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# Climaware at the end

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This is one (Riccardo Rigon's) contribution to the CLIMAWARE project. It contains a few paper on major journals and some research path to follow.

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### Climaware at the end

1. 1. CLIMAWARE at the end Riccardo Rigon & Coworkers Trento, July 4th, 2017 ScrivaniadiEnzoFerrari,MuseoFerrari
2. 2. !2 We promised to do the Adige Model Rigon et al. http://abouthydrology.blogspot.it/2015/10/workshop-on-coupled-hydrological.html
3. 3. !3 Instead we did mainly 5 things The Adige database 1 DatabaseDatabase NewAgeNewAge CLIMAWARE 23 settembre 2016 http://abouthydrology.blogspot.it/2016/09/the-adige-database-or-database-newage.html Rigon et al.
4. 4. !4 Instead we did mainly 5 things Add to the current theory Rigon et al. http://abouthydrology.blogspot.it/2016/05/age-ranked-hydrological-budgets-and.html the coldest months of the year, in which the evapotranspiration ﬂux is lower. On the contrary, smaller ⇥(tin) values were obtained in the summer months, with a minimum in June around 0.25. 0.25 0.50 0.75 1.00 Gen 1994 Apr 1994 Lug 1994 Ott 1994 Gen 1995 Time PartitioningcoefficientΘ January February March April May June July August September October November Jan 94 Apr 94 Jan 95Oct 94Jul 94 Figure 8. Evolution of the partitioning coefﬁcient in one year of hourly simulation: the highest value are achieved in January while the lowest in June. 7 Niemi’s relation245 As a result of deﬁnitions made in sections (4) and (5) two relations exist involving q(t,tin), i.e. equations (11) and (30), and aeT (t,tin), i.e. equations (12) and (31). Equating the corresponding two expression, results in:
5. 5. !5 Instead we did mainly 5 things Testing the model in a small catchment Rigon et al. http://abouthydrology.blogspot.it/2016/08/estimating-water-budget-components-and.html 0 100 200 300 400 500 01-2012 02-2012 03-2012 04-2012 05-2012 06-2012 07-2012 08-2012 09-2012 10-2012 11-2012 12-2012 Date(month) Q,ET,S(mm/month) Q ET S 0 100 200 300 J(mm/month) Figure 16. The same as ﬁgure 15, but monthly variability for the year 2012. 27 b Figure 1. The location of the Posina basin in the Northeast of Italy (a) and DEM elavation, location of rain gauges and hydrometer stations, subbasin-channel partitions used for in the simulation (b). 3.1 Watershed partition Pertinent to our approach is the use of a coarse degree of spatial information, at the level of the hydrologic response units (HRUs). These HRUs groups a set of hydrologically similar points close each other, that are treated as a single unit, on the basis of mathematical, physical or computational arguments. In other words, even if information can be calculated at pixels level, for instance for exploiting the accurate knowledge of topography, this information is subsequently coarse grained for5 getting single values for any HRU. The rationale of this choice is to capture the ’meaningful’ spatial heterogeneity in the input data and processes, similar to that adopted in other models (Lagacherie et al., 2010; Ascough et al., 2012). More speciﬁcally, in NewAGE the basin is partitioned into hillslopes and channel links. This partition is carried out according the procedure presented in Formetta et al. (2014b, 2011). Each hillslope and link is numbered according to the Pfafstetter scheme (Formetta et al., 2014a; Abera et al., 2014), which deﬁnes an identiﬁer for each link and hillslope, and an order to transverse them.10 Eventually, this approach allows the resolution of Eq. (1) for any of these units independently, from the most uphill one to the outlet. However, depending on the process, the value of each term in the equation can depend on some sub-HRU analysis. In this paper, the term hillslope, HRU, and subbasin are used alternatively for the same basin partitioning concept. A total of 42 HRUs is chosen for the basin (ﬁgure 1b). To illustrate the variability of hydrological quantities among HRUs, a sample of HRUs (four HRUs: Id 1, 4, 13, and 37) are systematically selected to represent different elevation (elevation ranges from 65615 5
6. 6. !6 Instead we did mainly 5 things Testing the model in a large catchment Rigon et al. http://abouthydrology.blogspot.it/2017/02/modelling-water-budget-of-upper-blue.html J 8 9 10 11 12 8 9 10 11 12 8 9 10 11 12 8 9 10 11 12 35 36 37 38 39 40 Lat(degree) 10 30 100 300 Q 35 36 37 38 39 40 Long (degree) 0.5 10 150 mm/month ET 35 36 37 38 39 40 20 60 150 ds/dt JanuaryAprilJulyOctober 35 36 37 38 39 40 -200 0 300
7. 7. !7 Worked on informatics to allow for independent and parallel treatment of hillslopes Instead we did mainly 5 things Rigon et al. http://abouthydrology.blogspot.it/2016/11/about-graphs-dsl-and-replicable.html
8. 8. !8 Possible offsprings Rigon et al. • Implementation of the river Adige model (estimated cost: 100 KEuro) • Studying the policies for the management of the Great Renaissance Dam (Blue Nile). In collaboration with Wuletawu Abera and Marco Pertile (?) • Implementation of the model on Basilicata Rivers (ongoing research financed by Basilicata Civil Protection, in collaboration with Prof. Salvatore Manfreda) • A book chapter in a book (possibly published by Springer-Verlag) edited by Paolo Turrini and Marco Pertile about the application of the Water Directive in Italy
9. 9. !9 Find this presentation at http://abouthydrology.blogspot.com Ulrici,2000? Other material at Links Rigon et al.