RESUMO
Climate change imposing additional stressors on groundwater resources globally, thereby predicting groundwater recharge (GR) changes is crucial to sustainably managing water resources, especially in the arid endorheic basins. Groundwater in the Endorheic Basins of Northwest China (NWEB) is potentially impacting regional socio-economic output and ecosystem stability due to the imbalance between supply and extraction exacerbated by climate change. Hence, recognizing the impacts of climate change on past and future GR is imperative for groundwater supply and sustainable groundwater management in the NWEB. Here, the impact of historical (1971-2020) and projected (2021-2100) climate changes on GR across the entire NWEB and three distinctive landscape regions (i.e., mountainous, oasis, and desert) were assessed. A coupled distributed hydrologic model (CWatM-HBV model), which integrates the Community Water Model (CWatM) and the HBV model, was run with three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, and SSP3-7.0) forcing from 10 general circulation models (GCMs) to simulate and analyze the interannual and seasonal variations of GR, along with their driving factors. Over the past 50 years, both precipitation and runoff have undergone significant increases, and leading to a dramatic rise in GR (0.09 mm yr-1). The future annual growth rate of GR is projected to range from 0.01 to 0.09 mm yr-1 from SSP1-2.6 to SSP3-7.0 across the entire NWEB, with the majority of the increase expected during the spring and summer seasons, driven by enhanced precipitation. GR from the mountainous region is the primary source (accounting for approximately 56-59 %) throughout the NWEB with the greatest increase anticipated. Precipitation and runoff have significant influences on GR in mountainous areas, and the impact of precipitation on GR is expected to increase over time. Changes in GR in oasis and desert areas are mainly limited by precipitation variation and increase in the SSP2-4.5 and SSP3-7.0 scenario. Additionally, the processes of glacial retreat and permafrost degradation will complicate the GR dynamics although the process is largely interfered with by anthropogenic environmental changes, especially in oasis-desert systems. The average annual recharge in the NWEB was 8.9 mm in the historical period and 13.6 ± 4.1 mm in the future. Despite an increase in GR due to climate change, groundwater storage is likely to continue to decline due to complex water demands in the NWEB. This study highlights the significance of future precipitation changes for GR and contributes to the understanding of the influence of climate change on groundwater systems and advances the sustainable management of water resources.
RESUMO
Vitamin C (VC), due to its chemical properties, can provide more oxygen-containing functional groups such as hydroxyl groups for biochar (BC), which promotes the adsorption of tetracycline on biochar. Therefore, in this study, cow dung biochar (CDBC) was modified with VC and VC-modified CDBC (CDBC-VC) was synthesized. The modified biochar was characterized and related factors, adsorption kinetics, isotherms and adsorption mechanisms were investigated. Adsorption kinetics indicate a fast rate of adsorption. The adsorption isotherms showed that the maximum adsorption capacity was 31.72 mg/g (CDBC) and 50.90 mg/g (CDBC-VC), respectively, and the adsorption process was inhomogeneous with multiple molecular layers and the adsorbent has a higher affinity. Mechanistic studies showed that hydrogen bonding interactions, π-π electron donor-acceptor interactions, hydrophobic interactions, and electrostatic interactions were the key to the adsorption process. The analysis of adsorbent regeneration showed that CDBC-VC had good adsorption performance. CDBC and CDBC-VC showed the best performance in simulated industrial wastewater with removal rates of 78.81% and 93.69%. The adsorption mechanism was comprehensively analyzed using six machine learning models. The extreme gradient boosting model gave the best fit. Analysis of the weights of the input variables for predicting adsorption efficiency showed that the ratio of initial TC concentration to BC dosage (29.8%), specific surface area (23%), isoelectric point (8.8%), and ash content (7.7%) had a significant effect on the predicted results.