Statistical bias correction of regional climate model simulations for climate change projection in the Jemma sub-basin, upper Blue Nile Basin of Ethiopia

This study evaluates bias correction methods and develops future climate scenarios using the output of a better bias correctiontechnique at the Jemma sub-basin. The performance of different bias correction techniques was evaluated using several statisticalmetrics. The bias correction methods performance under climate condition different from the current climate was also evaluatedusing the differential split sample testing (DSST) and reveals that the distribution mapping technique is valid under climatecondition different from the current climate. All bias correction methods were effective in adjusting mean monthly and annualRCM simulations of rainfall and temperature to the observed rainfall and temperature values. However, distribution mappingmethod was better in capturing the 90th percentile of observed rainfall and temperature and wet day probability of observedrainfall than other methods. As a result, we use the future (2021–2100) simulation of RCMs which are bias corrected usingdistribution mapping technique. The output of bias-adjusted RCMs unfolds a decline of rainfall, a persistent increase of temperature and an increase of extremes of rainfall and temperature in the future climate under emission scenarios of RepresentativeConcentration Pathways 4.5, 8.5 and 2.6 (RCP4.5, RCP8.5 and RCP2.6). Thus, climate adaptation strategies that can provideoptimal benefits under different climate scenarios should be developed to reduce the impact of future climate change

Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen’s slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies

Introducing a new open source GIS user interface for the SWAT model

The Soil and Water Assessment Tool (SWAT) model is a robust watershed modeling tool. It typically uses the ArcSWAT interface to create its inputs. ArcSWAT is public domain software which works in the licensed ArcGIS environment. The aim of this paper was to develop an open source user interface for the SWAT model. The interface, QSWAT, is written in the Python programming language and uses various functionalities of the open source geographic information system, QGIS. The current interface performs similar functions to ArcSWAT, but with additional enhanced features such as merging small subbasins and static and dynamic visualization of outputs. The interface is demonstrated through a case study in the Gumera watershed in the Lake Tana basin of Ethiopia, where it showed a successful performance. QSWAT will be a valuable tool for the SWAT scientific community, with improved availability and functionality compared with other options for creating SWAT models

Suitability of Water Harvesting in the Upper Blue Nile Basin, Ethiopia: A First Step towards a Mesoscale Hydrological Modeling Framework

Extreme rainfall variability has been one of the major factors to famine and environmental degradation in Ethiopia. The potential for water harvesting in the Upper Blue Nile Basin was assessed using two GIS-based Multicriteria Evaluation methods: (1) a Boolean approach to locate suitable areas for in situ and ex situ systems and (2) a weighted overlay analysis to classify suitable areas into different water harvesting suitability levels. The sensitivity of the results was analyzed to the influence given to different constraining factors. A large part of the basin was suitable for water harvesting: the Boolean analysis showed that 36% of the basin was suitable for in situ and ex situ systems, while the weighted overlay analysis showed that 6–24% of the basin was highly suitable. Rainfall has the highest influence on suitability for water harvesting. Implementing water harvesting in nonagricultural land use types may further increase the benefit. Assessing water harvesting suitability at the larger catchment scale lays the foundation for modeling of water harvesting at mesoscale, which enables analysis of the potential and implications of upscaling of water harvesting practices for building resilience against climatic shocks. A complete water harvesting suitability study requires socioeconomic analysis and stakeholder consultation

Evaluation of regional climate models performance in simulating rainfall climatology of Jemma sub-basin, Upper Blue Nile Basin, Ethiopia

This study examines the performance of 10 Regional Climate Model (RCM) outputs which are dynamically downscaled from the fifth phase of Coupled Model Inter-comparison Project (CMIP5) GCMs using different RCMs parameterization approaches. The RCMs are evaluated based on their ability to reproduce the magnitude and pattern of monthly and annual rainfall, characteristics of rainfall events and variability related to Sea Surface Temperature (SST) for the period 1981–2005. The outputs of all RCMs showed wet bias, particularly in the higher elevation areas of the sub-basin. Wet bias of annual rainfall ranges from 9.60% in CCLM4 (HadGEM2-ES) model to 110.9% in RCA4 (EC-EARTH) model. JJAS (June-September) rainfall is also characterized by wet bias ranges from 0.76% in REMO (MPI-ESM-LR) model to 100.7% in RCA4 (HadGEM2-ES) model. GCMs that were dynamically downscaled through REMO (Max Planck Institute) and CCLM4 (Climate Limited-Area Modeling) performed better in capturing the rainfall climatology and distribution of rainfall events. However, GCMs dynamically downscaled using RCA4 (SMHI Rossby Center Regional Atmospheric Model) were characterized by overestimation and there are more extreme rainfall events in the cumulative distribution. Most of the RCMs’ rainfall over the sub-basin showed a teleconnection with Sea Surface Temperature (SST) of CMIP5 GCMs in the Pacific and Indian Oceans, but weak. The ensemble mean of all 10 RCMs simulations was superior in capturing the seasonal pattern of the rainfall and had better correlation with observed annual (Correl = 0.6) and JJAS season rainfall (Correl = 0.5) than any single model (S-RCM). We recommend using GCMs downscaled using REMO and CCLM4 RCMs and stations based statistical bias correction to manage elevation based biases of RCMs in the Upper Blue Nile Basin, specifically in the Jemma sub-basin

The impacts of rice cultivation on an indigenous Fogera cattle population at the eastern shore of Lake Tana, Ethiopia

BackgroundEven though increasing population pressure and associated increased demand for food and economic development have led to overexploitation and degradation of wetlands throughout the world, the drivers are most severe in developing countries. For generations, Fogera wetlands in Ethiopia which are parts of Lake Tana Biosphere Reserve have been widely used for grazing of indigenous cattle. Fogera cattle are one of several recognized indigenous breeds of Abyssinian zebu bovine cattle (Bos primigenius indicus) found in Fogera district, Ethiopia. This study was conducted to quantify impacts of rice expansion on cattle population in Fogera wetlands. Data were collected through questionnaire, focus group discussions, interviews, and land use/land cover analysis. Respondents were selected using systematic random sampling. Variance and LEVENES test were used to analyze the livestock unit and to check homogeneity.ResultsThe study revealed that during the 20-year period preceding 2015, the number of cattle owned decreased from 3509 to 1510 heads. In the same period, rice cultivation increased from 182 to 9499 ha and production from 6701 to 714,013 qt. Grazing lands were reduced from 8550 to 3501 ha, wetlands from 3114 to 1060 ha, and forests from 1542 to 907 ha. Land use/land cover changes showed a negative balance of 40% dry matter requiring cattle feed to be increasingly supplemented through purchases, or reduction in herd number. The study also indicated that the land-use changes brought at the expense of traditional cattle production systems.ConclusionHence, proper management is required to maintain these valuable resources and keep their role in socioeconomic development of the area

Evaluation of static and dynamic land use data for watershed hydrologic process simulation: A case study in Gummara watershed, Ethiopia

Land Use Land Cover (LULC) change significantly affects hydrological processes. Several studies attempted to understand the effect of LULC change on biophysical processes; however, limited studies accounted dynamic nature of land use change. In this study, Soil and Water Assessment Tool (SWAT 2012) hydrological model and statistical analysis were applied to assess the impacts of land use change on hydrological responses such as surface runoff, evapotranspiration, and peak flow in Gummara watershed, Ethiopia. Moreover, the effects of static and dynamic land use data application on the SWAT model performance were evaluated. Two model setups, Static Land Use (SLU) and Dynamic Land Use (DLU), were studied to investigate the effects of accounting dynamic land use on hydrological responses. Both SLU and DLU model setups used the same meteorological, soil, and DEM data, but different land use. The SLU setup used the 1985 land use layer, whereas the DLU setup used 1985, 1995, 2005, and 2015 land use data. The calibration (validation) results showed that the model satisfactorily predicts temporal variation and peak streamflow with Nash Sutcliffe Efficiency (NSE) of 0.75 (0.71) and 0.73 (0.71) in the DLU and SLU setups, respectively. However, the DLU model setup simulated the detailed biophysical processes better during the calibration period. Both model setups equally predicted daily streamflow during the validation period. Better performance was obtained while applying the DLU model setup because of improved representation of the dynamic watershed characteristics such as curve number (CN2), overland Manning's (OV_N), and canopy storage (CANMX). Expansion of agricultural land use by 11.1% and the reduction of forest cover by 2.3% during the period from 1985 to 2015 increased the average annual surface runoff and peak flow by 11.6 mm and 2.4 m3/s, respectively and decreased the evapotranspiration by 5.3 mm. On the other hand, expansion of shrubland by 1% decreased the surface runoff by 1.2 mm and increased the evapotranspiration by 1.1 mm. The results showed that accounting DLU into the SWAT model simulation leads to a more realistic representation of temporal land use changes, thereby improving the accuracy of temporal and spatial hydrological processes estimation

Advances in water resources research in the Upper Blue Nile basin and the way forward: A review

The Upper Blue Nile basin is considered as the lifeline for ∼250 million people and contributes ∼50 Gm3/year of water to the Nile River. Poor land management practices in the Ethiopian highlands have caused a significant amount of soil erosion, thereby threatening the productivity of the Ethiopian agricultural system, degrading the health of the aquatic ecosystem, and shortening the life of downstream reservoirs. The Upper Blue Nile basin, because of limited research and availability of data, has been considered as the “great unknown.” In the recent past, however, more research has been published. Nonetheless, there is no state-of-the-art review that presents research achievements, gaps and future directions. Hence, this paper aims to bridge this gap by reviewing the advances in water resources research in the basin while highlighting research needs and future directions. We report that there have been several research projects that try to understand the biogeochemical processes by collecting information on runoff, groundwater recharge, sediment transport, and tracers. Different types of hydrological models have been applied. Most of the earlier research used simple conceptual and statistical approaches for trend analysis and water balance estimations, mainly using rainfall and evapotranspiration data. More recent research has been using advanced semi-physically/physically based distributed hydrological models using high-resolution temporal and spatial data for diverse applications. We identified several research gaps and provided recommendations to address them. While we have witnessed advances in water resources research in the basin, we also foresee opportunities for further advancement. Incorporating the research findings into policy and practice will significantly benefit the development and transformation agenda of the Ethiopian government