(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

Time Series Plot of NDVI 1993-2003

0,35

0,30

0,25

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

m m 30

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

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

t Kazakh

kyrgyz n

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. The semi-automatic extraction of objects of interest (vegetation, water bodies etc.) includes the construction of the ratio of different bands. The allocation of vegetation-covered areas by calculating the normalized difference vegetation index NDVI is widespread:

For the Landsat 8 images NIR is band 5, and RED is band 4. The range of NDVI values varies from -1 to 1, with the highest values indicating lush vegetation and the lowest values indicating rare vegetation cover. NDVI values should be classified in order to clearly identify vegetation-covered areas. Should define equal values for the classified NDVI visualization separately for each satellite image scene to calculate the difference between them.

Land cover (LC) can be defined as the “observed (bio) physical cover of the earth’s surface” and is a synthesis of the many processes taking place on the land. It reflects land occupation (and its transformation) by various natural, modified or artificial systems and to some extent how these systems affect the land. LC is one of the most easily detectable indicators of human intervention on land. Because it can change quickly over time, it is also a good proxy for dynamics of the earth surface resulting from a variety of drivers and factors. Temperature, Isambay station

25.0

20.0 20.3 18.3 17.7 17.9 16.7 15.0

10.0

Surface Surface temperature 5.0

0.0 2013 2014 2015 2016 2017

Temperature, Ayvaj station

19.5 19.3 19.2 19.0 18.6 18.7 18.5

18.0 17.8

17.5 Surface Surface temperature

17.0 2013 2014 2015 2016 2017 Axis Title Precipitation , Ayvaj Precipitation, Isambay

3.3 4.7 4.4

2.9 4.2 4.3

3.9 2.4 2.5

1.9 Average precipitation

2013 2014 2015 2016 2017 Years 2013 2014 2015 2016 2017

Precipitation, Ganjina

3.4 3.0 2.9 2.5

2014 2015 2016 2017

CONCLUSION

Studies conducted in the Amu Darya river basin have shown the need to introduce water-saving irrigation technologies, integrated water resources management, improvement of the ecological status of Transboundary Rivers, socio-economic living conditions of the population and improve the efficiency of irrigated land use. In addition, specific recommendations for the study, planning and implementation of the effective use of water resources of the partner countries will be developed and presented. GOOD PRACTICE

Afghanistan The Workshop The field trip

Climate

Kundoz River Basin North- Panjshir River Basin Solang Station Jabalusarage Station Hydrology Climate Change Impacts Land Cover Snow Cover Panjshir River Basin Land Cover Conclusion and Recommendations

. Land Cover: Limitation of data (Calculated and Recorded) but it is on the way. . General Project Implementation? . Water resources protection; conservation and management. . Rain water harvesting; Waste water treatment and reuse.  Climate Change Mitigation and Adaptation: . Ecosystem based approaches: water resources management and sustainable energy use. . Green Energy: Developing hydropower, solar, biomass, hydrothermal, wind energy resources no fossil fuel energy use.  Joint work of the Amu River Basin countries on: . Mitigation, adaptation and environmental management. • Capacity assessment, collection and sharing existing data, analyzing and interpretation of the data. • Transboundary water resources conservation and management. The Comparison of Panjshir and Pul-e-Khumri Based on Socio- Economic Questionnaire Household Numbers

Number of Household NUMBER OF HOUSEHOLD IN in Sayad PUL-E-KHUMRI 140 120

120 100 95 101 100 80 80 60 60 47 44 40 40 33 40

20 20

0 0 Total Childern eladerly Total Childern eladerly Room at floors

Rooms and Floors in Rooms and Floors in Pul-e-Khumri Sayad 160

70 140

60 120 100 100 50 45 80

40 60 30 40 20 19 20 20 0 10 Rooms floors -20

0 -40 Rooms floors Food Condition

Enough Food Sayad Enough Food PUL-E-KHUMRI

1-3 Months

3-6 Months no Enough food

6-9 Months Enough food

0 1 2 3 4 5 6 0 2 4 6 8 10 Drinking Water Sources

Drinking Water Source Sayad Drinking Water Source Pul-e-Khumri

river river lake lake top water top water ground water ground water Number of Livestock

NUMBER OF LIVESTOCK SAYAD Number of Livestock Pul-e- 60 Khumri

46.1538461 120 50 5 100 87.5 40 80

30 60 19.230769219.2307692 40 3 3 20 10.2564102 20 12.5 6 5.12820512 0 0 0 0 10 0 8 Sheep Cattel Goat Yark hourse poultry 0 -20 0 SHEEP CATTEL GOAT YARK HOURSE POULTRY -40 -10 Electricity

Electricity Pul-e-Khumri Chart Title 10

14 9 12 8 10 7 8 6 6 5 4 2 4 0 3 Electricity Generater -2 2

-4 1

-6 0 Elctricity generater Internet Access

internet access and land line Pul- internet access and land line Sayad e-khumri 1 14

0.9 12 0.8

10 0.7

0.6 8

0.5 6 0.4

0.3 4

0.2 2 0.1

0 0 internet Lamdline Internet access Land Line Distance from Paved Roads

Pul-e-Khumri DISTANCE TO PAVE ROADS 60

SAYAD 49.77777778 50 400 352.2222222 350 40 300

250 30

200 20 150

100 10 50 0.666666667 0.625 0 0 Distand Pave Roads Causing Problem Distand Pave Roads Causing Problem Income Sources

Income Source Pul-e-Khumri 6 Income Source Sayad 4.5 5 4

3.5 4

2.5 3

2 2 1.5

1 1 0.5

0 0 Machanic business Government Agriculture shop Keeper business Government Employee Employee Water Resource for Agriculture

Water Resourse for Agricultutre Water Resourse for Agricultutre Pul-e- Khumri Sayad 10 8 9 7 8

6 7

5 6

4 5 4 3 3 2 2

1 1

0 0 Ground Water River Lake Ground Water River Rain Remittance

REMITTANCE SAYAD Remittance Pul-e-Khumri 1.6 0.6

1.4 0.5

1.2 0.4 1

0.3 0.8

0.6 0.2

0.4 0.1

0.2 0 0 member outside months member outside months