Future changes in rainy seasons in the Upper Blue Nile Basin: Impacts on agriculture and water resources

Having a robust drought monitoring system for Ethiopia is crucial to mitigate the adverse impacts of droughts. Yet, such monitoring system still lacks in Ethiopia, and in the Upper Blue Nile (UBN) basin in particular. Several drought indices exist to monitor drought, however, these indices are unable, individually, to provide concise information on the occurrence of meteorological, agricultural and hydrological droughts. A combined drought index (CDI) using several meteorological, agricultural and hydrological drought indices can indicate the occurrence of all drought types, and can provide information that facilitates the drought management decision-making process. This thesis proposes an impact-based combined drought index (CDI) and a regression prediction model of crop yield anomalies for the UBN basin. The impact-based CDI is defined as a drought index that optimally combines the information embedded in other drought indices for monitoring a certain impact of drought, i.e. crop yield for the UBN. The developed CDI and the regression model have shown to be effective in indicating historic drought events in UBN basin. The impact-based CDI could potentially be used in the future development of drought monitoring in the UBN basin and support decision making in order to mitigate adverse drought impacts.

Diurnal rainfall variability over the Upper Blue Nile Basin: A remote sensing based approach

The present study aimed to analyze the long-term trends and variability of rainfall in the Upper Blue Nile (UBN) basin in Ethiopia using Climate Hazards Group Infrared Precipitation with Stations (CHIRPS-v2) rainfall product from 1981 to 2018. A pixel-based rainfall variability and trend analysis was made at the annual, seasonal, and monthly temporal scales. The coefficient of variation (CV) was applied to compute the rainfall variability. The trends for each pixel were analyzed using Mann–Kendall (MK) trend test, while the Theil-Sen slope was used to estimate the magnitude of the trend. Results indicated that monthly and seasonal rainfall variabilities are high with the CV up to 140% and 70%, respectively. Annual rainfall variability was found to be low with CV ranging from 6 to 18%. The annual rainfall anomaly analysis, on the other hand, indicated that there are variations in the amount of rainfall received at different years and parts of the basin. It captured the spatial distributions of below- and above-average rainfall periods and its associated drought and flood events, respectively, observed in the basin. In general, the MK monotonic trend analysis for the annual, summer, spring, and autumn rainfall over the entire basin showed an average increasing trend at a rate of 2.48 mm year−1,1.16 mm year−1, 0.92 mm year−1, and 0.67 mm year−1, respectively. In contrast, the rainfall average trend during the winter season (− 0.15 mm year−1) indicated a decreasing trend. The consistency of per-pixel trends with previous studies, based on rain gauge observations, demonstrates the robustness of the trends. Furthermore, the completely raster-based analysis made in this study has provided essential information regarding the spatial variability and trends of rainfall in the basin, which was not satisfactorily captured by the conventional systems due to the larger inter-station distance between rain gauges. Thus, this could be a valuable addition to the existing knowledge of rainfall characteristics in the UBN basin.

Changes in land use and land cover (LULC) and climate increasingly influence flood occurrences in the Gumara watershed, located in the Upper Blue Nile (UBN) basin of Ethiopia. This study assesses how these factors impact return period-based peak floods, flood source areas, and future high-flow extremes. Merged rainfall data (1981–2019) and ensemble means of four CMIP5 and four CMIP6 models were used for historical (1981–2005), near-future (2031–2055), and far-future (2056–2080) periods under representative concentration pathways (RCP4.5 and RCP8.5) and shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5). Historical LULC data for the years 1985, 2000, 2010, and 2019 and projected LULC data under business-as-usual (BAU) and governance (GOV) scenarios for the years 2035 and 2065 were used along with rainfall data to analyze flood peaks. Flood simulation was performed using a calibrated Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) model. The unit flood response (UFR) approach ranked eight subwatersheds (W1–W8) by their contribution to peak flood magnitude at the main outlet, while flow duration curves (FDCs) of annual maximum (AM) flow series were used to analyze changes in high-flow extremes. For the observation period, maximum peak flood values of 211.7, 278.5, 359.5, 416.7, and 452.7 m3/s were estimated for 5-, 10-, 25-, 50-, and 100-year return periods, respectively, under the 2019 LULC condition. During this period, subwatersheds W4 and W6 were identified as major flood contributors with high flood index values. These findings highlight the need to prioritize these subwatersheds for targeted interventions to mitigate downstream flooding. In the future period, the highest flow is expected under the SSP5-8.5 (2056–2080) climate scenario combined with the BAU-2065 land use scenario. These findings underscore the importance of strategic land management and climate adaptation measures to reduce future flood risks. The methodology developed in this study, particularly the application of RF-MERGE data in flood studies, offers valuable insights into the existing knowledge base on flood modeling.

A numerical framework to advance agricultural water management under hydrological stress conditions in a data scarce environment

Climate change is likely to have severe effects on water availability in Ethiopia. The aim of the present study was to assess the impact of climate change on the Gilgel Abay River, Upper Blue Nile Basin. The Statistical Downscaling Tool (SDSM) was used to downscale the HadCM3 (Hadley centre Climate Model 3) Global Circulation Model (GCM) scenario data into finer scale resolution. The Soil and Water Assessment Tool (SWAT) was set up, calibrated, and validated. SDSM downscaled climate outputs were used as an input to the SWAT model. The climate projection analysis was done by dividing the period 2010-2100 into three time windows with each 30 years of data. The period 1990-2001 was taken as the baseline period against which comparison was made. Results showed that annual mean precipitation may decrease in the first 30-year period but increase in the following two 30-year periods. The decrease in mean monthly precipitation may be as much as about -30% during 2010-2040 but the increase may be more than +30% in 2070-2100. The impact of climate change may cause a decrease in mean monthly flow volume between -40% to -50% during 2010-2040 but may increase by more than the double during 2070-2100. Climate change appears to have negligible effect on low flow conditions of the river. Seasonal mean flow volume, however, may increase by more than the double and +30% to +40% for the Belg (small rainy season) and Kiremit (main rainy season) periods, respectively. Overall, it appears that climate change will result in an annual increase in flow volume for the Gilgel Abay River. The increase in flow is likely to have considerable importance for local small scale irrigation activities. Moreover, it will help harnessing a significant amount of water for ongoing dam projects in the Gilgel Abay River Basin.

Accurately forecasting the weekly seasonal streamflow of the Upper Blue Nile basin (UBNB) in Ethiopia is essential for managing large-scale water projects of Nile basinwide countries. A wavelet-based, artificial neural network calibrated by genetic algorithm (ANN–GA) model and a statistical disaggregation algorithm were integrated to forecast weekly streamflow of the UBNB. The July to October (JASO) streamflow of the El Diem station of UBNB shows strong interannual oscillations prior to the 1920s and after 1990s. Two ANN-GA models were developed to forecast the UBNB JASO streamflow, the first one using the February to May (FMAM) seasonal sea surface temperature (SST) of the global oceans as predictors to directly forecast JASO streamflow, while the second, a hybrid model, is developed to forecast JASO streamflow from two sets of predictors, which consist of FMAM SST and the July to September (JJAS) seasonal rainfall previously forecasted by the wavelet-based, ANN-GA also driven by FMAM SST as pred...

Climate change plays a pivotal role in the hydrological dynamics of tributaries in the upper Blue Nile basin. The understanding of the change in climate and its impact on water resource is of paramount importance to sustainable water resources management. This study was designed to reveal the extent to which the climate is being changed and its impacts on stream flow of the Gumara watershed under the Representative Concentration Pathway (RCP) climate change scenarios. The study considered the RCP 2.6, RCP 4.5, and RCP 8.5 scenarios using the second-generation Canadian Earth System Model (CanESM2). The Statistical Downscaling Model (SDSM) was used for calibration and projection of future climatic data of the study area. Soil and Water Assessment Tool (SWAT) model was used for simulation of the future stream flow of the watershed. Results showed that the average temperature will be increasing by 0.84 °C, 2.6 °C, and 4.1 °C in the end of this century under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios, respectively. The change in monthly rainfall amount showed a fluctuating trend in all scenarios but the overall annual rainfall amount is projected to increase by 8.6%, 5.2%, and 7.3% in RCP 2.6, RCP 4.5, and RCP 8.5, respectively. The change in stream flow of Gumara watershed under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios showed increasing trend in monthly average values in some months and years, but a decreasing trend was also observed in some years of the studied period. Overall, this study revealed that, due to climate change, the stream flow of the watershed is found to be increasing by 4.06%, 3.26%, and 3.67%under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios, respectively.

ABSTRACTChanges in patterns of accumulated rainfall, as well as the rainy season onset, cessation and duration, can impact the availability of water resources and sectors such as agriculture, affecting the livelihoods of the population. The knowledge of these changes is crucial for regions driven by strong precipitation variability such as the Andean countries. Therefore, the aim of this work is to determine the present and future spatio‐temporal patterns of the onset, cessation and duration of the rainy season in Peru. For this purpose, we analysed in a first step the present variability and trends in 11 homogeneous regions using data from 377 ground stations for the period 1981–2019. The results showed significant trends (1981–2019) of earlier onset and increased duration only in the Southern Peruvian Amazon (Madre de Dios River basin). Furthermore, the accumulated rainfall has significant trends of increases in North East Andes, Northern and Southern Amazon. In a second step, we assessed future changes of the rainy season from an ensemble of statistically downscaled CMIP6 climate scenarios. A two‐tailed Student t‐test was used to evaluate the significance of changes. Two future time slices (2031–2060 and 2071–2100) relative to the reference period (1981–2010) were analysed. Future changes of the rainy season showed significant delays in the onset for the Central East Andes, South West Andes and Amazon regions in the period 2071–2100. Likewise, the rainy season duration presents future significant reductions in regions of the central and southern Andes under the SSP2‐4.5 scenario. Moreover, the accumulated precipitation is projected to increase significantly in the Pacific slope and Andes regions, mainly under the SSP5‐8.5 scenario. These findings are particularly important for sectors like agriculture, energy and water resources management.

Tailoring the surface energy balance algorithm for land-improved (SEBALI) model using high-resolution land/use land cover for monitoring actual evapotranspiration

Responses of soil erosion and sediment yield to land use/land cover changes: In the case of Fincha'a watershed, upper Blue Nile Basin, Ethiopia

Planning and decision making for new irrigation development projects requires the systematic assessment of irrigable land together with available water resources. The data required are usually not available in developing countries, and therefore a method was developed for quantifying surface water resources and potentially irrigable land in ungauged watersheds in the Upper Blue Nile Basin using Soil and Water Assessment Tool (SWAT) model and Multi-Criterion Decision Evaluation (MCDE). The method was tested using the Lah river basin in the Jabitenan district and then applied in the whole area, including ungauged areas. In MCDE, soil type, slope, land use, and river proximity were considered. Onion, Cabbage and Tomato were grown on the identified irrigable areas. The predicted monthly stream discharge agreed well with observed values, with Nash and Sutcliffe efficiencies of 0.87 during calibration and 0.68 for validation. The SWAT model calibrated parameters from the gauged catchment were used to simulate the discharge of the ungauged catchments. The potential irrigable land was determined in Jabitenan woreda and included the Rivers like Birr, Tikurwuha, Gunagun, Leza Lah, Geray, Arara, Debolah, Guysa, and Silala, with an area of 460 km2. By evaluating gross irrigation demand of irrigable land with available flow in rivers (both observed and simulated), the actual surface irrigation potential was 47 km2. The main limitation for surface irrigation in all districts was the available water and not the land suitable for irrigation. Therefore, the study suggests that in order to irrigate a greater portion of the irrigable land, water should be stored during the monsoon rain phase for use in the last part of the dry phase.

This study aims to evaluate stream flow predication capability of three hydrological models including Parameter Efficient Semi-Distributed Watershed Model (PED-WM) model, Hydrologiska Byrans Vattenbalansavdelning (HBV) and Hydraulic Engineering Center-Hydrologic Modeling System (HEC-HMS) in range of sizes of watersheds, Upper Blue Nile Basin, Ethiopia. The model efficiency on daily time scale during calibration period for PED-W (NSE = 0.76, 0.81 and 0.57), HBV-IHMS (NSE = 0.68, 0.79 and 0.59) and HEC-HMS (NSE = 0.63, 0.68 and 0.48) were obtained for Anjeni, Gumara and Main Belles watersheds respectively. Similarly, for validation period PED-W (NSE = 0.6, 0.73 and 0.37), HBV-IHMS (NSE = 0.56, 0.79 and 0.55) and HECHMS (NSE = 0.52, 0.74 and 0.37) were obtained for Anjeni, Gumara and Main Belles watersheds respectively. Similarly, the model performances on monthly time steps were also varied among three hydrological models and the results better than the daily time scale. In PED-W, saturation excess is the main direct runoff process. The overall model performance indicated that PED-W model was better than the other two models. The result indicates that the models in the highlands of Ethiopia are dominantly dependent on the runoff mechanism dominantly on saturation excess runoff mechanism. Hence, there should be an approach to integrate climate region specific model in our water resource development system for predicting stream flow for ungagged catchments.

Chapter 11 - The impact of climate change on mean and extreme state of hydrological variables in Megech watershed, Upper Blue Nile Basin, Ethiopia

Flooding, caused by the excessive accumulation of water on land, disrupts activities in floodplain regions, particularly during the rainy season. The main objective is to map Flood vulnerability areas and identify regions most vulnerable to flooding to inform effective flood management strategies using an integrated approach that combines remote sensing, geographic information systems (GIS), and the analytical hierarchy process (AHP) to assess Flood vulnerability in the Wuseta Watershed. The research was conducted in three phases: pre-fieldwork, fieldwork, and post-fieldwork. Key factors influencing Flood vulnerability such as drainage density, elevation, land use/land cover, and slope were hierarchically weighted to produce a Flood vulnerability map. Rainfall distribution was not considered as a contributing factor the Ethiopian Meteorological Agency has installed only one weather station in the study area, located in Wuseta watershed. As a result, the rainfall distribution is considered uniform throughout the watershed, making it unsuitable for flood susceptibility assessment. The Flood vulnerability map categorizes the watershed into five zones: very high (0.07km2), high (4.65km2), moderate (7.86km2), slight (4.41km2), and very slight (0.001km2). The results show that the upstream, northern, northwestern, and northeastern areas of the watershed face slight to very slight Flood vulnerability, while the southern region is highly vulnerable to flooding. These findings provide valuable insights for policymakers and local communities, aiding in the development of targeted mitigation strategies and raising awareness of flood-prone areas. This study underscores the value of integrating geospatial technologies and multi-criteria decision analysis in flood risk assessment, particularly in data-scarce regions, to enhance disaster preparedness and climate resilience.