Understanding the natural low flow of a catchment is critical for effective water management policy in semi-arid and arid lands. The Geba catchment in Ethiopia, forming the headwaters of Tekeze-Atbara basin was known for its severe land degradation before the recent large scale Soil and Water conservation (SWC) programs. Such interventions can modify the hydrological processes by changing the partitioning of the incoming rainfall on the land surface. However, the literature lacks studies to quantify the hydrological impacts of these interventions in the semi-arid catchments of the Nile basin. Statistical test and Indicators of Hydrological Alteration (IHA) were used to identify the trends of streamflow in two comparatives adjacent (one treated with intensive SWC intervention and control with fewer interventions) catchments. A distributed hydrological model was developed to understand the differences in hydrological processes of the two catchments. The statistical and IHA tools showed that the low flow in the treated catchment has significantly increased while considerably decreased in the control catchment. Comparative analysis confirmed that the low flow in the catchment with intensive SWC works was greater than that of the control by >30% while the direct runoff was lower by >120%. This implies a large proportion of the rainfall in the treated catchment is infiltrated and recharge aquifers which subsequently contribute to streamflow during the dry season. The proportion of soil storage was more than double compared to the control catchment. Moreover, hydrological response comparison from pre- and post-intervention showed that a drastic reduction in direct runoff (>84%) has improved the low flow by >55%. This strongly suggests that the ongoing intensive SWC works have significantly improved the low flows while it contributed to the reduction of total streamflow in the catchment.@en

Understanding the relationship between hydrological processes and environmental changes is important for improved water management. The Geba catchment in Ethiopia, forming the headwaters of Tekeze-Atbara basin, was known for its severe land degradation before the recent success in integrated watershed management. This study analyses the hydrological response attributed to land management change using an integrated approach composed of (i) simulating the hydrological response of Land Use/Cover (LULC) changes; (ii) assessing the alteration of streamflow using Alteration of Hydrological Indicators (IHA); and (iii) quantifying the contribution of individual LULC types to the hydrology using Partial Least Square Regression model (PLSR). The results show that the expansion of agricultural and grazing land at the expense of natural vegetation has increased the surface runoff 77% and decreased dry season flow by 30% in the 1990s compared to 1970s. However, natural vegetation started to recover from the late 1990s and dry season flows increased by 16%, while surface runoff declined by 19%. More pronounced changes of the streamflow were noticed at sub-catchment level, mainly associated with the uneven spatial distribution of land degradation and rehabilitation. However, the rate of increase of low-flow halted in the 2010s, most probably due to an increase of water withdrawals for irrigation. Fluctuations in hydrological alteration parameters are in agreement with the observed LULC change. The PLSR analysis demonstrates that most LULC types showed a strong association with all hydrological components. These findings demonstrate that changing water conditions are attributed to the observed LULC change dynamics. The combined analysis of rainfall-runoff modelling, alteration indicators and PLSR is able to assess the impact of environmental change on the hydrology of complex catchments. The IHA tool is robust to assess the magnitude of streamflow alterations obtained from the hydrological model while the PLSR method is useful to zoom into which LULC is responsible for this alteration.@en

The spatiotemporal variability of the Land Use/Cover (LULC) is a strong influence on the land management and hydrological processes of a river basin. In particular in semi-arid regions like the Tekeze-Atbara (T-A) basin, accurate information about LULC change is a prerequisite for improved land and water management. The human-induced landscape transformations in the T-A basin, one of the main tributaries of the Nile River, were investigated for the last four decades (1972–2014). Separate LULC maps for the years 1972, 1989, 2001, and 2014 were developed based on satellite images, Geographic Information System (GIS) and ground information. Change detection analysis based on the transitional probability matrix was applied to identify systematic transitions among the LULC categories. The results show that > 72% of the landscape has changed its category during the past 43 years. LULC in the basin experienced significant shifts from one category to other categories by 61%, 47%, and 45%, in 1972–1989, 1989–2001, and 2001–2014, respectively. Although both net and swap (simultaneous gain and loss of a given LULC during a certain period) change occurred, the latter is more dominant. Natural vegetation cover, including forests, reduced drastically with the rapid expansion of crops, grazing areas and bare lands during the first two decades. However, vegetation started to recover since the 1990s, when some of the agricultural and bare lands have turned into vegetated areas. Forest land showed a continuous decreasing pattern, however, it has increased by 28% in the last period (2001–2014). In contrast, plantation trees have increased by 254% in the last three decades. The increase of vegetation cover is a result of intensive watershed management programs during the last two decades. The driving forces of changes were also discussed and rapid population growth and changing government policies were found to be the most important.@en

The spatiotemporal variability of the Land Use/Cover (LULC) is a strong influence on the land management and hydrological processes of a river basin. In particular in semi-arid regions like the Tekeze-Atbara (T-A) basin, accurate information about LULC change is a prerequisite for improved land and water management. The human-induced landscape transformations in the T-A basin, one of the main tributaries of the Nile River, were investigated for the last four decades (1972–2014). Separate LULC maps for the years 1972, 1989, 2001, and 2014 were developed based on satellite images, Geographic Information System (GIS) and ground information. Change detection analysis based on the transitional probability matrix was applied to identify systematic transitions among the LULC categories. The results show that > 72% of the landscape has changed its category during the past 43 years. LULC in the basin experienced significant shifts from one category to other categories by 61%, 47%, and 45%, in 1972–1989, 1989–2001, and 2001–2014, respectively. Although both net and swap (simultaneous gain and loss of a given LULC during a certain period) change occurred, the latter is more dominant. Natural vegetation cover, including forests, reduced drastically with the rapid expansion of crops, grazing areas and bare lands during the first two decades. However, vegetation started to recover since the 1990s, when some of the agricultural and bare lands have turned into vegetated areas. Forest land showed a continuous decreasing pattern, however, it has increased by 28% in the last period (2001–2014). In contrast, plantation trees have increased by 254% in the last three decades. The increase of vegetation cover is a result of intensive watershed management programs during the last two decades. The driving forces of changes were also discussed and rapid population growth and changing government policies were found to be the most important.@en

The availability and distribution of water resources in catchments are influenced by various natural and anthropogenic factors. Human-induced environmental changes are key factors controlling the hydrological flows of semi-arid catchments. Land degradation, water scarcity and inefficient utilization of available water resources continue to be important constraints for socio-economic development in the headwater catchments of the Nile river basin in particular over the Ethiopian Catchments. This research investigates the impact of landscape anthropogenic changes on the hydrological processes in the Upper Tekeze basin (A tributary of the Nile). The hydrology of the basin is investigated through analysis of hydro-climatic data, remote sensing techniques, new field measurements and parsimonious hydrological models.@en

The Upper Tekezē-Atbara river sub-basin, part of the Nile Basin, is characterized by high temporal and spatial variability of rainfall and streamflow. In spite of its importance for sustainable water use and food security, the changing patterns of streamflow and its association with climate change is not well understood. This study aims to improve the understanding of the linkages between rainfall and streamflow trends and identify possible drivers of streamflow variabilities in the basin. Trend analyses and change-point detections of rainfall and streamflow were analysed using Mann-Kendall and Pettitt tests, respectively, using data records for 21 rainfall and 9 streamflow stations. The nature of changes and linkages between rainfall and streamflow were carefully examined for monthly, seasonal and annual flows, as well as indicators of hydrologic alteration (IHA). The trend and change-point analyses found that 19 of the tested 21 rainfall stations did not show statistically significant changes. In contrast, trend analyses on the streamflow showed both significant increasing and decreasing patterns. A decreasing trend in the dry season (October to February), short season (March to May), main rainy season (June to September) and annual totals is dominant in six out of the nine stations. Only one out of nine gauging stations experienced significant increasing flow in the dry and short rainy seasons, attributed to the construction of Tekezē hydropower dam upstream this station in 2009. Overall, streamflow trends and change-point timings were found to be inconsistent among the stations. Changes in streamflow without significant change in rainfall suggests factors other than rainfall drive the change. Most likely the observed changes in streamflow regimes could be due to changes in catchment characteristics of the basin. Further studies are needed to verify and quantify the hydrological changes shown in statistical tests by identifying the physical mechanisms behind those changes. The findings from this study are useful as a prerequisite for studying the effects of catchment management dynamics on the hydrological variabilities in the basin.@en

Satellite rainfall products are an important source of rainfall data in un-gauged catchments. However, these products need to be validated as their accuracy can be affected by geographical position, topography, climate and embedded algorithms. Eight satellite rainfall products such as African Rainfall Climatology (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPs), Global Precipitation Climatology Project GPCP), CPC Morphic technique (CMorph), Atmospheric Administration Climate Prediction Center (NOAA-CPC) merged analysis (CMap), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), African Rainfall Estimation Algorithm version 2 (RFEv2) and Tropical Rainfall Measurement Mission (TRMM) were evaluated against ground observations over the complex topography of the upper Tekeze-Atbara basin in Ethiopia. The accuracy of the datasets was evaluated at different temporal and larger spatial scales over the period 2002–2015. The results show that the rainfall data of CHIRPS outperformed all other products at all temporal and spatial scales. Next to CHIRPS, estimates from RFEv2, 3B42v7, and PERSIANN products are closest to the measurements at rain gauges for all spatiotemporal scales: daily, monthly and seasonal, and both at point and spatial scales. The percentage bias (PBias) and correlation coefficient (r) of these products were within ±25% and >0.5 for all scales. The remaining products performed poorly with PBias up to 200% and lower r (<0.5) at all scales. However, the performance of all products improved as the temporal scale increased to month and season at all spatial scales. Compared to low altitudes <2000 m above sea level (m.a.s.l.), the PBias at high altitude (>3000 m.a.s.l.) increased by 35% whilst r dropped by 28%. CHIRPS and 3B42v7 products showed best agreement in mountainous terrains. However, all datasets show no consistency of the error sign. CMorph and 3B42v7 consistently overestimate rainfall relative to all rain gauges during the pixel-to-point rainfall comparison approach and at lowland areas during the areal averaged rainfall comparison. The other six products showed a clear underestimation at all spatial scales. In summary, the results show that rainfall estimates by CHIRPS, RFEv2 and 3B42v7 have a consistently better agreement with ground rainfall at all spatiotemporal scales. Considering the complex topography and limited gauges, the performance of CHIRPS, RFEv2 and 3B42v7 indicates that these products can be used for hydrological and overall water management applications in the region.@en

Satellite rainfall products are an important source of rainfall data in un-gauged catchments. However, these products need to be validated as their accuracy can be affected by geographical position, topography, climate and embedded algorithms. Eight satellite rainfall products such as African Rainfall Climatology (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPs), Global Precipitation Climatology Project GPCP), CPC Morphic technique (CMorph), Atmospheric Administration Climate Prediction Center (NOAA-CPC) merged analysis (CMap), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), African Rainfall Estimation Algorithm version 2 (RFEv2) and Tropical Rainfall Measurement Mission (TRMM) were evaluated against ground observations over the complex topography of the upper Tekeze-Atbara basin in Ethiopia. The accuracy of the datasets was evaluated at different temporal and larger spatial scales over the period 2002–2015. The results show that the rainfall data of CHIRPS outperformed all other products at all temporal and spatial scales. Next to CHIRPS, estimates from RFEv2, 3B42v7, and PERSIANN products are closest to the measurements at rain gauges for all spatiotemporal scales: daily, monthly and seasonal, and both at point and spatial scales. The percentage bias (PBias) and correlation coefficient (r) of these products were within ±25% and >0.5 for all scales. The remaining products performed poorly with PBias up to 200% and lower r (<0.5) at all scales. However, the performance of all products improved as the temporal scale increased to month and season at all spatial scales. Compared to low altitudes <2000 m above sea level (m.a.s.l.), the PBias at high altitude (>3000 m.a.s.l.) increased by 35% whilst r dropped by 28%. CHIRPS and 3B42v7 products showed best agreement in mountainous terrains. However, all datasets show no consistency of the error sign. CMorph and 3B42v7 consistently overestimate rainfall relative to all rain gauges during the pixel-to-point rainfall comparison approach and at lowland areas during the areal averaged rainfall comparison. The other six products showed a clear underestimation at all spatial scales. In summary, the results show that rainfall estimates by CHIRPS, RFEv2 and 3B42v7 have a consistently better agreement with ground rainfall at all spatiotemporal scales. Considering the complex topography and limited gauges, the performance of CHIRPS, RFEv2 and 3B42v7 indicates that these products can be used for hydrological and overall water management applications in the region.@en

Satellite rainfall products are an important source of rainfall data in un-gauged catchments. However, these products need to be validated as their accuracy can be affected by geographical position, topography, climate and embedded algorithms. Eight satellite rainfall products such as African Rainfall Climatology (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPs), Global Precipitation Climatology Project GPCP), CPC Morphic technique (CMorph), Atmospheric Administration Climate Prediction Center (NOAA-CPC) merged analysis (CMap), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), African Rainfall Estimation Algorithm version 2 (RFEv2) and Tropical Rainfall Measurement Mission (TRMM) were evaluated against ground observations over the complex topography of the upper Tekeze-Atbara basin in Ethiopia. The accuracy of the datasets was evaluated at different temporal and larger spatial scales over the period 2002–2015. The results show that the rainfall data of CHIRPS outperformed all other products at all temporal and spatial scales. Next to CHIRPS, estimates from RFEv2, 3B42v7, and PERSIANN products are closest to the measurements at rain gauges for all spatiotemporal scales: daily, monthly and seasonal, and both at point and spatial scales. The percentage bias (PBias) and correlation coefficient (r) of these products were within ±25% and >0.5 for all scales. The remaining products performed poorly with PBias up to 200% and lower r (<0.5) at all scales. However, the performance of all products improved as the temporal scale increased to month and season at all spatial scales. Compared to low altitudes <2000 m above sea level (m.a.s.l.), the PBias at high altitude (>3000 m.a.s.l.) increased by 35% whilst r dropped by 28%. CHIRPS and 3B42v7 products showed best agreement in mountainous terrains. However, all datasets show no consistency of the error sign. CMorph and 3B42v7 consistently overestimate rainfall relative to all rain gauges during the pixel-to-point rainfall comparison approach and at lowland areas during the areal averaged rainfall comparison. The other six products showed a clear underestimation at all spatial scales. In summary, the results show that rainfall estimates by CHIRPS, RFEv2 and 3B42v7 have a consistently better agreement with ground rainfall at all spatiotemporal scales. Considering the complex topography and limited gauges, the performance of CHIRPS, RFEv2 and 3B42v7 indicates that these products can be used for hydrological and overall water management applications in the region.@en