The evolution of root-zone moisture capacities after deforestation: a step towards hydrological predictions under change?

Self Cite

Abstract. Catchment-scale hydrological models frequently miss essential characteristics of what determines the functioning of catchments. The most important active agent in catchments is the ecosystem. It manipulates and partitions moisture in a way that supports the essential functions of survival and productivity: infiltration of water, retention of moisture, mobilization and retention of nutrients, and drainage. Ecosystems do this in the most efficient way, establishing a continuous, ever-evolving feedback loop with the landscape and climatic drivers. In brief, hydrological systems are alive and have a strong capacity to adjust themselves to prevailing and changing environmental conditions. Although most models take Newtonian theory at heart, as best they can, what they generally miss is Darwinian theory on how an ecosystem evolves and adjusts its environment to maintain crucial hydrological functions. In addition, catchments, such as many other natural systems, do not only evolve over time, but develop features of spatial organization, including surface or sub-surface drainage patterns, as a by-product of this evolution. Models that fail to account for patterns and the associated feedbacks miss a critical element of how systems at the interface of atmosphere, biosphere and pedosphere function.In contrast to what is widely believed, relatively simple, semi-distributed conceptual models have the potential to accommodate organizational features and their temporal evolution in an efficient way, a reason for that being that because their parameters (and their evolution over time) are effective at the modelling scale, and thus integrate natural heterogeneity within the system, they may be directly inferred from observations at the same scale, reducing the need for calibration and related problems. In particular, the emergence of new and more detailed observation systems from space will lead towards a more robust understanding of spatial organization and its evolution. This will further permit the development of relatively simple time-dynamic functional relationships that can meaningfully represent spatial patterns and their evolution over time, even in poorly gauged environments.

Section: The Whole Is Greater Than the Sum Of The Partsmentioning

confidence: 99%

HESS Opinions Catchments as meta-organisms – a new blueprint for hydrological modelling

Savenije

Hrachowitz

2017

Self Cite

“…However, they also involve a plethora of (often difficult to validate) assumptions in their model structures and parameters. In practice, parameters set during calibration are rarely changed to account for changes in the modelled processes under future conditions, although by calibrating models for conditions similar to the expected future conditions, it may be possible to incorporate nonstationary parameter values (Nijzink et al, 2016). This idea could be integrated into DBM models by choosing identification periods which are most likely to reflect the conditions of the simulation period or through the use of state-dependent parameters.…”

Section: Advantages and Limitations Of The Modelling Methodsmentioning

confidence: 99%

Prediction of storm transfers and annual loads with data-based mechanistic models using high-frequency data

Ockenden

Tych

Beven

et al. 2017

Abstract. Excess nutrients in surface waters, such as phosphorus (P) from agriculture, result in poor water quality, with adverse effects on ecological health and costs for remediation. However, understanding and prediction of P transfers in catchments have been limited by inadequate data and over-parameterised models with high uncertainty. We show that, with high temporal resolution data, we are able to identify simple dynamic models that capture the P load dynamics in three contrasting agricultural catchments in the UK. For a flashy catchment, a linear, second-order (two pathways) model for discharge gave high simulation efficiencies for short-term storm sequences and was useful in highlighting uncertainties in out-of-bank flows. A model with nonlinear rainfall input was appropriate for predicting seasonal or annual cumulative P loads where antecedent conditions affected the catchment response. For second-order models, the time constant for the fast pathway varied between 2 and 15 h for all three catchments and for both discharge and P, confirming that high temporal resolution data are necessary to capture the dynamic responses in small catchments (10-50 km 2 ). The models led to a better understanding of the dominant nutrient transfer modes, which will be helpful in determining phosphorus transfers following changes in precipitation patterns in the future.

“…different mixtures of species), age distribution of the plants in the system, the density of plants (i.e. individual plants per unit area) or, being mostly snapshots in time, temporally evolving root systems (de Boer-Euser et al, 2016;Nijzink et al, 2016b;Savenije and Hrachowitz, 2017). In addition, the available meteorological forcing data may be overly smooth and/or unrepresentative due to the methods used to interpolate station data from sparse observing networks.…”

Section: Modelling Myths -Or Not?mentioning

confidence: 99%

“…A potentially effective starting point for the latter is to use observations at the modelling scale to infer information about the functional shapes and to quantify the actual parameters of individual processes at that scale. Examples include the concept of master recession curves (Lamb and Beven, 1997) or the water holding capacity in the unsaturated root zone (S U,max ), which is the core of many hydrological systems as it controls the partitioning of drainage and evaporative fluxes (Gao et al, 2014b;de Boer-Euser et al, 2016;Nijzink et al, 2016b). These system components integrate heterogeneities and quantify actual physical properties present and physical processes active at the observation and modelling scale.…”

Section: Modelling Myths -Or Not?mentioning

confidence: 99%

HESS Opinions: The complementary merits of competing modelling philosophies in hydrology

Hrachowitz

Clark

2017

Self Cite

183

130

Abstract. In hydrology, two somewhat competing philosophies form the basis of most process-based models. At one endpoint of this continuum are detailed, high-resolution descriptions of small-scale processes that are numerically integrated to larger scales (e.g. catchments). At the other endpoint of the continuum are spatially lumped representations of the system that express the hydrological response via, in the extreme case, a single linear transfer function. Many other models, developed starting from these two contrasting endpoints, plot along this continuum with different degrees of spatial resolutions and process complexities. A better understanding of the respective basis as well as the respective shortcomings of different modelling philosophies has the potential to improve our models. In this paper we analyse several frequently communicated beliefs and assumptions to identify, discuss and emphasize the functional similarity of the seemingly competing modelling philosophies. We argue that deficiencies in model applications largely do not depend on the modelling philosophy, although some models may be more suitable for specific applications than others and vice versa, but rather on the way a model is implemented. Based on the premises that any model can be implemented at any desired degree of detail and that any type of model remains to some degree conceptual, we argue that a convergence of modelling strategies may hold some value for advancing the development of hydrological models.