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The link between soil water content (SWC) and evapotranspiration (ET) is of great importance in ecohydrology, agroecosystem management, and land-atmosphere interaction of earth-system analysis. There is still a need to understand the key processes linking SWC and ET in different vegetated ecosystems, especially at larger scales. Therefore, in this work, we used wavelet coherence analysis to explore the long-term relationship between SWC and ET among the predominant land use types (cropland, evergreen needleleaf forest, mixed forest, open shrubland, wooden tundra, grassland, and mixed tundra) in Europe during the last four decades (1980-2020). To this end, first a principal component analysis was performed among the SWC and ET data from GLDAS, GLEAM, and ERA5-land, and the first component was then used for further analyses when the target variable was in demand. Using the first component, then, we averaged SWC and ET data over the pixels covered by each land use type. Then, for each land-use types, we averaged the data daily for each decade to account for a representative decadal year of daily data. Then, wavelet coherence analysis was conducted between those averaged data of SWC and ET for each land-use type. The results showed a negative correlation between ET and SWC for all land use types, with ET lagging behind SWC, with an average phase shift value of 134 days for grassland (the minimum) and 168 days for mixed tundra (the maximum). Converting the phase shift values to a time lag [lag = n/2 - phase shift for the case phase shift < -n/4 where n represents the period (1/frequency) of the signals] shows (Fig. 1) that ET controls SWC with a lag of 15 days in mixed tundra (the minimum) and 48 days in grassland (the maximum). Moreover, we applied Mann-Kendall trend analysis test and found that the lag between SWC and ET decreases in mixed and wooden tundras with a slope value of -2.4 days/year, while it increases in cropland and grassland with a slope value of 1.6 days/year. Although there is a significant downward trend in evergreen needleleaf forests (with a slope value of -0.3 days/year) and an increasing trend in mixed forests and open shrublands (with a slope value of 0.4 days/year), the lower slope values in these land use types indicate that the change is slower compared to grasslands, croplands, and tundras. Figure 1- Temporal evolution of the lag between soil water content and evapotranspiration in the annual cycle in different land use types in Europe

Water resources research 59(3), e2022WR032430 (2023). doi:10.1029/2022WR032430, Groundwater recharge is the main forcing of regional groundwater flow. In traditional partial‐differential‐equation (pde)‐based models that treat aquifers as separate compartments, groundwater recharge needs to be defined as a boundary condition or it is a coupling condition to other compartments. Integrated models that treat the vadose and phreatic zones as a continuum allow for a more sophisticated calculation of subsurface fluxes, as feedbacks between both zones are captured. However, they do not contain an explicit groundwater‐recharge term so it needs to be estimated by post‐processing. Groundwater recharge consists of changes in groundwater storage and of the flux crossing the water table, which can be calculated based on hydraulic gradients. We introduce a method to evaluate the change of groundwater storage by a time‐cumulative water balance over the depth section of water table fluctuations, avoiding the use of a specific yield. We demonstrate the approach first by a simple 1‐D vertical model that does not allow for lateral outflow and illustrates the ambiguity of computing groundwater recharge by different methods. We then apply the approach to a 3‐D model with a complex topography and subsurface structure. The latter example shows that groundwater recharge is highly variable in space and time with notable differences between regional and local estimates. Local heterogeneity of topography or subsurface properties results in complex redistribution patterns of groundwater. In fully integrated models, river‐groundwater exchange flow may severely bias the estimate of groundwater recharge. We, therefore, advise masking out groundwater recharge at river locations., Published by Wiley, [New York]

Reliable predictions of water systems’ response to external pressures and ongoing changes are highly important to ensure informed decision-making to support sustainable water resources management for human use and the functioning of healthy ecosystems. Recent strong development of numerical models offers a potential to understand and forecast water systems under anthropogenic and climatic influences to provide information for decision-making, process understanding of the ‘unseen’ part of the water cycle and hazard risk analysis. However, the reliability of numerical model predictions is strongly influenced by various sources of uncertainties, data qualities and assumptions, and often lacks stakeholders' point-of-view. A new, improved approach is needed and in this paper, we present six basic principles to improve the reliability and accuracy of numerical water model predictions considering explicitly stakeholders' needs and, thereby, better serving the society. Six highlighted principles are: (i) clearly defining the objectives and the purpose of the model, sustaining them during the entire modelling process; (ii) incorporating expert and local community knowledge through stakeholders' feedback; (iii) implementing a multi-model approach in which a range of conceptualizations are explored ; (iv) considering and representing the uncertainties arising from model inputs, parameters, conceptual model structure and measurement/information error; (v) translating the results to concrete and understandable strategies that policymakers can use for their informed decision-making; and (vi) long term capacity building and monitoring data collection to reduce knowledge gaps, test and improve predictions. We argue that implementing these six principles reduces uncertainties, improves the predictive capacity of the numerical water models, and ensures informed decision-making to support sustainable water resources management and thereby serve society better.

European Geoscience Union General Assembly, EGU 2023, Vienna, Austria, 24 Apr 2023 - 28 Apr 2023; doi:10.5194/egusphere-egu23-3095, Soil moisture (SM) sensors are widely used to monitor soil water dynamics and support irrigation management with the aim of achieving better yields while reducing water consumption. Unfortunately, due to the small measuring volume of point-scale sensors, their soil moisture readings are often not representative for heterogeneous agricultural fields. Therefore, in such cases, sensors with larger sensing volume are needed to address spatially variable SM. A suitable technique is the cosmic ray neutron sensor (CRNS) as it integrates SM over a large volume with a radius of ~130-210 m and a penetration depth of ~15-85 cm. The CRNS method is based on the inverse relationship between measured environmental neutron density and the presence of hydrogen pools (e.g., SM) in the instrument surroundings. However, the ability of CRNS to accurately monitor areas with complex SM heterogeneities (e.g., small irrigated fields) and the influence of detector design were not yet investigated. In this study, we used the neutron transport model URANOS to simulate the effect of SM variations on a CRNS placed in the centre of squared irrigated fields (0.5 to 8 ha dimensions). For this, SM in the irrigated field and in the surrounding was altered between 0.05 and 0.50 cm3 cm-3 (500 simulations in total). In addition, we investigated the effect of employing high-density polyethylene (HDPE) moderators with different thickness (5 to 35 mm) as well as a 25 mm HDPE moderator with an additional gadolinium oxide thermal shielding. Results showed that, in heterogeneous SM scenarios, the 2 e-folding lengths footprint (R86) can become smaller or larger than what previous studies showed in homogeneous SM distributions. In addition, a thin HDPE moderator will result in relatively smaller R86 whereas thicker moderators and the addition of a thermal shielding will result in relatively larger R86. However, we found that a relatively small footprint is not directly related to a better monitoring of SM nearby the instrument. In fact, in all the investigated field dimensions, the 25mm HDPE moderator with gadolinium shielding showed the largest values of R86 but also the largest variations of detected neutrons with changing SM. In addition, such moderator showed the highest chances of detecting irrigation events that increase SM by 0.05 or 0.10 cm3 cm-3 in the irrigated area. Generally, detection was uncertain only for SM variations of 0.05 cm3 cm-3 in fields of 0.5 ha when initial SM was 0.02 cm3 cm-3 or higher. Although the results of this study suggest the feasibility of monitoring and informing irrigation with CRNS, we found that SM variations outside the irrigated field have a considerable influence on CRNS measurements. Especially in fields of 0.5 and 1 ha dimension, it can be impossible to distinguish whether a relative change in detected neutrons is due to irrigation or to SM variations in the surroundings. These results are relevant for irrigation monitoring and the combination of neutron transport simulations and real-world installations has the potential to establish CRNS as a decision support system for irrigation management.

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Land surface models (LSMs) are increasingly being used to study how irrigated agriculture, the largest consumer of fresh water globally, affects crop growth, water resources status, and climate. This is especially of interest in dry and semi-dry agricultural regions such as the Mediterranean, where water scarcity, overexploitation and expected climate change impacts threaten local water resources. The simulation of these agricultural ecosystems necessitates comprehensive crop modules. Such modules must consider local irrigation patterns, crop types, and crop specific management practices to understand their influence on water and energy fluxes under present and future climates. This study explores the water footprint of fruit orchards in the Pinios Hydrological Observatory (PHO) in central Greece, using CLM5-FruitTree, a recent development of the Community Land Model version 5, to include deciduous fruit orchards and associated management practices. Initially, CLM5-FruitTree was setup and validated at field scale using data from two highly instrumented irrigated apple orchards within the PHO. The simulations used local climate, soil, crop management and phenology information. Model results were compared to observed apple yield, sap flow, irrigation amounts, and soil moisture. The latter was obtained from a distributed sensor network measuring soil moisture in three depths at 12 locations per field as well as two cosmic-ray neutron soil moisture sensors. The model was able to reproduce the soil moisture response to irrigation satisfactorily when the local irrigation schedule was considered. The simulated irrigation amount indicated that around 45% less water than the amount applied by the farmer could be used without reduction in yield. This suggests potential improvements in irrigation efficiency by reducing losses through evaporation or deep percolation. However, possible model weaknesses in the representation of soil properties and water fluxes should be further addressed. Successively, a modeling case for the PHO is set up to study the regional irrigation water consumption and the local groundwater aquifer recharge. Results from this study could help local authorities in the definition of water policies and serve as a basis for climate impact studies on regional irrigation management.

The agricultural sector is increasingly reliant on water availability, especially given expected increase of agricultural droughts related to climate change. Thus, improved soil moisture (SM) monitoring tools are needed to support more efficient water management strategies such as precision irrigation. A novel and non-invasive method is cosmic-ray neutron sensing (CRNS). It is characterized by a large footprint (~240m) and relies on the negative correlation between fast neutrons originating from cosmic radiation and SM. Despite promising results in the monitoring of SM dynamics and patterns, only a few studies explored the use of CRNS for irrigation management. In this study, two apple orchards of ~1.2 ha located in the Pinios Hydrological Observatory (Greece) were provided with CRNS probes. These were supported by extensive monitoring of SM and climate data in the context of the H2020 ATLAS project. In capturing irrigation events, the agreement between the CRNS and the validation measurements depended largely on a) the timing of irrigation, b) the CRNS calibration strategy, c) precipitation, and d) the management of the surrounding fields. In parallel, we performed neutron transport simulations of multiple scenarios with variable irrigated area and soil moisture by using the URANOS model. This allowed the study of how the surrounding environment influences the effectiveness of a CRNS sensor when its footprint is larger than the area of interest. This combination of simulations and experiments is providing key insights on how CRNS methods can move from a proof o concept to a relevant tool in actual precisionirrigation scenarios.