Опубликована: Янв. 1, 2024
Язык: Английский
Опубликована: Янв. 1, 2024
Язык: Английский
Water Resources Management, Год журнала: 2024, Номер 38(4), С. 1397 - 1417
Опубликована: Янв. 19, 2024
Язык: Английский
Процитировано
3Journal of Hydroinformatics, Год журнала: 2024, Номер 26(11), С. 2962 - 2979
Опубликована: Ноя. 1, 2024
ABSTRACT The performance of regional groundwater level (GWL) prediction model hinges on understanding intricate spatiotemporal correlations among monitoring wells. In this study, a graph convolutional network (GCN) with long short-term memory (LSTM) (GCN–LSTM) is introduced for GWL utilizing data from 16 wells located in the northeastern Xiangtan City, China. This designed to account both hybrid temporal dependencies and spatial autocorrelations It consists two parts: part employs GCNs extract characteristics self-similarity weight matrix an attribute wells; utilizes LSTM module capture patterns sequences, along monthly precipitation temperature data. dynamically predicts changes levels, achieving higher accuracy average compared single-well predictions using LSTM. By incorporating autocorrelations, GCN–LSTM demonstrated improvement goodness-of-fit approximately 11.21% over LSTM-based individual Its application holds significant reference value sustainable utilization development resources City.
Язык: Английский
Процитировано
2Scientific Reports, Год журнала: 2024, Номер 14(1)
Опубликована: Дек. 30, 2024
The Urmia Lake Basin has been severely affected by the unbalanced exploitation of water resources. To better manage use integrated resources, coupled SWAT-MODFLOW-NWT was adopted for Mahabad Plain in Basin, N.W. Iran. results indicated that a multifunctional calibration SWAT and MODFLOW-NWT hydrological models large-scale irrigated area necessary, using parameters such as evapotranspiration crop yield addition to usual surface runoff table measures. model then used evaluate several allocation scenarios, alternate proportions irrigation from conjunctive ultimate objective adopting these scenarios increase residual share supply order compensate deprived Lake. this study demonstrated able satisfactorily simulate groundwater balance components at different spatial temporal dimensions. indicate aquifer is capable supplying needs central northern regions, with some limitations around running rivers. Furthermore, sustainability indicators showed even an additional 30% groundwater, long-term resources preserved Ultimately, findings reduction waters can lead release lake 16 million cubic meters (21%) 18 (25%) years. outcomes serve guiding principle optimal sustainable highly competitive fragile basins Urmia.
Язык: Английский
Процитировано
1Water, Год журнала: 2024, Номер 16(13), С. 1772 - 1772
Опубликована: Июнь 22, 2024
Simulating shallow groundwater (SGW) flow dynamics and stream–SGW interactions using numerical modeling tools is necessary to develop a mechanistic understanding of water systems improve confidence in resource management practices. A three-dimensional (3D) SGW model was developed for riparian wetland mixed forest agricultural catchment West Virginia (WV), Appalachia, USA, Modular 3D Groundwater Model (MODFLOW). The MODFLOW simulation calibrated steady (R2 = 0.98, ME −0.21, RMSE 0.77), transient state 0.97, −0.41, 1.28) validated −0.28, 1.05) observed levels from thirteen nested piezometers under states. An experimental MT3D transport scenario show the lateral NO₃-N aquifer stream cells. Relatively stable head distribution observed. In downstream reach, discharge varied 948 m3/day 907 2020, with creek seepage ranging 802 790 m3/day. Similarly, input ranged 891 978 m3/day, while 796 800 2021. upstream reaches, losing conditions were January, June, September 2020 January April 2021, gaining prevailed during other months. Thus, an approximately monthly alternating gaining–losing condition area. resulted advection–dispersion scenario, showing cumulative loss 947 g NO3-N stream. Denitrification accounted 1406 SGW, surpassing 639 nitrate study period. Additionally, particle tracking MODPATH indicated long residence time nutrients, affirming efficiency nitrogen transformation through denitrification. This among first simulate hydrologic nutrient wetlands land use Appalachian region northeastern United States. results better inform decisions efforts similar physiographic regions globally.
Язык: Английский
Процитировано
1Опубликована: Янв. 1, 2024
The paucity of research on accurate predictions saturated hydraulic conductivity (Ksat), spatiotemporal analysis nutrient concentrations relative to water source types (stream and shallow groundwater (SGW)), flow directions, land use in riparian wetlands Appalachian mixed catchments underscored the need for this study. Additionally, lack SGW simulations stream-SGW interactions using three-dimensional (3D) numerical models (i.e., MODFLOW) these further highlighted gap. Observed data including soil properties, Ksat, surface (SW) levels, concentrations, nitrate (NO3-N), nitrite (NO2-N), ammonium (NH4-N), orthophosphate (PO43-P), total nitrogen (total_N), phosphorus (total_P) were collected from four stream stage monitoring sites with a 13 co-located piezometers during January 2020 December 2021. Validation against observed Ksat values revealed significant correlation texture, particularly clay content, yet low accuracy existing pedotransfer functions (PTFs), indicating pressing calibration development site-specific PTFs. Distinct profiles between SW SGW, significantly higher (p < 0.05) total_N total_P than SW. Principal Component Analysis (PCA) Spearman Correlation elucidated relationship distributions, types, adjacent uses. Relatively stable head distribution was slight monthly fluctuations due recharge rates 3D MODFLOW simulations. downstream reach study period illustrated losing condition, while alternating gaining-losing condition upstream area. In an experimental MT3D transport scenario advection-dispersion chemical reaction, lateral NO3-N observed, lost by denitrification surpassed stream. These studies provide valuable insights into complexities dynamics land-use region northeastern United States, offering foundation informed management decisions manage ecosystems sustainably.
Язык: Английский
Процитировано
0Опубликована: Янв. 1, 2024
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Язык: Английский
Процитировано
0Опубликована: Янв. 1, 2024
Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI
Язык: Английский
Процитировано
0Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
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