Quantifying the probabilistic divergences related to time-space scales for inferences in water resource management
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DOI: 10.1016/j.agwat.2019.03.004
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References listed on IDEAS
- Sohoulande Djebou, Dagbegnon C. & Singh, Vijay P., 2015. "Retrieving vegetation growth patterns from soil moisture, precipitation and temperature using maximum entropy," Ecological Modelling, Elsevier, vol. 309, pages 10-21.
- Slobodan P. Simonovic, 2017. "Bringing Future Climatic Change into Water Resources Management Practice Today," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 2933-2950, August.
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- Sohoulande, Clement D.D. & Stone, Kenneth & Szogi, Ariel & Bauer, Phil, 2019. "An investigation of seasonal precipitation patterns for rainfed agriculture in the Southeastern region of the United States," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
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Keywords
Time-space variability; Scaling; Kernel density modelling; Kullback–Leibler divergence; Water resources management;All these keywords.
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