Hydrological projections under climate change in the near future by RegCM4 in Southern Africa using a large-scale hydrological model

Li, Lü; Diallo, Ismaïla; Xu, Chong‐Yu; Stordal, Frøde

doi:10.1016/j.jhydrol.2015.05.028

Cited by 62 publications

(44 citation statements)

References 73 publications

(100 reference statements)

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“…The catchments selected for investigating the climatic effect on hydrological processes in this study are the source regions of Yangtze River and Yellow River (Figure b). With catchment areas of 13.77 × 10 4 and 12.19 × 10 4 km 2 , respectively (L. Li, Diallo, et al, ; X. P. Li, Wang, et al, ; T. Yang et al, ), the source regions of Yangtze River and Yellow River located in a transitional region of alpine semiarid climatic districts are dominated by high mountains and well‐developed hydrological networks (G. X. Wang, Bai, Li, & Hu, ). In general, the natural environment of both source regions is very harsh and fragile with dry and cold climates and low and sparse vegetation.…”

Section: Study Area Methods and Datamentioning

confidence: 99%

“…However, for impact assessment on hydrological regimes, RCMs cannot provide sufficient outputs, which is especially of interest by the hydrologists (Graham, Hagemann, Jaun, & Beniston, ; C. Y. Xu, Widén, & Halldin, ). In applications, the outputs from RCMs are therefore used as input to force or initialize a hydrological model to address this issue (L. Li, Diallo, Xu, & Stordal, ; X. P. Li, Wang, Chen, Yang, & Wang, ). Currently, RCMs are widely used in studies of climatic effect on hydrology all over the world (Arnell, ; Graham et al, ; Gosling, ; L. Li, Diallo, et al, ; X. P. Li, Wang, et al, ).…”

Section: Introductionmentioning

confidence: 99%

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Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Lü

Wang

Shao

et al. 2018

Hydrological Processes

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Understanding climate change impacts on hydrological regime and assessing future water supplies are essential to effective water resources management and planning, which is particularly true for the Tibetan Plateau (TP), one of the most vulnerable areas to climate change. In this study, future climate change in the TP was projected for 2041–2060 by a high‐resolution regional climate model, RegCM4, under 3 representative concentration pathways (RCPs): 2.6, 4.5, and 8.5. Response of all key hydrological elements, that is, evapotranspiration, surface run‐off, baseflow, and snowmelt, to future climate in 2 typical catchments, the source regions of Yellow and Yangtze rivers, was further investigated by the variable infiltration capacity microscale hydrological model incorporated with a 2‐layer energy balance snow model and a frozen soil/permafrost algorithm at a 0.25°×0.25° spatial scale. The results reveal that (a) spatial patterns of precipitation and temperature from RegCM4 agree fairly well with the data from China Meteorological Forcing Dataset, indicating that RegCM4 well reproduces historical climatic information and thus is reliable to support future projection; (b) precipitation increase by 0–70% and temperature rise by 1–4 °C would occur in the TP under 3 RCPs. A clear south‐eastern–north‐western spatial increasing gradient in precipitation would be seen. Besides, under RCP8.5, the peak increase in temperature would approach to 4 °C in spring and autumn in the east of the TP; (c) evapotranspiration would increase by 10–60% in 2 source regions due to the temperature rise, surface run‐off and baseflow in higher elevation region would experience larger increase dominantly due to the precipitation increase, and streamflow would display general increases by more than 3% and 5% in the source regions of Yellow and Yangtze rivers, respectively; (d) snowmelt contributes 11.1% and 16.2% to total run‐off in the source regions of Yellow and Yangtze rivers, respectively, during the baseline period. In the source region of Yangtze River, snowmelt run‐off would become more important with increase of 17.5% and 18.3%, respectively, under RCP2.6 and RCP4.5 but decrease of 15.0% under RCP8.5.

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Section: Study Area Methods and Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Lü

Wang

Shao

et al. 2018

Hydrological Processes

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“…Southern African water resources are regarded as being highly affected by seasonal variability, a fact that is likely to be exacerbated by climate change (Kusangaya et al, 2014). Zhu and Ringler (2010) estimated a decrease in Limpopo streamflow by 2030 due to climate change, which is contradictory to studies that found increases of precipitation (Tadross et al, 2005) and runoff (Li et al, 2015) in parts of southern Africa, including vast parts of the Limpopo Basin.…”

Section: Introductionmentioning

confidence: 92%

Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

Seibert

Merz

Apel

2017

Hydrol. Earth Syst. Sci.

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Abstract. The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study.1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated).2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Niño and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42 % explained variance), whereas teleconnections exert a stronger influence in large catchments.3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships.4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics (ROCs). Seasonal statistical forecasts in the Limpopo show promising results, and thus it is recommended to employ them as complementary to existing forecasts in order to strengthen preparedness for droughts.

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“…A list of the physical options available in RegCM4 is provided in Giorgi et al (2012). Based on previous studies over different African sub-regions (e.g., Mariotti et al 2014;Bamba et al 2015;Li et al 2015;Diallo et al 2015Diallo et al , 2016Diallo et al , 2018N'Datchoh et al 2018;Tall et al 2017) as well as a series of preliminary experiments, the following options were selected in this study: the radiation scheme from the NCAR Community Climate Model version 3 (CCM3; Kiehl et al 1996), the nonlocal vertical diffusion scheme of Holstag et al (1990) to represent the boundary layer processes, the sub-grid explicit moisture (SUBEX) resolvable scale precipitation scheme of Pal et al (2000), the ocean flux scheme of Zeng et al (1998), and the cumulus convection scheme of Grell et al (1994) with the Fritch-Chappell closure assumption (FC; Fritsch and Chappell 1980) to represent the convective precipitation.…”

Section: Model Descriptionmentioning

confidence: 99%

Effect of the African greenbelt position on West African summer climate: a regional climate modeling study

Bamba

Diallo

N’Datchoh

et al. 2018

Theor Appl Climatol

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This modeling study is conducted to examine the potential impact of the reforestation (greenbelt) location (either in Sahel or in Guinean region) on West African summer climate system. To this end, three simulations using the regional climate model RegCM4 driven by ERA-Interim reanalysis were performed at 50 km horizontal resolution over a West African domain for the period 2000-2011. The first experiment, namely the control (CTRL), uses the standard vegetation cover, while the two others incorporate throughout the model integration, a zonal reforestation band of evergreen broadleaf over different locations: (i) over a 13°N-17°N band latitudes in a Sahel-Sahara region (experiment hereafter referred to as GB15N) and (ii) between 8. 5°N-11.5°N in the Guinea Coast region (experiment hereafter referred to as GB10N). A comparison of the CTRL experiment with observation reveals a faithful reproduction of the mean boreal and summer seasonal precipitation pattern, though substantial dry/wet biases remain, especially in the Atlantic Ocean. In addition, the seasonal cycle over sub-regions matches satisfactory the observed pattern. The GB15N reforestation leads to a precipitation increase in the range of 2-4 mm/day over the forested areas, whereas in the GB10N reforestation, precipitation increase is weaker and not necessarily located in the forested areas. Temperature cooling is observed over the reforested area and may be explained by a decrease of ground heat flux related to a reduction of the surface albedo.

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Hydrological projections under climate change in the near future by RegCM4 in Southern Africa using a large-scale hydrological model

Cited by 62 publications

References 73 publications

Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

Effect of the African greenbelt position on West African summer climate: a regional climate modeling study

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