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Humans play a large role in the hydrological system, e.g. by extracting large amounts of water for irrigation, often resulting in water stress and ecosystem degradation. By implementing large-scale adaptation measures, such as the construction of irrigation reservoirs, water stress and ecosystem degradation can be reduced. Yet we know that many decisions, such as the adoption of more effective irrigation techniques or changing crop types, are made at the farm level by a heterogeneous farmer population. While these decisions are usually advantageous for an individual farmer or their community, aggregate effects of those decisions can have large effects downstream. Similarly, decisions made by other stakeholders, such as governments, often have basin-wide effects and affect each farmer differently. To fully comprehend how the human–natural water system evolves over time and space and to explore which interventions are suitable to reduce water stress, it is important to consider human behaviour and feedbacks to the hydrological system simultaneously at the local household and large basin scales. Therefore, we present the Geographical, Environmental, and Behavioural (GEB) model, a coupled agent-based hydrological model that simulates the behaviour and daily bidirectional interaction of more than 10 million individual farm households with the hydrological system on a personal laptop. Farmers exhibit autonomous heterogeneous behaviour based on their characteristics, assets, environment, management policies, and social network. Examples of behaviour are irrigation, generation of income from selling crops, and investment in adaptation measures. Meanwhile, reservoir operators manage the amount of water available for irrigation and river discharge. All actions can be taken at a daily time step and influence the hydrological system directly or indirectly. GEB is dynamically linked with the spatially distributed grid-based hydrological model CWatM at 30 ′′ resolution (< 1 km at the Equator). Because many smallholder farm fields are much smaller than 1 × 1 km, CWatM was specifically adapted to implement dynamically sized hydrological response units (HRUs) at the farm level, providing each agent with an independently operated hydrological environment. While the model could be applied anywhere globally at both large and small scales, we explore its implementation in the heavily managed Krishna basin in India, which encompasses ∼ 8 % of India's land area and ∼ 12.1 million farmers. [ABSTRACT FROM AUTHOR]

Groundwater recharge is difficult to estimate, especially in fractured aquifers, because of the spatial variability of the soil properties and because of the lack of data at basin scale. A relevant method, known as the water table fluctuation (WTF) method, consists in inferring recharge directly from the WTFs observed in boreholes. However, the WTF method neglects the impact of lateral groundwater redistribution in the aquifer; i.e., it assumes that all the WTFs are attributable to recharge. In this study, we developed the WTF approach in the frequency domain to better consider groundwater lateral flow, which quickly redistributes the impulse of recharge and mitigates the link between WTFs and recharge. First, we calibrated a 1D analytical groundwater model to estimate hydrodynamic parameters at each borehole. These parameters were defined from the WTFs recorded for several years, independently of prescribed potential recharge. Second, calibrated models are reversed analytically in the frequency domain to estimate recharge fluctuations (RFs) at weekly to monthly scales from the observed WTFs. Models were tested on two twin sites with a similar climate, fractured aquifer and land use but different hydrogeologic settings: one has been operated as a pumping site for the last 25 years (Ploemeur, France), while the second has not been perturbed by pumping (Guidel). Results confirm the important role of rainfall temporal distribution in generating recharge. While all rainfall contributes to recharge, the ratio of recharge to rainfall minus potential evapotranspiration is frequency-dependent, varying between 20 %–30 % at periods <10 d and 30 %–50 % at monthly scale and reaching 75 % at seasonal timescales. We further show that the unsaturated zone thickness controls the intensity and timing of RFs. Overall, this approach contributes to a better assessment of recharge and helps to improve the representation of groundwater systems within hydrological models. In spite of the heterogeneous nature of aquifers, parameters controlling WTFs can be inferred from WTF time series, providing confidence that the method can be deployed in different geological contexts where long-term water table records are available. [ABSTRACT FROM AUTHOR]

In the context of changing climate and increasing water demand, large-scale hydrological models are helpful for understanding and projecting future water resources across scales. Groundwater is a critical freshwater resource and strongly controls river flow throughout the year. It is also essential for ecosystems and contributes to evapotranspiration, resulting in climate feedback. However, groundwater systems worldwide are quite diverse, including thick multilayer aquifers and thin heterogeneous aquifers. Recently, efforts have been made to improve the representation of groundwater systems in large-scale hydrological models. The evaluation of the accuracy of these model outputs is challenging because (1) they are applied at much coarser resolutions than hillslope scale, (2) they simplify geological structures generally known at local scale, and (3) they do not adequately include local water management practices (mainly groundwater pumping). Here, we apply a large-scale hydrological model (CWatM), coupled with the groundwater flow model MODFLOW, in two different climatic, geological, and socioeconomic regions: the Seewinkel area (Austria) and the Bhima basin (India). The coupled model enables simulation of the impact of the water table on groundwater–soil and groundwater–river exchanges, groundwater recharge through leaking canals, and groundwater pumping. This regional-scale analysis enables assessment of the model's ability to simulate water tables at fine spatial resolutions (1 km for CWatM, 100–250 m for MODFLOW) and when groundwater pumping is well estimated. Evaluating large-scale models remains challenging, but the results show that the reproduction of (1) average water table fluctuations and (2) water table depths without bias can be a benchmark objective of such models. We found that grid resolution is the main factor that affects water table depth bias because it smooths river incision, while pumping affects time fluctuations. Finally, we use the model to assess the impact of groundwater-based irrigation pumping on evapotranspiration, groundwater recharge, and water table observations from boreholes. [ABSTRACT FROM AUTHOR]

Humans play a large role in the hydrological system; for example, by extracting large amounts of water for irrigation, often resulting in water stress and ecosystem degradation. By implementing large-scale adaptation measures, such as the construction of irrigation reservoirs, water stress and ecosystem degradation can be reduced. Yet we know that many decisions, such as the adoption of more effective irrigation techniques or changing crop types, are made at the farm level by a heterogeneous farmer population. While these decisions are often advantageous for an individual farmer or their community, detrimental effects are frequently experienced downstream. Therefore, to fully comprehend how the humannatural water system evolves over time and space, and to explore which interventions are suitable to reduce water stress, it is important to consider human behaviour and feedbacks to the hydrological system simultaneously at the local household and large basin scales. Therefore, we present the Geographical, Environmental and Behavioural model (GEB), a coupled agentbased hydrological model that simulates the behaviour and daily bi-directional interaction of up to ~10 million individual farm households with the hydrological system on a personal laptop. GEB is dynamically linked with the spatially distributed grid-based hydrological model CWatM at 30’’ resolution (< 1km at the equator). Because many small-holder farmer fields are much smaller than 1×1 km, CWatM was specifically adapted to implement dynamically sized hydrological response units (HRUs) at the farm level, providing each agent with an independently operated hydrological environment. While the model could be applied globally, we explore its implementation in the heavily managed Krishna basin in India, which encompasses ~8% of India’s land area and ~11.1 million farmers. Here, we show how six combinations of storylines with endogenous and exogenous drivers of adaptation affect both the hydrological system and the farmer population. [ABSTRACT FROM AUTHOR]

Humans play a large role in the hydrological system; for example, by extracting large amounts of water for irrigation, often resulting in water stress and ecosystem degradation. By implementing large-scale adaptation measures, such as the construction of irrigation reservoirs, water stress and ecosystem degradation can be reduced. Yet we know that many decisions, such as the adoption of more effective irrigation techniques or changing crop types, are made at the farm level by a heterogeneous farmer population. While these decisions are often advantageous for an individual farmer or their community, detrimental effects are frequently experienced downstream. Therefore, to fully comprehend how the human-natural water system evolves over time and space, and to explore which interventions are suitable to reduce water stress, it is important to consider human behaviour and feedbacks to the hydrological system simultaneously at the local household and large basin scales. Therefore, we present the Geographical, Environmental and Behavioural model (GEB), a coupled agent-based hydrological model that simulates the behaviour and daily bi-directional interaction of up to ~10 million individual farm households with the hydrological system on a personal laptop. GEB is dynamically linked with the spatially distributed grid-based hydrological model CWatM at 30" resolution (< 1 km at the equator). Because many small-holder farmer fields are much smaller than 1×1 km, CWatM was specifically adapted to implement dynamically sized hydrological response units (HRUs) at the farm level, providing each agent with an independently operated hydrological environment. While the model could be applied globally, we explore its implementation in the heavily managed Krishna basin in India, which encompasses ~8 % of India's land area and ~11.1 million farmers. Here, we show how six combinations of storylines with endogenous and exogenous drivers of adaptation affect both the hydrological system and the farmer population. [ABSTRACT FROM AUTHOR]

In the context of changing climate and increasing water demand, large-scale hydrological models are helpful for understanding and projecting future water resources across scales. Groundwater is a critical freshwater resource and strongly controls river flow throughout the year. It is also essential for ecosystems and contributes to evapotranspiration, resulting in climate feedback. However, groundwater systems worldwide are quite diverse, including thick multi-layer aquifers and thin heterogeneous aquifers. Recently, efforts have been made to improve the representation of groundwater systems in largescale hydrological models. The evaluation of the accuracy of these model outputs is challenging because: (1) they are applied at much coarser resolutions than hillslope scale, (2) they simplify geological structures generally known at local scale, and (3) they do not adequately include local water management practices (mainly groundwater pumping). Here, we apply a large-scale hydrological model (CWatM), coupled with the groundwater flow model MODFLOW, in two different climatic, geological, and socioeconomic regions, the Seewinkel area (Austria) and the Bhima basin (India). The coupled model enables simulation of the impact of the water table on groundwater-soils and groundwater-rivers exchanges, groundwater recharge through leaking canals, and groundwater pumping. This regional scale analysis enables assessment of the model's ability to simulate water tables at fine spatial resolutions (1 km for CWatM, 100-250 m for MODFLOW) and when groundwater pumping is well estimated. Evaluating large-scale models remains challenging, but the results show that the reproduction of (1) average water table fluctuations and (2) water table depths without bias can be a benchmark objective of such models. We found that subgrid resolution (river incision) is the main factor that affects water table depth bias, while pumping affects time fluctuations. Finally, we use the model to assess the impact of groundwater-based irrigation pumping on evapotranspiration, groundwater recharge, and water table observations from boreholes. [ABSTRACT FROM AUTHOR]

Groundwater recharge is difficult to estimate, especially in fractured aquifers, because of the spatial variability of the soil properties and because of the lack of data at basin scale. A relevant method, known as the WTF method, consists in inferring recharge directly from the water table fluctuations (WTF) observed in boreholes. However, the WTF method neglects the impact of lateral groundwater redistribution in the aquifer, i.e. assumes that all the WTF are attributable to recharge. In this study, we developed the WTF approach in the frequency domain to better consider groundwater lateral flow, which quickly redistributes the inpulse of recharge and mitigates the link between WTF and recharge. First, we calibrated a 1D analytical groundwater model to estimate hydrodynamic parameters at each borehole. These parameters were defined from the WTF recorded for several years, independently of prescribed potential recharge. Second, calibrated models are reversed analytically in the frequency domain to estimate recharge fluctuations (RF) at weekly to monthly scales from the observed WTF. Models were tested on two twin sites with similar climate, fractured aquifer, and land use but different hydrogeologic settings: one has been operated as a pumping site for the last 25 years (Ploemeur, France) while the second has not been perturbed by pumping (Guidel). Results confirm the important role of rainfall temporal distribution to generate recharge. While all rainfall contribute to recharge, the ratio of recharge to rainfall minus potential evapotranspiration is frequency dependent, varying between 20-30 % at periods <10 days, 30-50 % at monthly scale, and reaching 75 % at seasonal time scales. We further show that the unsaturated zone thickness controls the intensity and timing of RF. Overall, this approach contributes to better assess recharge and enable to improve the representation of groundwater systems within hydrological models. In spite of the heterogeneous nature of aquifers, parameters controlling WTF can be inferred from WTF time series. [ABSTRACT FROM AUTHOR]

Streamwater transit time distributions display a variable proportion of old waters (≥1 year). We hypothesize that the corresponding long transit times result from groundwater contributions to the stream and that seasonal streamwater transit time variations result from (a) the variable contributions of different flowpaths (overland flow, seepage flow and baseflow) and (b) the stratification of groundwater residence times. We develop a parsimonious model to capture the groundwater contribution to the stream discharge and its effect on transient transit times. Infiltration is partitioned according to the aquifer saturation between Boussinesq groundwater flow and overland flow. Time‐variable transit time distributions are obtained with a new 2D particle tracking algorithm. Hydraulic conductivity, total and drainable porosities are calibrated by using discharge and CFC tracer data on a crystalline catchment located in Brittany (France). The calibrated models succeed in reproducing CFCs concentrations and discharge dynamics. The groundwater flow contribution to the stream is controlled by the aquifer hydraulic conductivity, while its age is controlled by the drainable and total porosities. Old groundwater (≥1 year) is the source for approximately 75% of the streamflow with strong seasonal variations (between 40% and 95%). Mean transit times are approximately 13 years, varying between 6 and 20 years, proportional to the groundwater contribution. These seasonal variations are driven by the groundwater versus overland flow partitioning. The stratification of groundwater residence times in the aquifer plays a minor role in the streamwater transit times but is key for the transit time dynamics of the groundwater contribution to the stream. Plain Language Summary: Water entering a catchment as precipitation can take multiple paths with different transit times to the stream. While a significant fraction of water has short transit times (i.e., is "young") when it reaches the stream, there is also an important contribution of "old" water with long residence times in the subsurface. The age distribution of this old component is important for understanding the resilience of watersheds to climate change, the behavior of persistent pollutants and chemical weathering processes. We developed a model, informed with discharge time series and atmospheric age tracer (CFCs), to constrain the age distribution in both groundwater and streamwater and how they vary seasonally. In our temperate test catchment with crystalline bedrock (Brittany, France), we find that the mean age of streamwater exiting the catchment is approximately 13 years, but varies seasonally from 6 to 20 years as the relative contributions of older groundwater and younger runoff change. Groundwater stratification further influences the mean age of the groundwater contribution arriving at the stream. Key Points: Hydraulic conductivity controls groundwater flow contributions to streams while porosity directly scales the streamwater mean transit timesSeasonal groundwater contributions to streams modulate the mean transit times dynamics from 6 years at high flows to 20 years at low flowsStratified groundwater ages lead to a significant fraction (>75%) of old water to streamflow (>1 year) [ABSTRACT FROM AUTHOR]

We develop a new large-scale hydrological and water resources model, the Community Water Model (CWatM), which can simulate hydrology both globally and regionally at different resolutions from 30 arcmin to 30 arcsec at daily time steps. CWatM is open source in the Python programming environment and has a modular structure. It uses global, freely available data in the netCDF4 file format for reading, storage, and production of data in a compact way. CWatM includes general surface and groundwater hydrological processes but also takes into account human activities, such as water use and reservoir regulation, by calculating water demands, water use, and return flows. Reservoirs and lakes are included in the model scheme. CWatM is used in the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which compares global model outputs. The flexible model structure allows for dynamic interaction with hydro-economic and water quality models for the assessment and evaluation of water management options. Furthermore, the novelty of CWatM is its combination of state-of-the-art hydrological modeling, modular programming, an online user manual and automatic source code documentation, global and regional assessments at different spatial resolutions, and a potential community to add to, change, and expand the open-source project. CWatM also strives to build a community learning environment which is able to freely use an open-source hydrological model and flexible coupling possibilities to other sectoral models, such as energy and agriculture. [ABSTRACT FROM AUTHOR]

We develop a new large-scale hydrological and water resources model, the Community Water Model (CWatM), which can simulate hydrology both globally and regionally at different resolutions from 30 arc min to 30 arc sec at daily time steps. CWatM is open-source in the Python programming environment and has a modular structure. It uses global, freely available data in the netCDF4 file format for reading, storage, and production of data in a compact way. CWatM includes general surface and groundwater hydrological processes, but also takes into account human activities, such as water use and reservoir regulation, by calculating water demands, water use, and return flows. Reservoirs and lakes are included in the model scheme. CWatM is used in the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which compares global model outputs. The flexible model structure allows dynamic interaction with hydro-economic and water quality models for the assessment and evaluation of water management options. Furthermore, the novelty of CWatM is its combination of state-of the-art hydrological modeling, modular programming, an online user manual and automatic source code documentation, global and regional assessments at different spatial resolutions, and a potential community to add to, change, and expand the open-source project. CWatM also strives to build a community learning environment which is able to freely use an open-source hydrological model and flexible coupling possibilities to other sectoral models, such as energy and agriculture. [ABSTRACT FROM AUTHOR]