Application of Climatic Data in Hydrologic Models
Over the past few decades, global warming and climate change have impacted the hydrologic cycle. Many models have been developed to simulate hydrologic processes. Obtaining accurate climatic data on local/meso, and global scales is essential for the realistic simulation of hydrologic processes. Howe...
Guardado en:
| Formato: | Online |
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| Lenguaje: | inglés |
| Publicado: |
2022
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| Materias: | |
| Acceso en línea: | ONIX_20220916_9783036550657_147 |
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| _version_ | 1869517781385347072 |
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| collection | Directory of Open Access Books |
| description | Over the past few decades, global warming and climate change have impacted the hydrologic cycle. Many models have been developed to simulate hydrologic processes. Obtaining accurate climatic data on local/meso, and global scales is essential for the realistic simulation of hydrologic processes. However, the limited availability of climatic data often poses a challenge to hydrologic modeling efforts. Hydrologic science is currently undergoing a revolution in which the field is being transformed by the multitude of newly available data streams. Historically, hydrologic models that have been developed to answer basic questions about the rainfall–runoff relationship, surface water, and groundwater storage/fluxes, land–atmosphere interactions, have been optimized for previously data-limited conditions. With the advent of remote sensing technologies and increased computational resources, the environment for water cycle researchers has fundamentally changed to one where there is now a flood of spatially distributed and time-dependent data. The bias in the climatic data is propagated through models and can yield estimation errors. Therefore, the bias in climatic data should be removed before their use in hydrologic models. Climatic data have been a core component of the science of hydrology. Their intrinsic role in understanding and managing water resources and developing sound water policies dictates their vital importance. This book aims to present recent advances concerning climatic data and their applications in hydrologic models. |
| format | Online |
| id | doab-20.500.12854ir-92161 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| record_format | ojs |
| spelling | doab-20.500.12854ir-921612024-04-09T23:16:00Z Application of Climatic Data in Hydrologic Models Valipour, Mohammad Bateni, Sayed M. statistical weather generator stochastic process Diyala River basin Wilks’ technique hydrological models rainfall surface runoff linear regression models curve number SCS.CN model mulching wildfire prescribed fire n/a CHIRPS GPM-IMERG rainfall data scarcity agro-hydrology Rift Valley Lake Basin hydrological research basin precipitation temperature long-term trends climate change evapotranspiration groundwater recharge thresholds seasonality spatiotemporal variations regional-scale long-term HydroBudget model cold and humid climates Quebec (Canada) tank cascade system dry zone water governance flood control traditional knowledge community participation Sri Lanka thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Over the past few decades, global warming and climate change have impacted the hydrologic cycle. Many models have been developed to simulate hydrologic processes. Obtaining accurate climatic data on local/meso, and global scales is essential for the realistic simulation of hydrologic processes. However, the limited availability of climatic data often poses a challenge to hydrologic modeling efforts. Hydrologic science is currently undergoing a revolution in which the field is being transformed by the multitude of newly available data streams. Historically, hydrologic models that have been developed to answer basic questions about the rainfall–runoff relationship, surface water, and groundwater storage/fluxes, land–atmosphere interactions, have been optimized for previously data-limited conditions. With the advent of remote sensing technologies and increased computational resources, the environment for water cycle researchers has fundamentally changed to one where there is now a flood of spatially distributed and time-dependent data. The bias in the climatic data is propagated through models and can yield estimation errors. Therefore, the bias in climatic data should be removed before their use in hydrologic models. Climatic data have been a core component of the science of hydrology. Their intrinsic role in understanding and managing water resources and developing sound water policies dictates their vital importance. This book aims to present recent advances concerning climatic data and their applications in hydrologic models. 2022-09-16T13:48:40Z 2022-09-16T13:48:40Z 2022 book ONIX_20220916_9783036550657_147 9783036550657 9783036550664 https://directory.doabooks.org/handle/20.500.12854/92161 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/6038 https://mdpi.com/books/pdfview/book/6038 10.3390/books978-3-0365-5066-4 10.3390/books978-3-0365-5066-4 MDPI - Multidisciplinary Digital Publishing Institute 9783036550657 9783036550664 120 Basel open access |
| spellingShingle | statistical weather generator stochastic process Diyala River basin Wilks’ technique hydrological models rainfall surface runoff linear regression models curve number SCS.CN model mulching wildfire prescribed fire n/a CHIRPS GPM-IMERG rainfall data scarcity agro-hydrology Rift Valley Lake Basin hydrological research basin precipitation temperature long-term trends climate change evapotranspiration groundwater recharge thresholds seasonality spatiotemporal variations regional-scale long-term HydroBudget model cold and humid climates Quebec (Canada) tank cascade system dry zone water governance flood control traditional knowledge community participation Sri Lanka thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Application of Climatic Data in Hydrologic Models |
| title | Application of Climatic Data in Hydrologic Models |
| title_full | Application of Climatic Data in Hydrologic Models |
| title_fullStr | Application of Climatic Data in Hydrologic Models |
| title_full_unstemmed | Application of Climatic Data in Hydrologic Models |
| title_short | Application of Climatic Data in Hydrologic Models |
| title_sort | application of climatic data in hydrologic models |
| topic | statistical weather generator stochastic process Diyala River basin Wilks’ technique hydrological models rainfall surface runoff linear regression models curve number SCS.CN model mulching wildfire prescribed fire n/a CHIRPS GPM-IMERG rainfall data scarcity agro-hydrology Rift Valley Lake Basin hydrological research basin precipitation temperature long-term trends climate change evapotranspiration groundwater recharge thresholds seasonality spatiotemporal variations regional-scale long-term HydroBudget model cold and humid climates Quebec (Canada) tank cascade system dry zone water governance flood control traditional knowledge community participation Sri Lanka thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | statistical weather generator stochastic process Diyala River basin Wilks’ technique hydrological models rainfall surface runoff linear regression models curve number SCS.CN model mulching wildfire prescribed fire n/a CHIRPS GPM-IMERG rainfall data scarcity agro-hydrology Rift Valley Lake Basin hydrological research basin precipitation temperature long-term trends climate change evapotranspiration groundwater recharge thresholds seasonality spatiotemporal variations regional-scale long-term HydroBudget model cold and humid climates Quebec (Canada) tank cascade system dry zone water governance flood control traditional knowledge community participation Sri Lanka thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20220916_9783036550657_147 |