Addressing subjective decision-making inherent in GLUE-based multi-criteria rainfall–runoff model calibration

<p>Lake Taupo is the effective source of the Waikato River. The Waikato Power Scheme relies on the outflow from the lake for moderated flows throughout the year. As the lake is maintained between a 1.4m operating range, it is the inflows to the lake that determine the amount of water available to the scheme for electricity generation. These inflows have not been modelled in any detail prior to this dissertation. This dissertation aims to develop a predictive rainfall-runoff model that can provide accurate and reliable inflow and lake level forecasts for the Lake Taupo catchment. Model formulation is guided by a fundamental understanding of catchment hydrologic principles and an in-depth assessment of catchment hydrologic behaviour. The model is a semi-distributed physically-consistent conceptual model which aims to provide a parsimonious representation of different storages and flow pathways through a catchment. It has three linear sub-surface stores. Drainage to these stores is related to the size of the saturation zone, utilising the concept of a variable source area. This model is used to simulate inflows from gauged unregulated sub-catchments. It is also used to estimate the inflow from ungauged areas through regionalisation. For regulated sub-catchments, the model is modified to incorporate available data and information relating to the relevant scheme‟s operation, resource consent conditions and other physical and legislative constraints. The output from such models is subject to considerable uncertainty due to simplifications in the model structure, estimated parameter values and imperfect driving data. For robust decision making, it is important this uncertainty is reduced to within acceptable levels. In this study, a constrained Ensemble Kalman Filter (EnKF) is applied to the four unregulated gauged catchments to deal with model structure and data uncertainties. Used in conjunction with Monte Carlo simulations, all three sources of uncertainty are addressed. Simple mass and flux constraints are applied to the four (soil storage, baseflow, interflow and fastflow) model states. Without these constraints states can be adjusted beyond what is physically possible, compromising the integrity of model output. It is demonstrated that the application of a constrained EnKF improves the accuracy and reliability of model output.Due to the complexity of the Tongariro Power Scheme (TPS) and the limited data available to model it, the conceptual model is not suitable. Rather, a statistical probability analysis is used to estimate the discharge from this scheme given the month of the year, day of the week and hour of the day. Model output is combined and converted into a corresponding change in lake level. The model is evaluated over a wide range of hydrological and meteorological conditions. An in-depth critical evaluation is undertaken on eight events chosen a priori as representation of both extreme and „usual‟ conditions. The model provides reasonable predictions of lake level given the uncertainty with the TPS, complexity of the catchment and data/information constraints. The model performs particularly well in „normal‟ and dry conditions but also does a good job during rainfall events in light of errors associated with driving data. However, for real-time operational use the integration of the model with meteorological forecasts is required. Model recalibration would be required due to the issue of moving from point estimation to areal rainfall data. Once this is achieved, this operational model would allow robust decision-making and efficient management of the water resource for the Waikato Power Scheme. Although there is room for improvement, there is considerable scope for extending the application of the constrained EnKF and techniques for incorporating regulation to other catchments both in New Zealand and internationally.</p>

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Impacts of uncertain river flow data on rainfall-runoff model calibration and discharge predictions

Hydrological Processes ◽

10.1002/hyp.7587 ◽

2010 ◽

pp. n/a-n/a ◽

Cited By ~ 66

Author(s):

Hilary McMillan ◽

Jim Freer ◽

Florian Pappenberger ◽

Tobias Krueger ◽

Martyn Clark

Keyword(s):

Model Calibration ◽

River Flow ◽

Rainfall Runoff ◽

Flow Data ◽

Rainfall Runoff Model ◽

Runoff Model

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Sensitivity of the performance of a conceptual rainfall–runoff model to the temporal sampling of calibration data

Hydrology Research ◽

10.2166/nh.2012.061 ◽

2012 ◽

Vol 44 (3) ◽

pp. 484-494 ◽

Cited By ~ 19

Author(s):

Satish Bastola ◽

Conor Murphy

Keyword(s):

Temporal Resolution ◽

Model Calibration ◽

Flood Frequency Analysis ◽

Calibration Data ◽

Rainfall Runoff ◽

Time Step ◽

Scaling Relationship ◽

Simple Scaling ◽

Rainfall Runoff Model ◽

Runoff Model

The effect of the time step of calibration data on the performance of a hydrological model is examined through a numerical experiment where HYMOD, a rainfall–runoff model, is calibrated with data of varying temporal resolution. A simple scaling relationship between the parameters of the model and modelling time step is derived which enables information from daily hydrological records to be used in modelling at time steps much shorter than daily. Model parameters were found to respond differently depending upon the degree of aggregation of calibration data. A loss in performance, especially in terms of the Nash–Sutcliffe measure, is evident when behavioural simulators derived with one modelling time step are used for simulation at another time step. The loss in performance is greater when parameters derived from a longer time step were used for simulating flow with a shorter time step. The application of a simple scaling relationship derived from a multi-time step model calibration significantly decreased the loss in model performance. Such an approach may offer the prospect of conducting higher temporal resolution flood frequency analysis when finer scale data for model calibration are not available or limited.

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Understanding the effect of changing land use on floods and soil erosion in the Cagayan de Oro catchment

10.26686/wgtn.17134721.v1 ◽

2021 ◽

Author(s):

◽

Rubianca Benavidez

Keyword(s):

Decision Making ◽

Soil Erosion ◽

Land Cover ◽

The Philippines ◽

Flood Mitigation ◽

Baseline Scenario ◽

Rainfall Runoff ◽

Sediment Delivery ◽

Rainfall Runoff Model ◽

Runoff Model

<p>The destructive capability of typhoons affects lives and infrastructure around the world. Spatial analysis of historical typhoon records reveal an area of intense storm activity within the Southeast Asian (SEA) region. Within SEA is the Philippines, an archipelagic tropical country regularly struck by storms that often cause severe landslides, erosion and floods. Annually, ˜20 cyclones enter the Philippine Area of Responsibility, with about nine making landfall, causing high winds and intense rainfall. Thus, significant research in the Philippines has focused on increasing the resilience of ecosystems and communities through real-time disaster forecasting, structural protections, and programmes for sustainable watershed management (e.g. rehabilitation and conservation agriculture). This dissertation focused on the third aspect through computer modelling and scenario analysis. The study area is the Cagayan de Oro (CDO) catchment (˜1400km²) located in the Southern Philippines. The catchment experienced heavy flooding in 2012 from Typhoon Bopha and has major erosion problems due to mountainous slopes and heavy rainfall. Communities derive ecosystem services (ES) including agricultural production, water supply, recreation, mining resources, flood mitigation, etc. Since changes to the supply or distribution of these ES affects livelihoods and the hydrological response of the catchment to typhoon events, this research used the Land Utilisation and Capability Indicator (LUCI) model to understand the baseline ES and potential changes associated with basin management plans. This was the first detailed tropical application of LUCI, including parameterising it for Philippine soil and land cover datasets in CDO and extending its capability to be applied in future tropical areas. Aside from applying LUCI in a new geoclimatic region, this research contributed to the general development of LUCI through testing and improving its sediment delivery and inundation modelling. The sediment delivery was enhanced using the Revised Universal Soil Loss Equation (RUSLE) model that allows LUCI for the first time to account for impacts of specific land management such as agroforestry and contour cropping on erosion and sediment delivery. Progress was made in updating a flatwater inundation model for use with LUCI, including converting it to Python but this requires further development and testing before it is suitable for application in the Philippines. The development and rehabilitation scenarios showed improved flood mitigation, lower surficial soil erosion rates, and lower loads of nutrients compared to the baseline scenario. Additionally, ES mapping under different land cover scenarios has not been previously accomplished in CDO, and this research provides useful information to guide local decision-making and management planning. The rainfall-runoff model of LUCI was tested against the Hydrologic Engineering Center’s Hydrological Modelling System (HEC-HMS), showing good agreement with observed flow. Since the rainfall-runoff model of LUCI has been minimally utilised in past applications, this CDO application elucidated directions for future work around further testing under extreme rainfall events and climate change. Overall, this novel application of LUCI creates a framework to assist decision-making around land cover changes in the CDO, provides guidance around data requirements and parameterisation procedures to guide future international applications, and has significantly contributed to development and improvement of the LUCI framework to extend its modelling capabilities in the future.</p>

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Application of Conceptual Rainfall-Runoff Model METQ for Simulation of Daily Runoff and Water Level: The case of the Lake Burtnieks Watershed

Proceedings of the Latvian Academy of Sciences Section B Natural Exact and Applied Sciences ◽

10.2478/v10046-008-0002-5 ◽

2008 ◽

Vol 62 (1-2) ◽

pp. 47-54

Author(s):

Elga Apsīte ◽

Ansis Zīverts ◽

Anda Bakute

Keyword(s):

Water Level ◽

Correlation Coefficient ◽

Model Calibration ◽

Performance Model ◽

Model Structure ◽

Rainfall Runoff ◽

Rainfall Runoff Model ◽

Parameter Values ◽

Runoff Model ◽

Gauging Station

Application of Conceptual Rainfall-Runoff Model METQ for Simulation of Daily Runoff and Water Level: The case of the Lake Burtnieks Watershed In this study a conceptual rainfall-runoff METQ model—the latest version METQ2007BDOPT—was applied to simulate the daily runoff and water level of the Lake Burtnieks watershed from 1990 to 1999. The model structure and parameters were basically the same as in the METQ98, with some additional improvements and semi-automatical calibration performance. Model calibration was done for four rivers and one lake gauging station. The results of calibration showed a good correlation between the measured and simulated daily discharges. The Nash-Sutcliffe efficiency R2 varied from 0.90 to 0.58 and correlation coefficient r from 0.95 to 0.83. The highest values of R2 = 0.90 and r = 0.95 were obtained for the River Salaca and the lowest R2 = 0.53 and r = 0.83 for Lake Burtnieks. We observed some relationships between the model parameter values and physiographic characteristic of the sub-catchments.

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