Hydrology and Earth System Sciences Discussions, 2017
Excess nutrients in surface waters, such as phosphorus (P) from agriculture, result in poor water... more 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 non-linear 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 hours fo...
This paper is concerned with adaptive, off-line signal processing and forecasting for nonstationa... more This paper is concerned with adaptive, off-line signal processing and forecasting for nonstationary signals described by the unobserved component model yt=Tt+St+f(ut)+Nt +et, for et~N{O, σ2}, where yt is the observed time series, Tt is a trend or low-frequency component, St is a periodic component possibly exhibiting temporal changes in both amplitude and phase, f(ut) captures the influence of a vector
Phosphorus losses from land to water will be impacted by climate change and land management for f... more Phosphorus losses from land to water will be impacted by climate change and land management for food production, with detrimental impacts on aquatic ecosystems. Here we use a unique combination of methods to evaluate the impact of projected climate change on future phosphorus transfers, and to assess what scale of agricultural change would be needed to mitigate these transfers. We combine novel high-frequency phosphorus flux data from three representative catchments across the UK, a new high-spatial resolution climate model, uncertainty estimates from an ensemble of future climate simulations, two phosphorus transfer models of contrasting complexity and a simplified representation of the potential intensification of agriculture based on expert elicitation from land managers. We show that the effect of climate change on average winter phosphorus loads (predicted increase up to 30% by 2050s) will be limited only by large-scale agricultural changes (e.g., 20–80% reduction in phosphorus...
ABSTRACT The identification of periodic patterns in water cycle variables is critical to the unde... more ABSTRACT The identification of periodic patterns in water cycle variables is critical to the understanding of land-atmosphere interactions, climate change and the evaluation of General Circulation Model (GCM) output. SE Asia in particular plays a very important role on the global climate because it is a large source of energy and water fluxes into the upper atmosphere. Cycle identification is carried out following the Data Based Mechanistic (DBM) philosophy, which focuses on the use of parsimonious, rigorous models which are characterised by lack of a priori assumptions, built in uncertainty analysis and final model acceptance dependent on the physical interpretation of the results. The DBM tool used here is the Unobserved Component - Dynamic Harmonic Regression (UC-DHR) model, which is a statistical method that allows the identification of variability in time series by introducing Time Variable Parameter (TVP) estimation of harmonic components. UC-DHR is not scale dependent and was thus applied to both hourly (to investigate diurnal variation) and fortnightly datasets (for intra- and inter-annual variability). The data used in the analysis has been gathered from existing catchment datasets for three regions of tropical SE Asia, namely Northern Thailand, Central Peninsular Malaysia and Northeast Borneo. These regions were chosen because they represent the hydro-climatic gradient (seasonal to equatorial) present within the tropics and because SE Asia has the most extensive set of catchment/plot studies within the humid tropics. Results show modeling tools were able to quantify the main patterns present in the observations throughout different time scales (diurnal, intra-annual and inter-annual) and the strength of the correlation pattern between the four hydro-climatic variables. The subsequent discussion focuses on the physical processes behind those patterns (e.g. diurnal variability caused by local convection due to solar heating; impact of El Niño Southern Oscillation on inter-annual variability of rainfall and river discharge).
Hydrology and Earth System Sciences Discussions, 2017
Excess nutrients in surface waters, such as phosphorus (P) from agriculture, result in poor water... more 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 non-linear 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 hours fo...
This paper is concerned with adaptive, off-line signal processing and forecasting for nonstationa... more This paper is concerned with adaptive, off-line signal processing and forecasting for nonstationary signals described by the unobserved component model yt=Tt+St+f(ut)+Nt +et, for et~N{O, σ2}, where yt is the observed time series, Tt is a trend or low-frequency component, St is a periodic component possibly exhibiting temporal changes in both amplitude and phase, f(ut) captures the influence of a vector
Phosphorus losses from land to water will be impacted by climate change and land management for f... more Phosphorus losses from land to water will be impacted by climate change and land management for food production, with detrimental impacts on aquatic ecosystems. Here we use a unique combination of methods to evaluate the impact of projected climate change on future phosphorus transfers, and to assess what scale of agricultural change would be needed to mitigate these transfers. We combine novel high-frequency phosphorus flux data from three representative catchments across the UK, a new high-spatial resolution climate model, uncertainty estimates from an ensemble of future climate simulations, two phosphorus transfer models of contrasting complexity and a simplified representation of the potential intensification of agriculture based on expert elicitation from land managers. We show that the effect of climate change on average winter phosphorus loads (predicted increase up to 30% by 2050s) will be limited only by large-scale agricultural changes (e.g., 20–80% reduction in phosphorus...
ABSTRACT The identification of periodic patterns in water cycle variables is critical to the unde... more ABSTRACT The identification of periodic patterns in water cycle variables is critical to the understanding of land-atmosphere interactions, climate change and the evaluation of General Circulation Model (GCM) output. SE Asia in particular plays a very important role on the global climate because it is a large source of energy and water fluxes into the upper atmosphere. Cycle identification is carried out following the Data Based Mechanistic (DBM) philosophy, which focuses on the use of parsimonious, rigorous models which are characterised by lack of a priori assumptions, built in uncertainty analysis and final model acceptance dependent on the physical interpretation of the results. The DBM tool used here is the Unobserved Component - Dynamic Harmonic Regression (UC-DHR) model, which is a statistical method that allows the identification of variability in time series by introducing Time Variable Parameter (TVP) estimation of harmonic components. UC-DHR is not scale dependent and was thus applied to both hourly (to investigate diurnal variation) and fortnightly datasets (for intra- and inter-annual variability). The data used in the analysis has been gathered from existing catchment datasets for three regions of tropical SE Asia, namely Northern Thailand, Central Peninsular Malaysia and Northeast Borneo. These regions were chosen because they represent the hydro-climatic gradient (seasonal to equatorial) present within the tropics and because SE Asia has the most extensive set of catchment/plot studies within the humid tropics. Results show modeling tools were able to quantify the main patterns present in the observations throughout different time scales (diurnal, intra-annual and inter-annual) and the strength of the correlation pattern between the four hydro-climatic variables. The subsequent discussion focuses on the physical processes behind those patterns (e.g. diurnal variability caused by local convection due to solar heating; impact of El Niño Southern Oscillation on inter-annual variability of rainfall and river discharge).
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