BARUMODEL: Combined Data Based Mechanistic models of runoff response in a managed rainforest catchment

Chappell, Nick A.; Tych, Włodek; Chotai, A.; Bidin, Kawi; Sinun, Waidi; Chiew, Thang Hooi

doi:10.1016/j.foreco.2005.12.008

Cited by 38 publications

(42 citation statements)

References 60 publications

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“…The short duration of the storms in the Sapat Kalisun catchment, combined with the non-aquifer geology and small size (i.e. 4 km 2 ), explains the flashy nature of the stream hydrographs observed in this catchment (see Chappell et al (1999Chappell et al ( , 2004aChappell et al ( , 2006). …”

Section: Rain-event (Storm) Durationmentioning

confidence: 96%

“…This peak daily intensity is comparable to that recorded in the other non-cyclonic region, but much less than that recorded for cyclonic northeastern Australia, the global maximum or even the maximum for temperate UK ( Figure 5). The almost complete absence of 5 min periods with >50 mm h 1 equivalent rainfall events explains why the soils of the Sapat Kalisun catchment, with their mean topsoil permeability of 500 mm h 1 (Chappell et al, 1998), fail to generate significant volumes of infiltration-excess overland flow (see Chappell et al (1999Chappell et al ( , 2004aChappell et al ( , 2006). …”

Section: The 5-min Intensitymentioning

confidence: 99%

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Characteristics of rain events at an inland locality in northeastern Borneo, Malaysia

Bidin

Chappell

2006

Hydrol. Process.

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Abstract:Understanding the intensity and duration of tropical rain events is critical to modelling the rate and timing of wetcanopy evaporation, the suppression of transpiration, the generation of infiltration-excess overland flow and hence to erosion, and to river responsiveness. Despite this central role, few studies have addressed the characteristics of equatorial rainstorms. This study analyses rainfall data for a 5 km 2 region largely comprising of the 4 km 2 Sapat Kalisun Experimental Catchment in the interior of northeastern Borneo at sampling frequencies from 1 min 1 to 1 day1 . The work clearly shows that most rainfall within this inland, forested area is received during regular short-duration events (<15 min) that have a relatively low intensity (i.e. less than two 0Ð2 mm rain-gauge tips in almost all 5 min periods). The rainfall appears localized, with significant losses in intergauge correlations being observable in minutes in the case of the typical mid-afternoon, convective events. This suggests that a dense rain-gauge network, sampled at a high temporal frequency, is required for accurate distributed rainfall-runoff modelling of such small catchments. Observed rain-event intensity is much less than the measured infiltration capacities, and thus supports the tenet of the dominance of quick subsurface responses in controlling river behaviour in this small equatorial catchment.

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Section: Rain-event (Storm) Durationmentioning

confidence: 96%

Section: The 5-min Intensitymentioning

confidence: 99%

Characteristics of rain events at an inland locality in northeastern Borneo, Malaysia

Bidin

Chappell

2006

Hydrol. Process.

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“…Time constants are catchment specific; for example, for a first-order rainfall-runoff model which identifies just the dominant mode (one pathway), the time constant can vary from less than an hour (e.g. for a small, flashy catchment in Malaysian Borneo, Chappell et al, 2006) to more than 3 months (e.g. for a chalk stream in Berkshire, UK, Ockenden and Chappell, 2011).…”

Section: Transfer Function Model Identificationmentioning

confidence: 99%

“…The power law used to represent the rainfall-runoff non-linearity did not validate the data very well in the Blackwater catchment. Different representations of the rainfall-runoff linearity were also investigated, such as the Bedford Ouse Sub-Model (Chappell et al, 2006;Young, 2001;Young and Whitehead, 1977), in which the soil storage is related to an antecedent precipitation index. Although changes in the model non-linearity representation made minor differences to model fit, none of the model variants validated the data well for the Blackwater catchment.…”

Section: Interpretation Of Tp Load Dynamics Alongside Runoff Dynamicsmentioning

confidence: 99%

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

Ockenden

Tych

Beven

et al. 2017

Hydrol. Earth Syst. Sci.

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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.

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“…This led to numerous examples that have demonstrated the utility of DBM modeling applied to rainfall-flow processes [see e.g., Young, 1998;Lees, 2000;Young, 2001aYoung, , 2003Ratto et al, 2007;Chappell et al, 2006;Ochieng and Otieno, 2009;Young, 2010aYoung, , 2010bBeven et al, 2012;McIntyre et al, 2011, and references therein], including catchments affected by snow melt, where the nonlinearities are more complex .…”

Section: Introductionmentioning

confidence: 99%

Hypothetico‐inductive data‐based mechanistic modeling of hydrological systems

Young

2013

Water Resources Research

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[1] The paper introduces a logical extension to data-based mechanistic (DBM) modeling, which provides hypothetico-inductive (HI-DBM) bridge between conceptual models, derived in a hypothetico-deductive manner, and the DBM model identified inductively from the same time-series data. The approach is illustrated by a quite detailed example of HI-DBM analysis applied to the well-known Leaf River data set and the associated HyMOD conceptual model. The HI-DBM model significantly improves the explanation of the Leaf River data and enhances the performance of the original DBM model. However, on the basis of various diagnostic tests, including recursive time-variable and state-dependent parameter estimation, it is suggested that the model should be capable of further improvement, particularly as regards the conceptual effective rainfall mechanism, which is based on the probability distributed model hypothesis. In order to verify the efficacy of the HI-DBM analysis in a situation where the actual model generating the data is completely known, the analysis is also applied to a stochastic simulation model based on a modified HyMOD model.

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BARUMODEL: Combined Data Based Mechanistic models of runoff response in a managed rainforest catchment

Cited by 38 publications

References 60 publications

Characteristics of rain events at an inland locality in northeastern Borneo, Malaysia

Characteristics of rain events at an inland locality in northeastern Borneo, Malaysia

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

Hypothetico‐inductive data‐based mechanistic modeling of hydrological systems

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