Assessing spatio-temporal rainfall variability in a tropical mountain area (Ethiopia) using NOAA's rainfall estimates

Seasonal and interannual variation in rainfall can cause massive economic loss for farmers and pastoralists, not only because of deficient total rainfall amounts but also because of long dry spells within the rainy season. The semi-arid to sub-humid mountain climate of the North Ethiopian Highlands is especially vulnerable to rainfall anomalies. In this article, spatio-temporal rainfall patterns are analysed on a regional scale in the North Ethiopian Highlands using satellite-derived rainfall estimates (RFEs). To counter the weak correlation in the dry season, only the rainy season rainfall from March till September is used, responsible for approximately 91% of the annual rainfall. Validation analysis demonstrates that the RFEs are well correlated with the meteorological station (MS) rainfall data, i.e. 85% for RFE 1.0 (1996-2000) and 80% for RFE 2.0 (2001-2006). However, discrepancies indicate that RFEs generally underestimate MS rainfall and the scatter around the trendlines indicates that the estimation by RFEs can be in gross error. A local calibration of RFE with rain gauge information is validated as a technique to improve RFEs for a regional mountainous study area. Slope gradient, slope aspect, and elevation have no added value in the calibration of the RFEs. The estimation of monthly rainfall using this calibration model improved on average by 8%. Based upon the calibration model, annual rainfall maps and an average isohyet map for the period 1996-2006 were constructed. The maps show a general northeast-southwest gradient of increasing rainfall in the study area and a sharp east-west gradient in its northern part. Slope gradient, slope aspect, elevation, easting, and northing were evaluated as explanatory factors for the spatial variability of annual rainfall in a stepwise multiple regression with the calibrated average of RFE 1.0 as dependent variable. Easting and northing are the only significant contributing variables (R-2=0.86), of which easting has proved to be the most important factor (R-2=0.72). The scatter around the individual trendlines of easting and northing corresponds to an increase in rainfall variability in the drier regions. Despite the remaining underestimation of rainfall in the southern part of the study area, the improved estimation of spatio-temporal rainfall variability in a mountainous region by RFEs is valuable as input to a wide range of scientific models

Multi-scale Spatial Analysis of the Water-Food-Climate Nexus in the Nile Basin using Earth Observation Data

Securing enough water and food for everyone is a great challenge that the humanity faces today. This challenge is aggravated by many external drivers such as population growth, climate variability, and degradation of natural resources. Solutions for weak water and food securities require holistic knowledge of the different involved drivers through a nexus approach that looks at the interlinkages and the multi-directional synergies to be promoted and increased and trade-offs to be reduced or eliminated. In particular, the interlinkages between water, food, and climate, the so-called Water-Food-Climate Nexus (WFC Nexus) is critical for the given challenge in many regions around the world such as the Nile Basin (NB). Studying the WFC Nexus synergies and trade-offs might provide entry points for the required interventions that are potential to induce positive impacts on water and food securities. However, these synergies and trade-offs are not well known due to factors such as the complexity of the interactions which involve many dimensions within and across spatial and temporal domains and unavailability of reliable ground observations that could be used for such analysis. Therefore, multidisciplinary research that encompasses different methodologies and employs datasets with adequate spatial and temporal resolutions is required. The recent advancement in Earth Observation (EO) sensors and data processing algorithms have resulted in the accumulation of big data that are produced in rates faster than their usage in solving real challenges such as the one that is in the focus of the current research. The availability of public-domain datasets for several parameters with spatial and temporal coverage offers an excellent opportunity to discover the WFC Nexus interlinkages. To this end, the main goal of the current research is to employ EO data derived from public-domain datasets and supplemented with other primary and secondary data to identify WFC Nexus synergies and trade-offs in the NB region, taking the agricultural systems in Sudan as a central focus of this assessment. By concentrating mainly on the agricultural systems in Sudan, which are characterized by low performance and efficiency despite the huge potentials for food production, the current research provides a representative case study that could deliver helpful and transferrable knowledge to many areas within and outside the NB region. In the current research, multi-scale analysis of the WFC Nexus synergies and trade-offs was conducted. The assessment involved investigations on a country scale as a strategic level, and on river basin, agricultural scheme (both irrigated and rainfed systems) and field scales as operational levels. On a country scale, a general analysis of the vegetation’s Net Primary Productivity (NPP) and Water and Carbon Use Efficiencies (WUE and CUE, respectively) in different land cover types was carried out. A comparison between the land cover types in Sudan and Ethiopia was conducted to understand and compare the impact of inter-annual climate variability on the NPP, WUE and CUE indicators of these different land cover types under relatively different climate regimes. The results of this analysis indicate low magnitude of the three indicators in the land cover types that are in Sudan compared to their counterparts in Ethiopia. Moreover, the response of these indicators to climate variability varies widely among the land cover types. In addition, land cover types such as forests and woody savannah represent important natural sinks for the atmospheric CO2 that need to be protected. These observations suggest the need for effective policies that enhance crop productivity, especially in Sudan, and at the same time ensure preserving the land cover types that are important for climate change mitigation. On a river basin scale, which represented by the Blue Nile Basin (BNB), precipitation estimation is of utmost importance, as it is not only the main source of water in the basin but also because precipitation variability is controlling food production in the agricultural systems, especially in the rainfed schemes. The high spatial and temporal variation in precipitation within the BNB suggests the need for water storage and water harvesting be promoted and practiced. This would ensure water transfer spatially from wet to dry areas and temporally from wet to dry seasons. As a major staple cereal crop in Sudan, the performance of sorghum production in irrigated and rainfed schemes was investigated on agriculture schemes and field scales. A noticeable low and unstable sorghum yield is detected under both agricultural systems. This low performance represents a serious challenge, not only for food production but also for water availability. The current low performance was found to be controlled by many factors of physical, socio-economic and management nature. As many of these factors are closely linked, effectively addressing some of them might induce positive impacts on the other controlling factors. To conclude, the identified synergies and trade-offs of the WFC Nexus could be used as entry points to increase the efficiency of water use and bridge the crop yield gap. Even simple interventions in the field might induce positive effects to the total crop production of the agricultural schemes and water use efficiency. The increase of water availability in the river basin and improved production in the schemes would enhance the overall water and food security in the country and would minimize the need to convert land covers that are important for climate change mitigation into croplands. This paradigm shift needs to be done through a comprehensive sustainable intensification (SI) framework that is not only aimed at increasing crop yield but also targets promoting a healthy environment, improved livelihood, and a growing economy

Ephemeral stream dynamics, land cover changes and climate variability in the marginal grabens of the northern Ethiopian Rift Valley

This study focused on ephemeral streams morphodynamics and their relation with hydro-climatic and bio-physical characteristics in their headwater and graben floors in the marginal grabens along the northern Ethiopian Rift Valley. The Raya graben was taken as a case study area, which is the largest marginal graben in northern Ethiopia. The link between rainfall variability and land cover changes shows that there was a negative correlation between precipitation and deforestation which implies that an increase in precipitation decreases deforestation deterring the peasants from tree cutting. Regarding the relationship between upper catchment characteristics and river morphology, results show that upper catchment area is the most important controlling factor of the length of and the area occupied by the rivers in the graben bottom. A simple hydraulic analysis based on the change of specific discharge as the river ow approaches the bridges demonstrates that the abrupt change in channel width as the river approaches the bridge is the main cause of the thick deposition and, consequently, of the increased frequency of overbank oods upstream of the road bridges in the study area. The results related to channel bank erosion capacity of ash oods show that all the peak discharges were equally important in triggering channel bank erosion. Concomitantly, vegetated channels are much more resist- ant to channel bank erosion than non-vegetated banks. Land changes in graben bottoms dictate that the changes are not simply related to a distributary river system but that human interven- tion (e.g., the conversion of bushland and forests into cropland, settlement on alluvium, and avoidance of losing farmland to other land units) and natural vegetation regeneration (e.g., alluvial deposits into shrubland) are also important. Overall, the study suggests that to control the morphodynamics of the ephemeral rivers and their impact on farming activities in the gra- ben bottom, catchment rehabilitation activities need to focus both on the upper catchment and the river channels in the graben bottom. Key words: ephemeral streams, land change, graben, Rift Valley, land cover, climate variabilit

Upper Blue Nile basin water budget from a multi-model perspective

Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, insitu streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region

Ensemble-characterisation of satellite rainfall uncertainty and its impacts on the hydrological modelling of a sparsely gauged basin in Western Africa

Many areas of the planet lack the infrastructure required to make accurate and timely estimations of rainfall. This problem is especially acute in sub-Saharan Africa, where a paucity of rain recording radar and sufficiently dense raingauge networks combine with highly variable rainfall, a reliance on agriculture that is predominantly rain fed and systems that are prone to flooding and drought. Satellite Rainfall Estimates (SRFE) are useful as they can provide additional spatial and temporal information to drive various downstream environmental models and early warning systems (EWS). However, when operating at higher spatial and temporal resolutions SRFE contain large uncertainties which propagate through the downstream models. This thesis uses the TAMSAT1 SRFE algorithm developed by Teo (2006) to estimate the rainfall over a large, data sparse and heterogenous catchment in the Senegal Basin. The uncertainty within the TAMSAT1 SRFE is represented using a set of ensemble estimates, each unique but equiprobable based on the full conditional distribution of the recorded rainfall, produced using the TAMSIM algorithm, also developed by Teo (2006). The ensemble rainfall estimates were then used in turn to drive a Pitman Rainfall-Runoff model of the catchment hydrology. The use of ensemble rainfall estimates was shown to be incompatible with the pre-calibrated parameter values for the hydrological model. A novel approach, the EnsAll method, was developed to calibrate the hydrological model which incorporated each individual ensemble member. The EnsAll calibrated model showed the greatest skill when driven by the ensemble rainfall estimates and little bias. A comparison of the hydrographs produced from TAMSIM ensemble rainfall estimates and that from an ensemble of perturbed TAMSAT1 estimates showed that the full spatio-temporally distributed method used by TAMSIM is superior to a simpler perturbation method for characterizing SRFE uncertainty. Overall, the SRFE used were shown to outperform the rainfall estimates produced from the sparse raingauge network as a hydrological model driver. However, they did demonstrate a lack of ability to represent the large interseasonal variations in rainfall resulting in large systematic biases. These biases were observed propagating directly to the modelled hydrological ouput

Ensemble-characterisation of satellite rainfall uncertainty and its impacts on the hydrological modelling of a sparsely gauged basin in Western Africa

Many areas of the planet lack the infrastructure required to make accurate and timely estimations of rainfall. This problem is especially acute in sub-Saharan Africa, where a paucity of rain recording radar and sufficiently dense raingauge networks combine with highly variable rainfall, a reliance on agriculture that is predominantly rain fed and systems that are prone to flooding and drought. Satellite Rainfall Estimates (SRFE) are useful as they can provide additional spatial and temporal information to drive various downstream environmental models and early warning systems (EWS). However, when operating at higher spatial and temporal resolutions SRFE contain large uncertainties which propagate through the downstream models.This thesis uses the TAMSAT1 SRFE algorithm developed by Teo (2006) to estimate the rainfall over a large, data sparse and heterogenous catchment in the Senegal Basin. The uncertainty within the TAMSAT1 SRFE is represented using a set of ensemble estimates, each unique but equiprobable based on the full conditional distribution of the recorded rainfall, produced using the TAMSIM algorithm, also developed by Teo (2006). The ensemble rainfall estimates were then used in turn to drive a Pitman Rainfall-Runoff model of the catchment hydrology.The use of ensemble rainfall estimates was shown to be incompatible with the pre-calibrated parameter values for the hydrological model. A novel approach, the EnsAll method, was developed to calibrate the hydrological model which incorporated each individual ensemble member. The EnsAll calibrated model showed the greatest skill when driven by the ensemble rainfall estimates and little bias. A comparison of the hydrographs produced from TAMSIM ensemble rainfall estimates and that from an ensemble of perturbed TAMSAT1 estimates showed that the full spatio-temporally distributed method used by TAMSIM is superior to a simpler perturbation method for characterizing SRFE uncertainty.Overall, the SRFE used were shown to outperform the rainfall estimates produced from the sparse raingauge network as a hydrological model driver. However, they did demonstrate a lack of ability to represent the large interseasonal variations in rainfall resulting in large systematic biases. These biases were observed propagating directly to the modelled hydrological ouput