More than 100 results were found for [77AGG. COM]dewa138 slot batubara 188 slot olenation slot tajir 365 slot p0t.

Results:

• 11. Gudmundsson-etal-2011-PR-7282-26519-1-PB

  are currently melting at a fast rate. Over recent decades, annual mass balance field observations on the three largest ice caps in Iceland* Langjo¨kull (ca. 900 km2), Hofsjo¨kull (ca. 890 km2) and Vatnajo¨kull (ca. 8100 km2)*show a declining specific mass balance from about 0 m yr1 w. eq. on average from 1980 to 1994 to 1 to 1.3 m yr1 w. eq. on average after 1995 (Bjo¨rnsson et al. 2002 /media/ces/Gudmundsson-etal-2011-PR-7282-26519-1-PB.pdf

• 12. Keskitalo_et_al-MLG_and_adaptation_FINAL

  areas: to the regional arm of the state (the county administrative boards) to coordinate adaptation; to specific governmental bodies and agencies to develop a common elevation data basis; and for the assessment of flood risk and erosion defense measures around Lake Vänern. Risks considered by the Bill include the flooding of central Gothenburg, the second largest city of Sweden (a risk /media/loftslag/Keskitalo_et_al-MLG_and_adaptation_FINAL.pdf

• 13. 2010_005_

  Century control runs, as well as 21st Century forecast runs, submitted by various institutions to the Intergovernmental Panel on Climate Change (IPCC) for their Forth 11 Table 1. General circulation and regional climate models that were considered in this study. Model Version Model Name, Institute BCCR BCM 2.0 Bergen Climate Model, Bjerknes Centre for Climate Research, Bergen, Norway CCCMA CGCM 3.1 /media/ces/2010_005_.pdf

• 14. VI_2015_009

  flood models 1–24 (Eqs. 8 and 9 applied with variables 1–12). Ratio between esti- mated and reference index flood (solid black line). The solid blue line corresponds to the reference index flood (Ratio=1), estimated as the arithmetic mean of the observed AMF sample and the dashed blue lines the 95% CI derived from the GEV distribution. Large red symbol indicates overall best model. 18 4.2.2 Flood /media/vedurstofan/utgafa/skyrslur/2015/VI_2015_009.pdf

• 15. Daniell_etal-2010

  and evaluating impacts (see also Swallow et al. 2001, van Ast and Boot 2003). METHODS AND DATA This article is based on empirical data that originated from the analysis of the participatory exercise in the Dhuenn basin. The strong involvement of researchers from two research projects (NeWater[1] and ACER[2]) linked by a joint case study led to the variety of sources available for exploration, including /media/loftslag/Daniell_etal-2010.pdf

• 16. CES_D2.4_task1

  is projected to approach 90%. The impact of anthropogenic climate change on precipitation is still estimated to be very small at present. In the middle of this century, typically about 60% of all months are projected to have above-median precipitation in northern Europe, although with a substantial variation with the time of the year. An on-line appendix of this report provides detailed tables /media/ces/CES_D2.4_task1.pdf

• 17. VI_2020_008

  by the Peak-over-Threshold with MLE applied on daily and 24-hour accumulated precipitation from the ICRA. ............................... 58 8 Glossary 1M5 – Daily or 24-hour precipitation return level with a 5-year return period AMS – Annual Maxima Series CC – Closeness Coefficient CDO – Climate Data Operator EVA – Extreme Value Analysis GP – Generalized Pareto ICRA – Icelandic /media/vedurstofan-utgafa-2020/VI_2020_008.pdf

• 18. Journal_of_Hydrology_Veijalainen_etal

  A second, but usually smaller, increase in runoff oc- curs in the autumn. In northern Finland more than 95% of annual maximum floods are caused by spring snowmelt (cf. Fig. 7a). Also the small upstream lakes in the northern part of the lake area and the northernmost of the coastal rivers fall mainly into this cat- egory. In most coastal rivers the major floods can be caused by either snowmelt /media/ces/Journal_of_Hydrology_Veijalainen_etal.pdf

• 19. VI_2022_006_extreme

  77 91 109 Hraunaveita 132 116 136 159 117 140 169 Kvíslaveita 48 42 49 58 42 51 61 Sultartangi 66 57 68 80 58 69 84 Þingvallavatn 96 84 99 117 85 102 123 Þórisvatn 47 41 49 57 42 50 60 Tungnaá 76 67 79 92 67 80 98 Ufsarlón 104 92 108 126 93 112 134 36 Figure 19 – 1M5 maps for catchment Hálslón based on the ICRA dataset without projection (top left), with RCP 2.6 and 10th percentile /media/vedurstofan-utgafa-2022/VI_2022_006_extreme.pdf

• 20. VI_2014_006

  to reduce systematic biases in the flow forecasts, if any, a recursive error correction procedure which builds on the algorithm proposed by Boi (2004) is defined, assuming that dis- charge observations are available in real-time and are of good quality. The algorithm establishes a correction to be applied on predicted discharge issued at time t0, based on the error between observed and analyzed /media/vedurstofan/utgafa/skyrslur/2014/VI_2014_006.pdf