Local climate change projections and impact on the surface hydrology in the Vea catchment, West Africa

Larbi, Isaac; Hountondji, Fabien C. C.; Dotse, Sam-Quarcoo; Mama, Daouda; Nyamekye, Clement; Adeyeri, Oluwafemi E.; Koubodana, Houteta Djan’na; Odoom, Peter Rock Ebo; Asare, Yaw Mensah

doi:10.2166/nh.2021.096

Cited by 15 publications

(6 citation statements)

References 52 publications

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“…Changes in river discharge result from interactions between climate change and/or land use change [1][2][3][4][5], although it is also admitted that the physical characteristics of the basin (size, slope system, type of soil, etc.) increase their sensitivity to these factors [6,7].…”

Section: Introductionmentioning

confidence: 99%

Impact of Rainfall Variability and Land Use Change on River Discharge in South Cameroon

Ebodé

Braun

Nnomo

et al. 2022

Water

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Climate change, variability and anthropogenic forcings such as land use change are the main forcings of river discharge variability. However, an understanding of their simultaneous impacts on river discharge remains limited in some parts of the world. To shed light on this issue, the objective of this article is to investigate the effects of rainfall variability and land use change on river discharge in the Nyong basin (at Olama and Mbalmayo gauging stations) and some of its sub-basins (So’o and Mefou) over the long period 1950–2018. To achieve this goal, hydro-meteorological data of the Nyong basin and sub-basins were analyzed using the Pettitt test. Likewise, land use changes in the basin and sub-basins were also analyzed using supervised classifications of Landsat satellite images of the basins at different periods (1973, 2000 and 2018). On the annual scale, rainfall has decreased statistically over the studied basins. In the large basins (Olama and Mbalmayo), this decrease in rainfall is synchronous with that of discharges, while it is concomitant with an increase in the Mefou (small basin). After the ruptures within time series identified in the annual modules, the extreme discharges (maximum and minimum) decreased in Olama; in Mbalmayo, the maximum discharges remained stable while the minimum discharges decreased. On the other hand, the maximum and minimum discharges have significantly increased in the Mefou. The stability of maximum discharges at Mbalmayo and the increase in extremes on the Mefou in a context where the precipitation that generates the discharge has decreased can be attributed to land use change. These changes are essentially marked by an increase in impervious areas and a reduction in forest cover. On the seasonal scale, the impact of precipitation in the dry season is visible on the flows of the rainy seasons that follow them on the large basins (Olama and Mbalmayo). Between the decades 1970–1990 and 2000–2010, there was respectively a significant increase, then a decrease in summer precipitation, which impacted the autumn discharges in the same direction. Conversely, between the same intervals, there was a significant decrease, then a slight increase in winter precipitation. The impact of winter precipitation on the spring discharge is more visible during the first period only (1970–1990). During the second period, winter precipitation seems to have more of an impact on the runoff for the same season. In the Mefou sub-basin, the precipitation plays an essentially amplifying role in the increase in discharge in the seasons during which they occur. Those having experienced an increase, or a maintenance of precipitation (summer and spring) recorded the most significant increases in discharges. These results could be useful for long-term planning on the demand and use of water, as well as flood management in the basins

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Section: Introductionmentioning

confidence: 99%

Impact of Rainfall Variability and Land Use Change on River Discharge in South Cameroon

Ebodé

Braun

Nnomo

et al. 2022

Water

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“…Using SDSM, daily precipitation datasets were generated at a 0.002 km resolution. The model generated dataset according to the following steps: (1) control data quality, (2) screen predictor factor, (3) calibrate and validate the model, (4) generate weather generator, and (5) generate future scenario (Larbi et al, 2021).…”

Section: Wrf Model Temperature Simulationmentioning

confidence: 99%

High-resolution downscaled climate variables spatiotemporal variation and drought projected in the Sanjiang Plain, Northeast China

Huang

Xie

et al. 2023

Preprint

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Drought is greatly impacted by climate variables, and high-resolution downscaled climate variables are valuable for precisely identifying drought characteristics. Due to Sanjiang Plain’s crucial strategic position and drastic climate changes, we analyze its spatiotemporal variation in climate variables and standardized precipitation evapotranspiration index (SPEI). Two sharing economy pathway scenarios (SSP245 and SSP585) during the early (2023–2030), middle (2050–2060), and late periods (2090–2100) are projected. The Weather Research and Forecasting (WRF) and Statistical Downscaling Model (SDSM) are used for downscaling to simulate temperature and precipitation, respectively. WRF model is driven by the bias-corrected CMIP6 dataset, the ensemble of CMIP6 daily predictor variables are applied to SDSM, which generate high-resolution downscaled data named SSP-DS scenario. The SPEI computed from precipitation and reference evapotranspiration (ET0) is adopted to identify drought characteristics. The results indicate that downscaled results accurately reflect the CMIP6 original outputs change trend, but increase ET0 and reduce precipitation. The average temperature, total ET0, total precipitation manifests an increasing trend over time, and SSP585-DS scenario increases more significantly. High radiative forcing contributes to increasing temperature and ET0. Seven stations dry and wet characteristics have no obvious spatial heterogeneity; accumulated16 to 23 (17 to 24) drought events are captured, mild drought is the most frequent and extreme drought is the least under the SSP245-DS and SSP585-DS scenario. This study predicts the spatiotemporal variation in climate variables and drought characteristics based on high-resolution downscaled data, which contributes to Sanjiang Plain management strategy against drought risk and climate change.

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“…As the application of statistical downscaling tools continues to increase, Ghana's contribution remains limited, particularly in coastal zones. Few research studies, such as [44,[69][70][71], have utilized the SDSM in Ghana. It should be noted that these studies are confined to the river catchments and basin areas (Vea Catchment, White and Black Volta Basins) of the country, to the exclusion of other equally important regions, such as the coastal zones.…”

Section: Introductionmentioning

confidence: 99%

Extreme Temperature and Rainfall Events and Future Climate Change Projections in the Coastal Savannah Agroecological Zone of Ghana

2023

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The global climate has changed, and there are concerns about the effects on both humans and the environment, necessitating more research for improved adaptation. In this study, we analyzed extreme temperature and rainfall events and projected future climate change scenarios for the coastal Savannah agroecological zone (CSAZ) of Ghana. We utilized the ETCCDI, the RClimDex software (version 1.0), the Mann–Kendall test, Sen’s slope estimator, and standardized anomalies to analyze homogeneity, trends, magnitude, and seasonal variations in temperature (Tmax and Tmin) and rainfall datasets for the zone. The SDSM was also used to downscale future climate change scenarios based on the CanESM2 (RCP 2.6, 4.5, and 8.5 scenarios) and HadCM3 (A2 and B2 scenarios) models for the zone. Model performance was evaluated using statistical methods such as R2, RMSE, and PBIAS. Results revealed more changepoints in Tmin than in Tmax and rainfall. Results again showed that the CSAZ has warmed over the last four decades. The SU25, TXn, and TN90p have increased significantly in the zone, and the opposite is the case for the TN10p and DTR. Spatially varied trends were observed for the TXx, TNx, TNn, TX10p, TX90p, and the CSDI across the zone. The decrease in RX1day, RX5day, SDII, R10, R95p, and R99p was significant in most parts of the central region compared to the Greater Accra and Volta regions, while the CDD significantly decreased in the latter two regions than in the former. The trends in CWD and PRCPTOT were insignificant throughout the zone. The overall performance of both models during calibration and validation was good and ranged from 58–99%, 0.01–1.02 °C, and 0.42–11.79 °C for R2, RMSE, and PBIAS, respectively. Tmax is expected to be the highest (1.6 °C) and lowest (−1.6 °C) across the three regions, as well as the highest (1.5 °C) and lowest (−1.6 °C) for the entire zone, according to both models. Tmin is projected to be the highest (1.4 °C) and lowest (−2.1 °C) across the three regions, as well as the highest (1.4 °C) and lowest (−2.3 °C) for the entire zone. The greatest (1.6 ℃) change in mean annual Tmax is expected to occur in the 2080s under RCP8.5, while that of the Tmin (3.2 ℃) is expected to occur in the 2050s under the same scenario. Monthly rainfall is expected to change between −98.4 and 247.7% across the three regions and −29.0 and 148.0% for the entire zone under all scenarios. The lowest (0.8%) and highest (79%) changes in mean annual rainfall are expected to occur in the 2030s and 2080s. The findings of this study could be helpful for the development of appropriate adaptation plans to safeguard the livelihoods of people in the zone.

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Local climate change projections and impact on the surface hydrology in the Vea catchment, West Africa

Cited by 15 publications

References 52 publications

Impact of Rainfall Variability and Land Use Change on River Discharge in South Cameroon

Impact of Rainfall Variability and Land Use Change on River Discharge in South Cameroon

High-resolution downscaled climate variables spatiotemporal variation and drought projected in the Sanjiang Plain, Northeast China

Extreme Temperature and Rainfall Events and Future Climate Change Projections in the Coastal Savannah Agroecological Zone of Ghana

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