Estimating the role of upper Blue Nile basin moisture budget and recycling ratio in spatiotemporal precipitation distributions
Graphical abstract
Introduction
Understanding of freshwater availability has immense importance in assessing socio-economic and environmental impacts of climate and demographic change (Ganguly et al., 2015). It is also important to ensure energy and food security for climate adaptation (Elliott et al., 2013; Ganguly et al., 2015). There is a scarcity of fresh water around the countries within Abay basin. For instance, Egypt and Sudan received insufficient precipitation that affects their own ecological processes (Pimentel et al., 2004). Since precipitation is a critical factor for geomorphological, hydrological, and ecological processes (Charles and Patrick, 2015). The upper Blue Nile basin (UBNB) in Ethiopian is a highland area, which receives precipitation up to 2000 mm per year (Johnston and McCartney, 2010). It is an extremely vulnerable part of the country due to the availability of sufficient precipitation, surface water and underground water (Johnston and McCartney, 2010). Conversely, at the present time, the scarcity of precipitation and sometimes floods with an irregular frequency influences the surface and underground water due to different mechanisms (Allam et al., 2016; Abera et al., 2017).
As different researchers (Ozsoy, 1981; Kalim and Gao, 2012) indicated that the estimation of precipitation variability in complex geographical feature area is difficult; since it interacts with different moisture holding air masses. Similarly, UBNB basin in Ethiopia consists of variable topographic features. It captured moisture from external water bodies such as Atlantic Ocean, Indian Ocean, Red Sea, Arabian sea, Congo basin (Korecha and Barnston, 2007; Segele and Lamb, 2009), and the local water bodies (e.g. Lake Tana and Abay basin). Furthermore, water bodies, forests, and soil moisture contributed to high amount of evaporation to the study area (Zangvil et al., 2001; Zengxin et al., 2009; Fengjun et al., 2011; Allam et al., 2016). However, the contribution of the water bodies and the soil moisture evaporation on the spatiotemporal distribution of precipitation over UBNB is not well documented (Allen and Ingram, 2002; Held and Soden, 2006; Solomon et al., 2007; Seager and Vecchi, 2010). Since the interaction between different moisture carrying air masses with this variable topographic features leads to complex to study spatiotemporal precipitation variability on this region. Therefore, moisture budget analysis is a good approach for studying the spatiotemporal variability of precipitation and it is generation (Fengjun et al., 2011; Peter and Diane, 2012; Dawn et al., 2016). This is because the linkages between atmospheric dynamics, water vapor conditions, and precipitation are constrained by the moisture budget equation (Zangvil et al., 2001; Zengxin et al., 2009). The basic elements of moisture budget studies are wind vector, precipitation intensity, evaporation, recycling ratio, and outgoing long-wave radiation. The direction of the wind vector is indicated the sources of the moisture that contributed to the precipitation in the study area. The intensity of precipitation is high and the strength of wind vectors is low and diverges at high precipitation intensity levels are indicated the sources of precipitation is local moisture in addition to large scale moisture. This can be strongly evident from outgoing long-wave radiation (OLR) when the local moisture is high traps more OLR, its intensity is decreased (Liou, 2002). The numerical estimation of precipitation from the study area moisture is evaluated by recycling ratio (Fengjun et al., 2011). Conversely, the intensity of precipitation and the strength of wind velocity are proportional and not shown the sign of divergence or convergence, the study area moisture is coming from large scale moisture. Outgoing long-wave radiation has similar distributions when the precipitation is coming from large scale dynamics.
The precipitation and the moisture budget of east African countries are also affected by Inter-tropical convergence zone (ITCZ) (Sahalu et al., 2017). Since UBNB in Ethiopia is a part of east African country its rainfall variability is influenced by ITCZ (Ogallo and Halpert, 1988). The migration of ITCZ in the atmosphere is varied with season and governed by the tilt of the Earth by 23.5° (Emily et al., 2003). In the winter, when the Earth's southern hemisphere tilts towards the sun, the southern hemisphere captures high amount of radiation (Joanna, 2011). The wind blows from northern hemisphere to the southern hemisphere. Hence, gradually an ITCZ migrated to the southern hemisphere with similar to the direction of the wind velocity. Northerly winds is dry and not to contribute precipitation. Since 75% of the Ocean is located in the southern hemisphere (Emily et al., 2003). As UBNB is located in the northern hemisphere (above ITCZ); it couldn't get sufficient precipitation during the winter season. However, less amount of precipitation is got from the local moisture. During the summer season, the moisture dynamics seem to be reverse of the winter season. The wind blows from southwest to northeast and it is carrying moisture from Atlantic Ocean (Trenberth, 1997; Emily et al., 2003). Most of this moisture is captured by the Ethiopian highlands (UBNB) when compared to the other countries owing to its mountainous features.
During recent decades, numerous studies have been published on moisture budget and precipitation variability by different authors in different countries. For e.g. at China by Sun et al. (2007) and Zengxin et al. (2009), over Mediterranean by Fengjun et al. (2011) and, Jin and Zangvil (2010), over Amazon Basin by Drumond et al. (2014) and in Africa by Catherine et al. (2014). In Ethiopia, large scale moisture dynamics is studied by the number of authors (Korecha and Barnston, 2007; Segele and Lamb, 2009; Ellen and Asgeir, 2013), but they didn't estimate the contribution of the study area moisture for the precipitation system. In the case of UBNB, climate and hydrology relations is addressed by Conway (2000); the spatial and temporal rainfall variability is studied by Charles and Patrick (2015); estimation of evaporation variability is studied by Mariam et al. (2016) and water balance modeling is studied by Abera et al. (2017). According to previous literature survey, none is reported the study area moisture budget to contribute on UBNB precipitation. Therefore, for the first time, we estimated the role of UBNB moisture budget and recycling ratio in spatiotemporal precipitation distribution by investigating the long term data from 1979 to 2017 (39 years). It is also examined the variations of atmospheric moisture fields and moisture transport mechanisms over the UBNB.
UBNB is one of the most data scarce regions due to lack of hydro-meteorological stations (Allam et al., 2016; Abera et al., 2017). To fill in this gap, we employed various reanalysis data such as climatic research unit (CRU) and Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP), Climate Hazards Group Infrared Precipitation combined with Station (CHIRPS), and ECMWF ERA-interim data.
Section snippets
Study area description
The study is conducted in the domain of the UBNB of Ethiopia, it is located between 7.40 and 12.5 N and from 34.25 to 39.49 E with a drainage area of 176, 000 km2 (Fig. 1). Lake Tana and Abby River basin is the main water bodies in the study area. These two water bodies have a significant contribution of atmospheric moisture over the study domain. The basin's climate is varied from humid to semiarid (Abera et al., 2017). The annual precipitation increases from northeast to southwest (Conway,
Result and discussion
Lake Tana, Nile River and other many tributary rivers over the study area can have a definite influence on the local evaporation and boundary moisture.
Conclusions and recommendations
Moisture budget studies are a basic tool to understand dynamical, hydrological and climatological aspects of atmospheric research. This paper is aimed to estimate the role of upper Blue Nile basin moisture budget and recycling ratio in temporal and spatial precipitation distributions. ECMWF data is well agreed to the gauge and weather radar Z-R relation model. From the overall validation at annual temporal scale, ECMWF does have the highest skill (the lowest MRE and better bias ratio) values
Acknowledgments
The authors are thankful for constant financial support by Bahir Dar University, Ethiopia and partial support from Debre Markos University, Ethiopia. Our gratitude goes to Dawit Amogne (PhD), Degenie Sahalu (PhD), and Melessew Nigusie (PhD) for their substantial comments and suggestions for this work.
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