Shallow Water Table Depth Research Articles

Effects of water-table depth on seed quality as β-glucan content in waxy and non-waxy naked barley grains

ABSTRACT Naked barley (Hordeum vulgare L.) is often planted as a regional specialty crop in the western region of Japan, where there are many hilly and mountainous areas. Water-table depths there are often shallow, due to the inflow of spring melt-water and underground water from the mountains. In this study, the effects of water-table depth on growth and β-glucan content in naked barley were studied by using a lysimeter. The new, waxy-type, naked barley cultivar ‘Fukumifiber’, with high β-glucan content, showed that β-glucan content per grain with same ripeness were decreased by shallower water-table depth, while in the non-waxy cultivar ‘Ichibanboshi’, the effect to β-glucan content per grain was not significant. During ripening, the β-glucan content in both waxy and non-waxy cultivars increased sharply from the 20th to the 30th days after anthesis. In waxy-type cultivar ‘Fukumifiber’, β-glucan further accumulated from the 30th to the 50th days after anthesis, but the accumulation was suppressed as the water-table depth shallowed. While in non-waxy type cultivar ‘Ichibanboshi’, there was no significant increase from the 30th to the 50th days after anthesis and there were no significant differences due to the water-table depth. These results suggest that good drainage may be particularly important before from the 20th to the 30th days after anthesis for all cultivars. Furthermore, for some cultivars similar measures until the 50th day after anthesis may also be important. And even under shallow water-table depth condition, the difference between cultivars that have high β-glucan content or low content was maintained.

Biometeorological feedbacks on peatlands: Raising the water table to reduce meteorologically-related stress on cattle

Peatland restoration is an important mitigation action in the fight against climate change. Researchers encourage farmers to rewet deep-drained lands on organic soil to a shallow water table depth (WTD) to reduce carbon emissions. Raising WTD under grasslands will likely affect local air temperature (TA) and increase relative humidity (RH), with uncertain consequences during heat waves on cattle welfare. We used WTD, TA and RH data (both measured between 1.25 and 2 m above ground) from 22 peatland sites globally to evaluate peatlands’ overall Temperature Humidity Index (THI), an indicator correlated to cattle welfare used in dairy farms (THI>68 increases heart rate, breathing rate and reduces milk yield). We compared them with THI at state weather stations located on neighbouring lands with short grass on non-organic soil, and assessed the impact of WTD.At most sites, peatlands with shallow WTD had lower TA, higher RH, and an overall lower THI than surrounding lands, compared to those with deep WTD. In most cases, THI decreased with increasing WTD, especially at night in the temperate region, except for coastal peatlands. Shallow and submerged sites had 20 % less hours with stressful meteorologic conditions (high THI) than surrounding areas. In contrast, the number of hours with high THI did not change significantly on peatlands with WTD under 20 cm below ground level compared to control sites. Our results confirm the influence of WTD on local temperature and THI, and suggest that raising WTD on drained peatlands will slightly improve cattle welfare with reduced THI during heat waves, but also acknowledge that local geographic characteristics add complexity to this relationship. Our research indicates that raising WTD to ground level in sections of grasslands could provide “heat wave shelters” and increase cattle resilience to climate change while contributing to the global reduction of carbon emissions.

Implementing augmented deep Machine learning for effective shallow water table management and forecasting

This study addresses the gap in understanding and forecasting shallow water table depth (WTD), a critical factor in groundwater resource management and agricultural productivity. Despite the importance of accurately forecasting WTD for sustainable water resource management, current methods frequently struggle to capture the complexities and dynamics of WTD fluctuations. In response, this research, which was conducted in Québec, Canada, leverages machine learning techniques—namely, extreme learning machines (ELMs) and long short-term memory (LSTM) networks, augmented by the Holt-Winters (HW) state-space method—to develop a comprehensive analysis and forecasting approach for shallow WTD. The datasets were recorded by 8 sensors with hourly temporal resolutions from June to September, covering the growing season. The objective was to increase forecast accuracy by employing a detailed structural analysis of WTD time series data, selecting appropriate forecast steps, and fine-tuning model inputs through statistical tests and model-agnostic interpretation methods. The performance was evaluated via various metrics, including the correlation coefficient (R), root mean square error (RMSE), mean absolute relative error (MARE), and Theil’s U accuracy and quality coefficients, across short- to long-term forecasts (1-, 12-, 24-, 48-, and 72-hour ahead). Integration of HW with the ELM and LSTM models markedly improved the forecasting capabilities, particularly for the LSTM model, which achieved high accuracy of R = 0.988 for 1-hour forecasts and low error rates (RMSE = 0.648 cm, MARE = 0.007, UI = 0.005, and UII = 0.010), although accuracy decreased for longer forecast horizons, resulting in the lowest accuracy for 72-hour forecasts, with R = 0.638, RMSE = 4.550 cm, MARE = 0.051, UI = 0.036, and UII = 0.071. Similarly, the ELM model showed promising results in short-term forecasts when coupled with HW (R = 0.988, RMSE = 0.676 cm, MARE = 0.007, UI = 0.005, and UII = 0.010) but experienced a decrease in performance accuracy over more extended forecast periods (R = 0.707, RMSE = 5.559 cm, MARE = 0.053, UI = 0.045, and UII = 0.089). Although the ELM model presented a negligible strong correlation in some forecast steps, the LSTM model offered consistently higher forecast accuracy and quality across all assessed horizons. The study demonstrates the superiority of the LSTM model in consistently providing more accurate forecasts, highlighting the importance of integrating HW to capture complex temporal patterns in hydrological forecasting. This advancement in forecasting WTD has substantial implications for enhancing groundwater resource management and agricultural decision-making, significantly contributing to sustainable water resource utilization and supporting agricultural productivity through informed data-driven practices.

Investigating the role of groundwater in ecosystem water use efficiency in India considering irrigation, climate and land use

Terrestrial ecosystems (TEs) play a crucial role in carbon sequestration and climate regulation. While interactions between surface water and ecosystems are well-studied, groundwater-ecosystem relationships remain poorly understood, particularly in groundwater-dependent regions like India. This study investigates the relationship between water table depth (WTD) and ecosystem productivity across India, considering the variation in irrigation practices, land use and climate types, from 2000 to 2021. We employ Ecosystem Water Use Efficiency (WUEe), the rate of carbon uptake per unit of water consumed, to examine these interactions at different spatial scales. Our findings reveal a strong link between WUEe and WTD. Shallower WTD regions, such as the lower Himalayas and Northeast India with forests and dominated by a wet/humid subtropical climate, exhibit higher WUEe (1.5–3.5 g C/kg H2O). Whereas deeper WTD regions like northwest India, characterized by shrublands and an arid climate, display lower WUEe (<1 g C/kg H2O). This suggests vegetation in arid/semi-arid regions shows higher sensitivity to water availability compared to wetter areas. This is also evident by a declining WUEe trend and increasing elasticity of WUEe (εWUE) to interannual climatic variability with increasing WTD in these regions. Furthermore, the study identifies potential unsustainable groundwater use for irrigation in areas like the Trans Gangetic plains. Irrigation has a strong correlation with evapotranspiration (ET) (r = 0.4–0.6) in deep WTD zones, but no correlation with WUEe. This implies that intense and unsustainable irrigation might disrupt the natural water use strategies of vegetation. This research, by improving understanding of these interactions, aims to contribute to the sustainable management of India's groundwater resources.

Drainage effects on carbon budgets of degraded peatlands in the north of the Netherlands

Peatlands store vast amounts of carbon (C). However, land-use-driven drainage causes peat oxidation, resulting in CO2 emission. There is a growing need for ground-truthing CO2 emission and its potential drivers to better quantify long-term emission trends in peatlands. This will help improve National Inventory Reporting and ultimately aid the design and verification of mitigation measures. To investigate regional drivers of CO2 emission, we estimated C budgets using custom-made automated chamber systems measuring CO2 concentrations corrected for carbon export and import. Chamber systems were rotated among thirteen degraded peatland pastures in Friesland (the Netherlands). These peatlands varied in water table depth (WTD), drainage-irrigation management (fixed regulated ditch water level (DWL), subsurface irrigation, furrow irrigation, or dynamic regulated DWL), and soil moisture. We investigated (1) whether drainage-irrigation management and related hydrological drivers could explain variation in C budgets, (2) how nighttime ecosystem respiration (Reconight) related to hydrological drivers, and (3) how C budgets compared with estimates from Tier 1 and Tier 2 models regularly used in National Inventory Reporting. Deep-drained peatlands largely overlapped with C budgets from shallow-drained peatlands. The variation in C budgets could not be explained with drainage-irrigation measures or annual WTD, likely because of high variation between sites. Reconightincreased from 85 to 250 kg CO2 ha−1 day−1 as the WTD dropped from 0 to 50 cm across all sites. A deeper WTD had no apparent effect on Reconight, which could be explained by the unimodal relationship we found between Reconight and soil moisture. Finally, C budgets estimated by Tier 1 emission factors and Tier 2 national models mismatched the between-site and between-year variation found in chamber-based estimated NECBs. To conclude, our study showed that shallow WTDs greatly determine C budgets and that regional C budgets, which can be accurately measure with periodic automated chamber measurements, are instrumental for model validation.

Water Table Depth Estimates over the Contiguous United States Using a Random Forest Model.

Water table depth (WTD) has a substantial impact on the connection between groundwater dynamics and land surface processes. Due to the scarcity of WTD observations, physically-based groundwater models are growing in their ability to map WTD at large scales; however, they are still challenged to represent simulated WTD compared to well observations. In this study, we develop a purely data-driven approach to estimating WTD at continental scale. We apply a random forest (RF) model to estimate WTD over most of the contiguous United States (CONUS) based on available WTD observations. The estimated WTD are in good agreement with well observations, with a Pearson correlation coefficient (r) of 0.96 (0.81 during testing), a Nash-Sutcliffe efficiency (NSE) of 0.93 (0.65 during testing), and a root mean square error (RMSE) of 6.87 m (15.31 m during testing). The location of each grid cell is rated as the most important feature in estimating WTD over most of the CONUS, which might be a surrogate for spatial information. In addition, the uncertainty of the RF model is quantified using quantile regression forests. High uncertainties are generally associated with locations having a shallow WTD. Our study demonstrates that the RF model can produce reasonable WTD estimates over most of the CONUS, providing an alternative to physics-based modeling for modeling large-scale freshwater resources. Since the CONUS covers many different hydrologic regimes, the RF model trained for the CONUS may be transferrable to other regions with a similar hydrologic regime and limited observations.

The biogeography of embolism resistance across resource gradients in the Amazon

AbstractAimUnderstanding tree mortality under climate change‐induced droughts requires knowledge of hydraulic trait distribution across environmental gradients. The spatial distribution of embolism resistance (i.e., P50), a key trait linked to hydraulic failure, is currently unknown across the Amazon. Here, we tested how precipitation, water table depth (WTD) and soil fertility interact as filters modulating the geographic hydraulic trait distribution.LocationFour sites in three key regions across the Amazon basin: Central, Western peripheral area and Brazilian Shield.Time PeriodPresent.Major Taxa StudiedTree species.MethodWe measured hydraulic vulnerability curves of 64 tree species (165 individuals) using an orthogonal design contrasting seasonal precipitation gradients, soil fertility and WTD. To estimate the geographical distribution of hydraulic traits for the basin scale, we use the coefficients of the best generalized linear model, projected on a 1 km grid in each environmental layer.ResultsWe show that WTD and soil fertility are the main drivers of embolism resistance, while precipitation has a secondary effect. Trees in shallow WTD and fertile soils had riskier hydraulic strategies. Our spatial projection identified the Amazonian southern band and valleys across the basin as the most vulnerable areas. High soil fertility in these regions increases the variability of hydraulic traits and thus uncertainty in predictions of drought responses.Main ConclusionAt the scale of the Amazon basin, we show that dominant tree species traits converge toward hydraulic resistance when resource (water and nutrients) levels are low and towards hydraulic vulnerability (but with higher trait variability) when resources increase. These results highlight the importance of WTD and soil fertility in structuring hydraulic traits and their effects on tree mortality under climate change‐induced droughts. Further empirical tests covering a wider spatial range and more tree species will help validate our biogeographical distribution model.

Response mechanism of groundwater dynamics to Freeze–thaw process in seasonally frozen soil areas: A comprehensive analysis from site to regional scale

Studying the dynamic mechanism of water-level variations during the freeze–thaw period in seasonally frozen soil regions is an important premise and foundation for winter agricultural irrigation and groundwater resource assessment. Freezing and thawing-induced groundwater-level variations have been observed in regions with a shallow water table depth. However, whether the groundwater level is affected by the freeze–thaw process and the extent of this effect should be verified and discussed on a wider spatiotemporal scale. To this end, this study selected the plain area of Jilin Province, China as an example, and based on a comprehensive analysis of dynamic groundwater-level monitoring data from 114 monitoring wells, the distribution of the meteorological data and soil types and two typical experimental monitoring sites in the area, the dynamic characteristics and influencing factors of groundwater-level variations during the freeze–thaw period were identified. Combined with a multi-factor statistical analysis of the monitoring data at the regional scale of the plain area of Jilin Province, China, the response mechanism of the groundwater level to the freeze–thaw process in the seasonally frozen plain area was summarized. The results showed that: (1) The dynamic phenomenon where the groundwater level falls in the freezing period and rises in the thawing period due to the freeze–thaw process was widespread in seasonally frozen soil regions; (2) The depth threshold of the groundwater level affected by the freeze–thaw process was the sum of the maximum frozen soil depth and the maximum capillary rise height; (3) The main factors controlling the groundwater-level variation during the freeze–thaw period were the initial water-level depth and the maximum snow cover thickness; based on a random forest model, the groundwater-level variation during the freeze–thaw process could be accurately calculated with these main controlling factors; (4) The groundwater-level dynamics during the freeze–thaw process was mainly controlled by the exchange of water between the groundwater and the vadose zone system, and the rise in the water level was only partially replenished by the snowmelt water. The research results have an important guiding significance for winter agricultural irrigation and groundwater recharge resource evaluation.

Fine-grained water availability drives divergent trait selection in Amazonian trees

Water availability is an important driver of plant functional biogeography. Most studies focus on the effects of precipitation, and neglect the contribution of groundwater as a source when the water table depth (WTD) is accessible to roots. Previous studies suggested that shallow water tables select for acquisitive traits. These studies have mostly contrasted shallow vs. deep water tables, without considering a more fine-grained perspective within shallow water tables or the temporal WTD behavior. Here we tested whether the degree of variation in WTD translates into divergent modes of trait selection. We expect constantly shallow WTD leading to the selection of acquisitive traits, whilst high fluctuation of WTD would lead to tree communities with more conservative traits. We used community and trait data (wood density and leaf traits) from 25 1-ha forest monitoring plots spread over 600 km in central Amazonia, covering a gradient of shallow to intermediate (0–8 m deep) WTD along the Purus-Madeira interfluve. Wood density was measured directly in trunk cores (498 trees) and leaf traits (Specific Leaf Area, Leaf Dry Mass Content, Leaf Thickness) of &amp;gt;6,000 individuals were estimated with FT-NIR (Fourier-Transformed Near-Infrared Spectroscopy) spectral models calibrated with cross-Amazonian data. We observed a turnover of families, genera, and species along the gradient of temporal WTD fluctuation range. This taxonomic turnover was accompanied by a change in wood traits, with higher wood density associated to higher WTD fluctuation and higher climatic water deficit. Leaf traits, however, varied in the opposite direction than initially hypothesized, i.e., trees had more acquisitive traits toward intermediate WTD with higher fluctuation. Based on those results, we propose that the effect of WTD selection should be conceptualized in a quadratic form, going from water excess in very shallow WTD (&amp;lt;2 m, limiting condition due to anoxia, selecting conservative traits), to moist in intermediate WTD (between 2 and 5 m deep, favorable condition with constant water supply, selecting acquisitive traits), to water deficit in deep WTD (&amp;gt;5 m, limiting condition, with conservative traits again).

Potential Impacts of Climate Change Using Long-Term Historical Climate Data on Evapotranspiration (ET) and Groundwater Contribution to Wheat and Cotton Crop

Assessing the potential impacts of climate change on crop evapotranspiration (ET), groundwater contribution (GWC) towards meeting ET and yield is crucial in allocating water resources particularly in the areas where shallow water-table depths (WTDs) are expanding on larger area. The impact of climate change on crop ET and yield has been evaluated in the past by indirect methods using simulation models. However, those models are lacking the function of GWC which is one of the most important parameters while determining ET at different water-table depths (WTDs) and its impact on yield. Direct methods (without simulation models) using long term historical weather data (observed data) provide more accurate results of climate change impact on ET, GWC towards meeting ET and yield at different WTDs. In this study, long-term historical weather data for the last 34 years (1987-2020) and data obtained through lysimeteric studies were analyzed to examine the trends of climatic parameters, their relationship and impact on wheat and cotton ET, GWC to ET, yield and water use efficiency (WUE). These studies were carried out during 1986-1987 and 2017-2021 periods at 1.50 m, 2.25 m, and 2.75 m WTDs in Sultanpur soil series (silt loam textured) and Miani soil series (silty clay loam textured). The mean daily temperature has increased 0.45 oC and rainfall 75.5 mm/year over a period from 1987 to 2020 which is witnessing the climate change. Wheat ET is increased, GWC contribution to ET is decreased and, yield and WUE is highest during the cropping periods of 2017-2021 as compared to 1986-1987. Climate change has decreased cotton ET and GWC towards meeting ET. It has also reduced the wheat and cotton cropping cycles by 8 days and 21 days, respectively. Higher magnitude of rainfall (during July-September) in 2019 and 2020 resulted in reducing cotton average yield of 2017-2020 compared to 1987. The study demonstrates that irrigation allocation should be increased for wheat and decreased for cotton particularly in the shallow water-table areas under Sultanpur soil type where water-table remains at 1.50 m – 2.25 m depths. Moreover, cotton crop should be cultivated by the 1st week of April, so that highest yield of cotton could be harvested before onset of monsoon.

Development of flow model for partly and fully saturated soils using water balance and water table depth fluctuation analysis

Accurate estimation of soil water content and water table depth is important for making irrigation measures and rational groundwater use in arid agricultural areas with shallow water table depth. Soil water balance models are widely used due to their high computational efficiency, while they are less applicable in areas with shallow water table depths because they usually ignore the matric potential. In addition, the effect of capillary rise on soil water state is also ignored. To address these problems, a flow model for partly and fully saturated soil, referred to as modified UBMOD, was developed in this study based on UBMOD and the water table depth fluctuation analysis. UBMOD is a soil water balance model that differs from other water balance models by considering soil water movement driven by matric potential. In the modified UBMOD, soil water flow and groundwater recharge rate are calculated using the original UBMOD algorithm, and water table depth is calculated using the water table depth fluctuation analysis. The field capacity used in the modified UBMOD was considered as a variable related to the water table depth to reflect the impact of capillary rise, which helps to obtain accurate water flux across the saturated–unsaturated interface. Two synthetic cases, simulated with HYDRUS, were used to test the sensitivities of the model parameters and specifications. Two real-world cases were used to show the fidelity of the model to the observed data. The results demonstrated that the model could solve the unsaturated–saturated problems based on more readily available parameters, without stringent requirements on spatial and time steps, with a full guarantee of water balance and low computational cost. This study provides an effective tool for hydrodynamic studies in areas with shallow water table depths.

Recent results from an ecohydrological study of forest species in drained tropical peatlands

Ecohydrological studies in tropical peatland have mostly focused on a small number of non-native commercial species. However, studies of native species are urgently needed as they are considered to be a possible solution in the restoration of millions of hectares of degraded tropical peatlands. We investigated peatland species on Padang Island, Indonesia, to assess their responses to changing environmental factors, particularly the high fluctuation of the water table due to intensive peatland draining. We monitored the sap-flux velocity and radial growth of six trees (four native and one non-native peatland species) in high temporal resolution using sap-flux meters and dendrometers up to seven months. Monitoring also included hydrological and micrometeorological parameters. We found that sap-flux velocity in the monitored species was mainly controlled by air vapor pressure deficits, photosynthetic active radiation, and to some extent, by wind speed and water-table depth. We also observed a species-specific correlation between daily sap-flux velocity and daily radial growth. Non-native Acacia crassicarpa had up to twice the radial growth of native species. This growth of non-native species was significantly higher at a shallow water-table depth, while native species did not show the same relationship. The interaction between water-table depth, sap-flux velocity, and radial growth in daily timescale was not straightforward, presumably because of the complex carbon-allocation mechanism in trees.

Impacts of a shallow saline water table on maize evapotranspiration and groundwater contribution using static water table lysimeters and the dual Kc water balance model SIMDualKc

The occurrence of shallow saline water tables in arid zones provides for groundwater-fed natural vegetation and for a substantial amount of irrigated crops’ water needs. This is the case of the Hetao plain, upper Yellow River Basin, Inner Mongolia, China, where one of the major irrigation systems of China and the World is installed. As reviewed, numerous irrigation and water management studies have been developed in Hetao and the upstream irrigated plain of Yinchuan, Ningxia. These studies have demonstrated the need for controlling salts through the autumn irrigation and the appropriate irrigation methods and scheduling. Moreover, studies evidenced the need for adopting irrigation schedules that consider groundwater contribution during the crop cycle but most of these studies were empirical, resulting difficult to transfer results. When models adopted were mechanistic, they are difficult to use for irrigation scheduling purposes comparatively with soil water balance (SWB) models. Thus, the current study used two sets of five static water table lysimeters cropped with maize and having water table depths (WTD) fixed between 0.85 and 2.25 m. It was therefore possible to observe the daily capillary rise fluxes from the water table, the dynamics of water and salts and to calibrate the SWB model SIMDualKc. Results show that the average electrical conductivity of the saturated extract of the soil ranged from 3.10 to 4.69 dS m−1 with the higher values observed when WTD was smaller, while the electrical conductivity of irrigation water ranged 1.73–1.87 dS m−1. Results also show that shallower WTD required less irrigation water but caused higher salinity impacts on crop growth and yields. Thus, the best WTD were around 1.75–2.00 m when basin irrigation was adopted in 2017 and 2018. In these crop seasons, the simulated groundwater contribution to actual crop evapotranspiration (ETc act) was up to 37% in the lysimeters having a shallow WTD (1.25 m), while in the lysimeters with deeper WTD (2.00–2.25 m) it was about 11% of the ETc act. Contrastingly, in 2019, when maize was not irrigated, the average groundwater contribution represented 73% and 49% of ETc act in the lysimeters with shallow and deep WTD, respectively. Results were obtained when a large leaching autumn irrigation (200 mm) was performed. Those experiments showed that, solutions for using basin flooding irrigation are ready but still require that irrigation scheduling is adjusted to provide for appropriate use of the saline groundwater contribution, which may be performed with the model SIMDualKc, as demonstrated by the high goodness-of-fit indicators used to evaluate the referred simulations.

Contrasting water use characteristics of riparian trees under different water tables along a losing river

• Water use of riparian trees under various water table depth (WTD) along a losing river was determined. • Riparian trees accessed more upper soil water and had lower leaf δ 13 C under deep WTD compared to shallow WTD. • Water source contribution was a parabolic function of WTD and 2.1 m was the optimum WTD to utilize deep water. • Leaf δ 13 C had a positive linear relation with proportional contribution of deep water. Rivers losing flow into surrounding aquifers (‘losing’ rivers) are common under changing climates and groundwater overexploitation. The riparian plant-water relations under various water table dynamics along a losing river remain unclear. In this study, the water isotopes (δ 2 H and δ 18 O), leaf δ 13 C, and MixSIAR model were used combinedly for determining the root water uptake patterns and leaf water use efficiency (WUE) of Salix babylonica (L.) at three sites (A, B, and C) with different water table depths (WTDs) in the riparian zone of Jian and Chaobai River in Beijing, China. The correlations of water source contributions with WTD and WUE were quantified. The riparian S. babylonica primarily took up upper (0–80 cm) soil water (71.5%) with the lowest leaf δ 13 C (−28.8 ± 1.1 ‰) at site A under deep WTD (20.5 ± 0.5 m). In contrast, deep water below 80 cm depth including groundwater contributed 55.1% to S. babylonica at site B with fluctuated shallow WTD (1.9 ± 0.4 m), where leaf δ 13 C was highest (−27.9 ± 1.0 ‰). The S. babylonica mainly used soil water in 30–170 cm layer (56.9%) with mean leaf δ 13 C of − 28.2 ‰ ± 0.7 ‰ at site C with stable shallow WTD (1.5 ± 0.1 m). It was found that both the contributions of upper soil water in 0–80 cm and deep water below 80 cm had significantly quadratic correlations with WTD under shallow water table conditions ( p < 0.05). Leaf δ 13 C was negatively correlated with contributions of upper soil water above 80 cm depth, but it was positively related to the contributions of deep water below 80 cm in linear functions ( p < 0.001). The results indicated that 2.1 m was the optimum WTD for riparian trees, because they maximized the use of deep water sources to get the highest WUE. This study provides insights into managing groundwater, surface water resources and riparian afforestation in losing rivers.

How do groundwater dynamics influence heatwaves in southeast Australia?

Groundwater plays an integral role in land-atmosphere interactions by connecting the sub-surface storage of water to transpiration via interactions with the root zone. The role of groundwater in moderating heatwave intensity has rarely been examined in coupled climate simulations, as many models overlook this key component of the water cycle. We use a coupled land-atmosphere model with an explicit representation of groundwater dynamics to analyze three major heatwave events in southeast Australia. Groundwater moistens and cools the land surface, with impacts extending to the top of the atmospheric boundary layer during heatwaves. Associated with the cooling, an increase of net radiation and a reduction in the atmospheric boundary layer height occurred, primarily over areas with a shallow water table depth and woody vegetation. The maximum air temperatures were reduced by up to 3 °C at the surface and up to 1 °C through the atmospheric boundary layer. Our results point to an important influence of groundwater on heatwave intensity, implying the necessity of considering groundwater dynamics in climate models in the future heatwave predications.

Salt Accumulation during Cropping Season in an Arid Irrigation Area with Shallow Water Table Depth: A 10-Year Regional Monitoring

Nowadays, irrigation takes up about 35% of agricultural water consumption worldwide, and irrigation induced secondary soil salinizationsalinization affects the crop production and sustainable development of arid irrigation areas globally. However, the regular pattern of salt accumulation in the root zone during the cropping season and the contributions of its attribute factors are still unclear. Therefore, a 10-year monitoring was conducted in the Hetao Irrigation District to reveal the soil salt accumulation during the cropping season and to relate it to influential factors, including potential crop evapotranspiration, water input (field irrigation + precipitation) and water table depth. It was found that under the climate conditions and water-saving irrigation measures of the investigated 10-year period, (1) the salt accumulated during the cropping season could be effectively leached by autumn irrigation and the root zone soil could remain suitable for crop germination, (2) the cropping season water deficit (potential crop evapotranspiration − field irrigation − precipitation) showed strong correlation with the cropping season salt accumulation, and (3) maintaining the cropping season average water table depth larger than a critical depth (roughly 3 m) might be the most economical way to alleviate salt accumulation. Therefore, it is recommended to balance the salt leaching and the water table depth controlling in the future water-saving irrigation management practices.

Water table depth modulates productivity and biomass across Amazonian forests

AbstractAimWater availability is the major driver of tropical forest structure and dynamics. Most research has focused on the impacts of climatic water availability, whereas remarkably little is known about the influence of water table depth and excess soil water on forest processes. Nevertheless, given that plants take up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water conditions.LocationLowland Amazonian forests.Time period1971–2019.MethodsWe used 344 long‐term inventory plots distributed across Amazonia to analyse the effects of long‐term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil‐water and edaphic properties.ResultsWater supplied by both precipitation and groundwater affects forest structure and dynamics, but in different ways. Forests with a shallow water table (depth &lt;5 m) had 18% less above‐ground woody productivity and 23% less biomass stock than forests with a deep water table. Forests in drier climates (maximum cumulative water deficit &lt; −160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by the interaction between climatic water deficit and water table depth. On average, in drier climates the forests with a shallow water table had lower productivity than those with a deep water table, with this difference decreasing within wet climates, where lower productivity was confined to a very shallow water table.Main conclusionsWe show that the two extremes of water availability (excess and deficit) both reduce productivity in Amazon upland (terra‐firme) forests. Biomass and productivity across Amazonia respond not simply to regional climate, but rather to its interaction with water table conditions, exhibiting high local differentiation. Our study disentangles the relative contribution of those factors, helping to improve understanding of the functioning of tropical ecosystems and how they are likely to respond to climate change.

A new approach for estimating spatial-temporal phreatic evapotranspiration at a regional scale using NDVI and water table depth measurements

Accurate estimation of the spatial-temporal distribution of phreatic evapotranspiration (ET) is critical for managing water resources and preventing soil salinization in arid and semiarid agricultural areas where substantial water-saving efforts are needed. Traditional phreatic ET estimation approaches either are for small scales or cannot consider spatial and/or temporal variations in phreatic ET. This study developed a new approach for estimating the spatial-temporal phreatic ET based on the normalized difference vegetation index (NDVI) and measured water table depths. The NDVI was used to calculate the actual evapotranspiration (ETc act) by scaling it with the reference crop evapotranspiration (ETo). The water table depths measured during the periods of no other factors (i.e., precipitation, irrigation and groundwater extraction) were used to establish an equation used to estimate the phreatic ET contribution coefficient (defined as the ratio of phreatic ET to the corresponding ETc act). To improve estimation accuracy, a time-related correction factor was considered in the equation for estimating the phreatic ET. The new approach was used to estimate monthly phreatic ET with a spatial resolution of 250 m in the Hetao irrigation district, located in arid Northwest China. The estimated phreatic ET at different spatial and temporal scales matched well with the groundwater balance model results. The results show that the spatial distribution of phreatic ET is affected by both natural factors (e.g., land cover types) and human activities (e.g., groundwater extraction, planted crops). In the Hetao irrigation district, phreatic ET contributes an average of 24.4% to ETc act during the non-freezing-thawing period (from June to November), demonstrating the essential role of phreatic ET in supporting crop growth and the general ecological environment in arid areas with shallow water table depths. The new approach of estimating spatial-temporal phreatic ET may be used for designing effective and efficient water resource management policies at the regional scale.

The other side of tropical forest drought: do shallow water table regions of Amazonia act as large-scale hydrological refugia from drought?

Tropical forest function is of global significance to climate change responses, and critically determined by water availability patterns. Groundwater is tightly related to soil water through the water table depth (WT), but historically neglected in ecological studies. Shallow WT forests (WT < 5 m) are underrepresented in forest research networks and absent in eddy flux measurements, although they represent c. 50% of the Amazon and are expected to respond differently to global-change-related droughts. We review WT patterns and consequences for plants, emerging results, and advance a conceptual model integrating environment and trait distributions to predict climate change effects. Shallow WT forests have a distinct species composition, with more resource-acquisitive and hydrologically vulnerable trees, shorter canopies and lower biomass than deep WT forests. During 'normal' climatic years, shallow WT forests have higher mortality and lower productivity than deep WT forests, but during moderate droughts mortality is buffered and productivity increases. However, during severe drought, shallow WT forests may be more sensitive due to shallow roots and drought-intolerant traits. Our evidence supports the hypothesis of neglected shallow WT forests being resilient to moderate drought, challenging the prevailing view of widespread negative effects of climate change on Amazonian forests that ignores WT gradients, but predicts they could collapse under very strong droughts.

Water table variations on different land use units in a drained tropical peatland island of Indonesia

AbstractRestoration and water table control on peatlands to limit fire risk are national priorities in Indonesia. The present study was initiated at Padang Island, Sumatra, to increase understanding on peatland hydrology in the tropic. At the pilot site, water table and precipitation were monitored at different stations. The results show variation in water table depths (WTDs) over time and space due to spatial and temporal variability in rain intensity and drainage networks. In part of the island, large-scale drainage for plantations led to deep WTD (−1.8 m) and high WTD recession rates (up to 3.5 cm/day). Around villages, farm-scale drainages had a smaller impact with a lower recession rate (up to 1.8 cm/day) and shallow WTD, typically below −0.4 m, the threshold for sustainable peatland management in Indonesia. The recession rates levelled off at 1.0 cm/day near the drained forest/plantation and at 0.5 cm/day near the farm. Deeper layers had much lower specific yield (Sy), 0.1 at −1.5 m depth, compared with top peat soils with Sy up to 0.3. Proximity to drainages extended discharge flow to deeper layers. The results highlighted the severity of peatland drainage impact on most coastal zones of Padang Island, which have intensive drainage networks.