Investigating of River-Aquifer Interactions using Sub-Surface Hydrological Model and Remote Sensing Inputs in an agriculturally Dominated Kosi River Basin, India.

2021 ◽  
Author(s):  
Naga Venkata Satish Laveti ◽  
Suresh A. Kartha ◽  
Subashisa Dutta
Keyword(s):  
Remote Sensing ◽  
Groundwater Recharge ◽  
River Basin ◽  
Hydrological Model ◽  
Temporal Variations ◽  
Interaction Process ◽  
Groundwater Levels ◽  
Physically Based ◽  
Spatio Temporal ◽  
Exchange Flux

<p>River-Aquifer Interaction is a natural and complex phenomenon for understanding its physical dynamic processes. These interactions highly vary with time and space and are to be investigated at river reach scale. The present study aims to understand and quantify the spatio-temporal variations of river-aquifer interaction process in Kosi river basin, India. This basin is majorly dominated with agricultural lands and irrigation requirement of the crops are mostly met by groundwater. In order to quantify the river-aquifer exchange flux at reach scale, a physically based sub-surface hydrological model has been carried for the study area. For this purpose, high resolution remotely sensed evapotranspiration data and groundwater recharge (estimated using soil water budget method method) along with other aquifer parameters were utilized for simulating the monthly groundwater levels as well as exchange flux between river and aquifer. The model results showed that simulated groundwater levels were well calibrated and validated with measured groundwater levels. Further, this calibrated groundwater flow model has been used to quantify the river-aquifer exchange flux. Based on the obtained exchange flux values, three different interaction zones were identified from upstream (Kosi barrage) to downstream (confluence point with Ganga river) in the study reach. It is observed that the river mostly loses water to the aquifer (as influent) in Zone I (80km from upstream) and the river mostly gains water from the aquifer (as effluent) in Zone III (40 km above downstream to confluence point). Whereas, the river has a combination of both losing and gaining natures in Zone II (between Zone I and III). From this study, it can be concluded that use of satellite remote sensing inputs (groundwater recharge and evapotranspiration) in the sub-surface hydrological model, facilitated to improve the assessment and understanding river-aquifer interaction process in an alluvial River basin.</p>

scholarly journals Integration of water balance models in RIVERTWIN

2006 ◽  
Vol 9 ◽  
pp. 85-91 ◽  
Author(s):  
J. Götzinger ◽  
J. Jagelke ◽  
R. Barthel ◽  
A. Bárdossy
Keyword(s):  
Water Balance ◽  
Groundwater Recharge ◽  
River Basin ◽  
Hydrological Model ◽  
Internal State ◽  
River Basin Management ◽  
State Variables ◽  
Groundwater Runoff ◽  
Groundwater Levels ◽  
River Basin Management Plans

Abstract. In the project RIVERTWIN climate, hydrologic, groundwater and water quality models are integrated in order to evaluate river basin management plans established for the implementation of the EU Water Framework Directive. In such integrated models, which try to simulate all relevant processes in a river basin realistically, modelling of the water balance plays a key role. Therefore the integration of hydrological and groundwater models requires special attention. In this case study, the hydrological model simulates discharge and daily groundwater recharge in a high spatial resolution. Using the latter as input, the groundwater model calculates groundwater levels and groundwater runoff, which is then returned to the hydrological model. Such integration on the meso-scale brings up new problems such as commensurability, verification and compatibility of internal state variables and fluxes, but also provides the possibility to analyse the underlying assumptions and simplifications. As an example of this modelling approach the simulation of groundwater recharge, groundwater levels and groundwater runoff in the Neckar catchment are discussed and the problems of the current integration concept are described.

scholarly journals Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2699 ◽  
Author(s):  
Jian Li ◽  
Liqiao Tian ◽  
Qingjun Song ◽  
Zhaohua Sun ◽  
Hongjing Yu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Temporal Variations ◽  
Lake Area ◽  
Short Term ◽  
Chl A ◽  
Spatio Temporal

Monitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.

scholarly journals Spatial pattern evaluation of a calibrated national hydrological model – a remote sensing based diagnostic approach

2017 ◽  
Author(s):  
Gorka Mendiguren ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Hydrological Model ◽  
Remote Sensing Data ◽  
Driving Mechanism ◽  
Distributed Hydrological Model ◽  
Eof Analysis ◽  
Sensing Data ◽  
Spatio Temporal

Abstract. Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two source energy balance model (TSEB) driven mainly by satellite remote sensing data. The main hypothesis of the study is that while both approaches are essentially estimates, the spatial patterns of the remote sensing based approach are explicitly driven by observed land surface temperature and therefore represent the most direct spatial pattern information of ET; enabling its use for distributed hydrological model evaluation. Ideally the hydrological model simulation and remote sensing based approach should present similar spatial patterns and driving mechanism of ET. However, the spatial comparison showed that the differences are significant and indicating insufficient spatial pattern performance of the hydrological model. The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in 6 domains that are calibrated independently from each other, as it is often the case for large scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of Leaf Area Index (LAI), root depth (RD) and Crop coefficient (Kc) for each land cover type. This zonal approach of model parametrization ignores the spatio-temporal complexity of the natural system. To overcome this limitation, the study features a modified version of the DK-Model in which LAI, RD, and KC are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatio-temporal variability and spatial consistency between the 6 domains. The effects of these changes are analyzed by using the empirical orthogonal functions (EOF) analysis to evaluate spatial patterns. The EOF-analysis shows that including remote sensing derived LAI, RD and KC in the distributed hydrological model adds spatial features found in the spatial pattern of remote sensing based ET.

scholarly journals Comparison of soil moisture fields estimated by catchment modelling and remote sensing: a case study in South Africa

2008 ◽  
Vol 12 (3) ◽  
pp. 751-767 ◽  
Author(s):  
T. Vischel ◽  
G. G. S. Pegram ◽  
S. Sinclair ◽  
W. Wagner ◽  
A. Bartsch
Keyword(s):  
South Africa ◽  
Remote Sensing ◽  
Soil Moisture ◽  
Hydrological Model ◽  
Regional Scale ◽  
Remotely Sensed ◽  
Hydrological Models ◽  
Good Correspondence ◽  
Physically Based

Abstract. The paper compares two independent approaches to estimate soil moisture at the regional scale over a 4625 km2 catchment (Liebenbergsvlei, South Africa). The first estimate is derived from a physically-based hydrological model (TOPKAPI). The second estimate is derived from the scatterometer on board the European Remote Sensing satellite (ERS). Results show a good correspondence between the modelled and remotely sensed soil moisture, particularly with respect to the soil moisture dynamic, illustrated over two selected seasons of 8 months, yielding regression R2 coefficients lying between 0.68 and 0.92. Such a close similarity between these two different, independent approaches is very promising for (i) remote sensing in general (ii) the use of hydrological models to back-calculate and disaggregate the satellite soil moisture estimate and (iii) for hydrological models to assimilate the remotely sensed soil moisture.

scholarly journals Environmental Variables of the Seti Gandaki River Basin Pokhara, Nepal

2018 ◽  
Vol 22 (2) ◽  
pp. 129-139 ◽  
Author(s):  
Kishor Kumar Pokharel ◽  
Khadga Bahadur Basnet ◽  
Trilok Chandra Majupuria ◽  
Chitra Bahadur Baniya
Keyword(s):  
Water Temperature ◽  
River Basin ◽  
Environmental Variables ◽  
Temporal Variations ◽  
Total Alkalinity ◽  
Urban Site ◽  
Water Conductivity ◽  
Free Carbon Dioxide ◽  
Spatio Temporal ◽  
Carbon Dioxide Co2

Present paper focuses on the spatio-temporal variations and correlations among the environmental variables of the Seti Gandaki River basin, Pokhara, Nepal. A total of five sites, three along the river and two in tributaries were selected for this study. Water sampling was done fortnightly for environmental variables following standard methods during July 2011 to June 2012. Mean and standard deviation of the environmental variables revealed that the depth (0.9 ± 0.3), pH (8 ± 0.4), total phosphates (PO4) (0.10 ± 0.03) and nitrates (NO3) (0.13 ± 0.04) were normally variable among the sites. But the discharge (40.00 ± 37.00), width (32.30 ± 13.00), turbidity (81.40 ± 51.00), transparency (29.10 ± 15.00), conductivity (166.00 ± 80.00), water temperature (18.00 ±4.00), dissolved oxygen (DO) (8.00 ± 2.00), free carbon dioxide (CO2) (7.00 ± 2.00) and total alkalinity (98.00 ± 22.00) varied among sites equally. Correlation coefficient between the sites and environmental variables revealed that sites were found significantly correlated with water conductivity (r2 = 0.6), DO (r2 = -0.52), and free CO2 (r2 = 0.6); depth of water with width (r2 = 0.94), discharge (r2 = 0.96), turbidity (r2 = 0.71), transparency (r2 = -0.62), water temperature (r2 = 0.60), pH (r2 = -0.52) and DO (r2 = -0.48); water temperature with pH (r2 = -0.54), DO (r2 = -0.79), free CO2 (r2 = 0.69), total alkalinity (r2 = -0.58), total PO4 (r2 = 0.54) and NO3 (r2 = 0.62), etc. The enhancement of turbidity, conductivity, free CO2, phosphates and nitrates, while, suppression of transparency, pH and DO at the urban site indicated the urban influence. Journal of Institute of Science and TechnologyVolume 22, Issue 2, January 2018, page: 129-139

The spatio-temporal variations of vegetation cover in the Yellow River Basin from 2000 to 2010

2013 ◽  
Vol 33 (24) ◽  
Author(s):  
袁丽华 YUAN Lihua ◽  
蒋卫国 JIANG Weiguo ◽  
申文明 SHEN Wenming ◽  
刘颖慧 LIU Yinghui ◽  
王文杰 WANG Wenjie ◽  
...  
Keyword(s):  
River Basin ◽  
Vegetation Cover ◽  
Yellow River ◽  
Yellow River Basin ◽  
Temporal Variations ◽  
The Yellow River ◽  
Spatio Temporal ◽  
The Yellow River Basin
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