Unravelling the signatures of submarine groundwater discharge and seawater intrusion along the coastal plains of Odisha, India: a multi-proxy approach.

Submarine Groundwater Discharge (SGD) and Seawater Intrusion (SWI) are two contrary hydrological processes that occur across the land-sea continuum and understanding their nature is essential for management and development of coastal groundwater resource. Present study has attempted to demarcate probable zones of SGD and SWI along highly populated Odisha coastal plains which is water stressed due to indiscriminate-exploitation of groundwater leading to salinization and fresh groundwater loss from the alluvial aquifers. A multi-proxy investigation approach including decadal groundwater level dynamics, LANDSAT derived sea surface temperature (SST) anomalies and in-situ physicochemical analysis (pH, EC, TDS, salinity and temperature) of porewater, groundwater and seawater were used to locate the SGD and SWI sites. A total of 340 samples for four seasons (85 samples i.e., 30 porewater, 30 seawater and 25 groundwater in each season) were collected and their in-situ parameters were measured at every 1-2 km gap along ~ 145 km coastline of central Odisha (excluding the estuarine region). Considering high groundwater EC values (> 3000 µS/cm), three probable SWI and low porewater salinities (< 32 ppt in pre- and < 25 ppt in post-monsoons), four probable SGD zones were identified. The identified zones were validated with observed high positive hydraulic gradient (> 10 m) at SGD and negative hydraulic gradient (< 0 m) at SWI sites along with anomalous SST (colder in pre- and warmer in post-monsoon) near probable SGD locations. This study is first of its kind along the Odisha coast and may act as initial basis for subsequent investigations on fresh-saline interaction along the coastal plains where environmental integrity supports the livelihood of coastal communities and the ecosystem.

Delineation of submarine groundwater discharge and seawater intrusion zones using anomalies in the field water quality parameters, groundwater level fluctuation and sea surface temperature along the Gujarat coast of India.

Nature mediated processes like seawater intrusion (SWI) and its complementary processes like submarine groundwater discharge (SGD) often cause severe water stress on the coastal water resources worldwide. The present work attempts to delineate the SWI and SGD zones along the North-Western coast of India (constituting the entire coastline of Gujarat) which is currently facing severe water crises due to the freshwater salinization and water loss through the coastal aquifer system. In the present work site-specific water characteristics and groundwater level were used as a proxy for identifying the probable zones of SWI and SGD. For the delineation purpose, we have collected 540 water samples distanced at 5-10 km (seawater, porewater and groundwater; 180 each) from the entire coastline of Gujarat. Further, a three-tier validation system has been adopted for delineating the SWI and SGD zones followed by the physical verification of the locations through the integration of (i) Groundwater fluctuation dynamic, (ii) MODIS derived sea surface temperature (SST) anomaly, and (iii) Electrical conductivity (EC) based gradient mapping. The study has identified 9 out of 14 districts being vulnerable to SWI, whereas the remaining five districts from south Gujarat and the Saurashtra coast are suspectable for SGD. The present work will act as a preliminary basis for formulating a framework for the detailed investigation of the mixing process along the coast.

Assessing vulnerability of coastal aquifer to seawater intrusion using Convolutional Neural Network.

This study examined coastal aquifer vulnerability to seawater intrusion (SWI) in the Shiramin area in northwest Iran. Here, six types of hydrogeological data layers existing in the traditional GALDIT framework (TGF) were used to build one vulnerability map. Moreover, a modified traditional GALDIT framework (mod-TGF) was prepared by eliminating the data layer of aquifer type from the GALDIT model and adding the data layers of aquifer media and well density. To the best of our knowledge, there is a research gap to improve the TGF using deep learning algorithms. Therefore, this research adopted the Convolutional Neural Network (CNN) as a new deep learning algorithm to improve the mod-TGF framework for assessing the coastal aquifer vulnerability. Based on the findings, the CNN model could increase the performance of the mod-TGF by >30 %. This research can be a reference for further aquifer vulnerability studies.

Preliminary investigation of saline water intrusion (SWI) and submarine groundwater discharge (SGD) along the south-eastern coast of Andhra Pradesh, India, using groundwater dynamics, sea surface temperature and field water quality anomalies.

Intensive anthropogenic activities along the coastal plains of Andhra Pradesh (such as urbanisation, agriculture and aquaculture) rely extensively on coastal fresh groundwater resources that are pumped at unsustainable rates causing groundwater decline and water quality problems due to saline water intrusion. Hydrogeological studies are imperative to implement groundwater conservation strategies in coastal Andhra Pradesh, which is experiencing a severe freshwater shortage due to overexploitation and saline water intrusion as well as clean water loss through the aquifer system close to the coastal plains. An attempt is made in this study to demarcate the submarine groundwater discharge (SGD) and saline water intrusion (SWI) zones adopting a three-tier validation system, i.e. groundwater dynamic, LANDSAT resultant sea surface temperature (SST) variance and site-specific water characteristics along the southeast coast of Andhra Pradesh, India. A total of 234 water samples (139 porewater, 31 groundwater and 64 seawater samples) were evaluated along ~ 450 km southeast coastline of Andhra Pradesh. In situ porewater physio-chemical parameters, i.e. EC, TDS, pH, DO, temperature, and salinity, at every 1 km except non-accessible areas and groundwater for every 5 km were analysed and used for identification of SGD zones in the study area. The hydraulic gradient values vary from - 11 to 250 m in post-monsoon and - 14 to 250 m in pre-monsoon. And sea surface temperature anomaly for 2017, 2018 and 2019 varies between 21-39 °C, 15-34 °C and 20-39 °C. Three districts out of the four districts studied (Krishna, Guntur and Nellore) were shown to be prone to SWI, whereas Prakasam district was susceptible for SGD. For the first time, this kind of preliminary study was carried out in the coastal Andhra Pradesh region, and it will serve as a basis for the meticulous analysis of the fresh and saline water mixing zones/process as well as to develop and manage the groundwater resources along the water-stressed coastal plains of Andhra Pradesh, India.

Optimal redesign of coastal groundwater quality monitoring networks under uncertainty: application of the theory of belief functions.

This paper presents a new methodology for the optimal redesign of water quality monitoring networks in coastal aquifers. The GALDIT index is used to evaluate the extent and magnitude of seawater intrusion (SWI) in coastal aquifers. The weights of the GALDIT parameters are optimized using the genetic algorithm (GA). A SEAWAT-based simulation model, a spatiotemporal Kriging interpolation technique, and an artificial neural network surrogate model are then implemented to simulate total dissolved solids (TDS) concentration in coastal aquifers. To obtain more precise estimations, an ensemble meta-model is developed using the Dempster-Shafer's belief function theory (D-ST) to combine the results obtained from the three individual simulation models. The combined meta-model is then used for calculating more precise TDS concentration. Some plausible scenarios are defined for variation of water elevation and water salinity at the coastline to incorporate uncertainty through the concept of value of information (VOI). Finally, the potential wells with the highest values of information are taken into consideration to redesign coastal groundwater quality monitoring network under uncertainty. The performance of the proposed methodology is evaluated by applying it to the Qom-Kahak aquifer, north-central Iran, which is threatened by SWI. At first, the individual and ensemble simulation models are developed and validated. Then, several scenarios are defined regarding the plausible changes in TDS concentration and water level at the coastline. In the next step, the scenarios, the GALDIT-GA vulnerability map, and the VOI concept are used for redesigning the existing monitoring network. The results illustrate that the revised groundwater quality monitoring network containing 10 new sampling locations outperforms the existing one based on the VOI criterion.

Multi-objective optimization-based reactive nitrogen transport modeling for the water-environment-agriculture nexus in a basin-scale coastal aquifer.

The quantification of trade-offs between social-economic and environmental effects is of great importance, especially in the semi-arid coastal areas with highly developed agriculture. The study presents an integrated multi-objective simulation-optimization (S-O) framework to evaluate the basin-scale water-environment-agriculture (WEA) nexus. First, the variable-density groundwater model (SEAWAT) is coupled to the reactive transport model (RT3D) for the first attempt to simulate the environmental effects subject to seawater intrusion (SWI) and nitrate pollution (NP). Then, the surrogate assisted multi-objective optimization algorithm is utilized to investigate the trade-offs between the net agricultural benefits and extents of SWI and NP while considering the water supply, food security, and land availability simultaneously. The S-O modeling methodology is applied to the Dagu River Basin (DRB), a typical SWI region with intensive agricultural irrigation in China. It is shown that the three-objective space based on Pareto-optimal front can be achieved by optimizing planting area in the irrigation districts, indicating the optimal evolution of the WEA nexus system. The Pareto-optimal solutions generated by multi-objective S-O model are more realistic and pragmatic, avoiding the decision bias that may often lead to cognitive myopia caused by the low-dimensional objectives. Although the net agricultural benefits in Pareto-optimal solutions are declined to some extent, the environmental objectives (the extents of SWI and NP) are improved compared to those in the pre-optimized scheme. Therefore, the proposed multi-objective S-O framework can be applied to the WEA nexus in the river basin with intensive agriculture development, which is significant to implement the integrated management of water, food, and environment, especially for the semi-arid coastal aquifers.

Spatio-temporal assessment and trend analysis of surface water salinity in the coastal region of Bangladesh.

The study was designed to collect water samples over two seasons-wet-monsoon season (n = 96) (March-April) and dry-monsoon season (n = 44) (September-October)-to understand the seasonal variation in anion and cation hydrochemistry of the coastal rivers and estuaries contributing in the spatial trend in salinity. Hydrochemical examination of wet-monsoon season primarily revealed Ca-Mg-HCO3 type (66%) and followed by Na-Cl type (17.70%) water. In the dry-monsoon season, the scenario reversed with primary water being Na-Cl type (52.27%) followed by Ca-Mg-HCO3 type (31.81%). Analysis of Cl/Br molar ratio vs. Cl (mg/L) depicted sampling area affected by seawater intrusion (SWI). Spatial analysis by ordinary kriging method confirmed approximately 77% sample in the dry-monsoon, and 34% of the wet-monsoon season had shown SWI. The most saline-intruded areas in the wet-monsoon seasons were extreme south-west coastal zone of Bangladesh, lower Meghna River floodplain and Meghna estuarine floodplain and south-eastern part of Chittagong coastal plains containing the districts of Chittagong and Cox's Bazar adjacent to Bay of Bengal. In addition, mid-south zone is also affected slightly in the dry-monsoon season. From the analyses of data, this study could further help to comprehend seasonal trends in the hydrochemistry and water quality of the coastal and estuarine rivers. In addition, it can help policy makers to obligate some important implications for the future initiatives taken for the management of land, water, fishery, agriculture and environment of coastal rivers and estuaries of Bangladesh.