Evapotranspiration

From 7-11 of November, 2016, I attended an international symposium on ecohydrology in Africa. It is the 2nd African international symposium on ecohydrology for water and ecosystem service, and it seems that the symposium has a back from the political officials with the aim to establish an Ecohydrological centre at Addis Ababa. There were many interesting presentations, with different case studies. The list of presentations and the downloadable slides is available at http://ehsymposiumafrica.org/programme-symposium-africa/

My presentation was  on the methods to estimate basin scale evapotranspiration, eventually water budget. Here you can find my slides.

Wuletawu Abera, presentation on basin scale evapotranspiration, at "ecohydrology in Africa" Symposium (photo credit: Professor Zalewski)

Cloud Cover on the surface net radiation

Solar radiation is the key  driving force for water cycle. It modulates how much water land surface evaporates and plant transpires. The  explicitly estimation of  radiation is essential for water budget modelling. One of the major factor affect the net surface radiation is the cloud cover. It can affect the net radiation in many ways.  The influence of cloud on the land surface energy depends on several factors, such as cloud altitude, it size, the nature of the cloud particles.

Due to the lack of accurate cloud cover information, the  net radiation modelling thereby the processes of  land-atmosphere interaction is poorly characterised. Some spatial cloud cover data, as given by recent satellite imagery, however, can contribute for better estimation of the basin water budget simulation.  For effort in this direction, EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) cloud cover fraction data can be useful resource. Here I have processed this data for Upper Blue Nile basin to be used in water budget modelling. A sample of the monthly mean could cover map over the basin for the 1994 is shows in figure 1.

The seasonality of the cover can be clearly seen, and this contributes to the reason for  governing factors of  the seasonality in the basin  water budget.  

Some papers on cloud and hydrology 

Cawkwell, F. G. L., and J. L. Bamber. "The impact of cloud cover on the net radiation budget of the Greenland ice sheet." Annals of Glaciology 34.1 (2002): 141-149.

Alados, I., et al. "Relationship between net radiation and solar radiation for semi-arid shrub-land." Agricultural and Forest Meteorology 116.3 (2003): 221-227.

Frank Richards and Phil Arkin , 2009: On the Relationship between Satellite-Observed Cloud Cover and Precipitation. Monthly Weather Review, 109, 1081–1093, doi: 10.1175/1520-0493(1981)109<1081:OTRBSO>2.0.CO;2.

J. A. Griggs and J. L. Bamber , 2010: Assessment of Cloud Cover Characteristics in Satellite Datasets and Reanalysis Products for Greenland. Journal of Climate, 21, 1837–1849, doi: 10.1175/2007JCLI1570.1.

to be updated….

Nile is flowing out from the Upper Blue Nile basin

Nile is flowing out from the Upper Blue Nile basin, I mean, here at my blog.  We have been working on the Upper Blue Nile basin to estimate each term of the water budget at various time scale and temporal scale. Discharge needs to be modelled at each channel links and  can be verified at links where there is observation data. The discharge for the summer 1994 is shown in the following animation. The daily  discharge  from May - Sept 1994 of each channels of  Upper Blue Nile basin was like this, as we estimated!

Fig: discharge at each channel link for each day from May 01 to Sept 31, 1994

Comparison of different satellite rainfall data

We have done a comparison study on different satellite rainfall data in Upper Blue Nile, you can find it here. Here narrowing the choice of products to three, based on their performances,  the long term (2002-2012) mean daily  spatial distribution, is depicted in figure 1.

fig1: the long term mean daily rainfall data in UBN basin

And, similarly, the long term mean annual comparison is shown in figure 2.

fig 2: The long term annual mean rainfall of UBN basin. 

Note on spatial pattern of the rainfall and the difference between these products. I will come back another time for detail discussion on this.

EGU Topical conference

This year, three important meetings of water science  jointly organised at Addis Ababa, from November 18-20, 2015.  The three meetings are the Alexander von Humboldt Conference of the European Geosciences Union, the STAHY workshop of the International Commission on Statistical Hydrology of the International Association of Hydrological Sciences (ICSH-IAHS) and the Leonardo Conference of the Hydrological Sciences Division of the European Geosciences Union. While there were a lot of good presentation, the following three presentations were more interesting topics of  basin water balance modelling  in general and our (my) approach of doing water balance estimation in particular. 

• Towards Optimization of Reservoir Operations for Hydropower Production in East Africa: Seasonal Climate Forecasts (Leonardo Lecture) --- by Mekonnen Gebremichael. Abstract 
• Education and TAHMO, the Trans-African Hydro-Meteorological Observatory --- by Nick van de Giesen. Abstract  
• How important are soils for hydrological modelling?  --- by Hubert H.G. Savenije. Abstrac 
• characterisation of the regional variability of seasonal water balances within the Omo-Gibe River basin --- by Adanech Yared Jillo 

I had two presentations: One on the comparison of satellite rainfall estimation products for the purpose of basin water balance modelling inputs, and the second was a work in progress on JGrass-NewAge set-up for water balance estimation in Upper Blue Nile basin.  The abstract can be found here and here, respectively. A video of  one of the my presentation (or a part of it) is recorded by my friend and can also be found in this you tube. 

satellite rainfall estimation products in Upper Blue Nile Basin

This is stub for the complimentary material for our paper: Comparative evaluation of  satellite rainfall estimation products and bias correction in Upper Blue Nile Basin. I will provide the data, R scripts and some supplementary results soon....

• The Satellite rainfall dataset 
• The ground-gauge dataset 
• The DEM 
• R scripts 

All will be filled soon


Table: Bias correction function for different SREs in UBN basin

The small, the large, and the macro hydrological system

The global hydrological cycle is a closed system, meaning that the amount of water is fixed.  No input, no output. It is just the circulation! Every river basin  takes the amount of water it needs for its ecosystem maintenance and return it back to the global hydrological system. For a river system, the input to the  basin is precipitation whereas the outputs are  the amount of water that the basin return it back to the system. These are the discharge ( river flow), and  evapotranspiration driven by the energy balance.  As the system changed from the closed system to the open system as moving to the global cycle to basin water cycle,  the basin scale at which the hydrological cycle is looked at  matters. This mean that the proportion of the components such as the precipitation, discharge, evapotranspiration, storage varies across scale. 

The first procedure in modelling the hydrological system is the geometry at which the cycle is estimated. This geometry is extracted from the digital elevation models. These days, they can be easily available from different sources.    Based on the objective and purpose of the modelling, the spatial scale of the basin  can be ranged from few kilometres to hundreds of kilometres (or continental scale).  The digital watershed modelling (DWM) is the pre requisite for modelling, for instance, we are interested at different scales, and  we have been working in the following:

1. Posina Bain, small scale basin

1. Adige scale, large scale basin 

1. Upper Blue Nile basin, Macro scale 

2. Adige river basin

I will not talk about Posina basin in this post. I will have other post about small basin DWM, and hydrological modelling  space-time variability.  Adige is one of the largest,   the second largest basin in Italy(?).  It provides water resources to all the Bolzano, Trentino and Veneto region. We have interest to  model water resource at this basin, and the first step is  the DWM. It is possible to start from the whole basin, and look it into the detail.  To work on the maximum detail topographic information, following series of steps as described in other post, DEM need to be partitioned into many detail, for instance, here the Adige is divided into about 1200 HRUs.  

Adige basin partion into 1200 HRUs using JGrass Spatial toolbox

However, such large numbers of HRUs could computationally be demanding and difficult for data management,  particularly if we are interested to the hydrological outputs at each HRUs. For this reason, the basin can be separated into major basin, and the simulation can be take care of at each particular basin, and use some routing system to estimate at the furthest outlet of the whole basin.  For instance, Adige basin can be divided into several basin (notice the black divides inside the basin, in to five major  basin), and then hydrological simulation can be carried out at each basin, and some sort of routing mechanism can be applied to route to the outlet. 

Some of these can be: 

The position of Adige-Passirio basin (right)  and the topography partitioning into HRU 

 

            Isarco  basin (relatively small basin) that can be singled out for simulation purpose

                    Rienza basin and its topographic partitioning 

Avisio basin and its partition

Noce basin and its partition

3. Upper Blue Nile basin

What we have to do if we are interested even larger (very larger ) basin than the Adige ??? For instance Upper Blue Nile basin, the Ethiopia part of the Blue Nile?  Let's start from what people already did: 

   

 Lake Tana basin where most hydrological studies in the UBN basin is conducted 

• e.g Alemseged T. Haile, Tom Rientjes, Ambro Gieske, and Mekonnen Gebremichael, 2009: Rainfall Variability over Mountainous and Adjacent Lake Areas: The Case of Lake Tana Basin at the Source of the Blue Nile River. J. Appl. Meteor. Climatol., 48, 1696–1717. doi: http://dx.doi.org/10.1175/2009JAMC2092.

Senay, G. B., Asante, K. and Artan, G. (2009), Water balance dynamics in the Nile Basin. Hydrol. Process., 23: 3675–3681. doi: 10.1002/hyp.7364

At this study of water balance at the whole Nile basin, UBN is used as single basin. No space-time variabilities study 

Dile et al, also studied water balance at Lake Tana basin ..... as example for UBN basin study 

 Dile, Yihun Taddele and Raghavan Srinivasan, 2014. Evaluation of CFSR Climate Data for Hydrologic Prediction in Data-Scarce Watersheds: An Application in the Blue Nile River Basin. Journal of the American Water Resources Association  (JAWRA) 1-16. DOI: 10.1111/jawr.12182

Gebrehiwot et al, selected 12 basins a way of looking spatial variabilities in water balance  temporal dynamics  

Gebrehiwot, S., Gardenas, A., Bewket, W., Seibert, J., Ilstedt, U. et al. (2014). The long-term hydrology of East Africa's water tower: statistical change detection in the watersheds of the Abbay Basin.

Similarly for looking space-time varibaility, Tekleab et al  select 18 basin and modelling the water balance at those sub basin. 

Tekleab, S., Uhlenbrook, S., Mohamed, Y., Savenije, H. H. G., Temesgen, M., and Wenninger, J.: Water balance modeling of Upper Blue Nile catchments using a top-down approach, Hydrol. Earth Syst. Sci., 15, 2179-2193, doi:10.5194/hess-15-2179-2011, 2011.

"  .......a conceptual process-based hydrological model is developed .....to study the runoff mechanisms and rainfall–runoff processes..."

Dessie, M., Verhoest, N. E. C., Pauwels, V. R. N., Admasu, T., Poesen, J., Adgo, E., Deckers, J., and Nyssen, J.: Analyzing runoff processes through conceptual hydrological modeling in the Upper Blue Nile Basin, Ethiopia, Hydrol. Earth Syst. Sci., 18, 5149-5167, doi:10.5194/hess-18-5149-2014, 2014.

  

ANIL MISHRA & TAKESHI HATA (2006) A grid-based runoff generation and flow routing model for the Upper Blue Nile basin, Hydrological Sciences Journal, 51:2, 191-206, DOI: 10.1623/hysj.51.2.191

This study is grid-based distributed analysis, however, the focus is on runoff production, where evapotranspiration and other component are not explicitly considered.

 Kim and Jagath made interesting set-up to  model the UBN using 6 sub-basin! However, space-time  modelling of UBN using 6 is not something to envisaged ...... 

Kim, Ungtae and Jagath J. Kaluarachchi, 2009. Climate Change Impacts on Water Resources in the Upper Blue Nile River Basin, Ethiopia. Journal of the American Water Resources Association  (JAWRA) 45(6):1361-1378. DOI: 10.1111 ⁄  j.1752-1688.2009.00369.x

Obviously, further space-time hydrological budget characterisation is necessary in UBN basin. In contrast to the maximum subbasin of 6  partition used to study the whole UBN basin, we need to decide some level of partition that really capture the true variability of the rainfall, evapotranspiration, runoff and storage function. 10 ? 20 ? 50 ? 100? 200? 500?  For the moment, lets try with 300 HRUs. 

Upper Blue Nile basin discretisation into 300 HRUs

To be continued........