Using observed river flow data to improve the hydrological functioning of the JULES land surface model (vn4.3) used for regional coupled modelling in Great Britain (UKC2)

Torre, Alberto Martínez-de la; Blyth, Eleanor; Weedon, Graham P.

doi:10.5194/gmd-12-765-2019

Cited by 26 publications

(19 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This result of transpiration enhancement from the groundwater reservoir and its lateral convergence has been reported by the use of other groundwater-land surface coupled models (e.g. Maxwell and Condon, 2016).…”

Section: Discussionsupporting

confidence: 79%

“…Notwithstanding, most modelling schemes fail to produce a realistic water table spatial distribution, which compromises the generality of their results. One important reason why this happens is that most land surface models (LSMs) treat the evolution of the water table as a process dominated by vertical fluxes, as they do with soil moisture, ignoring or misrepresenting the lateral gravitational groundwater flow, which is the main driver of the water table distribution across the landscape (Fan et al, 2013;de Graaf et al, 2015;Maxwell and Condon, 2016). The main modelling challenge thus remains to couple groundwater to soil moisture with a realistic water table; only then can the importance of their mutual interaction for climate be reliably assessed on a large scale.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Groundwater influence on soil moisture memory and land–atmosphere fluxes in the Iberian Peninsula

Torre

Míguez-Macho

2019

Hydrol. Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

Groundwater plays an important role in the terrestrial water cycle, interacting with the land surface via vertical fluxes through the water table and distributing water resources spatially via gravity-driven lateral transport. It is therefore essential to have a correct representation of groundwater processes in land surface models, as land-atmosphere coupling is a key factor in climate research. Here we use the LEAFHYDRO land surface and groundwater model to study the groundwater influence on soil moisture distribution and memory, and evapotranspiration (ET) fluxes in the Iberian Peninsula over a 10-year period. We validate our results with time series of observed water table depth from 623 stations covering different regions of the Iberian Peninsula, showing that the model produces a realistic water table, shallower in valleys and deeper under hilltops. We find patterns of shallow water table and strong groundwater-land surface coupling over extended interior semi-arid regions and river valleys. We show a strong seasonal and interannual persistence of the water table, which induces bimodal memory in the soil moisture fields; soil moisture "remembers" past wet conditions, buffering drought effects, and also past dry conditions, causing a delay in drought recovery. The effects on land-atmosphere fluxes are found to be significant: on average over the region, ET is 17.4 % higher when compared with a baseline simulation with LEAFHYDRO's groundwater scheme deactivated. The maximum ET increase occurs in summer (34.9 %; 0.54 mm d −1 ). The ET enhancement is larger over the drier southern basins, where ET is water limited (e.g. the Guadalquivir basin and the Mediterranean Segura basin), than in the northern Miño/Minho basin, where ET is more energy limited than water limited. In terms of river flow, we show how dry season baseflow is sustained by groundwater originating from accumulated recharge during the wet season, improving significantly on a free-drain approach, where baseflow comes from water draining through the top soil, resulting in rivers drying out in summer. Convective precipitation enhancement through local moisture recycling over the semi-arid interior regions and summer cooling are potential implications of these groundwater effects on climate over the Iberian Peninsula. Fully coupled land surface and climate model simulations are needed to elucidate this question.

show abstract

Section: Discussionsupporting

confidence: 79%

mentioning

confidence: 99%

Groundwater influence on soil moisture memory and land–atmosphere fluxes in the Iberian Peninsula

Torre

Míguez-Macho

2019

Hydrol. Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The Joint UK Land Environment Simulator (JULES) is a widely used land surface model, developed by the UK MetOffice, and used for operational services and research to simulate the energy, carbon and water balance between the land surface and the lower atmosphere (Best et al, 2011; Clark et al, 2011). The hydrological components of JULES have been tested for runoff predictions at monthly and inter‐annual scales (Gudmundsson et al, 2012a & 2012b; MacKellar, Dadson, New, & Wolski, 2013) and at daily resolution (Dadson & Bell, 2010; Dadson, Bell, & Jones, 2011; Martínez‐de la Torre, Blyth, & Weedon, 2019; Weedon et al, 2015; Zulkafli, Buytaert, Onof, Lavado, & Guyot, 2013). In a model intercomparison experiment for simulating the inter‐annual variability of observed runoff in Europe (Gudmundsson, Tallaksen, et al, 2012), JULES was ranked third out of 10 large‐scale hydrological models.…”

Section: Introductionmentioning

confidence: 99%

Towards the representation of groundwater in the Joint UK Land Environment Simulator

Batelis

Rahman

Kollet

et al. 2020

Hydrological Processes

View full text Add to dashboard Cite

Groundwater is an important component of the hydrological cycle with significant interactions with soil hydrological processes. Recent studies have demonstrated that incorporating groundwater hydrology in land surface models (LSMs) considerably improves the prediction of the partitioning of water components (e.g., runoff and evapotranspiration) at the land surface. However, the Joint UK Land Environment Simulator (JULES), an LSM developed in the United Kingdom, does not yet have an explicit representation of groundwater. We propose an implementation of a simplified groundwater flow boundary parameterization (JULES‐GFB), which replaces the original free drainage assumption in the default model (JULES‐FD). We tested the two approaches under a controlled environment for various soil types using two synthetic experiments: (1) single‐column and (2) tilted‐V catchment, using a three‐dimensional (3‐D) hydrological model (ParFlow) as a benchmark for JULES’ performance. In addition, we applied our new JULES‐GFB model to a regional domain in the UK, where groundwater is the key element for runoff generation. In the single‐column infiltration experiment, JULES‐GFB showed improved soil moisture dynamics in comparison with JULES‐FD, for almost all soil types (except coarse soils) under a variety of initial water table depths. In the tilted‐V catchment experiment, JULES‐GFB successfully represented the dynamics and the magnitude of saturated and unsaturated storage against the benchmark. The lateral water flow produced by JULES‐GFB was about 50% of what was produced by the benchmark, while JULES‐FD completely ignores this process. In the regional domain application, the Kling‐Gupta efficiency (KGE) for the total runoff simulation showed an average improvement from 0.25 for JULES‐FD to 0.75 for JULES‐GFB. The mean bias of actual evapotranspiration relative to the Global Land Evaporation Amsterdam Model (GLEAM) product was improved from −0.22 to −0.01 mm day−1. Our new JULES‐GFB implementation provides an opportunity to better understand the interactions between the subsurface and land surface processes that are dominated by groundwater hydrology.

show abstract

“…JULES was calibrated and tested on the period 1991-2000. Crooks et al (2014) ran CLASSIC-GB for 41 stations, including the 13 test stations used by Martínez-de la Torre et al (2019).…”

Section: Inter-model Performancesmentioning

confidence: 99%

Comment on hess-2021-127

2021

View full text Add to dashboard Cite

Long short-term memory models (LSTMs) are recurrent neural networks from the emerging field of Deep Learning (DL), which have shown recent promise when predicting time-series especially when data are abundant. Rainfall-runoff modelling presents a challenge, yet accurate hydrological models are vital for flood forecasting, hazard impact assessment, and to assess the potential effects of climate change on floods and water resources. In this study, we compare the performance of two DL-based models, a LSTM and an Entity Aware LSTM (EA LSTM). The DL models were trained using a newly published data set, CAMELS-GB, for a sample of 518 catchments across Great Britain. To identify spatial and seasonal patterns in model performance, we compare the DL models against benchmark outputs from four lumped conceptual models recently configured for rainfall-runoff modelling in Great Britain. Our findings show that the LSTM models simulate discharge with consistently high model performance scores, including in catchments typically considered difficult to model. The LSTM achieves a mean catchment NSE of 0.88 (0.86 for the EALSTM), which represents a performance improvement of 10% -16% compared with the benchmark conceptual models. Seasonal and spatial patterns indicate that the largest performance improvement relative to the benchmark is in the drier summer months and in drier catchments in the South East of England. By comparing LSTMs with conceptual models, we diagnose possible reasons for their different performance. We suggest that LSTMs offer useful predictive capability for rainfall-runoff modelling in Great Britain and elsewhere and note their value to support process understanding in locations where processes are less well understood. IntroductionRainfall-runoff models have evolved over many decades, reflecting a diversity of applications and purposes. These models range from physically based, spatially explicit models such as SHE (

show abstract

Using observed river flow data to improve the hydrological functioning of the JULES land surface model (vn4.3) used for regional coupled modelling in Great Britain (UKC2)

Cited by 26 publications

References 58 publications

Groundwater influence on soil moisture memory and land–atmosphere fluxes in the Iberian Peninsula

Groundwater influence on soil moisture memory and land–atmosphere fluxes in the Iberian Peninsula

Towards the representation of groundwater in the Joint UK Land Environment Simulator

Comment on hess-2021-127

Contact Info

Product

Resources

About