How Climate Extremes Influence Conceptual Rainfall-Runoff Model Performance and Uncertainty

Abstract

Rainfall-runoff models are frequently used for assessing climate risks by predicting changes in streamflow and other hydrological processes due to anticipated anthropogenic climate change, climate variability, and land management. Historical observations are commonly used to calibrate empirically the performance of conceptual hydrological mechanisms. As a result, calibration procedures are limited when extrapolated to novel climate conditions under future scenarios. In this paper, rainfall-runoff model performance and the simulated catchment hydrological processes were explored using the JAMS/J2000 model for the Berg River catchment in South Africa to evaluate the model in the tails of the current distribution of climatic conditions. An evolutionary multi-objective search algorithm was used to develop sets of parameters which best simulate “wet” and “dry” periods, providing the upper and lower bounds for a temporal uncertainty analysis approach to identify variables which are affected by these climate extremes. Variables most affected included soil-water storage and timing of interflow and groundwater flow, emerging as the overall dampening of the simulated hydrograph. Previous modeling showed that the JAMS/J2000 model provided a “good” simulation for periods where the yearly long-term mean precipitation shortfall was <28%. Above this threshold, and where autumn precipitation was reduced by 50%, this paper shows that the use of a set of “dry” parameters is recommended to improve model performance. These “dry” parameters better account for the change in streamflow timing of concentration and reduced peak flows, which occur in drier winter years, improving the Nash-Sutcliffe Efficiency (NSE) from 0.26 to 0.60 for the validation period 2015–2018, although the availability of climate data was still a potential factor. As the model performance was “good” (NSE > 0.7) during “wet” periods using parameters from a long-term calibration, “wet” parameters were not recommended for the Berg River catchment, but could play a large role in tropical climates. The results of this study are likely transferrable to other conceptual rainfall/runoff models, but may differ for various climates. As greater climate variability drives hydrological changes around the world, future empirically-based hydrological projections need to evaluate assumptions regarding storage and the simulated hydrological processes, to enhanced climate risk management.

Towards the development of an isotope‐enabled rainfall‐runoff model: Improving the ability to capture hydrological and anthropogenic change

“…Furthermore, the impact of a changing contribution from the headwaters, as well as the quantity of flows generated from surface runoff, interflow and baseflow require investigation during dry periods to conceptualize whether a single long‐term model parameter set is viable for predictions under climatic extremes (i.e. Watson, Midgley, Ray, et al, 2022). High intensity rainfall events over a short period of time typically have a more distinct isotope signal (Mccabe‐glynn et al, 2016) and could be a better tracer to constrain the flow components in the J2000iso model.…”

“…$$ was shortened to $$$ {\updelta}_{{\mbox{\fontencoding{U}\fontfamily{wasy}\selectfont\char104}} } $$$. It was assumed that the collected rainfall samples were representative of surface runoff water given the limited time for fractionation (2–5 days: Watson, Midgley, Ray, et al, 2022), as well as the low average temperature in winter in the catchment (average 14°C, relative humidity 72%) (Table 1). The model aggregated the upper (RG1) and lower (RG2) groundwater component as the total contribution from groundwater.…”

“…The Berg River catchment has recently been subject to an intense drought (2015)(2016)(2017)(2018), and future climate adaptation measures hinge on the ability to accurately simulate current and future hydrological flows. The approach investigated the potential of reducing the model parameter uncertainty of previous studies (Watson et al, 2021;Watson, Kralisch, et al, 2020;Watson, Miller, Künne, & Kralisch, 2022) and whether more robust model parameters could be identified for modelling under enhanced climate variability outlined by Watson, Midgley, Ray, et al, 2022. Furthermore, the catchment has shown recent changes in average hydrological flows (Watson, Miller, Künne, & Kralisch, 2022), as a response to changes in the upper Berg River, and the J2000iso was used to validate these changes.…”

Advancing isotope‐enabled hydrological modelling for ungauged calibration of data‐scarce humid tropical catchments

“…Given the prevalence of ungauged catchments lacking sufficient data, the development of robust hydrological models in the absence of gauging data is an important goal (e.g., Fowler et al, 2020; Wagener & Montanari, 2011; Watson, Midgley, et al, 2022; Watson, Miller, et al, 2022). Typically, a robust model would aim to simulate hydrological processes and changes that extend beyond the scope of calibration conditions, especially when dealing with stronger climate variability or anthropogenic changes.…”