scholarly journals Estimating seepage flux from ephemeral stream channels using surface water and groundwater level data

2014 ◽  
Vol 50 (2) ◽  
pp. 1474-1489 ◽  
Author(s):  
Saskia L. Noorduijn ◽  
Margaret Shanafield ◽  
Mark A. Trigg ◽  
Glenn A. Harrington ◽  
Peter G. Cook ◽  
...  
Keyword(s):  
Surface Water ◽  
Groundwater Level ◽  
Stream Channels ◽  
Ephemeral Stream ◽  
Surface Water And Groundwater ◽  
Level Data

Coherent intra-annual ensemble forecasts of surface and groundwater availability

2021 ◽  
Author(s):  
David Robertson ◽  
Guobin Fu ◽  
Olga Barron ◽  
Geoff Hodgson ◽  
Andrew Schepen
Keyword(s):  
Surface Water ◽  
Water Resources ◽  
Groundwater Level ◽  
Forecast Skill ◽  
Lead Times ◽  
Ensemble Forecasts ◽  
Error Models ◽  
Groundwater Availability ◽  
Surface Water And Groundwater ◽  
Surface And Groundwater

<p>In many parts of the world, surface water and groundwater are used complementarily to supply agricultural production and to meet urban water demands. Conjunctive management of these water resources requires balancing of the different characteristics of surface water and groundwater with respect to availability, quality and cost of supply. Ensemble forecasts of surface water and groundwater availability can inform management decisions but require explicit representation of the complex processes controlling surface and groundwater interactions. While many methods and operational services exist that provide independent forecasts for surface and groundwater availability, to our knowledge no approaches for coupled forecasting have been developed yet.</p><p>In this presentation we introduce an approach that generates coupled forecasts of surface water and groundwater availability. It extends the Forecast Guided Stochastic Scenarios (FoGSS) (Bennett et al., 2016) approach to forecast groundwater level at specified locations, in addition to streamflow totals, to lead times of 12 months at monthly time steps. We adapt a conceptual hydrological model to improve predictions of streamflow and, as a by-product, groundwater level. We then apply independent error models to streamflow and groundwater level to reduce bias, update predictions using recent observations and quantify residual uncertainty. Ensemble streamflow and groundwater forecasts are generated by forcing the hydrological and error models with ensemble rainfall forecasts generated by post-processing ECMWF System 5 outputs. The skill, bias and reliability of the rainfall, streamflow and groundwater level forecasts were assessed for a case-study catchment in South-East Queensland, Australia. We find that skill of forecasts is dependent on the forecast issue month and lead time, with groundwater level forecasts displaying significant skill to lead times of 12 months, while streamflow forecast skill rarely persists beyond 3 months.  We conclude by describing opportunities to improve forecast skill and some of the challenges that may be faced in the operational delivery of water resource forecasts in real-time.</p><p>Reference</p><p>Bennett, J. C., Wang, Q. J., Li, M., Robertson, D. E., and Schepen, A.: Reliable long-range ensemble streamflow forecasts: Combining calibrated climate forecasts with a conceptual runoff model and a staged error model, Water Resources Research, 52, 8238-8259, 10.1002/2016WR019193, 2016.</p>

scholarly journals Factors influencing surface water and groundwater interaction in alluvial fan

2020 ◽  
Author(s):  
Fanao Meng ◽  
Changlai Xiao ◽  
Xiujuan Liang ◽  
Ge Wang ◽  
Ying Sun ◽  
...  
Keyword(s):  
Surface Water ◽  
River Runoff ◽  
Groundwater Level ◽  
Alluvial Fan ◽  
Water Levels ◽  
Key Factors ◽  
Groundwater Exploitation ◽  
Factors Affecting ◽  
Surface Water And Groundwater ◽  
The Relationship

Abstract In this study, the surface water balance method was used to calculate the interaction between surface water and groundwater (SGW) in the Taoer River alluvial fan in Jilin Province, China, from 1956 to 2014. The automatic linear model was used to determine the key and non-key influencing factors, and correlation analysis was performed to evaluate their relationship with one another. River runoff and groundwater level were the key factors affecting the SGW interaction, and sand–gravel exposure in the fan was more conducive to SGW interaction. There was a positive correlation between runoff and SGW interaction, and the relationship between the groundwater and surface water levels was correlated and affected by groundwater exploitation and groundwater runoff. Groundwater exploitation and evaporation and precipitation indirectly influenced the SGW interaction by affecting the groundwater level and river runoff key factors, respectively, and were considered non-key factors.

scholarly journals Characterizing groundwater and surface-water interaction using hydrograph-separation techniques and groundwater-level data throughout the Mississippi Delta, USA

2019 ◽  
Vol 27 (6) ◽  
pp. 2167-2179 ◽  
Author(s):  
Courtney D. Killian ◽  
William H. Asquith ◽  
Jeannie R. B. Barlow ◽  
Gardner C. Bent ◽  
Wade H. Kress ◽  
...  
Keyword(s):  
Surface Water ◽  
Groundwater Level ◽  
Mississippi Delta ◽  
Hydrograph Separation ◽  
Separation Techniques ◽  
Water Interaction ◽  
Level Data

Antibiotic resistance genes in surface water and groundwater from mining affected environments

2021 ◽  
Vol 772 ◽  
pp. 145516
Author(s):  
Hai-Yan Zou ◽  
Liang-Ying He ◽  
Fang-Zhou Gao ◽  
Min Zhang ◽  
Shuai Chen ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Surface Water ◽  
Resistance Genes ◽  
Antibiotic Resistance Genes ◽  
Surface Water And Groundwater
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