CCL

Összesen 3 találat.
#/oldal:
Részletezés:
Rendezés:

1.

001-es BibID:BIBFORM123409
Első szerző:Chakilu, Gashaw Gismu
Cím:The patterns of potential evapotranspiration and seasonal aridity under the change in climate in the upper Blue Nile basin, Ethiopia / Gashaw Gismu Chakilu, Szegedi Sándor, Túri Zoltán, Kwanele Phinzi
Dátum:2024
ISSN:0022-1694
Megjegyzések:Evapotranspiration is one of the determinant components of the hydrological process, highly influenced by climate change due to the increase in atmospheric temperature at global and regional scales. This study was designed to evaluate the extent to which climate change affects the Potential Evapotranspiration (PET) and the consequent Aridity Index (AI) in the high-emission scenario of Representative Concentration Pathways (RCPs) in the Gilgel Abay, Ribb, Gumara, and Megech watersheds using six Global Climate Models in the 2011-2040, 2041-2070, and 2071-2100 relative to the 1971-2000 (baseline period). The average PET is simulated using the Soil Water Assessment Tool (SWAT) model. Penman-Monteith and Hargreaves methods were used in the computation of PET using the water balance technique, and the Hargreaves method was found more efficient in calibration and validation processes. The Aridity Index (AI) of watersheds is calculated using the ratio of precipitation and potential evapotranspiration. The study revealed that the change in annual average PET is showing an increasing pattern in the three time periods, and the highest rate of changes in Megech, Gilgel Abay, Ribb, and Gumara, watersheds are 16.66%, 15.53%, 14.68%, and 13.46%, respectively in the 2071-2100 time period. Seasonally, the highest rate of change in PET is 20.37% (September), 19.29% (April), 17.46% (March), and 17.02% (March) in the Megech, Gilgel Abay, Ribb, and Gumara, respectively. Similarly, the seasonal highest change in Aridity Index (AI) is also likely to be observed in the 2071-2100 in which in the dry season, it accounts -0.303 (March), -0.299 (March), -0.285 (April), and -0.276 (April) in the Ribb, Gumara, Gilgel Abay, and Megech, respectively, whereas in the rainy season, the change is 0.263, 0.258, 0.238, and 0.211 in the Gilgel Abay, Gumara, Ribb, and Megech, respectively. In general, due to the rising atmospheric temperature, the amount of moisture during dry seasons in the headwater catchments of the upper Blue Nile basin is expected to deplete in the 21st century. Therefore, it is highly recommended to use different climate change adaptation mechanisms including adopting suitable physical and biological water conservation techniques to enhance the amount of water stored in the subsurface and joining the groundwater during the rainy season.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
climate change
potential evapotranspiration
aridity index
Upper Blue Nile
Ethiopia
Megjelenés:Journal of Hydrology. - 641 (2024), p. 1-12. -
További szerzők:Szegedi Sándor (1970-) (klimatológus) Túri Zoltán (1980-) (geográfus) Phinzi, Kwanele (1989-)
Internet cím:Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
Borító:

2.

001-es BibID:BIBFORM102813
035-os BibID:(cikkazonosító)101175 (WoS)000854013600003 (Scopus)85134573015
Első szerző:Chakilu, Gashaw Gismu
Cím:Climate change and the response of streamflow of watersheds under the high emission scenario in Lake Tana sub-basin, upper Blue Nile basin, Ethiopia / Gashaw Gismu Chakilu, Szegedi Sándor, Túri Zoltán, Kwanele Phinzi
Dátum:2022
ISSN:2214-5818
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Journal of Hydrology-Regional Studies. - 42 (2022), p. 1-16. -
További szerzők:Szegedi Sándor (1970-) (klimatológus) Túri Zoltán (1980-) (geográfus) Phinzi, Kwanele (1989-)
Internet cím:Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
Borító:

3.

001-es BibID:BIBFORM115323
035-os BibID:(WoS)001086503900002 (Scopus)85174061140
Első szerző:Phinzi, Kwanele
Cím:Understanding the role of training sample size in the uncertainty of high-resolution LULC mapping using random forest / Kwanele Phinzi, Njoya Silas Ngetar, Quoc Bao Pham, Gashaw Gismu Chakilu, Szilárd Szabó
Dátum:2023
ISSN:1865-0473 1865-0481
Megjegyzések:High-resolution sensors onboard satellites are generally reputed for rapidly producing land-use/land-cover (LULC) maps with improved spatial detail. However, such maps are subject to uncertainties due to several factors, including the training sample size. We investigated the effects of different training sample sizes (from 1000 to 12,000 pixels) on LULC classification accuracy using the random forest (RF) classifier. Then, we analyzed classification uncertainties by determining the median and the interquartile range (IQR) of the overall accuracy (OA) values through repeated k-fold cross-validation. Results showed that increasing training pixels significantly improved OA while minimizing model uncertainty. Specifically, larger training samples, ranging from 9000 to 12,000 pixels, exhibited narrower IQRs than smaller samples (1000-2000 pixels). Furthermore, there was a significant variation (Chi2 = 85.073; df = 11; p < 0.001) and a significant trend (J-T = 4641, p < 0.001) in OA values across various training sample sizes. Although larger training samples generally yielded high accuracies, this trend was not always consistent, as the lowest accuracy did not necessarily correspond to the smallest training sample. Nevertheless, models using 9000-11,000 pixels were effective (OA > 96%) and provided an accurate visual representation of LULC. Our findings emphasize the importance of selecting an appropriate training sample size to reduce uncertainties in high-resolution LULC classification.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
High-resolution sensor
LULC
Training sample size
Random forest
Classification uncertainty
Megjelenés:Earth Science Informatics. - 16 : 4 (2023), p. 3667-3677. -
További szerzők:Ngetar Njoya Silas Pham, Quoc Bao Chakilu, Gashaw Gismu Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:K138079
Egyéb
K138503
Egyéb
Internet cím:Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Rekordok letöltése1