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We propose a deep learning model: long short-term memory (LSTM) networks to spatially downscale Global Recovery and Climate Experiment (GRACE)-derived terrestrial water storage anomalies (TWSA) with an objective to map groundwater level anomalies (GWLA) at 0.25 degrees resolution for basin-scale applications. Monthly TWSA from global spherical harmonic (GSH) and global mascons (GM) during 2002 to 2017 were obtained at 1 degrees scales for the Krishna River. Eleven hydro-climatic variables were considered to observe their dependence on TWSA and further reduced to three principal components. The LSTM's recurrent neural networks, with a 12-month lag to control flow of information in the memory units, were applied to downscale TWSA. At basin scale, downscaled GWLA from the two GRACE solutions have reasonably captured the observed trends (r > 0.6); however, GSH has underestimated the peaks (BIAS = 7.83 cm). The strong signal amplitude resulting from reduced leakage made GM a better choice over GSH in downscaling TWSA, particularly for the land-ocean mixed pixels (r(GM) = 0.74, r(GSH) = 0.62).

The computational complexity of distributed groundwater models poses a significant challenge in the conjunctive management of surface and groundwater resources. Here, we propose a multi-model framework to predict groundwater recharge using a simple water balance model. We compare and contrast two lumped parsimonious conceptual models of groundwater recharge, one based on P only and another, additionally including PE as a predictor. Both model variants also include an option to specify annually fixed or seasonally varying recharge factors, as well as a number of pumping scenarios. We incorporate these models within a python based open-source toolbox, REGSim (Recharge Estimation and Groundwater Simulation). The toolbox features a multi-objective evolutionary algorithm (NSGA-II), the Generalized Likelihood Uncertainty Estimation (GLUE) method, and regional sensitivity analysis (RSA). These functionalities allow the users to perform multi-objective calibration of the models, obtain confidence intervals on predicted groundwater heads, and understand the relative importance of different model parameters. REGSim is used to simulate groundwater heads for the urban agglomeration of Hyderabad, India. Using REGSim, we tested alternative conceptualizations of groundwater recharge and pumping processes in the city. We found that the intra-annual dynamics of groundwater levels are better explained by seasonally varying the recharge factors than annually fixed recharge factors. The model achieved an NSE of 0.64 and 0.70 during the validation for the formulations based on P only and using both P and PE, respectively. Furthermore, sensitivity analysis revealed that specific yield is the most influential parameter affecting the simulated groundwater head in the region. © 2021

Accurate quantification of water use efficiency (WUE) and characterization of its variability across multiple time scales can help to initiate appropriate management measures for cropland ecosystems in response to natural and anthropogenic changes. This study is aimed to understand the diurnal and seasonal patterns in WUE and its dominant controls in the citrus orchards of central India. We used eddy covariance measurements to estimate the evapotranspiration (ET) and gross primary product (GPP) fluxes from two crop cycles (2016 and 2017). On a daily scale, ET and GPP exhibited similar patterns, with peaks occurring during the fruit development stage. The daily WUE ranged from 0.22 to 3.39 g C kg−1 H2O with a mean of 1.77 g C kg−1 H2O. We observed high interseasonal variability in WUE, which emphasized the need to partition the fluxes between the growth stages. Landsat images were then acquired to characterize the spatiotemporal variability in WUE at the regional scale. Satellite-derived ET, GP and WUE (= GPP/ET) estimates were consistent with ground-based measurements (R2 > 0.80, n = 16). Eight biophysical indices derived from Landsat were then regressed with WUE estimates to see whether these indices, either independently or in combination, can explain the WUE dynamics in citrus orchards. Our results indicated that the enhanced vegetation index and soil-adjusted vegetation index are strongly related to WUE with correlation strengths greater than 0.75 at all growth stages. We then developed the constitutive relations between WUE and biophysical indices that could be utilized by water managers to improve crop water productivity in response to changing agro-climatic conditions. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

To understand the mechanism of bacteria growth in a reactive transport model inside a bio barrier for bioremediation, numerical modeling in the pore scale has to be done. An attempt has been made to understand and simulate the growth and decay of indigenous bacteria in a saturated porous medium at pore scale having a known concentration of Cr VI and to predict the enhanced microbial activity for the transformation of Cr VI to Cr III. Darcy scale models previously developed failed to address the hydrodynamics of the system, and contaminant degradation rates were over-predicted. In this study, the pore scale model combines processes such as fluid flow, solute transport with advection & diffusion equations of Cr VI reactive transport. Along with biotransformation of Cr VI and substrate consumption, the model majorly incorporates bacterial growth and decay on a pore scale. The model is divided into three portions, one for each of the processes and operated on different time scales. The mathematical equations are solved using FEM with appropriate initial and boundary conditions. The model developed can predict the velocity and pressure profiles developed fairly well. It can also predict the movement and, consumption of the substrate and biotransformation of Cr (VI) by bacteria along with the changes in its concentration.

In this study, We evaluated the effectiveness of the Hydraulic Tomography combining with Electrical Resistivity Tomography using an inversion technique to estimate the hydraulic and storage properties of a heterogeneous aquifer system. The resistivity tomogram obtained from the ERT inversion was used to distribute the pilot points around the heterogeneity which cross-hole in the subsurface. Also, it was used to constrain the values of hydraulic parameters during HT inversion. The groundwater flow model numerical studies were performed using GMS interface and Modflow-2000 compiler for the forward modeling and Regularized Parameter Estimation algorithm was used for the inversion technique for representing the spatial property variation. We created two aquifer realizations synthetically in which a typical layered system which mostly found in alluvial soils and an embedded system, a representative of weathered granitic aquifers. In both cases, the point estimates were estimated and obtained the spatial distribution of parameters using geostatistical interpolation, which is utilized to perform zones based regularisation. The HT was performed in both the aquifer systems and used the vast time-drawdown data sets in the inversion. The regularized inversion was performed using pilot points. The regularization technique is a two-part optimization technique in which both the data misfit and the structure of the model was preserved. The inversion was performed using three methods in which the first represents the uniform distribution of the pilot points; the second represents the kriging based distribution of pilot points, and the third represents ERT based distribution of pilot points. Independent pumping tests were used to evaluate the performance of the inversion models and the efficiency of the models was statistically analyzed using the model to measurement discrepancies in drawdowns. Our results conclude that using ERT as a priori to HT inversion guiding the pilot points

Characterizing the eco-hydrological processes and associated interactions within the soil-plant-atmosphere continuum (SPAC) pose formidable challenges to agronomists, irrigation engineers, plant physiologists, and water managers. These processes include: i) water and nutrient uptake by the plants that is influenced by root morphology and soil moisture availability, and ii) water lost to transpiration vis-à-vis carbon gain to photosynthesis that are influenced by plant phenology, stomatal conductance and meteorological conditions. Vidarbha region in Maharashtra, India is the largest producer of mandarin oranges (Citrus Retuculata) accounting for about 40% of country’s production with a yield of 6 t/Ha, much lower than nation’s average of 9.2 t/Ha. Low citrus crop production is primarily attributed to improper management activities practiced in the region that result in the formation and propagation of a water mold disease called root rot (Phytophthora spp.). The disease originates in the rhizosphere and progress towards the trunk with symptoms seen at the surface at much later time, thus making difficult to implement management practices. A physical understanding and critical assessment of soil-water-disease interactions can help in managing the disease and improve citrus crop productivity, with available resources. This research is aimed at a comprehensive understanding of eco-hydrological processes happening between rhizosphere and planetary boundary layer for the citrus trees of Vidarbha region. The specific objectives of this research include: i) Understand the hydrological and plant controls on root water uptake (RWU) mechanism dominated by health of citrus tree ii) Develop disease stress response functions and incorporate into a variable saturated flow model to simulate RWU from healthy and disease citrus trees iii) Develop single and dual crop coefficient curves for citrus trees viii iv) Characterize water use efficiency (WUE) of citrus trees of central India

This research aims at assessing the spatiotemporal patterns of water use efficiency (WUE) obtained from Landsat 8 products and to validate the results with eddy covariance (EC) measurements within the footprint area. We also correlated vegetation indices such as NDVI and EVI with Landsat derived WUE fluxes. METRIC and VPM algorithms were used to estimate ET and GPP fluxes respectively. Temporally, WUE showed a pronounced seasonal pattern starting from initial to crop development stage with clear sitinction between dry and wet seasons in the region. A decrease in WUE was observed during the dry season, which was related to the low water availability and increased vapour pressure deficit during the dry period, which induces stomatal closure, leading to a decline in the photosynthetic rate. Both EVI and NDVI showed good agreement with WUE during the crop growth stages from initial to crop development to harvesting

Accurate quantification of in situ heterogeneity and flow processes through fractured geologic media remains elusive for hydrogeologists due to the complexity in fracture characterization and its multiscale behavior. In this research, we demonstrated the efficacy of tracer-electrical resistivity tomography (ERT) experiments combined with numerical simulations to characterize heterogeneity and delineate preferential flow paths in a fractured granite aquifer. A series of natural gradient saline tracer experiments were conducted from a depth window of 18 to 22 m in an injection well (IW) located inside the Indian Institute of Technology Hyderabad campus. Tracer migration was monitored in a time-lapse mode using two cross-sectional surface ERT profiles placed in the direction of flow gradient. ERT data quality was improved by considering stacking, reciprocal measurements, resolution indicators, and geophysical logs. Dynamic changes in subsurface electrical properties inferred via resistivity anomalies were used to highlight preferential flow paths of the study area. Temporal changes in electrical resistivity and tracer concentration were monitored along the vertical in an observation well located at 48 m to the east of the IW. ERT-derived tracer breakthrough curves were in agreement with geochemical sample measurements. Fracture geometry and hydraulic properties derived from ERT and pumping tests were further used to evaluate two mathematical conceptualizations that are relevant to fractured aquifers. Results of numerical analysis conclude that dual continuum model that combines matrix and fracture systems through a flow exchange term has outperformed equivalent continuum model in reproducing tracer concentrations at the monitoring wells (evident by a decrease in RMSE from 199 to 65 mg/L). A sensitivity analysis on model simulations conclude that spatial variability in hydraulic conductivity, local-scale dispersion, and flow exchange at fracture-matrix interface have a

Variably saturated flow models that simulate soil–water–plant interactions within the rhizosphere largely ignore the effect of plant health. This makes it difficult for them to effectively simulate root water uptake (RWU) and implement alternate management practices for diseased trees. This research was aimed at understanding the hydrological and plant controls on RWU simulations dominated by the health of the tree using experimental and numerical frameworks. Two research plots, one around a healthy mature and the other around a diseased mature (Phytophthora spp. affected) orange tree (Citrus reticulate Blanco), in the Vidarbha region of India were considered for our analysis. Three-dimensional electrical resistivity tomography (ERT) performed at the two locations revealed that the soil moisture profiles following irrigation are different between the two plots. A two-dimensional axisym-metric form of Richards’ equation was then solved using HYDRUS (2D/3D) by incorporating a root distribution function. A global sensitivity analysis was performed to identify the root distribution parameters that influence soil moisture simulations. These parameters were then optimized using a genetic algorithm for healthy and diseased conditions. We observed that the diseased orange tree had consumed less water, leaving high soil moisture in the rhizosphere, a condition favorable for the further growth of disease-causing fungi. Hence, managing irrigation water in accordance with RWU patterns is essential for diseased trees. To understand the error propagation in RWU estimation, we simulated RWU from a diseased tree with the optimal parameters derived for a healthy case. Results show that the error in estimating RWU from the model cells progressively increases with radial distance and soil depth. © Soil Science Society of America.

Fixed plot survey was undertaken to plot correlation between environmental factors with population of Phytophthora spp. in soil and the disease intensity during June 2015 to May 2016. Agro-meteorological data was recorded by using wireless sensors (for air temperature 107 Temperature probe, for relative humidity HC2S3 and for rainfall measurement Texas Electronic rain gauge) in selected plots. All four orchards were found infected with Phytophthora in the range of 3.2–43.6 cfu/g of soil. There was consistent increase in pathogen population in all plots with increase in rainfall, relative humidity with decrease in temperature and vice versa. At high rainfall condition intensity of root rot was increased to 35.81 per cent in the month of August and gummosis (41.01%) was also increased in the month of October with average propagules of 25.84 cfu/g of soil. Increase in temperature decreased intensity of gummosis (26.29%) and root rot (20.09%) in the month of May, with the average propagules, i.e., 4.56 cfu/g of soil. Present findings suggest that, humidity and rainfall were significantly correlates with population dynamics of Phytophthora spp. and disease intensity, while temperature was found inversely proportional.

Epidemics caused by Phytophthora spp. were monitored in four commercial citrus orchards to plot correlation between environmental and soil factors with root rot disease caused by Phytophthora spp. in citrus. Agro - meteorological d ata was recorded by using wireless sensors (for air temperature 107 Temperature probe, for relative humidity HC2S3 with 30 minutes time interval for both the sensors and for rainfall measurement Texas Electronic rain gauge) in selected plots. The soil mois ture, soil pH and soil EC was recorded at fortnightly interval. The observations recorded in order to characterise the progression of the symptoms expression over the time and to provide evidence for the possible correlation of inoculum dynamics with root rot and environmental factors. The relationship of rainfall, temperature, relative humidity, soil moisture, soil pH and soil EC on disease development was investigated. Sensor based data was recorded for rainfall, temperature, relative humidity and convert ed to forth nightly interval. The disease progress and inoculum potential recorded at forth nightly interval from June 2016 to May 2017. There was significant progression in the disease development with the increase in the rainfall and soil moisture. There was significant increase in the disease at second fort night of August (38.53%) and progression continued up to October (87.58%). Progress in disease was attributed to increase in soil moisture, relative humidity and decrease in the air temperature. A ten dency of spreading the disease at adjoining trees was observed. Drainage of water, possibly containing propagules of the pathogen may have been responsible for disease progression. The disease initially low but gradually increases with time. There was posi tive correlation between rainfalls, soil moisture, relative humidity, soil EC with disease progression and inverse correlation with air temperature

An accurate quantification of in situ heterogeneity and flow processes through fractured geologic media remains elusive for hydrog eologists due to the complexity involved in fracture characterization and its multi - scale behavior. In this research, we demonstrated the efficacy of tracer - ERT experiments coupled with numerical simulations in delineating heterogeneity and preferential fl ow paths of a fractured granite aquifer. A series of natural gradient saline tracer experiments were conducted from a depth window of 18 to 22 m in an injection well located inside IIT Hyderabad campus. Tracer migration was monitored in a time - lapse mode u sing two cross - sectional surface ERT profiles placed in the direction of flow gradient. ERT data quality was improved by considering stacking, reciprocal measurements, resolution indicators, and geophysical logs. The dynamic changes in sub - surface electric al properties inferred via resistivity anomalies were used to highlight preferential flow paths of the study area. Temporal changes in fluid resistivity, electrical resistivity, and tracer concentration were monitored along the vertical in an observation w ell located at 48 m to the north - east of injection well. ERT derived tracer break through curves were in agreement with geochemical sample measurements (R 2 =0.74). Fracture geometry and hydraulic properties derived from ERT and pumping tests were used to ev aluate two mathematical conceptualizations that are relevant to fractured aquifers. Results of numerical analysis conclude that, a dual continuum model that combines matrix and fracture systems through a flow exchange term has outperformed equivalent conti nuum model in reproducing tracer concentrations at the monitoring wells (evident by decrease in RMSE from 199 mg/l to 65 mg/l). A sensitivity analysis of the model parameters conclude that spatial variability in hydraulic conductivity, local - scale dispersi on, and flow exchange at fracture - matrix interface h

Vidarbha region in Maharashtra, India is witnessing a continuous decrease in orange crop due to the propagation of `Phytopthora root rot', a water mold disease. Under favorable conditions, the disease causing bacteria can attack the plant root system and propagates to the surface (where first visual impression is made), making difficult to regain the plant health. This research aims at co-relating eco-hydrological fluxes with disease sensing parameters of orange trees. Two experimental plots around a healthy-young and declined-young orange trees were selected for our analysis. A 3-dimentional electrical resistivity tomography (ERT) (Figure) was carried at each plot to quantify the soil moisture distribution at a vadose zone. Pedo-electric relations were obtained considering modified Archie's law parameters. ERT derived moisture data was validated with time domain reflectometry (TDR) point observations. Soil moisture profiles derived from ERT were observed to be differ marginally between the two plots. Disease quantification was done by estimating the density of Phytopthora spp. inoculum in soils sampled along the root zone. Identification of Phytopthora spp. was done in the laboratory using taxonomic and morphologic criteria of the colonies. Spatio-temporal profiles of soil moisture and inoculum density were then co-related to comment on the eco-hydrological fluxes contributing to the health propagation of root rot in orange tree for implementing effective water management practices.

Image reconstruction algorithms derived from electrical resistivity tomography (ERT) are highly non-linear, sparse, and ill-posed. The inverse problem is much severe, when dealing with 3-D datasets that result in large sized matrices. Conventional gradient based techniques using L2 norm minimization with some sort of regularization can impose smoothness constraint on the solution. Compressed sensing (CS) is relatively new technique that takes the advantage of inherent sparsity in parameter space in one or the other form. If favorable conditions are met, CS was proven to be an efficient image reconstruction technique that uses limited observations without losing edge sharpness. This paper deals with the development of an open source 3-D resistivity inversion tool using CS framework. The forward model was adopted from RESINVM3D (Pidlisecky et al., 2007) with CS as the inverse code. Discrete cosine transformation (DCT) function was used to induce model sparsity in orthogonal form. Two CS based algorithms viz., interior point method and two-step IST were evaluated on a synthetic layered model with surface electrode observations. The algorithms were tested (in terms of quality and convergence) under varying degrees of parameter heterogeneity, model refinement, and reduced observation data space. In comparison to conventional gradient algorithms, CS was proven to effectively reconstruct the sub-surface image with less computational cost. This was observed by a general increase in NRMSE from 0.5 in 10 iterations using gradient algorithm to 0.8 in 5 iterations using CS algorithms.

Groundwater Assessment, Modeling, and Management explores the management of water resources and the impact of climate change on groundwater. Expert contributors provide practical information on hydrologic engineering and groundwater resources management for students, researchers, scientists, and other practicing professionals in environmental engineering, hydrogeology, irrigation, geophysics, and environmental science.

This research aims at improving the performance of regional groundwater models by incorporating high-resolution elevation data into the head-dependent packages of MODFLOW. Model code specific to the evapotranspiration package (EVT) of MODFLOW was modified to account for the variability in elevation data and to effectively delineate the evapotranspiration (ET) simulated region at user-specified digital elevation model (DEM) resolution. The regional groundwater model of the Rincon Valley–Mesilla Basins (NMOSE-2007 flow model) was improved and considered to evaluate and validate the developed code. The base DEM of the study area is smoothened and aggregated to various resampled resolutions that are integer divisors of NMOSE-2007 flow model resolution for use with ET simulation. A gradual decrease in ET outflow is observed when the variability in elevation is eliminated across the grid cell. Also, changes in cumulative ET outflow (as a fraction of total outflow) at different resampled grids followed a similar trend during the simulation. The computational cost is high for the models simulated at fine resolution, whereas the simulation accuracy is low for the models simulated at coarse resolution. To select the optimum resampled DEM resolution to simulate the ET component of groundwater for use with the NMOSE-2007 flow model, a chi-square test of homogeneity was performed at 5 and 10% significance levels by considering computational cost and simulation accuracy as the base parameters. Results of the statistical analysis concluded that simulating ET component at 80.467-m resolution and integrating the outflows to model cell (402.336 m) resolution would significantly improve the performance of the flow model without compromising on the computational cost.