Observed Water Table Research Articles

Assimilation of Sentinel‐Based Leaf Area Index for Modeling Surface‐Ground Water Interactions in Irrigation Districts

AbstractVegetation‐related processes, such as evapotranspiration (ET), irrigation water withdrawal, and groundwater recharge, are influencing surface water (SW)—groundwater (GW) interaction in irrigation districts. Meanwhile, conventional numerical models of SW‐GW interaction are not developed based on satellite‐based observations of vegetation indices. In this paper, we propose a novel methodology for multivariate assimilation of Sentinel‐based leaf area index (LAI) as well as in‐situ records of streamflow. Moreover, the GW model is initially calibrated based on water table observations. These observations are assimilated into the SWAT‐MODFLOW model to accurately analyze the advantage of considering high‐resolution LAI data for SW‐GW modeling. We develop a data assimilation (DA) framework for SWAT‐MODFLOW model using the particle filter based on the sampling importance resampling (PF‐SIR). Parameters of MODFLOW are calibrated using the parameter estimation (PEST) algorithm and based on in‐situ observation of the GW table. The methodology is implemented over the Mahabad Irrigation Plain, located in the Urmia Lake Basin in Iran. Some DA scenarios are closely examined, including univariate LAI assimilation (L‐DA), univariate streamflow assimilation (S‐DA), and multivariate streamflow‐LAI assimilation (SL‐DA). Results show that the SL‐DA scenario results in the best estimations of streamflow, LAI, and GW level, compared to other DA scenarios. The streamflow DA does not improve the accuracy of LAI estimation, while the LAI assimilation scenario results in significant improvements in streamflow simulation, where, compared to the open loop run, the (absolute) bias decreases from 75% to 6%. Moreover, S‐DA, compared to L‐DA, underestimates irrigation water use and demand as well as potential and actual crop yield.

Design and numerical analysis of inverted well technique for aquifer recharge estimation

The seasonal polarization due to climate change and population explosion in developing countries is translating into rapid groundwater depletion. In the populous cities relying on groundwater for their water requirements, aquifers are turning into exiguity due to much higher depletion corresponding to recharge rate. Therefore, it is imperative to model the aquifer conditions for extrapolating the future scenario and adopting efficient and safe groundwater recharge techniques based on simulation results to counter the proliferating depletion rate. In this study, an efficient inverted well design with effective multiple filtration compartments is proposed for ground water recharge at natural runoff collection points having high conductivity and effective filtration. The current depletion rate and design recharge capability was assessed by simulating the aquifer conditions along with boundary conditions confined to model town area, groundwater table data of extraction and observation wells in study area from year 2014–2020, precipitation data 2008 to 2020, and other spatial and temporal variations in model town area of Lahore in VISUAL MODFLOW program. The model results exhibited that the depletion rate of Lahore (model town area having a land area of 5.9 km2 approximately) was 0.96 m per year (investigating year 2014–2020), this concurred with the depletion rate recorded by water table observations of extraction and observations wells from year 2014–2020. The depressions in model town park area of Lahore were simulated as recharge points, and 4 inverted wells with their calculated conductivity were simulated in model. The precipitation data with peak runoff generations for 7 years (2014–2020) was intercalated in the model. The results explicated that the simulation of inverted wells recharge technique at natural rainfed depressions of model town park area significantly reduced the depletion rate from 0.93 m per year (2014–2020) to 0.76 m per year (2021–2023) in MODFLOW visual water table contours. Therefore, this inverted well design-based recharge technique can effectively be used for efficient groundwater recharge, and its application at natural depressions in the groundwater dependent cities can effectively hinder and stabilize the depleting ground water resources.

Water level and soil moisture monitoring for peatland fire risk indicator

Peatland forest conversion into cultivated land often creates environmental issues in the form of increasing greenhouse gas (GHG) emissions caused by the decomposition of organic matter that eventually increase the risk of peat forest fires. This paper presents the results of a study of the peatland water table dynamics based on certain peatland characteristics (depth and maturity) and water management techniques (canal blocking), as well as an analysis of water level and soil moisture data for the peatland fire early warning model. This study was conducted in April-December 2018 at a palm oil plantation in Pangkalan Pisang Village, Riau Province. Peatland water table observations were carried out using a water level logger at each of the midpoints of three oil palm blocks measuring 30 ha each. Meanwhile, soil moisture contents were observed using a logger with two humidity sensors at two depths. The recorded observation data showed that the water table level was very dynamic and fluctuating, both temporally and spatially. The temporal observation data indicates that the water table levels after the rain had stopped in the three observed blocks decreased at the rates of 10.3, 10.6, and 13.6 mm/day, respectively. This research shows a significant correlation between soil moisture dry weight percent and the risk level of peatland fires. Soil moisture content was less than 100% dry weight and highly flammable.

Effects of stand age, tree species, and climate on water table fluctuations and estimated evapotranspiration in managed peatland forests

Lowland conifer forests dominated by black spruce (Picea mariana) and tamarack (Larix laricina) typically occur in peatlands in the boreal North American forest with near-surface water tables throughout the year. These forests are ecologically and economically important resources that may be impacted by climate change. However, information characterizing effects of forest disturbance, such as even-aged harvest on water table dynamics is needed to evaluate which forest tree species cover types are most hydrologically susceptible to even-aged harvest and changes in precipitation. We used a chronosequence approach to evaluate water table fluctuations and evapotranspiration across four stand age classes (<10, 15–30, 40–80, and >100-years old) and three distinct forest cover types (productive black spruce, stagnant black spruce, and tamarack) for a period of three years in Minnesota, USA. In general, there is limited evidence for elevated water tables in the younger age classes; the <10-year age class had no significant difference in mean weekly water table depth compared to the older age classes across all cover types. Estimated actual daily evapotranspiration (ET) generally agreed with the water table observations, with the exception of the tamarack cover type where ET was significantly lower in the <10-year age class. Productive black spruce sites that are 40–80-years old had higher evapotranspiration, and lower water table, possibly reflecting increased transpiration associated with the stem exclusion stage of stand development. Tamarack in the 40-80-year age class had higher water tables but no difference in ET compared to all other age classes, indicating that other external factors are driving higher water tables in that age class. To evaluate susceptibility to changing climate, we also assessed the sensitivity and response of water table dynamics to pronounced differences in growing season precipitation that occurred across study years. In general, tamarack forests are more sensitive to changes in precipitation compared to the two black spruce forest cover types. These findings can inform expected responses of site hydrology for a range of precipitation scenarios that may occur under future climate and be used by forest managers to evaluate hydrologic impacts of forest management activities across lowland conifer forest cover types.

Hydrological dynamics and associated greenhouse gas fluxes in a mountain peatland under different climate scenarios

AbstractPeatlands have sequestered atmospheric carbon dioxide (CO2) for millennia and can also act as significant sources of atmospheric methane (CH4). Hydrological processes that control water table dynamics, and climatic conditions such as air temperature, play important roles in mediating peatland–atmosphere exchange of these greenhouse gases. These controls are likely to be impacted by climate change, particularly for those peatlands found in cold environments, including mountain regions. In this study, we developed empirical models to simulate hydrological dynamics and ecosystem–atmosphere C exchange in a mountain peatland under three climate scenarios (2012 air temperatures, +2°C and +4°C). Observed water table dynamics and air temperature were used to model ecosystem–atmosphere C exchange during the 2012 growing season. Modelled snowmelt dynamics were used to predict water table position at the beginning of the growing season for warming scenarios, and the subsequent water table dynamics and increased air temperature were used to drive the same C exchange models during the growing seasons. Increased air temperatures led to earlier snowmelt and water table decline, causing water tables to drop by 10 and 19 cm for the +2 and +4°C scenarios, respectively. This led to roughly a two‐fold decrease in growing season net ecosystem production (NEP) in both warming scenarios, as a result of increased ecosystem respiration relative to gross primary production. Methane efflux was positively correlated with NEP and therefore decreased under the warming scenarios, albeit to a lesser degree. These results indicate that reductions in NEP and CH4 efflux are possible in low‐elevation mountain peatlands that are dependent on snowpack‐derived hydrologic inputs. These ecosystems are found at elevations where future winter precipitation will increasingly fall as rain rather than snow and melting of snowpack will occur earlier under warmer conditions.

Coupling a large-scale hydrological model (CWatM v1.1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale

Abstract. 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.

Groundwater level prediction with meteorologically sensitive Gated Recurrent Unit (GRU) neural networks

Precise estimation of groundwater level (GWL) fluctuations has a substantial effect on water resources management. In the present study, to forecast the regional mean monthly time series groundwater level (GWL) with a range of 4.82 (m) in Urmia plain, three different layer structures of Gated Recurrent Unit (GRU) deep learning-based neural network models via the module of sequence-to-sequence regression are designed. In this sense, 180-time series datasets of regional mean monthly meteorological, hydrological, and observed water table depths of 42 different monitoring piezometers during the period of Oct 2002–Sep 2017 are employed as the input variables. By using Shannon entropy method, the most influential parameters on GWL are determined as regional mean monthly air temperature (Tam), precipitation (Pm), total (sum) water diversion discharge (Wdm) of four main rivers. Nevertheless, Cosine amplitude sensitivity analysis confirmed Tam as a dominant factor. For preventing overfitting problem, an algorithm tuning technique via different kinds of hyperparameters is operated. In this respect, several scenarios are implemented and the optimal hyperparameters are accomplished via the trial-and-error process. As stated by the performance evaluation metrics, Model Grading process, and Total Learnable Parameters (TLP) value, the innovative and unique suggested model (3), entitled GRU2+, (Double-GRU model coupled with Addition layer (+)) with seven layers is carefully chosen as the best model. The unique suggested model (3) in the optimal hyperparameters, resulted in an R2 of 0.91, a total grade (TG) of 7.76, an RMSE of 0.094 (m), and a running time of 47 (s). Thus, the model (3) can be certainly employed as an effective model to forecast GWL in different agricultural areas.

The Impact of Groundwater Variability on Mangrove Greenness in Karimunjawa National Park based on Remote Sensing Study

This study aims to understand the impact of groundwater table on soil moisture and mangrove greenness in different seasons in Karimunjawa National Park (KNP). We used Sentinel-2 L2A satellite imagery, Global Precipitation Measurement (GPM) satellite rainfall data, and water table observations at KNP. This study estimates Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) on time series Sentinel-2 imagery in 2019-2020 using Google Earth Engine. In addition, we compared the monthly average rainfall data, the monthly average water table data, and the monthly average NDVI, NDWI data extracted at the water table observation points. NDVI is a method to estimate mangrove greenness, and NDWI to estimate soil moisture. The obtained results indicate that NDVI and NDWI in the near shoreline area show a higher value than in the middle area of the KNP that is far from the shoreline. In addition, the value of the NDVI and NDWI correlation coefficients is 0.94, which indicates a positive and strong correlation. Moreover, The NDWI and water table correlation coefficients are 0.79, which indicates a relatively strong positive correlation. Furthermore, the correlation between rainfall and the water table is 0.61, which indicates a relatively strong positive correlation. Thus, these findings show that the water table influences soil moisture and then affects the mangrove greenness. Besides that, the water table change is governed by rainfall, and therefore, the mangrove greenness in KNP depends on seasons and is vulnerable to drought.

Where and When to Collect Tracer Data to Diagnose Hillslope Permeability Architecture

AbstractThe permeability architecture has a major influence on hillslope flow path and hydrogeochemistry. To constrain this architecture and overcome equifinality in the diagnosis of hillslope flow paths within hydrologic transport models, different types of complementary data (e.g., tracer) have been recommended. However, there is still little information on the extent to which such complementary data can unravel the permeability architecture, and where and when to measure such data to most efficiently constrain models. Here, we couple a Richards‐based flow and transport model with extensive long‐term field measurements to compare the relative value of different types of hydrometric and tracer data in discriminating between contrasting permeability (or saturated hydraulic conductivity ()) architectures, in the absence of macropore flow. Our results show that compared to streamflow and water table observations, stream tracer data have a stronger evaluative potential to constrain hillslope vertical pattern in , in particular during seasons when flow is on average low (e.g., winter or summer). Tracer data from within the hillslope are even more helpful to discriminate between different vertical patterns in Ks than stream tracer data. This suggests a higher evaluative potential for hillslope tracer observations. This evaluative potential of hillslope data depends on where and when the data are collected, and increases with depth from the soil surface, with distance from the stream and during seasons when flow is low. The findings also emphasize the importance of incorporating hillslope permeability architecture in hydrologic transport models in order to reduce the uncertainty in the predictions of stream water quality.

Fuzzy linear regression analysis for groundwater response to meteorological drought in the aquifer system of Xanthi plain, NE Greece

Abstract This paper studies, through the principles of fuzzy set theory, groundwater response to meteorological drought in the case of an aquifer system located in the plains at the southeast of Xanthi, NE Greece. Meteorological drought is expressed through standardized Reconnaissance Drought Index (RDISt) and Standardized Precipitation Index (SPI), which are calculated for various reference periods. These drought indices are considered as independent variables in multiple fuzzy linear regression based on Tanaka's model, while the observed water table regarding two areas is used as a dependent variable. The fuzzy linear regression of Tanaka is characterized by the inclusion constraints where all the observed data must be included in the produced fuzzy band. Hence, each fuzzy output can get an interval of values where a membership degree corresponds to each of them. A modification of the Tanaka model by adding constraints is proposed in order to avoid irrational behavior. The results show that there was a significant influence of the meteorological drought of the previous hydrological year, while geology plays an important role. Furthermore, the use of RDISt improves the results of fuzzy linear regressions in all cases. Two suitability measures and a measure of comparison between fuzzy numbers are used.

The fluctuation of peatland water table at Tumbang Nusa, Central Kalimantan

Burnt peatland restoration by planting needs stable hydrological condition for the plant’s growth. Water table fluctuation becoming a challenge in the planting effort on degraded peatland. This research aims to determine the water table on degraded peatland and over burnt peat at Tumbang Nusa Forest for Specific Purposes, Pulang Pisau District, Central Kalimantan Province. The data was analyzed to determine the relationship between precipitation characteristics, water table and land elevation. Water table observation was carried out on several fires starting 1997, 2003, 2006 and 2009. We observed 17 points of water table of the total length of 4 km and 250 m distance between points, started from the river edge up to secondary forests. The level of vegetation cover and condition varied from woody plants with low density and open crown up to woody plants with good canopy cover. The result showed that the water table was closely related with the elevation and distance from canal. The fluctuation was closely related with precipitation. Nevertheless, the rainfall did not directly relate but there was a certain interlude period so that the water table was rising or decreasing. This condition shall be considered in the land rehabilitation by planning the right plant in the right time so that the plants can reach optimum growth

Evaluating integrated surface/subsurface permafrost thermal hydrology models in ATS (v0.88) against observations from a polygonal tundra site

Abstract. Numerical simulations are essential tools for understanding the complex hydrologic response of Arctic regions to a warming climate. However, strong coupling among thermal and hydrological processes on the surface and in the subsurface and the significant role that subtle variations in surface topography have in regulating flow direction and surface storage lead to significant uncertainties. Careful model evaluation against field observations is thus important to build confidence. We evaluate the integrated surface/subsurface permafrost thermal hydrology models in the Advanced Terrestrial Simulator (ATS) against field observations from polygonal tundra at the Barrow Environmental Observatory. ATS couples a multiphase, 3D representation of subsurface thermal hydrology with representations of overland nonisothermal flows, snow processes, and surface energy balance. We simulated thermal hydrology of a 3D ice-wedge polygon with geometry that is abstracted but broadly consistent with the surface microtopography at our study site. The simulations were forced by meteorological data and observed water table elevations in ice-wedge polygon troughs. With limited calibration of parameters appearing in the soil evaporation model, the 3-year simulations agreed reasonably well with snow depth, summer water table elevations in the polygon center, and high-frequency soil temperature measurements at several depths in the trough, rim, and center of the polygon. Upscaled evaporation is in good agreement with flux tower observations. The simulations were found to be sensitive to parameters in the bare soil evaporation model, snowpack, and the lateral saturated hydraulic conductivity. Timing of fall freeze-up was found to be sensitive to initial snow density, illustrating the importance of including snow aging effects. The study provides new support for an emerging class of integrated surface/subsurface permafrost simulators.

Investigating Atrazine Concentrations in the Zwischenscholle Aquifer Using MODFLOW with the HYDRUS-1D Package and MT3DMS

Simulation models that describe the flow and transport processes of pesticides in soil and groundwater are important tools to analyze how surface pesticide applications influence groundwater quality. The aim of this study is to investigate whether the slow decline and the stable spatial pattern of atrazine concentrations after its ban, which were observed in a long-term monitoring study of pesticide concentrations in the Zwischenscholle aquifer (Germany), could be explained by such model simulations. Model simulations were carried out using MODFLOW model coupled with the HYDRUS-1D package and MT3DMS. The results indicate that the spatial variability in the atrazine application rate and the volume of water entering and leaving the aquifer through lateral boundaries produced variations in the spatial distribution of atrazine in the aquifer. The simulated and observed water table levels and the average annual atrazine concentrations were found to be comparable. The long-term analysis of the simulated impact of atrazine applications in the study area shows that atrazine persisted in groundwater even 20 years after its ban at an average atrazine concentration of 0.035 µg/L. These results corroborate the findings of the previous monitoring studies.

Groundwater use of a small Eucalyptus patch during the dry monsoon phase

Given the critical role of water in rural development, it is essential to quantify water use by various sectors. Reportedly, a significant water loss during the dry monsoon phase is by Eucalyptus trees in the Ethiopian highlands but few quantitative studies have been carried out. In our study in the Fogera plain near Lake Tana, consumptive water use of a small Eucalyptus patch was calculated from the fluctuating diurnal water table observations for two dry monsoon phases. During the dry monsoon phase in 2014, the groundwater table declined linearly at a rate of 2.6 cm d−1 and in 2015 the decline was 2.5 cm d−1. Daily fluctuations in groundwater were around 20 cm. Translating changing groundwater levels in precise evapotranspiration rates was cumbersome because of uncertainty in the value of drainable porosity. We concluded that the evapotranspiration over the small Eucalyptus patch was at a minimum 3.4 mm d−1 but more likely around 10 mm d−1 at the end of the dry phase. The 10 mm d−1 is twice the reference evaporation rate. This is in accordance with advection aridity approach where the actual evaporation of isolated patches with access to groundwater in dry environments can evaporate at twice the reference rate. The current and future extent of Eucalyptus patches and forests need, therefore, be considered in the management of the groundwater resource.

DSSAT-MODFLOW: A new modeling framework for exploring groundwater conservation strategies in irrigated areas

Groundwater models are often used to assess the impact of climate or management strategies on groundwater resources in arid and semiarid regions of the world. However, these models do not account for crop growth and crop yield, and thus cannot be used for evaluating long-term impacts of climate and management strategies on water use efficiency and farm profitability of agricultural systems while managing the aquifers sustainably. This study presented a linkage between DSSAT, an agronomic model, and MODFLOW, a groundwater flow model. The linkage between these two models occurred on an annual basis, with rates of irrigation and deep percolation from an ensemble of field-scale DSSAT simulations converted to pumping rates and recharge rates for the MODFLOW simulation. MODFLOW simulated groundwater head, which can be used to update saturated thickness and thereby well capacities for each pumping well in the model domain. Simulated well capacities were then used to constrain irrigation applications in the DSSAT simulations during the following growing season. Python scripts were used to convert output from one model to input files for the other model. The DSSAT-MODFLOW modeling system was applied to the Ogallala aquifer underlying Finney County, Kansas, a region experiencing significant groundwater depletion due to irrigation practices, and was tested against observed water table elevation and crop yield. Over a decadal period, well capacity decreased by > 50 % for many pumping wells in the county. A no-irrigation scenario for this same time period resulted in average water table elevation increasing by 2 m, but also a 70 % decline in crop yield. Additional work is needed to balance groundwater conservation with crop yield. The DSSAT-MODFLOW modeling system can be used in regions worldwide to assess changes in irrigation technologies, crop selection, and climate change adaptation strategies.

Catchment-Scale Integrated Surface Water-Groundwater Hydrologic Modelling Using Conceptual and Physically Based Models: A Model Comparison Study

This paper presents a comparative analysis of the use of an externally linked (MOBIDIC-MODFLOW) and a physically based (MIKE SHE) surface water-groundwater model to capture the integrated hydrologic responses of the Thomas Brook catchment, in Canada. The main objective of the study is to investigate the effect of simplification in representation of the hydrological processes in MOBIDIC-MODFLOW on its simulation accuracy. To this aim, MOBIDIC and MODFLOW were coupled in order to sequentially exchange the groundwater recharge and baseflow discharges within each computation time step. Using identical sets of hydrogeological properties for the two models, the coefficients of the gravity and capillary reservoirs in MOBIDIC were calibrated so as to closely predict the hydrological budget of the catchment simulated with MIKE SHE. The simulated results show that the two models can closely replicate the observed water table responses at two monitoring wells. However, in very shallow water table locations, the instantaneous response of the water table was not precisely captured in MOBIDIC-MODFLOW. Additionally, the simplified conceptualization of the unsaturated flow in MOBIDIC-MODFLOW resulted in overestimated groundwater recharge during spring and underestimation during summer. Moreover, the computational efficiency of MOBIDIC-MODFLOW, as compared to MIKE SHE, along with less required input data, confirms its potential for regional scale groundwater-surface water interaction modelling applications.

Exploring reciprocal interactions between groundwater and land cover decisions in flat agricultural areas and variable climate

We present Hydroman, a flexible spatially explicit model coupling human and hydrological processes to explore shallow water tables and land cover interactions in flat agricultural landscapes, modeled after the Argentine Pampas. With fewer parameters, Hydroman aligned well with established hydrological models, and was validated with observed water table patterns and crop yield data. Simulations with different climate, phreatic and land cover conditions confirmed that climate remains the main driver, but crops also influence water levels and yields, depending on the growing cycle. We also examined the impacts of two alternative sowing strategies. Risk aversion proves robust in minimizing crop losses, but often results in less sowing, exacerbating flooding. Strict rotators risk more, but help stabilize the groundwater levels. Reintroducing pasture further stabilizes the system. Future work will engage farmers to derive and assess land cover strategies that maximize yield and minimize losses, and transfer our modeling approach to other applications.

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.

Groundwater potential in a drought prone Betwa river basin, Bundelkhand

This study presented a modified concept of assessing groundwater potential and water table level behavior under varying rate of recharge potential for regional scale modeling of Betwa basin using Processing ModFlow for Windows model. Betwa basin of Bundelkhand region which covered the districts of Madhya Pradesh and Utter Pradesh was selected to apply this concept. The model was calibrated and validated using observed water table elevation data for the period 2005–2013, which showed agreement between observed and predicted water table elevation. The coefficient of determination (R2) ranged between 0.74–0.87 for calibration and 0.63–0.87for validation. Scenario analysis represents the water table elevation under three varying groundwater recharge condition in Shahijina, Garrauli, Mohana and Basoda sub-basin of Betwa basin. Results shows that the scenario based on recharge with 60% of surface runoff combined with river bed recharge and natural recharge has maximum influence on groundwater recharge. Groundwater recharge under the scenario varied from 0.33–1.61 m above reference level. Recharge from 30% of surface runoff combined with river bed recharge and natural recharge varied from 0.16–1.05 m above reference level. The study shall be useful for planning of groundwater development in Betwa basin and to suggest an alternate location for development of soil and water conservation structure. The water table elevation simulation also showed that the recharge levels and the sustainability of groundwater resources cannot be ensured unless water availability in arid to semi-arid region river basin increased.

Revisiting the White method for estimating groundwater evapotranspiration: a consideration of sunset and sunrise timings

The well-known White method (A method of estimating ground-water supplies based on discharge by plants and evaporation from soil: Results of investigation in Escalante Valley, Utah. Washington D.C, US Geological Survey. Water Supply Paper 659-A United States Department of the Interior, 1932) based on diurnal water table observations has been widely applied to estimate groundwater evapotranspiration (ETG) from phreatophyte vegetation. One of the limitations of this method is its large uncertainties in quantifying the daily groundwater recovery rate (r), which is assumed to be equal to the average rate of groundwater level rise between midnight (i.e., 00:00 h) and 04:00 h. Recent studies pointed out that ETG is highly dependent on the shape and duration of the diurnal clear-sky solar radiation curve and that using the groundwater recovery rate over a short interval of nighttime hours to represent the daily r may lead to large uncertainties in ETG estimates. In this study, we analysed the dependence of the estimated daily r on the sunset and sunrise timings. Numerical experiment results showed that the estimated r is highly sensitive to the duration between sunset and sunrise, which varies seasonally. Instead of using fixed time spans (TSs), e.g., from midnight to 04:00 h, we recommend a more universal method for determining the TS, which is associated with the sunset and/or sunrise timings and used to estimate the daily r. This dynamic TS approach was tested at a Tamarix ramosissima-dominated riparian site with a hyper-arid climate (precipitation of 35 mm a−1) in northwestern China. Compared with the observed evapotranspiration (ET), our approach showed better performance and less subjectivity in estimating ETG than the traditional White approach.