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

Abstract. 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.

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

10.5194/hess-2018-626 ◽

2019 ◽

Author(s):

Alberto Martínez-de la Torre ◽

Gonzalo Miguez-Macho

Keyword(s):

Soil Moisture ◽

Iberian Peninsula ◽

Water Table ◽

Land Surface ◽

River Flow ◽

Climate Model ◽

Moisture Distribution ◽

Convective Precipitation ◽

Wet Season ◽

Shallow Water Table

Abstract. 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 Land Surface and Groundwater Model LEAFHYDRO 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 day−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 semiarid 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.

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Quantifying the impact of groundwater depth on evapotranspiration in a semi-arid grassland region

Hydrology and Earth System Sciences ◽

10.5194/hess-15-787-2011 ◽

2011 ◽

Vol 15 (3) ◽

pp. 787-806 ◽

Cited By ~ 81

Author(s):

M. E. Soylu ◽

E. Istanbulluoglu ◽

J. D. Lenters ◽

T. Wang

Keyword(s):

Soil Moisture ◽

Water Table ◽

Soil Texture ◽

Land Surface ◽

Surface Interactions ◽

Water Table Depth ◽

Richards Equation ◽

Hydraulic Parameter ◽

Soil Hydraulic ◽

Semi Arid

Abstract. Interactions between shallow groundwater and land surface processes play an important role in the ecohydrology of riparian zones. Some recent land surface models (LSMs) incorporate groundwater-land surface interactions using parameterizations at varying levels of detail. In this paper, we examine the sensitivity of land surface evapotranspiration (ET) to water table depth, soil texture, and two commonly used soil hydraulic parameter datasets using four models with varying levels of complexity. The selected models are Hydrus-1D, which solves the pressure-based Richards equation, the Integrated Biosphere Simulator (IBIS), which simulates interactions among multiple soil layers using a (water-content) variant of the Richards equation, and two forms of a steady-state capillary flux model coupled with a single-bucket soil moisture model. These models are first evaluated using field observations of climate, soil moisture, and groundwater levels at a semi-arid site in south-central Nebraska, USA. All four models are found to compare reasonably well with observations, particularly when the effects of groundwater are included. We then examine the sensitivity of modelled ET to water table depth for various model formulations, node spacings, and soil textures (using soil hydraulic parameter values from two different sources, namely Rawls and Clapp-Hornberger). The results indicate a strong influence of soil texture and water table depth on groundwater contributions to ET. Furthermore, differences in texture-specific, class-averaged soil parameters obtained from the two literature sources lead to large differences in the simulated depth and thickness of the "critical zone" (i.e., the zone within which variations in water table depth strongly impact surface ET). Depending on the depth-to-groundwater, this can also lead to large discrepancies in simulated ET (in some cases by more than a factor of two). When the Clapp-Hornberger soil parameter dataset is used, the critical zone becomes significantly deeper, and surface ET rates become much higher, resulting in a stronger influence of deep groundwater on the land surface energy and water balance. In general, we find that the simulated sensitivity of ET to the choice of soil hydraulic parameter dataset is greater than the sensitivity to soil texture defined within each dataset, or even to the choice of model formulation. Thus, our findings underscore the need for future modelling and field-based studies to improve the predictability of groundwater-land surface interactions in numerical models, particularly as it relates to the parameterization of soil hydraulic properties.

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Examining the relationship between intermediate-scale soil moisture and terrestrial evaporation within a semi-arid grassland

Hydrology and Earth System Sciences ◽

10.5194/hess-20-3987-2016 ◽

2016 ◽

Vol 20 (10) ◽

pp. 3987-4004 ◽

Cited By ~ 8

Author(s):

Raghavendra B. Jana ◽

Ali Ershadi ◽

Matthew F. McCabe

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Root Zone ◽

Water Cycle ◽

Cosmic Ray ◽

Moisture Distribution ◽

Observation Data ◽

Cold Temperatures ◽

Intermediate Scale ◽

Semi Arid

Abstract. Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale mismatch when compared to coarser-resolution satellite-based soil moisture or evaporation estimates. The Cosmic Ray Neutron Probe (CRNP) was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here, we present a study to assess the utility of CRNP soil moisture observations in validating model evaporation estimates. The CRNP soil moisture product from a pasture in the semi-arid central west region of New South Wales, Australia, was compared to evaporation derived from three distinct approaches, including the Priestley–Taylor (PT-JPL), Penman–Monteith (PM-Mu), and Surface Energy Balance System (SEBS) models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson's correlations, quantile–quantile (Q–Q) plots, and analysis of variance (ANOVA) were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly 2 years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q–Q plots and ANOVA illustrate that the root-zone soil moisture represented by the CRNP measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold temperatures were present, while SEBS model estimates displayed a disconnect from the soil moisture distribution in summers with long dry spells. Importantly, no single evaporation model matched the statistical distribution of the measured soil moisture for the entire period, highlighting the challenges in effectively capturing evaporative flux response within changing landscapes. One of the outcomes of this work is that the analysis points to the feasibility of using intermediate-scale soil moisture measurements to evaluate gridded estimates of evaporation, exploiting the independent, yet physically linked nature of these hydrological variables.

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Predictability of soil moisture and river flows over France for the spring season

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-8-7947-2011 ◽

2011 ◽

Vol 8 (4) ◽

pp. 7947-7986

Author(s):

S. Singla ◽

J.-P. Céron ◽

E. Martin ◽

F. Regimbeau ◽

M. Déqué ◽

...

Keyword(s):

Soil Moisture ◽

Land Surface ◽

River Flow ◽

Climate Model ◽

Mediterranean Area ◽

Added Value ◽

Atmospheric Forcing ◽

Initial State ◽

The North ◽

Skill Scores

Abstract. Sources of spring predictability of the hydrological system over France were studied on a seasonal time scale over the 1960–2005 period. Two random sampling experiments were set up in order to test the relative importance of the land surface initial state and the atmospheric forcing. The experiments were based on the SAFRAN-ISBA-MODCOU hydrometeorological suite which computed soil moisture and river flow forecasts over a 8-km grid and more than 800 river-gauging stations. Results showed that the predictability of hydrological variables primarily depended on the seasonal atmospheric forcing (mostly temperature and total precipitation) over most plains, whereas it mainly depended on snow cover over high mountains. However, the Seine catchment area was an exception as the skill mainly came from the initial state of its large and complex aquifer. Seasonal meteorological hindcasts with the Météo-France ARPEGE climate model were then used to force the ISBA-MODCOU hydrological model and obtain seasonal hydrological forecasts from 1960 to 2005 for the entire March-April-May period. Scores from this seasonal hydrological forecasting suite could thus be compared with the random atmospheric experiment. Skill scores clearly showed the added value in seasonal meteorological forecasts in the north of France, contrary to the Mediterranean area where values worsened.

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Examining the relationship between intermediate scale soil moisture and terrestrial evaporation within a semi-arid grassland

10.5194/hess-2016-186 ◽

2016 ◽

Cited By ~ 2

Author(s):

Raghavendra B. Jana ◽

Ali Ershadi ◽

Matthew F. McCabe

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Root Zone ◽

Water Cycle ◽

Cosmic Ray ◽

Moisture Distribution ◽

Observation Data ◽

Cold Temperatures ◽

High Soil Moisture ◽

Semi Arid

Abstract. Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale-mismatch when compared to coarser-resolution satellite-based soil moisture or evaporation estimates. The Cosmic Ray Soil Moisture Observing System (COSMOS) was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here we present an examination of the links observed between COSMOS soil moisture retrievals and evaporation estimates over a pasture in the semi-arid central-west region of New South Wales, Australia. The COSMOS soil moisture product was compared to evaporation derived from three distinct approaches, including the Priestley-Taylor (PT-JPL), Penman-Monteith (PM-Mu) and Surface Energy Balance System (SEBS) models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson’s Correlations, Quantile-Quantile (Q-Q) plots, and Analysis of Variance (ANOVA) were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly two years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q-Q plots and ANOVA illustrate that the root-zone soil moisture represented by the COSMOS measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold temperatures were present, while SEBS model estimates displayed a disconnect from the soil moisture distribution in summers with long dry spells. Importantly, no single evaporation model matched the statistical distribution of the measured soil moisture for the entire period, highlighting the challenges in effectively capturing evaporative flux response within changing landscapes.

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Predictability of soil moisture and river flows over France for the spring season

Hydrology and Earth System Sciences ◽

10.5194/hess-16-201-2012 ◽

2012 ◽

Vol 16 (1) ◽

pp. 201-216 ◽

Cited By ~ 31

Author(s):

S. Singla ◽

J.-P. Céron ◽

E. Martin ◽

F. Regimbeau ◽

M. Déqué ◽

...

Keyword(s):

Soil Moisture ◽

Land Surface ◽

River Flow ◽

Climate Model ◽

Mediterranean Area ◽

Added Value ◽

Atmospheric Forcing ◽

Initial State ◽

The North ◽

Skill Scores

Abstract. Sources of spring predictability of the hydrological system over France were studied on a seasonal time scale over the 1960–2005 period. Two random sampling experiments were set up in order to test the relative importance of the land surface initial state and the atmospheric forcing. The experiments were based on the SAFRAN-ISBA-MODCOU hydrometeorological suite which computed soil moisture and river flow forecasts over a 8-km grid and more than 880 river-gauging stations. Results showed that the predictability of hydrological variables primarily depended on the seasonal atmospheric forcing (mostly temperature and total precipitation) over most plains, whereas it mainly depended on snow cover over high mountains. However, the Seine catchment area was an exception as the skill mainly came from the initial state of its large and complex aquifers. Seasonal meteorological hindcasts with the Météo-France ARPEGE climate model were then used to force the ISBA-MODCOU hydrological model and obtain seasonal hydrological forecasts from 1960 to 2005 for the entire March-April-May period. Scores from this seasonal hydrological forecasting suite could thus be compared with the random atmospheric experiment. Soil moisture and river flow skill scores clearly showed the added value in seasonal meteorological forecasts in the north of France, contrary to the Mediterranean area where values worsened.

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Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-12-13019-2015 ◽

2015 ◽

Vol 12 (12) ◽

pp. 13019-13067

Author(s):

A. Barella-Ortiz ◽

J. Polcher ◽

P. de Rosnay ◽

M. Piles ◽

E. Gelati

Keyword(s):

Soil Moisture ◽

Radiative Transfer ◽

Iberian Peninsula ◽

Land Surface ◽

Function Analysis ◽

Microwave Emission ◽

Radiative Transfer Model ◽

Retrieval Algorithm ◽

Transfer Model ◽

Brightness Temperatures

Abstract. L-Band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm. The work exposed compares brightness temperatures measured by the Soil Moisture and Ocean Salinity (SMOS) mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The latter were estimated using a radiative transfer model and state variables from two land surface models: (i) ORganising Carbon and Hydrology In Dynamic EcosystEms (ORCHIDEE) and (ii) Hydrology – Tiled ECMWF Scheme for Surface Exchanges over Land (H-TESSEL). The radiative transfer model used is the Community Microwave Emission Model (CMEM). A good agreement in the temporal evolution of measured and modelled brightness temperatures is observed. However, their spatial structures are not consistent between them. An Empirical Orthogonal Function analysis of the brightness temperature's error identifies a dominant structure over the South-West of the Iberian Peninsula which evolves during the year and is maximum in Fall and Winter. Hypotheses concerning forcing induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for it at the moment. Further hypotheses are proposed at the end of the paper.

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Improving Numerical Weather Predictions of Summertime Precipitation over the Southeastern United States through a High-Resolution Initialization of the Surface State

Weather and Forecasting ◽

10.1175/2011waf2222455.1 ◽

2011 ◽

Vol 26 (6) ◽

pp. 785-807 ◽

Cited By ~ 35

Author(s):

Jonathan L. Case ◽

Sujay V. Kumar ◽

Jayanthi Srikishen ◽

Gary J. Jedlovec

Keyword(s):

United States ◽

Soil Moisture ◽

High Resolution ◽

Land Surface ◽

Weather Prediction ◽

Southeastern United States ◽

Model Verification ◽

Sea Surface ◽

Convective Precipitation ◽

Numerical Weather

Abstract It is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high-resolution models. This paper presents model verification results of a case study period from June to August 2008 over the southeastern United States using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the National Aeronautics and Space Administration’s (NASA) Land Information System (LIS) and sea surface temperatures (SSTs) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction’s (NCEP) 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a resolution comparable to the 4-km model grid spacing. Soil moisture from the LIS spinup run is shown to respond better to the extreme rainfall of Tropical Storm Fay in August 2008 over the Florida peninsula. The LIS has slightly lower errors and higher anomaly correlations in the top soil layer but exhibits a stronger dry bias in the root zone. The model sensitivity to the alternative surface initial conditions is examined for a sample case, showing that the LIS–MODIS data substantially impact surface and boundary layer properties. The Developmental Testbed Center’s Meteorological Evaluation Tools package is employed to produce verification statistics, including traditional gridded precipitation verification and output statistics from the Method for Object-Based Diagnostic Evaluation (MODE) tool. The LIS–MODIS initialization is found to produce small improvements in the skill scores of 1-h accumulated precipitation during the forecast hours of the peak diurnal convective cycle. Because there is very little union in time and space between the forecast and observed precipitation systems, results from the MODE object verification are examined to relax the stringency of traditional gridpoint precipitation verification. The MODE results indicate that the LIS–MODIS-initialized model runs increase the 10 mm h−1 matched object areas (“hits”) while simultaneously decreasing the unmatched object areas (“misses” plus “false alarms”) during most of the peak convective forecast hours, with statistically significant improvements of up to 5%. Simulated 1-h precipitation objects in the LIS–MODIS runs more closely resemble the observed objects, particularly at higher accumulation thresholds. Despite the small improvements, however, the overall low verification scores indicate that much uncertainty still exists in simulating the processes responsible for airmass-type convective precipitation systems in convection-allowing models.

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Physical factors of influence in the interactions between rainfall, evapotranspiration and soil moisture driving the spatio-temporal evolution of drought patterns in the Ebro Basin (NE Spain).

10.5194/egusphere-egu21-2377 ◽

2021 ◽

Author(s):

Jaime Gaona ◽

Pere Quintana-Seguí ◽

Maria José Escorihuela

Keyword(s):

Soil Moisture ◽

Land Cover ◽

Iberian Peninsula ◽

Land Surface ◽

Temporal Analysis ◽

Drought Indices ◽

Surface Model ◽

Physical Factors ◽

Spatio Temporal ◽

The Impact

Droughts in the Iberian Peninsula are a natural hazard of great relevance due to their recurrence, severity and impact on multiple environmental and socioeconomic aspects. The Ebro Basin, located in the NE of the Iberian Peninsula, is particularly vulnerable to drought with consequences on agriculture, urban water supply and hydropower. This study, performed within the Project HUMID (CGL2017-85687-R), aims at evaluating the influence of the climatic, land cover and soil characteristics on the interactions between rainfall, evapotranspiration and soil moisture anomalies which define the spatio-temporal drought patterns in the basin.The onset, propagation and mitigation of droughts in the Iberian Peninsula is driven by anomalies of rainfall, evapotranspiration and soil moisture, which are related by feedback processes. To test the relative importance of such anomalies, we evaluate the contribution of climatic, land-cover and geologic heterogeneity on the definition of the spatio-temporal patterns of drought. We use the K&#246;ppen-Geiger climatic classification to assess how the contrasting climatic types within the basin determine differences on drought behavior. Land-cover types that govern the partition between evaporation and transpiration are also of great interest to discern the influence of vegetation and crop types on the anomalies of evapotranspiration across the distinct regions of the basin (e.g. forested mountains vs. crop-dominated areas). The third physical characteristic whose effect on drought we investigate is the impact of soil properties on soil moisture anomalies.The maps and time series used for the spatio-temporal analysis are based on drought indices calculated with high-resolution datasets from remote sensing (MOD16A2ET and SMOS1km) and the land-surface model SURFEX-ISBA. The Standardized Precipitation Index (SPI), the EvapoTranspiration Deficit Index (ETDI) and the Soil Moisture Deficit Index (SMDI) are the three indices chosen to characterize the anomalies of the corresponding rainfall (atmospheric), evapotranspiration (atmosphere-land interface) and soil moisture (land) anomalies (components of the water balance). The comparison of the correlations of the indices (with different time lags) between contrasting regions offers insights about the impact of climate, land-cover and soil properties in the dominance, the timing of the response and memory aspects of the interactions. The high spatial and temporal resolution of remote sensing and land-surface model data allows adopting time and spatial scales suitable to investigate the influence of these physical factors with detail beyond comparison with ground-based datasets.The spatial and temporal analysis prove useful to investigate the physical factors of influence on the anomalies between rainfall, evapotranspiration and soil moisture. This approach facilitates the physical interpretation of the anomalies of drought indices aiming to improve the characterization of drought in heterogeneous semi-arid areas like the Ebro River Basin.

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Irrigation in JULES Land-Only Simulations over South and East Asia

10.5194/egusphere-egu21-12213 ◽

2021 ◽

Author(s):

Markus Todt ◽

Pier Luigi Vidale ◽

Patrick C. McGuire ◽

Omar V. Müller

Keyword(s):

Soil Moisture ◽

East Asia ◽

Land Surface ◽

River Flow ◽

Heat Fluxes ◽

Global Climate Models ◽

Irrigated Agriculture ◽

Irrigation Season ◽

Irrigation Scheme ◽

The Impact

Capturing soil moisture-atmosphere feedbacks in a weather or climate model requires realistic simulation of various land surface processes. However, irrigation and other water management methods are still missing in most global climate models today, despite irrigated agriculture being the dominant land use in parts of Asia. In this study, we test the irrigation scheme available in the land model JULES (Joint UK Land Environment Simulator) by running land-only simulations over South and East Asia driven by WFDEI (WATCH Forcing Data ERA-Interim) forcing data. Irrigation in JULES is applied on a daily basis by replenishing soil moisture in the upper soil layers to field capacity, and we use a version of the irrigation scheme that extracts water for irrigation from groundwater and rivers, which physically limits the amount of irrigation that can be applied. We prescribe irrigation for C3 grasses in order to simulate the effects of agriculture, albeit retaining the simpler, widely used 5-PFT (plant functional type) configuration in JULES. Irrigation generally increases soil moisture and evapotranspiration, which results in increasing latent heat fluxes and decreasing sensible heat fluxes. Comparison with combined observational/machine-learning products for turbulent fluxes shows that while irrigation can reduce biases, other biases in JULES, unrelated to irrigation, are larger than improvements due to the inclusion of irrigation. Irrigation also affects water fluxes within the soil, e.g. runoff and drainage into the groundwater level, as well as soil moisture outside of the irrigation season. We find that the irrigation scheme, at least in the uncoupled land-atmosphere setting, can rapidly deplete groundwater to the point that river flow becomes the main source of irrigation (over the North China Plain and the Indus region) and can have the counterintuitive effect of decreasing annual average soil moisture (over the Ganges plain). Subsequently, we will explore the impact of irrigation on regional climate by conducting coupled land-atmosphere simulations.

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