Regional climate projections for impact assessment studies in East Africa

Gebrechorkos, Solomon H.; Hülsmann, Stephan; Bernhofer, Christian

doi:10.1088/1748-9326/ab055a

Cited by 80 publications

(54 citation statements)

References 55 publications

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“…The impacts of climate change such as rising temperatures and unpredictable precipitation intensity and patterns have become undeniably unequivocal in East Africa [1][2][3], impacting the fragile ecosystems such as wetlands in the region. In addition, human and environmental stressors such as land use changes associated with rapid urbanization and uncoordinated expansion of intensive agricultural production in these wetlands negatively impair their water availability, quality and other ecosystem services and functioning [2,4,5]. The negative impacts associated with climate and land use change are also compounded by other factors, notably exacerbating poverty and high population pressure, which is anticipated to increase demand for food and water in the future [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…Most parts of eastern Africa have experienced frequent droughts and a decline in total rainfall during the long rains [26,27], although GCM projections show wetter conditions in the future [27], a contradiction which has been referred to as the East African paradox by Rowell et al [26]. In fact, the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) reports large levels of uncertainty in the temporal and spatial variability of precipitation over East Africa in the future [5]. According to Endris et al [25], the GCM and RCM data project a decrease in seasonal rainfall over most parts of East Africa during the June to September (JJAS) and March to May (MAM) seasons.…”

Section: Introductionmentioning

confidence: 99%

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Impact of Climate and Land Use/Land Cover Change on the Water Resources of a Tropical Inland Valley Catchment in Uganda, East Africa

Gabiri

Diekkrüger

Näschen

et al. 2020

Climate

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The impact of climate and land use/land cover (LULC) change continues to threaten water resources availability for the agriculturally used inland valley wetlands and their catchments in East Africa. This study assessed climate and LULC change impacts on the hydrological processes of a tropical headwater inland valley catchment in Uganda. The hydrological model Soil and Water Assessment Tool (SWAT) was applied to analyze climate and LULC change impacts on the hydrological processes. An ensemble of six regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment for two Representative Concentration Pathways (RCPs), RCP4.5 and RCP8.5, were used for climate change assessment for historical (1976–2005) and future climate (2021–2050). Four LULC scenarios defined as exploitation, total conservation, slope conservation, and protection of headwater catchment were considered. The results indicate an increase in precipitation by 7.4% and 21.8% of the annual averages in the future under RCP4.5 and RCP8.5, respectively. Future wet conditions are more pronounced in the short rainy season than in the long rainy season. Flooding intensity is likely to increase during the rainy season with low flows more pronounced in the dry season. Increases in future annual averages of water yield (29.0% and 42.7% under RCP4.5 and RCP8.5, respectively) and surface runoff (37.6% and 51.8% under RCP4.5 and RCP8.5, respectively) relative to the historical simulations are projected. LULC and climate change individually will cause changes in the inland valley hydrological processes, but more pronounced changes are expected if the drivers are combined, although LULC changes will have a dominant influence. Adoption of total conservation, slope conservation and protection of headwater catchment LULC scenarios will significantly reduce climate change impacts on water resources in the inland valley. Thus, if sustainable climate-smart management practices are adopted, the availability of water resources for human consumption and agricultural production will increase.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of Climate and Land Use/Land Cover Change on the Water Resources of a Tropical Inland Valley Catchment in Uganda, East Africa

Gabiri

Diekkrüger

Näschen

et al. 2020

Climate

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“…In studies like the one performed by Nakaegawa [40] or Ospina [41], river discharge in the north of Colombia was analyzed using direct output from a GCM as a hydrometeorological input of the model, and similar studies could be performed in the four selected water districts at the east of Colombia considering the results of the current study in order to use the historical records from these areas to develop a regional climate downscaling or water budget analysis. The spatial and temporal data resolutions show acceptable characteristics for the purpose of performing reliable posterior analysis such as some developed through statistical regional downscaling on other areas with similar characteristics [31,32,[42][43][44], or water budget analysis [45][46][47][48][49]. The use of a dynamical downscaling method could also provide more accurate results, but this approach demands much more intensive computational resources and require large volumes of data which are not available for the studied regions, thus, using a statistical downscaling technique is recommended as a first approach.…”

Section: Discussionmentioning

confidence: 99%

“…Downscaling using stochastic and transfer function methods is performed by modifying parameters using weather generators and developing a statistical relationship between predictands and predictors, respectively. The input data for the SD model must be carefully analyzed since the statistical relationship between the predictors and predictands is the more important aspect in statistical models [31].…”

Section: Regional Downscalingmentioning

confidence: 99%

Assessment of Regional and Historical Climate Records for a Water Budget Approach in Eastern Colombia

Molina

Bernhofer

2019

Water

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Regions located on the eastern side of Colombia are vulnerable to climate change due to the high diversity of fauna and flora located there, the potentially direct impact on agricultural activities, as well as the pressure on water resources. Limited research and work have been conducted to accurately create a description of the climate of these specific regions. The characteristics of the available records, which is valuable information, together with complementary data can be used to simulate the impacts of climate change and the effects it has on the water cycle. A description of the climate for the eastern region of Colombia was made and historical daily records from 669 hydrometeorological stations were considered in order to analyze the robustness and spatial distribution of the data. According to the available data, four of the water districts that compose the eastern region of the country were selected to show both a representative analysis of the climate variability and a consistency analysis using a cross-correlation procedure. A high percentage of missing values was found in the available records; however, with regards to the climatological analysis for the period from 1980 to 2015, 40% of missing values or less seems to be a good threshold for the datasets to be used. Temperature records show monthly small variations and a decreasing average rate from lower to higher elevations, i.e., 5 • C every 1000 m. Precipitation shows different patterns according to the region with monomodal and bimodal patterns. Correlations between datasets of the same region are positive and a significant correlation is obtained with temperature for stations at similar elevations or those located close to each other, and low correlations of precipitation are found. These data records are considered a good source of input data which could be used to perform further analysis such as a climate downscaling procedure, as well as a potential water budget approach for the four studied regions.

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“…High performance of CHIRPS has been proven in areas where station data are not included [13,86]. In addition, the product has been used in many evaluation studies [87,88] and recommended to support hydrological forecasts and trends analysis, for instance, as proved in an Ethiopian case study [89,90] and other studies that use CHIRPS as input in hydro climate modeling [58,90]. Table 10 below shows the results of CHIRPS performance in several previous studies.…”

Section: Statistical Estimatorsmentioning

confidence: 99%

Evaluation the Performance of Several Gridded Precipitation Products over the Highland Region of Yemen for Water Resources Management

et al. 2020

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Management of water resources under climate change is one of the most challenging tasks in many arid and semiarid regions. A major challenge in countries, such as Yemen, is the lack of sufficient and long-term climate data required to drive hydrological models for better management of water resources. In this study, we evaluated the accuracy of accessible satellite and reanalysis-based precipitation products against observed data from Al Mahwit governorate (highland region, Yemen) during 1998–2007. Here, we evaluated the accuracy of the Climate Hazards Group Infrared Precipitation with Station (CHIRPS) data, National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Tropical Rainfall Measuring Mission (TRMM 3B42), Unified Gauge-Based Analysis of Global Daily Precipitation (CPC), and European Atmospheric Reanalysis (ERA-5). The evaluation was performed on daily, monthly, and annual time steps by directly comparing the data from each single station with the data from the nearest grid box for each product. At a daily timescale, CHIRPS captures the daily rainfall characteristics best, such as the number of wet days, with average deviation from wet durations around 11.53%. TRMM 3B42 is the second-best performing product for a daily estimate with an average deviation of around 34.7%. However, CFSR (85.3%) and PERSIANN-CDR (103%) and ERA-5 (−81.13%) show an overestimation and underestimation of wet days and do not reflect rainfall variability of the study area. Moreover, CHIRPS is the most accurate gridded product on a monthly basis with high correlation and lower bias. The average monthly correlation between the observed and CHIRPS, TRMM 3B42, PERSIANN-CDR, CPC, ERA-5, and CFSR is 0.78, 0.56, 0.53, 0.15, 0.20, and 0.51, respectively. The average monthly bias is −2.9, −5.25, 7.35, −25.29, −24.96, and 16.68 mm for CHIRPS, TRMM 3B42, PERSIANN-CDR, CPC, ERA-5, and CFSR, respectively. CHIRPS displays the spatial distribution of annual rainfall pattern well with percent bias (Pbias) of around −8.68% at the five validation points, whereas TRMM 3B42, PERSIANN-CDR, and CFSR show a deviation of greater than 15.30, 22.90, and 66.21%, respectively. CPC and ERA-5 show Pbias of about −88.6% from observed data. Overall, in absence of better data, CHIRPS data can be used for hydrological and climate change studies on the highland region of Yemen where precipitation is often episodical and measurement records are spatially and temporally limited.

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Regional climate projections for impact assessment studies in East Africa

Cited by 80 publications

References 55 publications

Impact of Climate and Land Use/Land Cover Change on the Water Resources of a Tropical Inland Valley Catchment in Uganda, East Africa

Impact of Climate and Land Use/Land Cover Change on the Water Resources of a Tropical Inland Valley Catchment in Uganda, East Africa

Assessment of Regional and Historical Climate Records for a Water Budget Approach in Eastern Colombia

Evaluation the Performance of Several Gridded Precipitation Products over the Highland Region of Yemen for Water Resources Management

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