Spatio-temporal groundwater variations associated with climatic and anthropogenic impacts in South-West Western Australia

Spatiotemporal patterns of groundwater over South Korea

Understanding the large-scale spatiotemporal pattern of multi-depth groundwater levels is critical to develop water management plans and policies for sustainable ecological and social prosperity, which are still lacking. Here, we investigate three major spatiotemporal modes of groundwater levels from ∼200 groundwater monitoring stations over the southern Korean Peninsula (2009-2020), using the Cyclostationary empirical orthogonal function analysis. The first two major modes are associated with the seasonality of recharge and discharge and groundwater use during the 2016/17 drought, which explained half of the total variance. The third major mode indicated a decreasing trend of deep groundwater levels over the western Korean Peninsula, where key administrative and authority offices have been relocated via balanced national land development policies. Furthermore, at least three million Koreans over this region likely experience groundwater depletion by the 2080s. Observational evidence of emerging groundwater depletion suggests a window of opportunity for pre-emptive groundwater management plans.

Spatiotemporal variability and controlling factors of groundwater depletion in endorheic basins of Northwest China

Recent global groundwater overpumping is threatening ecosystem stability and food security, particularly in arid basins. A solid investigation regarding the drivers of groundwater depletion is vital for groundwater restoration, hitherto, yet it remains largely unquantified. Here, a framework to quantify the contribution of natural forcing (NF) and anthropogenic perturbations (AP) to groundwater storage anomalies (GWSA) variability by separating the GWSA estimated by the Gravity Recovery and Climate Experiment (GRACE) satellite into natural- and human-induced GWSA was proposed in the northwest endorheic basin (NWEB) of China. Further, a multiple linear regression model was established for GWSA change prediction. Our results showed that, during the period 2003-2020, the GWSA depleted at a rate of 0.25 cm yr-1 in the entire NWEB. In addition, GWSA was found to decrease significantly (exceeding 1 cm yr-1) in the west of NWEB where there are heavily irrigated areas, and has become one of the regions with the most serious groundwater depletion in China. Whereas a significantly increasing trend (greater than 0.5 cm yr-1) was observed in the Qaidam basin and south part of the Tarim River basin, becoming a groundwater enrichment reservoir in NWEB. The negative contribution of AP to groundwater depletion has increased from 3% to 95% in the last decade, as determined by separating the effects of NF and AP on GWSA. The rapid expansion of the cropland area and the increase in water use due to population growth are investigated to be the main reasons for GWSA depletion, particularly in the North Tianshan Rivers, Turpan-Hami, and Tarim River basins. Therefore, we conclude that AP are dominating and accelerating groundwater depletion in the NWEB. The increase of GWSA in the Qaidam basin has been attributed to the increase in solid water melt and regional precipitation. The western route project of China's south-north water diversion and water-saving irrigation are important ways to solve the problem of groundwater depletion in NWEB. Our results emphasize that a more feasible framework capable of reliably identifying the driving factors of groundwater storage change is a necessary tool for promoting the sustainable management of groundwater resources under both NF and AP in arid endorheic basins.

Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques

Groundwater is the main source to answer the irrigation supply in several arid and semi-arid areas. In the present work, groundwater quality for irrigation purposes in the arid region of Menzel Habib (Tunisia) for thirty-six groundwater samples is assessed considering the application of different conventional water quality indicators, particularly, electrical conductivity (EC), sodium absorption ratio (SAR), soluble sodium percentage (SSP), magnesium adsorption ratio (MAR), Kelly ratio (KR), and permeability index (PI). The results obtained indicate a variability for EC: 3.06 to 14.98 mS.cm^-1; SAR: 4.08 to 19.30; SSP: 35.78 to 71.53%; MAR: 34.19 to 56.01; PI: 38.47 to 72.74; and KR: 0.56 to 2.47. These results suggest that groundwater from Menzel Habib aquifer system is classified between excellent to unsuitable according to the applied water quality indices. Furthermore, the groundwater samples are also plotted in the Richards diagram classification system, based on the relation between SAR and EC, suggesting that almost groundwater samples present a harmful quality. Moreover, fuzzy logic model has been proposed and created to assess groundwater quality for irrigation. The membership functions are constructed for six significant parameters such as EC, SAR, SSP, MAR, KR, and PI and the rules are, then, fired to get a simple Fuzzy Irrigation Water Quality Index (FIWQI). The obtained groundwater quality results suggest that 3% of the samples from Menzel Habib region are considered as "good" for irrigation, 3% are classified as "good to permissible", 33% with a "permissible" quality, 36% "permissible to unsuitable", while 25% of groundwater present an "unsuitable" quality. Thus, the use of fuzzy logic techniques has more reliable and robust results by overcoming the uncertainties in the decision-making attributed to the conventional methods by the creation of new classes (excellent to good, good to permissible, and permissible to unsuitable) in addition to the classes proposed by Richards diagram classification (excellent, good, permissible, and unsuitable) to assess the groundwater quality suitability for irrigation purposes.

Revealing the impact of water conservancy projects and urbanization on hydrological cycle based on the distribution of hydrogen and oxygen isotopes in water

In recent years, the development and utilization of water resources have imposed great impacts on hydrological characteristics and ecological environment. In this paper, methods based on stable isotopes were used to analyze the cumulative effect of water projects and urbanization on the hydrological cycle in Qingbaijiang River Basin. Isotope evidence shows that the hydrological processes affected by water regulation and urbanized runoff generation differentiate greatly from the natural state. The annual mean isotopic values follow an order of groundwater > rainwater > river water. Consistent isotopic composition and variation trend between the near-bank groundwater and river water were only observed from May to late June 2018 and from February to April 2019 in the upper zone, indicating the dominant recharge of river to the groundwater. However, the isotopic variations between the two waters in the middle and lower zones suggested that the hydraulic exchange was limited, demonstrating the significant changes in river water level caused by the reservoir impoundment. The isotopic enrichment rate along the flow path is highest in January (0.0265‰/km), followed by October (0.0160‰/km), indicating the significant evaporation, while slight spatial changes in July (0.0027‰/km) reflected masked evaporation effect. This variability can be mainly attributed to the flow rate change and increase of water salinity in anthropic zones. Periodic regression analysis was employed to evaluate the difference in rainfall-runoff responses between hydrographic zones and estimate the mean residence time (MRT). Periodicity of isotopes in river water increased from upper to lower reaches with increasing R² values from 0.04 in SW1 to 0.46 in SW8. The MRT grew shorter along the flow path from 870 days in SW1 to 293 days in SW8, reflecting accelerated rainfall-runoff process due to the increasing impervious surface area and drainage system. These results identify the sensitivity of stable isotopes to the land use changes, runoff generation, and topography, and have implication for the potential water and environmental risks. Based on these understandings, suggestions for sustainable water-environment management in urban and rural areas were proposed.

Impacts of extreme climate on Australia's green cover (2003-2018): A MODIS and mascon probe

Australia as a continent represents a semi-arid environment that is generally water-limited. Changes in rainfall pattern will inevitably occur due to rising temperatures caused by climate change, which has a direct impact on the distribution of Australia's vegetation (green cover). As variability in rainfall continues to increase, i.e., in frequency and/or magnitude, due to climate change, extreme climate events such as droughts are predicted to become more pervasive and severe that will have an adverse effect on vegetation. This study investigates the effects of extreme climate on Australia's green cover during 2003-2018 for the end of rainy seasons of April and October in the northern and southern parts, respectively, to (i) determine the state of vegetation and its changes, (ii) identify "hotspots", i.e., regions that constantly experienced statistically significant decrease in NDVI, and (iii), relate changes in the identified hotspots to GRACE-hydrological changes. These are achieved through the exploitation of the statistical tools of Principal Component Analysis (PCA) and Mann-Kendel Test on Gravity Recovery and Climate Experiment (GRACE) hydrological products on the one hand, and the utilization of Australia's rainfall product and Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index (MODIS-NDVI) used here with its native spatial resolution of 0.002413^∘ × 0.002413^∘ on the other hand. Differences between 3-year intervals from 2003 to 2018 for both April and October datasets are used to quantify vegetation variations. Through area change analysis, the vegetation differences (2003-2018) indicate that April exhibited larger increase (13.77% of total vegetation area) than decrease (7.83%) compared to October, which experienced slightly larger decrease (9.41%) than increase (8.71%). South Australia and Western Australia emerge as "hotspots" in which vegetation statistically decreased in October, with no noticeable change in April. GRACE-based hydrological changes in both hotspots reflect a decreasing trend (2003-2009) and increasing trend (2009-2012) that peaks in 2011, which then transitions towards a gradually decreasing trend after 2012. Australia-wide climate variability (ENSO and IOD) influenced vegetation variations during the data period 2003 to 2018.

Spatio-Temporal Evaluation of Water Storage Trends from Hydrological Models over Australia Using GRACE Mascon Solutions

The Gravity Recovery and Climate Experiment (GRACE) data have been extensively used to evaluate the total terrestrial water storage anomalies (TWSA) from hydrological models. However, which individual water storage components (i.e., soil moisture storage anomalies (SMSA) or groundwater water storage anomalies (GWSA)) cause the discrepancies in TWSA between GRACE and hydrological models have not been thoroughly investigated or quantified. In this study, we applied GRACE mass concentration block (mascon) solutions to evaluate the spatio-temporal TWSA trends (2003–2014) from seven prevailing hydrological models (i.e., Noah-3.6, Catchment Land Surface Model (CLSM-F2.5), Variable Infiltration Capacity macroscale model (VIC-4.1.2), Water—Global Assessment and Prognosis (WaterGAP-2.2d), PCRaster Global Water Balance (PCR-GLOBWB-2), Community Land Model (CLM-4.5), and Australian Water Resources Assessment Landscape model (AWRA-L v6)) in Australia and, more importantly, identified which individual water storage components lead to the differences in TWSA trends between GRACE and hydrological models. The results showed that all of the hydrological models employed in this study, except for CLM-4.5 model, underestimated the GRACE-derived TWSA trends. These underestimations can be divided into three categories: (1) ignoring GWSA, e.g., Noah-3.6 and VIC-4.1.2 models; (2) underrating both SMSA and GWSA, e.g., CLSM-F2.5, WaterGAP-2.2d, and PCR-GLOBWB-2 models; (3) deficiently modeling GWSA, e.g., AWRA-L v6 model. In comparison, CLM-4.5 model yielded the best agreement with GRACE but overstated the GRACE-derived TWSA trends due to the overestimation of GWSA. Our results underscore that GRACE mascon solutions can be used as a valuable and efficient validation dataset to evaluate the spatio-temporal performance of hydrological models. Confirming which individual water storage components result in the discrepancies in TWSA between GRACE and hydrological models can better assist in further hydrological model development.