Your search found 33 records
(Location: IWMI HQ Call no: e-copy only Record No: H051141)
(5.74 MB) (5.74 MB)
Climate change knowledge can inform regional and local adaptation decisions. However, estimates of future climate are uncertain and methods for assessing uncertainties typically rely on the results of climate model simulations, which are constrained by the quality of assumptions used in model experiments and the limitations of available models. To strengthen scientific knowledge for climate services and climate change adaptation decisions, we explore the use of structured expert elicitation to assess future regional climate change. Using the Lower Yangtze region in China as a case study, we elicit judgements from six experts on future changes in temperature and precipitation as well as uncertainty sources, and compare it with climate model outputs from the Couple Model Intercomparison Project phase 5 (CMIP5). We find high consensus amongst experts that the Lower Yangtze region will be warmer in the coming decades, albeit with differences in the magnitude of change. There is less consensus about the direction and magnitude of future precipitation change. Compared with CMIP5 climate model outputs, experts provide similar or narrower uncertainty ranges for temperature change and very different uncertainty ranges for precipitation. Experts considered additional factors (e.g. model credibility, observations, theory and paleo-climatic evidence) and uncertainties not usually represented in conventional modelling approaches. We argue that, in context of regional climate information provision, expert-elicited judgements can characterise less predictable, or less explored, elements of the climate system and expert-elicited reasoning provides additional information and knowledge that is absent from modelling approaches. We discuss the value in bringing together multiple lines of evidence, arguing that expert elicited information can complement model information to strengthen regional climate change knowledge and help in building dialogue between climate experts and regional stakeholders, as part of a more complete climate service.
2 Miller, J.; Taylor, C.; Guichard, F.; Peyrille, P.; Vischel, T.; Fowe, T.; Panthou, G.; Visman, E.; Bologo, M.; Traore, K.; Coulibaly, G.; Chapelon, N.; Beucher, F.; Rowell, D. P.; Parker, D. J. 2022. High-impact weather and urban flooding in the West African Sahel – a multidisciplinary case study of the 2009 event in Ouagadougou. Weather and Climate Extremes, 36:100462. [doi: https://doi.org/10.1016/j.wace.2022.100462]
(Location: IWMI HQ Call no: e-copy only Record No: H051203)
(7.32 MB) (7.32 MB)
On September 1st 2009 an extreme high-impact weather event occurred in Burkina Faso that had significant impacts upon the capital city Ouagadougou and its inhabitants. Subsequent reporting and research has however not focused on the contributing socio-economic and hydrological factors and the role of global warming and climatic change remains uncertain. This reflects a paucity of evidence attributing such extreme weather events to climate change for the West Africa region and limits the knowledge base for urban planning to climate-related risks which pose serious threats. This case study provides a holistic assessment of the most extreme urban hydrometeorological event recorded in the West African Sahel, that links synoptic conditions to climate change and through to hydrological impacts on vulnerable urban populations. The intention is to inform regional decision-makers on climate change and flood-generating high-impact weather events at the urban scale and to bridge the gap between what scientists understand as useful and decision-makers view as useable at the city scale by providing interdisciplinary answers to key questions raised by local stakeholders.
Such an approach was shown to foster enhanced dialogue and engagement with stakeholders, while also providing a focus for communicating science at variable time- and spatial scales and between disciplines to improve understanding of how global processes have localised consequences. This reveals that Ouagadougou remains vulnerable to climate change and that such extreme weather events will become more frequent. But it is also demonstrated the complexity of attributing extreme events at such localised ‘urban’ scales to atmospheric phenomena affected by global climate change. Regional climate models are evolving and becoming more able to represent such extreme weather phenomena at suitable scales, enabling improved representation of climate-driven changes on such events, improving the ability for short-range forecasts in the future. Frameworks for managing flood risks however remain weak and under-resourced and there is limited capacity to manage flood risk from such events, particularly when rapid urbanisation amplifies vulnerability concerns. Recommendations are made to improve flood-resilience to future storms.
(Location: IWMI HQ Call no: e-copy only Record No: H051238)
(1.12 MB) (1.12 MB)
Climate change impact studies that evaluated the biases of climate models’ simulations showed the presence of large systematic errors in their outputs. However, many studies continue to arbitrarily select bias correction methods for error reduction. This work evaluated the implications of bias correction methods on the projections of climate change impact on streamflow of the Gidabo sub-basin, Ethiopia. Climate outputs from four global climate model and regional climate model (GCM–RCM) combinations for the representative concentration pathway (RCP4.5) scenario were used. Five bias correction methods were used to reduce the systematic errors of the simulated rainfall data. The future changes in rainfall pattern, evapotranspiration, and streamflow were analyzed by using their relative percentage difference between the projected and the baseline period. The distribution mapping method provided better results in mean and extreme rainfall cases. This is also reflected in streamflow projections, as the daily interquartile range value indicates the lowest variability of the projected streamflow. The wet season streamflow will likely decrease in the future, whereas the short rainy season streamflow will increase. Our findings show that climate models and bias correction methods considerably limit the magnitude of future projections of streamflow. However, similar research should be conducted in other catchments to extend the conclusions of this study.
(Location: IWMI HQ Call no: e-copy only Record No: H051243)
(2.55 MB)
This study assesses bias error of rainfall from climate models and related error propagation effects to simulated streamflow in the Gidabo sub-basin, Ethiopia. Rainfall is obtained from a combination of four global and regional climate models (GCM-RCMs), and streamflow is simulated by means of the Hydrologiska Byråns Vattenbalansavdelning (HBV-96) rainfall-runoff model. Five bias correction methods were tested to reduce the rainfall bias. To assess the effects of rainfall bias error propagation, percent bias (PBIAS), difference in coefficient of variation (CV), and 10th and 90th percentile indicators were applied. Findings indicate that the bias of the uncorrected rainfall caused large errors in simulated streamflow. All five bias correction methods improved the HBV-96 model performance in terms of capturing the observed streamflow. Overall, the findings of this study indicate that the magnitude of the error propagation varies subject to the selected performance indicator, bias correction method and climate model.
(Location: IWMI HQ Call no: e-copy only Record No: H051220)
(1.85 MB) (1.85 MB)
This research aims at establishing an integrated modelling framework to assess the impact of climate change on water supply and demand across an arid area in the western Haouz plain in Morocco. Five general circulation models (GCMs) are used to evaluate the availability of future water resources under Representative Concentration Pathways (RCP4.5 and RCP8.5 emission scenarios). The projected crop water demand and irrigation water demand were analysed using the Aquacrop software, taking into account the impact of climate change on both reference evapotranspiration and crop cycle lengths. The future water balance is simulated by means of the Water Evaluation And Planning (WEAP) tool, including several socio-economic and land use scenarios under RCP4.5 and RCP8.5 scenarios. The results reveal an important decrease in net precipitation with an average of -36.2% and -50.5% under RCP4.5 and RCP8.5 scenarios, respectively. In terms of water balance, the ‘business as usual’ scenario would lead to an increasing unmet water demand of about +22% in the 2050 horizon and to an increased depletion of the water table that could reach 2 m/year. Changing water management and use practices remains the only solution to ensure sustainable water use and deal with the projected water scarcity.
(Location: IWMI HQ Call no: e-copy only Record No: H051323)
(3.50 MB) (3.50 MB)
To understand the potential impacts of projected climate change on the vulnerable agriculture in Central Asia (CA), six agroclimatic indicators are calculated based on the 9-km-resolution dynamical downscaled results of three different global climate models from Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and their changes in the near-term future (2031–50) are assessed relative to the reference period (1986–2005). The quantile mapping (QM) method is applied to correct the model data before calculating the indicators. Results show the QM method largely reduces the biases in all the indicators. Growing season length (GSL, day), summer days (SU, day), warm spell duration index (WSDI, day), and tropical nights (TR, day) are projected to significantly increase over CA, and frost days (FD, day) are projected to decrease. However, changes in biologically effective degree days (BEDD, °C) are spatially heterogeneous. The high-resolution projection dataset of agroclimatic indicators over CA can serve as a scientific basis for assessing the future risks to local agriculture from climate change and will be beneficial in planning adaption and mitigation actions for food security in this region.
(Location: IWMI HQ Call no: e-copy only Record No: H051379)
(13.70 MB) (13.7 MB)
The projected climate change substantially impacts agricultural productivity and global food security. The cropping system models (CSM) can help estimate the effects of the changing climate on current and future crop production. The current study evaluated the impact of a projected climate change under shared socioeconomic pathways (SSPs) scenarios (SSP2-4.5 and SSP5-8.5) on the grain yield of winter wheat in the North China Plain by adopting the CSM-DSSAT CERES-Wheat model. The model was calibrated and evaluated using observed data of winter wheat experiments from 2015 to 2017 in which nitrogen fertigation was applied to various growth stages of winter wheat. Under the near-term (2021–2040), mid-term (2041–2060), and long-term (2081–2100) SSP2-4.5 and SSP5-8.5 scenarios, the future climate projections were based on five global climate models (GCMs) of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The GCMs projected an increase in grain yield with increasing temperature and precipitation in the near-term, mid-term, and long-term projections. In the mid-term, 13% more winter wheat grain yield is predicted under 1.3 C, and a 33 mm increase in temperature and precipitation, respectively, compared with the baseline period (1995–2014). The increasing CO2 concentration trends projected an increase in average grain yield from 4 to 6%, 4 to 14%, and 2 to 34% in the near-term, mid-term, and long-term projections, respectively, compared to the baseline. The adaptive strategies were also analyzed, including three irrigation levels (200, 260, and 320 mm), three nitrogen fertilizer rates (275, 330, and 385 kg ha-1 ), and four sowing times (September 13, September 23, October 3, and October 13). An adaptive strategy experiments indicated that sowing winter wheat on October 3 (traditional planting time) and applying 275 kg ha-1 nitrogen fertilizer and 260 mm irrigation water could positively affect the grain yield in the North China Plain. These findings are beneficial in decision making to adopt and implement the best management practices to mitigate future climate change impacts on wheat grain yields.
(Location: IWMI HQ Call no: e-copy only Record No: H051618)
(1.55 MB) (1.55 MB)
This study aims to assess the impact of climate change on the water balance component of the Katar and Meki watersheds of the Central Rift Valley Lakes Basin, Ethiopia. The semi-distributed soil and water assessment tool hydrological model and multiple regional climate model outputs were used to assess climate change impacts on water balance components and stream flow. Future climate scenarios were developed under a representative concentration pathway (RCP 4.5 and 8.5) for the 2040s (2021–2050) and 2070s (2051–2080). The study found that future annual and seasonal rainfall will show increasing and decreasing trends but that they are statistically insignificant. Furthermore, future temperatures show a significant increase in the subbasins. For the applied scenarios, an increasing and decreasing trend of future rainfall and increased temperatures would decrease the water yield by 4.9–15.3% at the Katar subbasin and 6.7–7.4% at the Meki subbasin. Furthermore, annual water yields will increase in the range of 0.38–57.1% and 6.57–49.9% for the Katar and Meki subbasins, respectively. The findings of this study will help basin planners, policymakers, and water resource managers develop appropriate adaptation strategies to mitigate the negative effects of climate change in the rift-bound lake system.
9 Chen, J.; Shi, X.; Gu, L.; Wu, G.; Su, T.; Wang, H.-M.; Kim, J.-S.; Zhang, L.; Xiong, L. 2023. Impacts of climate warming on global floods and their implication to current flood defense standards. Journal of Hydrology, 618:129236. (Online first) [doi: https://doi.org/10.1016/j.jhydrol.2023.129236]
(Location: IWMI HQ Call no: e-copy only Record No: H051699)
(10.30 MB)
Floods usually threaten human lives and cause serious economic losses, which can be more severe with global warming. Therefore, it is a salient challenge to find out how global flood characteristic changes and whether current flood protection standards will face more pressures. This study aims to characterize changes in global floods and explicit flood defense pressures in warming climates of 1.5–3.0 °C above pre-industrial levels by running four well-calibrated lumped hydrological models using bias-corrected Global Climate Model (GCM) simulations for 9045 watersheds worldwide. The results show that global warming from 1.5 to 3.0 °C has increasingly dominated all continents, with amplification effects on changes of flood frequency and magnitude. Southeast Eurasia, Africa, and South America are hotspots of changes for significant proportions of watersheds with larger flood patterns and greater changing extents than others. For example, for the 3.0 °C warming period under the combination of shared socioeconomic pathway 2 and representative concentration pathway 4.5 (SSP245) scenario, the regionally averaged 50-year flood magnitude will increase by 25.6 %, 30.6 %, and 16.4 % for these regions, respectively. The increases in occurrence and magnitude indicate that current flood protection standards will face increasing pressures in future warming climates. The design-level flood frequency is projected to increase for about 47 %, 55 %, 70 %, and 74 % of watersheds in 1.5, 2.0, 2.5, and 3.0 °C warming periods under the SSP245 scenario. However, large uncertainty are observed for the change of flood characteristics dominated by GCMs and their interactions with SSP scenarios and hydrological models. This study implies that the current flood defense standards should be enhanced and climate adaptation and mitigation strategies should be proposed to cope the change of future flood.
(Location: IWMI HQ Call no: e-copy only Record No: H051758)
(8.11 MB) (8.11 MB)
Climate change is affecting the agriculture, water, and energy sectors in East Africa and the impact is projected to increase in the future. To allow adaptation and mitigation of the impacts, we assessed the changes in climate and their impacts on hydrology and hydrological extremes in East Africa. We used outputs from seven CMIP-6 Global Climate Models (GCMs) and 1981–2010 is used as a reference period. The output from GCMs are statistically downscaled using the Bias Correction-Constructed Analogs with Quantile mapping reordering method to drive a high-resolution hydrological model. The Variable Infiltration Capacity and vector-based routing models are used to simulate runoff and streamflow across 68,300 river reaches in East Africa. The results show an increase in annual precipitation (up to 35%) in Ethiopia, Uganda, and Kenya and a decrease (up to 4.5%) in Southern Tanzania in the 2050s (2041–2070) and 2080s (2071–2100). During the long rainy season (March–May), precipitation is projected to be higher (up to 43%) than the reference period in Southern Ethiopia, Kenya, and Uganda but lower (up to -20%) in Tanzania. Large parts of Kenya, Uganda, Tanzania, and Southern Ethiopia show an increase in precipitation (up to 38%) during the short rainy season (October–December). Temperature and evapotranspiration will continue to increase in the future. Further, annual and seasonal streamflow and hydrological extremes (droughts and floods) are projected to increase in large parts of the region throughout the 21st century calling for site-specific adaptation.
11 Rizwan, M.; Li, X.; Chen, Y.; Anjum, L.; Hamid, S.; Yamin, M.; Chauhdary, J. N.; Shahid, M. A.; Mehmood, Q. 2023. Simulating future flood risks under climate change in the source region of the Indus River. Journal of Flood Risk Management, 16(1):e12857. [doi: https://doi.org/10.1111/jfr3.12857]
(Location: IWMI HQ Call no: e-copy only Record No: H051719)
(7.52 MB) (7.52 MB)
Pakistan experiences extreme flood events almost every year during the monsoon season. Recently, flood events have become more disastrous as their frequency and magnitude have increased due to climate change. This situation is further worsened due to the limited capacity of existing water reservoirs and their ability to absorb and mitigate peak floods. Thus, the simulation of stream flows using projected data from climate models is essential to assess flood events and proper water resource management in the country. This study investigates the future floods (in near future and far future periods) using the integrated flood analysis system (IFAS) model under the RCP2.6, RCP4.5, and RCP8.5 climate change scenarios. Downscaled and bias corrected climatic data of six general circulation models and their ensemble were used in this study. The IFAS model simulated the stream flow efficiently (R2 = 0.86–0.93 and Nash–Sutcliffe efficiency = 0.72–0.92) in the Jhelum River basin (JRB), Kabul River basin (KRB), and upper Indus River basin (UIRB) during the calibration and validation periods. The simulation results of the model showed significant impact of projected climate change on stream flows that will cause the mean monthly stream flow in the JRB to be lower, while that of the KRB and UIRB to be higher than that of the historical period. The highest flow months are expected to shift from May–June (Jhelum basin) and June–July (Kabul basin) to April–May with no changes in the UIRB. Higher frequencies of low to medium floods are projected in the KRB and UIRB, while the JRB expects fewer flood events. Based on the results from the IFAS model, it is concluded that stream flow in the study area will increase with several flood events.
12 Alaminie, A.; Amarnath, Giriraj; Padhee, Suman; Ghosh, Surajit; Tilahun, S.; Mekonnen, M.; Assefa, G.; Seid, Abdulkarim; Zimale, F.; Jury, M. 2023. Application of advanced Wflow_sbm Model with the CMIP6 climate projection for flood prediction in the data-scarce: Lake-Tana Basin, Ethiopia [Abstract only]. Paper presented at the European Geosciences Union (EGU) General Assembly 2023, Vienna, Austria and Online, 24-28 April 2023. 1p. [doi: https://doi.org/10.5194/egusphere-egu23-1113]
(Location: IWMI HQ Call no: e-copy only Record No: H051891)
(0.28 MB) (289 KB)
(Location: IWMI HQ Call no: e-copy only Record No: H051868)
(0.82 MB) (840 KB)
Climate change is believed to have led to changes in global patterns. This study evaluated the hydrological responses to climate change in the Deme watershed using the Soil and Water Assessment Tool (SWAT) for two consecutive periods of 2031–2050 and 2051–2070. Climate variables were downscaled from RACMO22T, under RCP4.5 and RCP8.5 scenarios from CORDEX-Africa. Distribution mapping and variance scaling methods were used for bias correction of precipitation and temperatures, respectively, and for further analysis. The SWAT model was calibrated (and validated) for the 1989–2000 (2001–2010) period, and the hydrological model showed a reasonably good agreement. The result shows that the rainfall and streamflow show a decreasing signal in the wet season. The maximum projected change in annual temperature, PET, and ET was 2.15 °C, 10.89, and 9.24%, respectively, in the far future period under the RCP8.5 scenario. These incremental changes have an impact on declining annual rainfall and streamflow up to 27.6 and 26.2%, respectively, under the RCP8.5 scenario in 2031–2050. The subsequent results were the maximum decline of surface runoff by 15.10%, groundwater by 14.78%, and total water yield by 26.10% in 2031–2050 under the RCP8.5 scenario. Thus, the concerned body integrates its duties with climate change.
(Location: IWMI HQ Call no: e-copy only Record No: H052016)
(22.40 MB) (22.4 MB)
The effects of climate change (CC) have intensified in Ghana, especially in the Greater Accra region over the last two decades. CC assessment under the new IPCC scenarios and consistent local station data is limited. Consequently, CC assessment is becoming difficult in data-scarce regions in Ghana. This study utilizes six different Regional Climate Models under the 6th IPCC Report’s Shared Socioeconomic Pathway scenarios (SSPs) of the CMIP6, which were bias-corrected with CMhyd over Greater Accra using ground station and PUGMF reanalysis data. The study reveals a reduction and potential shift in the intensity of precipitation in the region under the SSPs. Maximum temperature is expected to increase by 0.81–1.45 C, 0.84–1.54 C, 0.96–1.70 C and 0.98–1.73 C, while minimum temperature would likely increase by 1.33–2.02 C, 1.49–2.22 C, 1.71–4.75 C and 1.75–4.83 C under SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5 scenarios, respectively. Thus, temperature will likely increase, especially at night in the near future. Rising temperatures and changes in precipitation have impacts on all strata of society, from agricultural production to power generation and beyond. These findings can help inform Ghanaian policymaking on Sustainable Development Goals 11 and 13 as well as nationally determined contributions within the Paris Agreement.
15 Siabi, E. K.; Phuong, D. N. D.; Kabobah, A. T.; Akpoti, Komlavi; Anornu, G.; Incoom, A. B. M.; Nyantakyi, E. K.; Yeboah, K. A.; Siabi, S. E.; Vuu, C.; Domfeh, M. K.; Mortey, E. M.; Wemegah, C. S.; Kudjoe, F.; Opoku, P. D.; Asare, A.; Mensah, S. K.; Donkor, P.; Opoku, E. K.; Ouattara, Z. A.; Obeng-Ahenkora, N. K.; Adusu, D.; Quansah, A. 2023. Projections and impact assessment of the local climate change conditions of the Black Volta Basin of Ghana based on the Statistical DownScaling Model. Journal of Water and Climate Change, 14(2):494-515. [doi: https://doi.org/10.2166/wcc.2023.352]
(Location: IWMI HQ Call no: e-copy only Record No: H052017)
(1.27 MB) (1.27 MB)
The uncertainties and biases associated with Global Climate Models (GCMs) ascend from global to regional and local scales which delimits the applicability and suitability of GCMs in site-specific impact assessment research. The study downscaled two GCMs to evaluate effects of climate change (CC) in the Black Volta Basin (BVB) using Statistical DownScaling Model (SDSM) and 40-year ground station data. The study employed Taylor diagrams, dimensionless, dimensioned, and goodness of fit statistics to evaluate model performance. SDSM produced good performance in downscaling daily precipitation, maximum and minimum temperature in the basin. Future projections of precipitation by HadCM3 and CanESM2 indicated decreasing trend as revealed by the delta statistics and ITA plots. Both models projected near- to far-future increases in temperature and decreases in precipitation by 2.05-23.89, 5.41–46.35, and 5.84–35.33% in the near, mid, and far future respectively. Therefore, BVB is expected to become hotter and drier by 2100. As such, climate actions to combat detrimental effects on the BVB must be revamped since the basin hosts one of the largest hydropower dams in Ghana. The study is expected to support the integration of CC mitigation into local, national, and international policies, and support knowledge and capacity building to meet CC challenges.
(Location: IWMI HQ Call no: e-copy only Record No: H052035)
(0.95 MB)
Model-derived climate projections have been used by decision-makers for climate change impact assessment, adaptation, and vulnerability studies at large scale. However, they are reported to have significant bias against observed data. The accuracy of dynamically downscaled data depends on the large-scale forcings; however, they still have some systematic errors, so it requires further bias correction. Before using these data for further studies, they need to be processed for performance evaluation. This review article provides current understanding in the field of analyzing global climate projections. It includes studies from the multi-criteria decision-making approaches along with its pros/cons to the performance evaluation of climate models. Moreover, this article discusses several bias correction approaches, multi-model ensemble approaches, and their applications for climate change studies.
(Location: IWMI HQ Call no: e-copy only Record No: H052102)
(1.52 MB) (1.52 MB)
This study aimed to compare the performance of six regional climate models (RCMs) in simulating observed and projecting future climate in the Savannah zone of Ghana, in order to find suitable methods to improve the accuracy of climate models in the region. The study found that the accuracy of both individual RCMs and their ensemble mean improved with bias correction, but the performance of individual RCMs was dependent on location. The projected change in annual precipitation indicated a general decline in rainfall with variations based on the RCM and location. Projections under representative concentration pathway (RCP) 8.5 were larger than those under RCP 4.5. The changes in mean temperature recorded were 1 °C for the 2020s for both RCPs, 1–4 °C for the 2050s under both RCPs, and 1– 4 °C under RCP 4.5, and from 2 to 8 °C for the 2080s. These findings will aid farmers and governments in the West African subregion in making informed decisions and planning cost-effective climate adaptation strategies to reduce the impact of climate change on the ecosystem. The study highlights the importance of accurate climate projections to reduce vulnerability to climate change and the need to improve climate models in projecting climate in the West African subregion.
(Location: IWMI HQ Call no: e-copy only Record No: H052158)
(5.27 MB) (5.27 MB)
Climate change strongly influences the available water resources in a watershed due to direct linkage of atmospheric driving forces and changes in watershed hydrological processes. Understanding how these climatic changes affect watershed hydrology is essential for human society and environmental processes. Coupled Model Intercomparison Project phase 6 (CMIP6) dataset of three GCM’s (BCC-CSM2-MR, INM-CM5-0, and MPI-ESM1-2-HR) with resolution of 100 km has been analyzed to examine the projected changes in temperature and precipitation over the Astore catchment during 2020–2070. Bias correction method was used to reduce errors. In this study, statistical significance of trends was performed by using the Man- Kendall test. Sen’s estimator determined the magnitude of the trend on both seasonal and annual scales at Rama Rattu and Astore stations. MPI-ESM1-2-HR showed better results with coefficient of determination (COD) ranging from 0.70–0.74 for precipitation and 0.90–0.92 for maximum and minimum temperature at Astore, Rama, and Rattu followed by INM-CM5-0 and BCC-CSM2-MR. University of British Columbia Watershed model was used to attain the future hydrological series and to analyze the hydrological response of Astore River Basin to climate change. Results revealed that by the end of the 2070s, average annual precipitation is projected to increase up to 26.55% under the SSP1–2.6, 6.91% under SSP2–4.5, and decrease up to 21.62% under the SSP5–8.5. Precipitation also showed considerable variability during summer and winter. The projected temperature showed an increasing trend that may cause melting of glaciers. The projected increase in temperature ranges from - 0.66°C to 0.50°C, 0.9°C to 1.5°C and 1.18°C to 2°C under the scenarios of SSP1–2.6, SSP2–4.5 and SSP5–8.5, respectively. Simulated streamflows presented a slight increase by all scenarios. Maximum streamflow was generated under SSP5–8.5 followed by SSP2–4.5 and SSP1–2.6. The snowmelt and groundwater contributions to streamflow have decreased whereas rainfall and glacier melt components have increased on the other hand. The projected streamflows (2020–2070) compared to the control period (1990–2014) showed a reduction of 3%–11%, 2%–9%, and 1%–7% by SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively. The results revealed detailed insights into the performance of three GCMs, which can serve as a blueprint for regional policymaking and be expanded upon to establish adaption measures.
(Location: IWMI HQ Call no: e-copy only Record No: H052162)
(1.79 MB) (1.79 MB)
Ethiopia is highly susceptible to the effects of climate change and variability. This study evaluated the performances of 37 CMIP6 models against a gridded rainfall product of Ethiopia known as Enhancing National Climate Services (ENACTS) in simulating the observed rainfall from 1981 to 2014. Taylor Skill Score was used for ranking the performance of individual models for mean monthly, June–September, and February–May seasonal rainfall. Comprehensive rating metrics (RM) were used to derive the overall ranks of the models. Results show that the performances of the models were not consistent in reproducing rainfall distributions at different statistical metrics and timeframes. More than 20 models simulated the largest dry bias on high topographic and rainfall-receiving areas of the country during the June–September season. The RM-based overall ranks of CMIP6 models showed that GFDL-CM4 is the best-performing model followed by GFDL-ESM4, NorESM2-MM, and CESM2 in simulating rainfall over Ethiopia. The ensemble of these four Global Climate Models showed the best performance in representing the spatiotemporal patterns of the observed rainfall relative to the ensembles of all models. Generally, this study highlighted the existence of dry bias in climate model projections for Ethiopia, which requires bias adjustment of the models, for impact assessment.
(Location: IWMI HQ Call no: e-copy only Record No: H052224)
(10.80 MB) (10.8 MB)
Sustainable water management requires evidence-based information on the current and future states of water resources. This study presents a comprehensive modelling framework that integrates the fully distributed mesoscale Hydrologic Model (mHM) and climate change scenarios with the Water Accounting Plus (WA+) tool to anticipate future water resource challenges and provide mitigation measures in the transboundary Volta River basin (VRB) in West Africa. The mHM model is forced with a large ensemble of climate change projection data from CORDEX-Africa. Outputs from mHM are used as inputs to the WA+ framework to report on water flows and consumption over the historical baseline period 1991–2020 and the near-term future 2021–2050 at the basin scale, and also across spatial domains including four climatic zones, four sub-basins and six riparian countries. The long-term multi-model ensemble mean of the net inflow to the basin is found to be 419 km3 /year with an inter-annual variability of 11% and is projected to slightly increase in the near-term future (2021–2050). However, evaporation consumes most of the net inflow, with only 8% remaining as runoff. About 4 km3 /year of water is currently used for man-made activities. Only 45% of the available water is beneficially consumed, with the agricultural sector representing 34% of the beneficial water consumption. Water availability is projected to increase in the future due to the increase in rainfall, along with higher inter-model and inter-annual variabilities, thereby highlighting the need for adaptation strategies. These findings and the proposed climate-resilient land and water management strategies can help optimize the water-energy-food-ecosystem nexus and support evidence-based decisions and policy-making for sustainable water management in the VRB.
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