Your search found 3 records
1 Mizutani, M.; Rath, B.; Mohanty, B. P.; Kalita, P. K. 1991. Estimation of effective rainfall in wet season paddy: Observational studies on water requirement of lowland rice in Thailand (II) Irrigation Engineering and Rural Planning, 21:15-28.
Irrigation practices ; Irrigation requirements ; Irrigated farming ; Water balance ; Water requirements ; Simulation models ; Rain ; Paddy fields ; Rice / Thailand
(Location: IWMI-HQ Call no: P 2919 Record No: H013371)
2 Mohanty, B. P.; Tim, U. S.; Anderson, C. E.; Woestman, T. 1994. Impacts of agricultural drainage well closure on crop production: A watershed case study. Water Resources Bulletin, 30(4):687-703.
Watershed management ; Case studies ; Wells ; GIS ; Drainage ; Groundwater ; Models ; Crop yield / USA / Iowa
(Location: IWMI-HQ Call no: PER Record No: H015677)
3 Jena, S.; Panda, R. K.; Ramadas, M.; Mohanty, B. P.; Samantaray, A. K.; Pattanaik, S. K. 2021. Characterization of groundwater variability using hydrological, geological, and climatic factors in data-scarce tropical savanna region of India. Journal of Hydrology: Regional Studies, 37:100887. [doi: https://doi.org/10.1016/j.ejrh.2021.100887]
Groundwater ; Hydrogeology ; Climatic factors ; Land use ; Land cover ; Savannas ; Aquifers ; River basins ; Rain ; Geomorphology ; Topography / India / Odisha
(Location: IWMI HQ Call no: e-copy only Record No: H050697)
https://www.sciencedirect.com/science/article/pii/S2214581821001166/pdfft?md5=5803ba8adba3ab6a18c6c2bf86c59a78&pid=1-s2.0-S2214581821001166-main.pdf
https://vlibrary.iwmi.org/pdf/H050697.pdf
https://vlibrary.iwmi.org/pdf/H050697.pdf
(12.60 MB) (12.6 MB)
Study Region: State of Odisha, a data-scarce tropical savanna region in eastern India.
Study Focus: This study evaluated the temporal variability in depth to groundwater (DTW) in the study region with heavily stressed aquifers during 1995–2015 using the modified Mann Kendall test. Subsequently, Shannon’s entropy assessed spatial variability in DTW and determined the dominant Hydrological, Geological, and Climatological (HGC) factor regulating the observed spatio-temporal variability taking land use/ land cover (LULC), geomorphology, lithology, topography, and rainfall as HGC factors.
New Hydrological Insights: The overall and seasonal trend analysis revealed that the study region possessed both rising and declining trends with a slightly higher percentage of wells with a rising trend. The spatial distribution of trends and the associated magnitude accentuated the unforeseen groundwater temporal variability and higher-order susceptibility of DTW to rising and declining trends. The marginal entropy revealed the higher-order spatial variability associated with deeper DTW and vice versa. Evaluation of the HGC factors revealed that LULC could explain the maximum variability in the DTW as a dominant HGC factor. It was found that the impact of LULC features on DTW variability is not straightforward, necessitating impact assessment studies in the location with significant to highly significant trends. This formulated approach can immensely contribute to the planning and management in attaining groundwater sustainability in data-scarce regions.
Study Focus: This study evaluated the temporal variability in depth to groundwater (DTW) in the study region with heavily stressed aquifers during 1995–2015 using the modified Mann Kendall test. Subsequently, Shannon’s entropy assessed spatial variability in DTW and determined the dominant Hydrological, Geological, and Climatological (HGC) factor regulating the observed spatio-temporal variability taking land use/ land cover (LULC), geomorphology, lithology, topography, and rainfall as HGC factors.
New Hydrological Insights: The overall and seasonal trend analysis revealed that the study region possessed both rising and declining trends with a slightly higher percentage of wells with a rising trend. The spatial distribution of trends and the associated magnitude accentuated the unforeseen groundwater temporal variability and higher-order susceptibility of DTW to rising and declining trends. The marginal entropy revealed the higher-order spatial variability associated with deeper DTW and vice versa. Evaluation of the HGC factors revealed that LULC could explain the maximum variability in the DTW as a dominant HGC factor. It was found that the impact of LULC features on DTW variability is not straightforward, necessitating impact assessment studies in the location with significant to highly significant trends. This formulated approach can immensely contribute to the planning and management in attaining groundwater sustainability in data-scarce regions.
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