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  Tanzania Meteorological Agency (TMA),
University of Dodoma, Administration Block,
Department of Computer Science and intuitive education,

  1 CIVE Street, P.O Box 27, 41218 DODOMA.

  Phone +255 26 2962610
  met@meteo.go.tz

Modeling non-stationarity in extreme rainfall data and implications for climate adaptation: A case s
Masanja, Verdiana, 2024, Eng
The Southern Highlands region of Tanzania has witnessed an increased frequency of severe flash
floods.

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Modeling non-stationarity in extreme rainfall data and implications for climate adaptation: A case s - Masanja, Verdiana, 2024, Eng

Modeling non-stationarity in extreme rainfall data and implications for climate adaptation: A case s - Masanja, Verdiana, 2024, Eng

Abstract

The Southern Highlands region of Tanzania has witnessed an increased frequency of severe flash
floods.

Modeling non-stationarity in extreme rainfall data and implications for climate adaptation
Erick A. Kyojo , Silas Mirau , Sarah E. Osima , Verdiana G. Masanja, 2024, Eng
The Southern Highlands region of Tanzania has witnessed an increased frequency of severe flash
floods. This study examines rainfall data of four stations (Iringa, Mbeya, Rukwa, and Ruvuma)

Preview Read More

Modeling non-stationarity in extreme rainfall data and implications for climate adaptation - Erick A. Kyojo , Silas Mirau , Sarah E. Osima , Verdiana G. Masanja, 2024, Eng

Modeling non-stationarity in extreme rainfall data and implications for climate adaptation - Erick A. Kyojo , Silas Mirau , Sarah E. Osima , Verdiana G. Masanja, 2024, Eng

Abstract

The Southern Highlands region of Tanzania has witnessed an increased frequency of severe flash
floods. This study examines rainfall data of four stations (Iringa, Mbeya, Rukwa, and Ruvuma)
spanning 30 years (1991–2020) to investigate drivers of extreme rainfall and non-stationarity
behavior. The Generalized Extreme Value (GEV) model, commonly used in hydrological studies,
assumes constant distribution parameters, which may not be true due to climate variability,
potentially leading to bias in extreme quantile estimation

Modeling non-stationarity in extreme rainfall data and implications for climate adaptation
Erick A. Kyojo , Silas Mirau , Sarah E. Osima , Verdiana G. Masanja, 2024, Eng
The Southern Highlands region of Tanzania has witnessed an increased frequency of severe flash
floods. This study examines rainfall data of four stations (Iringa, Mbeya, Rukwa, and Ruvuma)

Preview Read More

Modeling non-stationarity in extreme rainfall data and implications for climate adaptation - Erick A. Kyojo , Silas Mirau , Sarah E. Osima , Verdiana G. Masanja, 2024, Eng

Modeling non-stationarity in extreme rainfall data and implications for climate adaptation - Erick A. Kyojo , Silas Mirau , Sarah E. Osima , Verdiana G. Masanja, 2024, Eng

Abstract

The Southern Highlands region of Tanzania has witnessed an increased frequency of severe flash
floods. This study examines rainfall data of four stations (Iringa, Mbeya, Rukwa, and Ruvuma)
spanning 30 years (1991–2020) to investigate drivers of extreme rainfall and non-stationarity
behavior. The Generalized Extreme Value (GEV) model, commonly used in hydrological studies,
assumes constant distribution parameters, which may not be true due to climate variability,
potentially leading to bias in extreme quantile estimation.

MWONGOZO WA KILIMO BORA CHA UYOGA KUKABILIANA NA ATHARI ZA MABADILIKO HALI YA HEWA NA TABIANCHI, TAN
Dk. S. Augustino, 2014, Sw
Inakadiriwa kuwa zaidi ya watu millioni 20 nchini Tanzania hususan kutoka katika jamii zinazozunguka raslimali za misitu hutegemea Mazao si Timbao kwa ajili ya kuboresha hali ya maisha yao na kipat

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MWONGOZO WA KILIMO BORA CHA UYOGA KUKABILIANA NA ATHARI ZA MABADILIKO HALI YA HEWA NA TABIANCHI, TAN - Dk. S. Augustino, 2014, Sw

MWONGOZO WA KILIMO BORA CHA UYOGA KUKABILIANA NA ATHARI ZA MABADILIKO HALI YA HEWA NA TABIANCHI, TAN - Dk. S. Augustino, 2014, Sw

Abstract

Inakadiriwa kuwa zaidi ya watu millioni 20 nchini Tanzania hususan kutoka katika jamii zinazozunguka raslimali za misitu hutegemea Mazao si Timbao kwa ajili ya kuboresha hali ya maisha yao na kipato kazi. Licha ya utegemezi huo