Your search found 4 records
1 Maheswaran, R.; Khosa, R.; Gosain, A. K.; Lahari, S.; Sinha, S. K.; Chahar, B. R.; Dhanya, C. T.. 2016. Regional scale groundwater modelling study for Ganga River Basin. Journal of Hydrology, 541(Part B):727-741. [doi: https://doi.org/10.1016/j.jhydrol.2016.07.029]
Groundwater extraction ; Models ; Water levels ; Aquifers ; Recharge ; Forecasting ; River basins ; Tributaries ; Boundaries ; Drainage ; Pumping ; Hydrogeology ; Monsoon climate ; Alluvial land ; Land use ; Land cover ; Calibration / India / Ganga River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H047896)
(8.44 MB)
Subsurface movement of water within the alluvial formations of Ganga Basin System of North and East India, extending over an area of 1 million km2 , was simulated using Visual MODFLOW based transient numerical model. The study incorporates historical groundwater developments as recorded by various concerned agencies and also accommodates the role of some of the major tributaries of River Ganga as geo-hydrological boundaries. Geo-stratigraphic structures, along with corresponding hydrological parameters, were obtained from Central Groundwater Board, India, and used in the study which was carried out over a time horizon of 4.5 years. The model parameters were fine tuned for calibration using Parameter Estimation (PEST) simulations. Analyses of the stream aquifer interaction using Zone Budget has allowed demarcation of the losing and gaining stretches along the main stem of River Ganga as well as some of its principal tributaries. From a management perspective, and entirely consistent with general understanding, it is seen that unabated long term groundwater extraction within the study basin has induced a sharp decrease in critical dry weather base flow contributions. In view of a surge in demand for dry season irrigation water for agriculture in the area, numerical models can be a useful tool to generate not only an understanding of the underlying groundwater system but also facilitate development of basin-wide detailed impact scenarios as inputs for management and policy action.
2 Assefa, A.; Haile, Alemseged Tamiru; Dhanya, C. T.; Walker, D. W.; Gowing, J.; Parkin, G. 2021. Impact of sustainable land management on vegetation cover using remote sensing in Magera micro Watershed, Omo Gibe Basin, Ethiopia. International Journal of Applied Earth Observation and Geoinformation, 103:102495. [doi: https://doi.org/10.1016/j.jag.2021.102495]
Sustainable land management ; Normalized difference vegetation index ; Watershed management ; Remote sensing ; Satellite imagery ; Datasets ; Land cover mapping ; Hydrological factors ; Rain / Ethiopia / Omo Gibe Basin / Magera Watershed
(Location: IWMI HQ Call no: e-copy only Record No: H050722)
https://www.sciencedirect.com/science/article/pii/S0303243421002026/pdfft?md5=adc6f5caeb7b85ee841a993c82269f8c&pid=1-s2.0-S0303243421002026-main.pdf
https://vlibrary.iwmi.org/pdf/H050722.pdf
https://vlibrary.iwmi.org/pdf/H050722.pdf
(11.20 MB) (11.2 MB)
The hydrological impact of many expensive investments on watershed interventions remains unquantified due to lack of time series data. In this study, remote sensing imagery is utilized to quantify and detect vegetation cover change in Magera micro-watershed, Ethiopia, where sustainable land management interventions have been implemented. Normalized difference vegetation index (NDVI) values were retrieved for the period 2010 to 2019, which encompasses before, during and after the interventions. Mann-Kendal trend test was used to detect temporal trends in the monthly NDVI values. In addition, multiple change-point analyses were carried out using Pettitt’s, Buishand’s and Standard Normal Homogeneity (SNH) tests to detect any abrupt changes due to the watershed interventions. The possible influence of rainfall on changes in vegetation cover was investigated. A significant increasing trend (from 1.5% to 33%) was detected for dense vegetation at the expense of a significant reduction in bare land from 40.9% to 0.6% over the analysis period. An abrupt change in vegetation cover was detected in 2015 in response to the interventions. A weak and decreasing correlation was obtained between monthly rainfall magnitude and NDVI values, which indicates that the increase in vegetation cover is not from rainfall influences. The study shows that the sustainable land management has an overall positive impact on the study area. The findings of this research support the applicability of remote sensing approaches to provide useful information on the impacts of watershed intervention investments.
3 Bernhofen, M. V.; Cooper, S.; Trigg, M.; Mdee, A.; Carr, A.; Bhave, A.; Solano-Correa, Y. T.; Pencue-Fierro, E. L.; Teferi, E.; Haile, Alemseged Tamiru; Yusop, Z.; Alias, N. E.; Sa'adi, Z.; Ramzan, M. A. B.; Dhanya, C. T.; Shukla, P. 2022. The role of global data sets for riverine flood risk management at national scales. Water Resources Research, 58(4):e2021WR031555. [doi: https://doi.org/10.1029/2021WR031555]
Flooding ; Disaster risk management ; Datasets ; Rivers ; Vulnerability ; Governance / Colombia / England / Ethiopia / India / Malaysia
(Location: IWMI HQ Call no: e-copy only Record No: H051573)
https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2021WR031555
https://vlibrary.iwmi.org/pdf/H051573.pdf
https://vlibrary.iwmi.org/pdf/H051573.pdf
(3.81 MB) (3.83 MB)
Over the last two decades, several data sets have been developed to assess flood risk at the global scale. In recent years, some of these data sets have become detailed enough to be informative at national scales. The use of these data sets nationally could have enormous benefits in areas lacking existing flood risk information and allow better flood management decisions and disaster response. In this study, we evaluate the usefulness of global data for assessing flood risk in five countries: Colombia, England, Ethiopia, India, and Malaysia. National flood risk assessments are carried out for each of the five countries using six data sets of global flood hazard, seven data sets of global population, and three different methods for calculating vulnerability. We also conduct interviews with key water experts in each country to explore what capacity there is to use these global data sets nationally. We find that the data sets differ substantially at the national level, and this is reflected in the national flood risk estimates. While some global data sets could be of significant value for national flood risk management, others are either not detailed enough, or too outdated to be relevant at this scale. For the relevant global data sets to be used most effectively for national flood risk management, a country needs a functioning, institutional framework with capability to support their use and implementation.
4 Magotra, B.; Prakash, V.; Saharia, M.; Getirana, A.; Kumar, S.; Pradhan, R.; Dhanya, C. T.; Rajagopalan, B.; Singh, R. P.; Pandey, A.; Mohapatra, M. 2024. Towards an Indian land data assimilation system (ILDAS): a coupled hydrologic-hydraulic system for water balance assessments. Journal of Hydrology, 629:130604. [doi: https://doi.org/10.1016/j.jhydrol.2023.130604]
Water balance ; Assessment ; Stream flow ; Water resources ; Models ; Precipitation ; Evapotranspiration ; Soil moisture ; Water storage ; Uncertainty ; Moderate resolution imaging spectroradiometer / South Asia / Indian / Rajasthan
(Location: IWMI HQ Call no: e-copy only Record No: H052546)
(18.30 MB)
Effective management of water resources requires reliable estimates of land surface states and fluxes, including water balance components. But most land surface models run in uncoupled mode and do not produce river discharge at catchment scales to be useful for water resources management applications. Such integrated systems are also rare over India where hydrometeorological extremes have wreaked havoc on the economy and people. So, an Indian Land Data Assimilation System (ILDAS) with a coupled land surface and a hydrodynamic model has been developed and driven by multiple meteorological forcings (0.1°, daily) to estimate land surface states, channel discharge, and floodplain inundation. ILDAS benefits from an integrated framework as well as the largest suite of observation records collected over India and has been used to produce a reanalysis product for 1981–2021 using four forcing datasets, namely, Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), ECMWF’s ERA-5, and Indian Meteorological Department (IMD) gridded precipitation. We assessed the uncertainty and bias in these precipitation datasets and validated all major components of the terrestrial water balance, i.e., surface runoff, soil moisture, terrestrial water storage anomalies, evapotranspiration, and streamflow, against a combination of satellite and in situ observation datasets. Our assessment shows that ILDAS can represent the hydrological processes reasonably well over the Indian landmass with IMD precipitation showing the best relative performance. Evaluation against ESA-CCI soil moisture shows that MERRA-2 based estimates outperform the others, whereas ERA-5 performs best in simulating evapotranspiration when evaluated against MODIS ET. Evaluations against observed records show that CHIRPS-based estimates have the highest performance in reconstructing surface runoff and streamflow. Once operational, this system will be useful for supporting transboundary water management decision making in the region.
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