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(IWRM) and SEA of Kabul and Amu Darya Rivers

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(IWRM) and SEA of Kabul and Amu Darya Rivers Integrated Water Resources Management (IWRM) and SEA of Kabul and Amu Darya Rivers Dr. Zheenbek Kulenbekov PEER NAS USAID Forum 10th -14th of December, 2018 Amu Darya river basin Kyrgyzstan The Workshops The field trips Water quality, stream flow Eutech instruments Velocity Upper stream of Dara river (Doorot- Korgon village) pH = 8.47, t = 8,4 °C Q = 2,427 mᶾ/S Q = 2,668 mᶾ/S N 39° 33.141' Ion = -82 mʋ V = 1,44 m/S V = 1,6 m/S E 072° 11.395' Conductivity = 316,2 μS H = 1,665 m H = 0,664 m Elevation: 2525 м TDS = 303,2 ppm 12:42 Radiation background: 0,23 mrSv NaCl = 281,1 ppm Q = 1,950 mᶾ/S Q = 2,440 mᶾ/S Resistivity = 1,650 kƱ V = 1,24 m/S V = 1,47 m/S O2 = 74,6% , 5,7 mg/L при t=12,4 °C H = 1,584 m H= 0,684 m Dara river end,joined with Kyzyl-Suu pH = 8.71, t = 13,9 °C Q = 2,066 mᶾ/S Q = 2,167 mᶾ/S river Ion = -97,9 mʋ V = 1,23 m/S V = 1,29 m/S N 39 33.851' Conductivity = 310,6 μS H = 0,674 m H = 0,705 m E 072 11.789' Elevation: 2473 м TDS = 297.5 ppm Radiation background: 0,22 mrSv NaCl = 285.8 ppm Resistivity = 1,681 kƱ O2 = 72% , 5,08 mg/L при t=14 °C Methods Land cover and land use Interaction between classification practices by NDVI and weather using remote sensing variables • On-site, ground surveys • Climate change affects are desirable for high- precipitation, quality and valid land temperature and NDVI cover classification globally • Use of cadastral maps • By understanding the would be beneficial for relationship between NDVI land classification as well. and climatic variables it is possible to predict future climate change scenario. 7 Kyzyl-Suu River Basin Results • Two years (1994, 2003) have been found with significant correlation coefficient between NDVI and climatic variables • Not enough to establish a significant annual trend between NDVI and climatic variables • Seasonal trend was found: as a rule, the lowest NDVI values are observed in May than reaches its peak at the end of July and at the beginning of August and decreases at the middle or end of September • Trend was found in NDVI values over the last five years in Daroot-Korgon – there is an inter-annual even distribution of values without any sharp fluctuations and variations 9 Time Series Plot of NDVI 1993-2003 0,35 0,30 0,25 I V D N 0,20 0,15 0,10 1 3 3 4 4 6 0 0 0 2 3 9 9 9 9 9 0 0 0 0 0 19 19 19 19 19 0 0 2 0 0 . .2 .2 . .2 .2 6 9 6 8 5 5 7 5 6 7 .0 .0 .0 .0 .0 . 0 .0 . 0 .0 .0 0 1 0 3 1 0 0 0 1 3 1 2 2 2 0 2 3 3 1 2 Date 10 Time Series Plot of Precipitation from 1993 to 2003 70 60 50 40 m m 30 20 10 0 4 4 5 6 6 0 1 1 2 3 3 9 9 9 9 9 0 0 0 0 0 0 9 9 9 9 9 0 0 0 0 0 0 1 1 1 1 1 2 2 2 2 2 2 1. 1. 0 9 5 0 10 6 2 9 7 3 9 . .0 .0 . .0 .0 .0 .0 .0 .0 10 0 0 0 10 0 8 0 0 0 0 1 2 3 2 2 1 2 3 1 1993-2003 Time series of NDVI over the last five years 0.5 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 August 2013 August 2014 August 2015 August 2016 August 2017 August 2013 August 2014 August 2015 August 2016 August 2017 0.37 0.35 0.38 0.43 0.40 12 Daroot – Korgon summer NDVI value 2013 13 Daroot – Korgon summer NDVI value 2017 14 Land cover classification of Daroot - Korgon 15 Conclusion • Only two years (1994 and 2003) were found with a positive correlation between NDVI and climatic variables • Not enough to establish a significant annual trend between NDVI and climatic variables • Seasonal trend was found: as a rule, the lowest NDVI values are observed in May than reaches its peak at the end of July and at the beginning of August and decreases at the middle or end of September • Trend was found in NDVI values over the last five years in Daroot- Korgon – there is an inter-annual even distribution of values without any sharp fluctuations and variations. • Due to partial lack of weather station observations as well as NDVI values, it is hard to analyze the interlink between NDVI and climatic variables Page 16 Daroot Korgon Administrative center Population 4726 (2009) Elevation 2469 Source: Google Maps Methods of Data Collection • Map • GPS coordinates • Questionnaire (qualitative) • Preliminary preparation and practical guidelines • Focus group Methodology • Primary data: • Surveys and questionnaires (total:92 households; 46 Boroldoi village, 17 Oirondu, 12 Kuntuu, 17 Daroot Korgon) • Socio-economic analysis and compare Case Studies from Kyrgyzstan (Chui Valley and Chon Alay valley) • Secondary data: • Software excel and Minitab • Articles and Scientific Researches as supplementary material Key points of socio-economic analysis • Water Accessibility • Household conditions • Access to electricity • Agricultural machinery • Crops • Average income • Livestock • Infrastructure(electricity, landline, internet) Results and Findings Number of rooms per household in % Number of rooms per house household in % in in Daroot Korgon settlement Chui valley villages 30.0% 45.0% 42.3% 40.0% 25.0% 35.0% 20.0% 30.0% 23.9% 25.0% 15.0% 29.4% 29.4% rooms 20.0% 16.9% 16.9% 23.5% rooms 15.0% 10.0% 17.6% 10.0% 5.0% 5.0% 0.0% 0.0% 3 4 5 5> 3 4 5 5> Material for wall in Chui Material for wall in % Valley in % Daroot Korgon 15.8% 8% 11% 47.4% 30% 51% 36.8% adobe brick clay,loam others adobe loam brick Material for roof in Chui Material for roof in % Valley villages in % Daroot Korgon 18% 16.7% 16.7% 66.7% 82% shiver metal,iron shivers iron others Chui Valley neighbourhoods Chon Alay, Daroot Korgon 17.6 82.4 Agriculture Machines in % 23.6 76.4 Agriculture Machines in % Cars in % 76.5 23.5 Cars in % 47.2 52.8 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% YES NO YES NO Enough food Chui Villages Enough food Daroot Korgon 11 61 6 11 YES NO YES NO Chui VIllages number of household members Chon Alay, Daroot Korgon number of household members 30.3 48.9 39.5 42.1 20.8 18.4 Children Elderly Others children Elderly others Chui valley villages in % Daroot Korgon, Chon Alay in % 120 90.0 82.4 82.4 80.0 76.5 94.4 95.8 70.6 100 70.0 80 76.4 60.0 65.3 50.0 60 40.0 29.4 40 34.7 30.0 23.5 17.6 17.6 23.6 20.0 20 5.6 4.2 10.0 0 0.0 Electricity Generator Internet Landline Electricity Generator Internet Landline YES NO YES NO Number of livestock in Chui % Number of Livestocks in Chon Villages in % Alay, Daroot Korgon Poultry Horse 27% Yak 1% Poultry She Sheep 2% 14% ep Cattle Horse Goat Catt 6% Goat 1% le Sheep Goa Yak Yak 55% Cattle t Sheep Yak 0% Horse 7% 75% Goat Poultry Cattle 0% 12% Income per household in % in Income per household in Oirondu 40 001-100 000 KGS % 2.5%in Boroldoi 40 001-50 000 KGS 7.1% 30 001-40 000 KGS 2.5% 20 001-30 000 KGS 7.5% 30 001-40 000 KGS 21.4% 15 001-20 000 KGS 12.5% 20 001-30 000 KGS 14.3% 10 001-15 000 KGS 20.0% 5 001-10 000 KGS 30.0% 15 001-20 000 KGS 21.4% 1 000-5 000 KGS 25.0% 10 001-15 000 KGS 35.7% -10.0% 0.0% 10.0% 20.0% 30.0% 40.0% 0.0% 10.0% 20.0% 30.0% 40.0% Income per household in % in Income per household in % in Kuntuu Daroot Korgon 30 001-40 000 KGS 10.0% 20 001-30 000 KGS 20.0% 20 001-30 000 KGS 0.0% 15 001-20 000 KGS 20.0% 15 001-20 000 KGS 20.0% 10 001-15 000 KGS 30.0% 10 001-15 000 KGS 0.0% 5 001-10 000 KGS 30.0% 5 001-10 000 KGS 70.0% 0.0% 10.0% 20.0% 30.0% 40.0% -20.0% 0.0% 20.0% 40.0% 60.0% 80.0% Size of land per household in Size of land per household in % in Boroldoi % in Daroot Korgon 35.0% 32.6% 40.0% 36.4% 30.0% 35.0% 25.0% 30.0% 20.0% 25.0% 16.3% 16.3%16.3% 18.2%18.2% 15.0% 20.0% 9.3% 15.0% 10.0% 4.7% 9.1%9.1% 9.1% 2.3%2.3% 10.0% 5.0% 0.0% 5.0% 0.0% 0.0% 0.0% 0.0% 0.0% SIZE OF LAND PER HOUSEHOLD IN % IN BOROLDOI SIZE OF LAND PER HOUSEHOLD IN % IN DAROOT KORGON 0,01-1 га 1,01-2 га 2,01-3 га 0,01-1 га 1,01-2 га 2,01-3 га 3,01-4 га 4,01-5 га 5,01-7 га 3,01-4 га 4,01-5 га 5,01-7 га 7,01-17 га 17,01 -32 га > 32,01 га 7,01-17 га 17,01 -32 га > 32,01 га Size of land per household in % Size of land per household in % in in Oirondu Kuntuu 40.0% 33.3% 30.0% 100.0% 20.0% 20.0% 54.5% 36.4% 20.0% 13.3% 50.0% 9.1% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 6.7% 6.7% 10.0% 0.0% 0.0% 0.0% 0.0% SIZE OF LAND PER HOUSEHOLD IN % IN KUNTUU 0.0% SIZE OF LAND PER HOUSEHOLD IN % IN OIRONDU 0,01-1 га 1,01-2 га 2,01-3 га 0,01-1 га 1,01-2 га 2,01-3 га 3,01-4 га 4,01-5 га 5,01-7 га 3,01-4 га 4,01-5 га 5,01-7 га 7,01-17 га 17,01 -32 га > 32,01 га 7,01-17 га 17,01 -32 га > 32,01 га Drinking water source in % Drinking water source in % in in Boroldoi Oirondu village 7.0% 6.3% 23.3% 9.3% 12.5% 32.6% 27.9% 81.3% 0.0% 10.0% 20.0% 30.0% 40.0% 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% water spring Artezian well groundwater (column) river tap water (water pipe) groundwater (column) drift water, aryk (Самотек) tap water (water pipe) Source of drinking water in % in Daroot Korgon Source of drinking water in % in Kuntuu village 10.0% 25.0% 9.1% 30.0% 90.9% 35.0% 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% 0.0% 10.0% 20.0% 30.0% 40.0% groundwater (column) channel, irrigation ditch river tap water (water pipe) groundwater (column) tap water (water pipe) Descriptive statistics of ethnicity and age of respondents in Chui and Chon Alay valley Dotplot of Age Dotplot of Age y t Kazakh i y c i t i n c i h t kyrgyz n E h russian t E kyrgyz 28 35 42 49 56 63 70 77 30 36 42 48 54 60 66 Age Age Conclusion • Social vulnerability(water issues, food insuffiency) • Presence of poor and rich class social disputes and tensions • High dependence on agriculture and cattle breeding • Poor quality of institutional and government support Tajikistan The workshop The field trip MUNIM ABDUSAMADOV, ANVAR KODIROV, ZAMONIDDIN NASRIDDINOV, JAFAR NIYAZOV PEER NAS USAID «Integrated Water Resource Management and Strategic Environmental Assessment of Kabul and Amu Darya Rivers», American University of Central Asia, Bishkek, Kyrgyz Republic, on 10-15 October, 2018 The objects detection and definition on the Earth's surface useful to combine different bands to produce so-called images in natural colors or pseudo-color images.
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