Improving the Representation of Long‐Term Storage Variations With Conceptual Hydrological Models in Data‐Scarce Regions

Hulsman, Petra; Hrachowitz, Markus; Savenije, H. H. G.

doi:10.1029/2020wr028837

Cited by 12 publications

(5 citation statements)

References 125 publications

(223 reference statements)

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“…Here, we have defined three HRUs that represent wetlands, hillslopes and plateaus, respectively and which are connected through a common groundwater storage (e.g. Hulsman et al, 2021). The HRUs were delineated using the MERIT hydro dataset at 60 m…”

Section: Hydrological Modelmentioning

confidence: 99%

Vegetation Response to Climatic Variability: Implications for Root Zone Storage and Streamflow Predictions

Tempel,

Bouaziz,

Taormina

et al. 2024

Preprint

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Abstract. This paper investigates the influence of multi-decadal climatic variability on the temporal evolution of root zone storage capacities (Sr,max) and its implications for streamflow predictions at the catchment scale. Through a comprehensive analysis of 286 catchments across Europe and the US, we analyse the deviations in evaporative ratios (IE) from expected values based on catchment aridity (IA) and their subsequent impact on Sr,max predictions. Our findings reveal that while catchments do not strictly adhere to their specific parametric Budyko curves over time, the deviations in IE are generally very minor, with an average ΔIE = 0.01 and an interquartile range IQR= -0.01 to 0.03. Consequently, these minor deviations lead to limited changes in predictions of Sr,max, mostly ranging between -10.5 and +21.5 mm (-5.1 % to +9.9 %). When these uncertainties in Sr,max are incorporated into hydrological models, the impact on streamflow predictions is found to be marginal, with the most significant shifts in monthly evaporation and streamflow not exceeding 4 % and 12 %, respectively. Our study underscores the utility of parametric Budyko-style equations for first order estimates of future Sr,max in hydrological models, even in the face of climate change and variability. This research contributes to a more nuanced understanding of hydrological responses to changing climatic conditions and offers valuable insights for future climate impact studies in hydrology.

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Section: Hydrological Modelmentioning

confidence: 99%

Vegetation Response to Climatic Variability: Implications for Root Zone Storage and Streamflow Predictions

Tempel,

Bouaziz,

Taormina

et al. 2024

Preprint

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“…Consistent inaccuracies of the bucket models in replicating slow hydrological behaviors suggest a lack of key mechanisms involved in the hydrological system. Alongside structural deficiencies (Fowler et al, 2020;Bouaziz et al, 2021), reasons for erratic model performance also involve data errors (Kuczera et al, 2010;Hulsman et al, 2021), model structural deficiencies (Fowler et al, 2020;Bouaziz et al, 2021), poor parameterization (Fowler et al, 2016(Fowler et al, , 2018, or their combination. However, model structural deficiency likely plays the key role in most cases of poor performance (Fowler et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, groundwater usually responds slowly to rainfall variability and the lag time scales are mediated by the hydrogeology of aquifers and the soil physical characteristics (Hughes et al, 2012;Markovich et al, 2016). Thus, it is suggested that inter-basin groundwater flow should be incorporated in hydrological models through a new deeper groundwater reservoir to allow models to better reproduce the long-term storage fluctuations (Bouaziz et al, 2018;Hulsman et al, 2021). Although some aspects are improved by the model reconfigurations or modifications, other aspects of the hydrology behavior are still not captured or reflected well, for instance those related to the effect of the terrestrial vegetation on the long-term and slow dynamics in hydrological models (Fowler et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

System dynamics perspective: lack of long-term endogenous feedback accounts for failure of bucket models to replicate slow hydrological behaviors

Zhou,

Sheng,

Manevski

et al. 2024

Preprint

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Abstract. Hydrological models with the conceptual tipping bucket and the process-based evapotranspiration models are the most common tools in hydrology. However, these models consistently fail to replicate long-term and slow dynamics of a hydrological system, indicating the need for model augmentation and shift in approach. This study employed an entirely different approach – system dynamics – towards more realistic replication of long-term and slow hydrological behaviors by removing limits of exogenous climate on evapotranspiration and involving endogenous soil water-vegetation feedback loop. Using the headwaters of Baiyang Lake in China as a case study, the mechanisms of slow hydrological dynamics were gradually unraveled from 1982 to 2015 through wavelet analysis, Granger's causality test, and system dynamics. The wavelet analysis and Granger's causality test identified a negative-correlated, bidirectional causal relationship between evapotranspiration and the water budget across distinct climatic periodicities, suggesting a robust endogenous soil water-vegetation feedback structure operating on a long-term scale. The system dynamics approach successfully captured the slow behavior of the hydrological system under both natural and human-intervention scenarios, demonstrating a self-sustained oscillation arising within the system's boundary. Conventional hydrological models, which rely on process-based evapotranspiration models, operate on an instantaneous scale and are thus susceptible to short-time climatic and vegetation physiological variations. This results in inaccurate depletion rate of soil water stock and in turn, can lead to incorrect calculations of other hydrological variables. However, long-term and slow hydrological dynamics typically involves in endogenous state-dependent modulation and feedback related to changes in vegetation structure, thus are insensitive to exogenous disturbances and can be well replicated using system dynamics approach. This insight that the failure of hydrological models to replicate slow dynamics can be attributed to a time-scale mismatch may offer potential solutions for improving conventional hydrological models.

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“…Huang et al (2017) investigated the time of propagation from meteorological drought to hydrological drought, represented by SPI and SSI, respectively, and found that the propagation was a seasonal process; that is, the seasonality was effective on the propagation. Hulsman, Hrachowitz, et al (2021), Hulsman, Savenije, et al (2021) analysed spatially averaged and local drought duration, intensity and severity using precipitation, total water storage and reservoir water level data in different drought years from a basin in the Zambezi River at the border of Zambia and Zimbabwe, and found that alternative data sources improved runoff predictions in poorly gauged basins and lead to enhanced understanding of hydrological processes under dry conditions. Um et al (2022) used standardized precipitation‐evaporation index (SPEI), standardized runoff index (SRI) and standardized soil moisture index (SSMI) for meteorological, hydrological and agricultural droughts, respectively, in the Yangtze River basin, China, and found that the 12‐month indices are clearer indicators of drought propagation than the 6‐month indices as they are based on longer accumulation periods of precipitation deficit, and they become more prone to propagate into deficit in streamflow or soil moisture as their time scale increases.…”

Section: Introductionmentioning

confidence: 99%

Formative drought rate to quantify propagation from meteorological to hydrological drought

Yildirim,

Aksoy,

Hrachowitz

2024

Hydrological Processes

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In this study, we propose a probabilistic metric, the formative drought rate (FDR), to quantify drought propagation. It is the probability that a meteorological drought in precipitation forms a hydrological drought in streamflow. Drought events were identified based on the standardized precipitation index and streamflow drought index, respectively, at 1‐, 3‐, 6‐ and 12‐month timescales. The method was tested in three river basins in Turkey (Kucuk Menderes, Gediz and Ergene). In each river basin, meteorological stations were coupled with streamflow gauging stations to form pairs of stations depending on their distance from each other and the length of their common record periods. The FDR was calculated across all timescales for each pair of stations. It was found capable to describe the river basin‐specific spatial and temporal variability of drought propagation. As the FDR is defined in the form of probability, it is expected to be a useful metric for quantifying propagation from meteorological to hydrological drought. Thus, it carries a potential for scientific research and practice in water resources management.

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Improving the Representation of Long‐Term Storage Variations With Conceptual Hydrological Models in Data‐Scarce Regions

Cited by 12 publications

References 125 publications

Vegetation Response to Climatic Variability: Implications for Root Zone Storage and Streamflow Predictions

Vegetation Response to Climatic Variability: Implications for Root Zone Storage and Streamflow Predictions

System dynamics perspective: lack of long-term endogenous feedback accounts for failure of bucket models to replicate slow hydrological behaviors

Formative drought rate to quantify propagation from meteorological to hydrological drought

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