Infrastructure Engineering - Research Publications
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ItemEvolution of the human-water relationships in the Heihe River basin in the past 2000 years(COPERNICUS GESELLSCHAFT MBH, 2015)Abstract. This paper quantitatively analyzed the evolution of human–water relationships in the Heihe River basin of northern China over the past 2000 years by reconstructing the catchment water balance by partitioning precipitation into evapotranspiration and runoff. The results provided the basis for investigating the impacts of societies on hydrological systems. Based on transition theory and the rates of changes of the population, human water consumption and the area of natural oases, the evolution of human–water relationships can be divided into four stages: predevelopment (206 BC–AD 1368), take-off (AD 1368–1949), acceleration (AD 1949–2000), and the start of a rebalancing between human and ecological needs (post AD 2000). Our analysis of the evolutionary process revealed that there were large differences in the rate and scale of changes and the period over which they occurred. The transition of the human–water relationship had no fixed pattern. This understanding of the dynamics of the human–water relationship will assist policy makers in identifying management practices that require improvement by understanding how today's problems were created in the past, which may lead to more sustainable catchment management in the future.
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ItemAssimilation of stream discharge for flood forecasting: Updating a semidistributed model with an integrated data assimilation scheme(AMER GEOPHYSICAL UNION, 2015-05)Abstract Real‐time discharge observations can be assimilated into flood models to improve forecast accuracy; however, the presence of time lags in the routing process and a lack of methods to quantitatively represent different sources of uncertainties challenge the implementation of data assimilation techniques for operational flood forecasting. To address these issues, an integrated error parameter estimation and lag‐aware data assimilation (IEELA) scheme was recently developed for a lumped model. The scheme combines an ensemble‐based maximum a posteriori (MAP) error estimation approach with a lag‐aware ensemble Kalman smoother (EnKS). In this study, the IEELA scheme is extended to a semidistributed model to provide for more general application in flood forecasting by including spatial and temporal correlations in model uncertainties between subcatchments. The result reveals that using a semidistributed model leads to more accurate forecasts than a lumped model in an open‐loop scenario. The IEELA scheme improves the forecast accuracy significantly in both lumped and semidistributed models, and the superiority of the semidistributed model remains in the data assimilation scenario. However, the improvements resulting from IEELA are confined to the outlet of the catchment where the discharge observations are assimilated. Forecasts at “ungauged” internal locations are not improved, and in some instances, even become less accurate.
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ItemPredicting shifts in rainfall-runoff partitioning during multiyear drought: Roles of dry period and catchment characteristics(AMER GEOPHYSICAL UNION, 2016-12)Abstract While the majority of hydrological prediction methods assume that observed interannual variability explores the full range of catchment response dynamics, recent cases of prolonged climate drying suggest otherwise. During the ∼decade‐long Millennium drought in south‐eastern Australia significant shifts in hydrologic behavior were reported. Catchment rainfall‐runoff partitioning changed from what was previously encountered during shorter droughts, with significantly less runoff than expected occurring in many catchments. In this article, we investigate the variability in the magnitude of shift in rainfall‐runoff partitioning observed during the Millennium drought. We re‐evaluate a large range of factors suggested to be responsible for the additional runoff reductions. Our results suggest that the shifts were mostly influenced by catchment characteristics related to predrought climate (aridity index and rainfall seasonality) and soil and groundwater storage dynamics (predrought interannual variability of groundwater storage and mean solum thickness). The shifts were amplified by seasonal rainfall changes during the drought (spring rainfall deficits). We discuss the physical mechanisms that are likely to be associated with these factors. Our results confirm that shifts in the annual rainfall‐runoff relationship represent changes in internal catchment functioning, and emphasize the importance of cumulative multiyear changes in the catchment storage for runoff generation. Prolonged drying in some regions can be expected in the future, and our results provide an indication of which catchments characteristics are associated with catchments more susceptible to a shift in their runoff response behavior.
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ItemDual assimilation of satellite soil moisture to improve streamflow prediction in data-scarce catchments(AMER GEOPHYSICAL UNION, 2016-07)Abstract This paper explores the use of active and passive microwave satellite soil moisture products for improving streamflow prediction within four large (>5000km2) semiarid catchments in Australia. We use the probability distributed model (PDM) under a data‐scarce scenario and aim at correcting two key controlling factors in the streamflow generation: the rainfall forcing data and the catchment wetness condition. The soil moisture analysis rainfall tool (SMART) is used to correct a near real‐time satellite rainfall product (forcing correction scheme) and an ensemble Kalman filter is used to correct the PDM soil moisture state (state correction scheme). These two schemes are combined in a dual correction scheme and we assess the relative improvements of each. Our results demonstrate that the quality of the satellite rainfall product is improved by SMART during moderate‐to‐high daily rainfall events, which in turn leads to improved streamflow prediction during high flows. When employed individually, the soil moisture state correction scheme generally outperforms the rainfall correction scheme, especially for low flows. Overall, the combined dual correction scheme further improves the streamflow predictions (reduction in root mean square error and false alarm ratio, and increase in correlation coefficient and Nash‐Sutcliffe efficiency). Our results provide new evidence of the value of satellite soil moisture observations within data‐scarce regions. We also identify a number of challenges and limitations within the schemes.
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ItemA synthetic study to evaluate the utility of hydrological signatures for calibrating a base flow separation filter(AMER GEOPHYSICAL UNION, 2016-08)Abstract Estimation of base flow from streamflow hydrographs has been a major challenge in hydrology for decades, leading to developments of base flow separation filters. When without tracer or groundwater data to calibrate the filters, the standard approach to apply these filters in practice involves some degrees of subjectivity in choosing the filter parameters. This paper investigates the use of signature‐based calibration in implementing base flow filtering by testing seven possible hydrological signatures of base flow against modeled daily base flow produced by Li et al. (2014) for a range of synthetic catchments simulated with HydroGeoSphere. Our evaluation demonstrates that such a calibration method with few selected signatures as objectives is capable of calibrating a filter–Eckhardt filter–to yield satisfactory base flow estimates at daily, monthly and long‐term time scales, outperforming the standard approach. The best performing signatures can be readily derived from streamflow time series. While their performance depends on the catchment characteristics, the catchments where the signature method performs can be distinguished using commonly‐used descriptors of flow dynamics.
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ItemEnsemble forecasting of short-term system scale irrigation demands using real-time flow data and numerical weather predictions(AMER GEOPHYSICAL UNION, 2016-06)Abstract Irrigation demands fluctuate in response to weather variations and a range of irrigation management decisions, which creates challenges for water supply system operators. This paper develops a method for real‐time ensemble forecasting of irrigation demand and applies it to irrigation command areas of various sizes for lead times of 1 to 5 days. The ensemble forecasts are based on a deterministic time series model coupled with ensemble representations of the various inputs to that model. Forecast inputs include past flow, precipitation, and potential evapotranspiration. These inputs are variously derived from flow observations from a modernized irrigation delivery system; short‐term weather forecasts derived from numerical weather prediction models and observed weather data available from automatic weather stations. The predictive performance for the ensemble spread of irrigation demand was quantified using rank histograms, the mean continuous rank probability score (CRPS), the mean CRPS reliability and the temporal mean of the ensemble root mean squared error (MRMSE). The mean forecast was evaluated using root mean squared error (RMSE), Nash–Sutcliffe model efficiency (NSE) and bias. The NSE values for evaluation periods ranged between 0.96 (1 day lead time, whole study area) and 0.42 (5 days lead time, smallest command area). Rank histograms and comparison of MRMSE, mean CRPS, mean CRPS reliability and RMSE indicated that the ensemble spread is generally a reliable representation of the forecast uncertainty for short lead times but underestimates the uncertainty for long lead times.
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ItemCan we manage groundwater? A method to determine the quantitative testability of groundwater management plans(AMER GEOPHYSICAL UNION, 2016-06)Abstract Groundwater is the world's largest freshwater resource and due to overextraction, levels have declined in many regions causing extensive social and environmental impacts. Groundwater management seeks to balance and mitigate the detrimental impacts of development, with plans commonly used to outline management pathways. Thus, plan efficiency is crucial, but seldom are plans systematically and quantitatively assessed for effectiveness. This study frames groundwater management as a system control problem in order to develop a novel testability assessment rubric to determine if plans meet the requirements of a control loop, and subsequently, whether they can be quantitatively tested. Seven components of a management plan equivalent to basic components of a control loop were determined, and requirements of each component necessary to enable testability were defined. Each component was weighted based upon proposed relative importance, then segmented into rated categories depending on the degree the requirements were met. Component importance varied but, a defined objective or acceptable impact was necessary for plans to be testable. The rubric was developed within the context of the Australian groundwater management industry, and while use of the rubric is not limited to Australia, it was applied to 15 Australian groundwater management plans and approximately 47% were found to be testable. Considering the importance of effective groundwater management, and the central role of plans, our lack of ability to test many plans is concerning.
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ItemOn the structural limitations of recursive digital filters for base flow estimation(AMER GEOPHYSICAL UNION, 2016-06)Abstract Recursive digital filters (RDFs) are widely used for estimating base flow from streamflow hydrographs, and various forms of RDFs have been developed based on different physical models. Numerical experiments have been used to objectively evaluate their performance, but they have not been sufficiently comprehensive to assess a wide range of RDFs. This paper extends these studies to understand the limitations of a generalized RDF method as a pathway for future field calibration. Two formalisms are presented to generalize most existing RDFs, allowing systematic tuning of their complexity. The RDFs with variable complexity are evaluated collectively in a synthetic setting, using modeled daily base flow produced by Li et al. (2014) from a range of synthetic catchments simulated with HydroGeoSphere. Our evaluation reveals that there are optimal RDF complexities in reproducing base flow simulations but shows that there is an inherent physical inconsistency within the RDF construction. Even under the idealized setting where true base flow data are available to calibrate the RDFs, there is persistent disagreement between true and estimated base flow over catchments with small base flow components, low saturated hydraulic conductivity of the soil and larger surface runoff. The simplest explanation is that low base flow “signal” in the streamflow data is hard to distinguish, although more complex RDFs can improve upon the simpler Eckhardt filter at these catchments.
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ItemUsing a data-driven approach to understand the interaction between catchment characteristics and water quality responses(River Basin Management Society, 2016)
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ItemMultiple runoff processes and multiple thresholds control agricultural runoff generation(COPERNICUS GESELLSCHAFT MBH, 2016-11-11)Abstract. Thresholds and hydrologic connectivity associated with runoff processes are a critical concept for understanding catchment hydrologic response at the event timescale. To date, most attention has focused on single runoff response types, and the role of multiple thresholds and flow path connectivities has not been made explicit. Here we first summarise existing knowledge on the interplay between thresholds, connectivity and runoff processes at the hillslope–small catchment scale into a single figure and use it in examining how runoff response and the catchment threshold response to rainfall affect a suite of runoff generation mechanisms in a small agricultural catchment. A 1.37 ha catchment in the Lang Lang River catchment, Victoria, Australia, was instrumented and hourly data of rainfall, runoff, shallow groundwater level and isotope water samples were collected. The rainfall, runoff and antecedent soil moisture data together with water levels at several shallow piezometers are used to identify runoff processes in the study site. We use isotope and major ion results to further support the findings of the hydrometric data. We analyse 60 rainfall events that produced 38 runoff events over two runoff seasons. Our results show that the catchment hydrologic response was typically controlled by the Antecedent Soil Moisture Index and rainfall characteristics. There was a strong seasonal effect in the antecedent moisture conditions that led to marked seasonal-scale changes in runoff response. Analysis of shallow well data revealed that streamflows early in the runoff season were dominated primarily by saturation excess overland flow from the riparian area. As the runoff season progressed, the catchment soil water storage increased and the hillslopes connected to the riparian area. The hillslopes transferred a significant amount of water to the riparian zone during and following events. Then, during a particularly wet period, this connectivity to the riparian zone, and ultimately to the stream, persisted between events for a period of 1 month. These findings are supported by isotope results which showed the dominance of pre-event water, together with significant contributions of event water early (rising limb and peak) in the event hydrograph. Based on a combination of various hydrometric analyses and some isotope and major ion data, we conclude that event runoff at this site is typically a combination of subsurface event flow and saturation excess overland flow. However, during high intensity rainfall events, flashy catchment flow was observed even though the soil moisture threshold for activation of subsurface flow was not exceeded. We hypothesise that this was due to the activation of infiltration excess overland flow and/or fast lateral flow through preferential pathways on the hillslope and saturation overland flow from the riparian zone.