explained by the presence of large water bodies for some catchments, while large flatland areas explained it for other catchments in the same class. In conclusion, we find that this type of comparative hydrology is a helpful tool for understanding hydrological variability, but is constrained by unknown human impacts on the water cycle and by relatively crude explanatory variables.
88 citations
01 Apr 2018
TL;DR: In this article, the authors analyzed seven hydrological hazard indicators that characterize freshwater-related hazards for humans, freshwater biota and vegetation, and identified for all but one indicator that areas with either significantly wetter or drier conditions (calculated as percent changes from 2006-2015) are smaller in the 1.5 °C and 2 °C world.
Abstract: To support implementation of the Paris Agreement, the new HAPPI ensemble of 20 bias-corrected simulations of four climate models was used to drive two global hydrological models, WaterGAP and LPJmL, for assessing freshwater-related hazards and risks in worlds approximately 1.5 °C and 2 °C warmer than pre-industrial. Quasi-stationary HAPPI simulations are better suited than transient CMIP-like simulations for assessing hazards at the two targeted long-term global warming (GW) levels. We analyzed seven hydrological hazard indicators that characterize freshwater-related hazards for humans, freshwater biota and vegetation. Using a strict definition for significant differences, we identified for all but one indicator that areas with either significantly wetter or drier conditions (calculated as percent changes from 2006-2015) are smaller in the 1.5 °C world. For example, 7-day high flow is projected to increase significantly on 11% and 21% of the global land area under 1.5 °C and 2 °C, respectively. However, differences between hydrological hazards at the two GW levels are significant on less than 12% of the area. GW affects a larger area and more people by increases – rather than by decreases – of mean annual and 1-in-10 dry year streamflow, 7-day high flow, and groundwater recharge. The opposite is true for 7-day low flow, maximum snow storage, and soil moisture in the driest month of the growing period. Mean annual streamflow shows the lowest projected percent changes of all indicators. Among country groups, low income countries and lower middle income countries are most affected by decreased low flows and increased high flows, respectively, while high income countries are least affected by such changes. The incremental impact between 1.5 °C and 2 °C on high flows would be felt most by low income and lower middle income countries, the effect on soil moisture and low flows most by high income countries.
45 citations
01 Dec 2006
TL;DR: It is suggested that while an education with a common basis is desirable, it is clearly not available at the moment and this lack of consistency may be contributing to slow progress in hydrologic science.
Abstract: As a group of young hydrologists, we conducted a short, online survey to understand some of the main characteristics of current hydrology education and its educators. The survey provided a very interesting view on the great diversity found in hydrology education and suggests that while an education with a common basis is desirable, it is clearly not available at the moment. Hydrology educators are challenged to identify common principles, core knowledge, and approaches that should be included, in addition to areas where clear consensus is lacking. This lack of consistency may be contributing to slow progress in hydrologic science since each hydrologist's definition of what a hydrologist should know depends on their education and background. Kirchner (2006) and Bloeschl (2006) discuss in separate papers that advancements in hydrological science will likely come from synthesis of different approaches, from 'collision' of theory and data, and from better communication. Hydrology education is clearly one way to facilitate this communication.
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34,393 citations
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01 Jan 1989
6,659 citations
"On doing large-scale hydrology with..." refers background in this paper
...First, the process of scientific evolution proposed by Popper (1959) where hypotheses are falsified through evidence (data) and remain conditionally valid only as long as they are consistent with all available evidence....
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City College of New York1, University of Michigan2, University of Wisconsin-Madison3, Swiss Federal Institute of Aquatic Science and Technology4, University of Hong Kong5, University of New Hampshire6, Griffith University7, Southern Cross University8, University of Washington9, University of Western Australia10
TL;DR: The first worldwide synthesis to jointly consider human and biodiversity perspectives on water security using a spatial framework that quantifies multiple stressors and accounts for downstream impacts is presented.
Abstract: Protecting the world’s freshwater resources requires diagnosing threats over a broad range of scales, from global to local. Here we present the first worldwide synthesis to jointly consider human and biodiversity perspectives on water security using a spatial framework that quantifies multiple stressors and accounts for downstream impacts. We find that nearly 80% of the world’s population is exposed to high levels of threat to water security. Massive investment in water technology enables rich nations to offset high stressor levels without remedying their underlying causes, whereas less wealthy nations remain vulnerable. A similar lack of precautionary investment jeopardizes biodiversity, with habitats associated with 65% of continental discharge classified as moderately to highly threatened. The cumulative threat framework offers a tool for prioritizing policy and management responses to this crisis, and underscores the necessity of limiting threats at their source instead of through costly remediation of symptoms in order to assure global water security for both humans and freshwater biodiversity.
5,401 citations
TL;DR: Verification and validation of numerical models of natural systems is impossible because natural systems are never closed and because model results are always nonunique.
Abstract: Verification and validation of numerical models of natural systems is impossible. This is because natural systems are never closed and because model results are always nonunique. Models can be confirmed by the demonstration of agreement between observation and prediction, but confirmation is inherently partial. Complete confirmation is logically precluded by the fallacy of affirming the consequent and by incomplete access to natural phenomena. Models can only be evaluated in relative terms, and their predictive value is always open to question. The primary value of models is heuristic.
2,909 citations
"On doing large-scale hydrology with..." refers background in this paper
...It has been widely discussed that the more complex a model (or a hypothesis), the harder it is to reject it during testing because it has more degrees of freedom (parameters) and thus greater variability in its outputs (Young et al., 1996; Oreskes et al., 1994; Kirchner, 2006)....
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...Where do our models diverge from the expected hydrologic behaviour derived from our perceptual model(s) (if no suitable observations of the system response for direct assessment are available)? It has been widely discussed that the more complex a model (or a hypothesis), the harder it is to reject it during testing because it has more degrees of freedom (parameters) and thus greater variability in its outputs (Young et al., 1996; Oreskes et al., 1994; Kirchner, 2006)....
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01 May 2005
TL;DR: Global estimates of the seasonal flux of sediment, on a river-by-river basis, under modern and prehuman conditions are provided, showing African and Asian rivers carry a greatly reduced sediment load; Indonesian rivers deliver much more sediment to coastal areas.
Abstract: Here we provide global estimates of the seasonal flux of sediment, on a river-by-river basis, under modern and prehuman conditions. Humans have simultaneously increased the sediment transport by global rivers through soil erosion (by 2.3 ± 0.6 billion metric tons per year), yet reduced the flux of sediment reaching the world's coasts (by 1.4 ± 0.3 billion metric tons per year) because of retention within reservoirs. Over 100 billion metric tons of sediment and 1 to 3 billion metric tons of carbon are now sequestered in reservoirs constructed largely within the past 50 years. African and Asian rivers carry a greatly reduced sediment load; Indonesian rivers deliver much more sediment to coastal areas.
2,054 citations
"On doing large-scale hydrology with..." refers background in this paper
...Global and continental-scale hydrologic models increasingly reveal human influence on global fluxes of terrestrial sediments to the oceans (Syvitski et al., 2005), risks to global river biodiversity (Vörösmarty et al., 2010), global depletion of groundwater resources (Wada et al., 2010), impacts of…...
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...Global and continental-scale hydrologic models increasingly reveal human influence on global fluxes of terrestrial sediments to the oceans (Syvitski et al., 2005), risks to global...
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