Interactions between Hydrology and LCLUC

Alexander Shiklomanov Water Systems Analysis Group, University of New Hampshire

NASA Land-Cover and Land-Use Change Science Team MeetingUniversity of Maryland, College Park, 03/28/2011 : 03/30/2011

Eshleman (UMCES): Exacerbation of flooding in Carpathian Mountains due to deforestation;Fox (EWC); The Expansion of Rubber and its Implications for Water and Carbon Dynamics in Montane Mainland Southeast Asia;Aizen (UI): Diagnosis of changes in alpine water storages and land surface degradation in Pamir mountains and Amu Darya River Basin;Ozdogan (UWM); Investigating the Relationship Between Land Use/Land Cover Change, Hydrologic Cycle, and Climate in Semi-Arid Central AsiaSaatchi (UCLA): Towards an Integrative and Sustainable Science Program for Caspian Sea Environment;Henebry (SDSU): Evaluating the effects of institutional change on regional hydrometeorology: Assessing the vulnerability of the Eurasian semi-arid grain belt;Shiklomanov (UNH): Northern Eurasian Landscapes: Interactions between Humans, Hydrology, Land Cover and Land Use;Tian (AU): Land Use - Ecosystem - Climate Interactions in Monsoon Asia;Lammers (UNH): Role of LCLUC in hydrology of Eurasian pan-Arctic

WATER CYCLE IMPACTS PROJECTS in NASA LCLUC PROGRAMSu

bco

nti

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tal

Reg

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alLo

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Human

Irrigation

Drainage

Land cultivation/use

Forest cutting

Forestation

Reservoirs

Urbanization

Erosion

Mining

Development

LCLUC and Water Cycle interactions and impacts

Examples for this talk: Central Asia – humanEurasian pan-Arctic – climateAnalysis and integration – NEESPI RIMS

Climate

Snow

Glaciers

Lakes/Wetlands

Soil (freeze/thaw,

permafrost)

Erosion

Fires

Vegetation shift

Human or climate can play major role in different regions

Analysis & Integration

•Inefficient irrigation with soil sterilization problem;

Salinization and desertification of lands

•Pollution of surface and ground waters

Some Water and Land Use Issues in Central Asia

Tajikistan and Kyrgyzstan ~ 80% of total water resources Uzbekistan and Turkmenistan –75% of total water use;

Extensive and inefficient water usePopulation increase

Syr Darya

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Syr Darya at Kazalinsk

Syr Darya at Kal

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Amu Darya

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Amu Darya at SamanbaiAmu Darya at KerkiLinear (Amu Darya at Kerki)

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Discharge variability

Irrigated Area Map of Central AsiaDerived from AVHRR (10km) and SPOT (1km)

UNH Gridded Irrigation Area time-series for Northern Eurasia using Global Irrigated Area Map (1-km resolution derived from remote sensing data) and historical census data from FAO.

Irrigation time-series analysis

Using UNH hydrological model (WBMplus) we evaluated changes in water demand for irrigation over the long-term period

Irrigation water demand in the Syr Daria basin continues to increase

Annual observed air temperature (left) & precipitation (right) variation from CRU 30’ grids and station data

Grids of linear slopes over periods are shown

1940-2002

1950-2002

1960-2002

1940-2002

1950-2002

1960-2002

Courtesy to V. Aizen

Tian Shan mountains, Syr Daria upstream annual discharge variations

Chirchik, DArea=11200 km2

Uchkushoi, DArea=1210 km2

Urmaral, DArea=1120 km2

Bol. Naryn, DArea=5710 km2

Uzunakhmat, DArea=1790 km2

Sokh, DArea=2480 km2

Oigaing, DArea=1010 km2

Talas, DArea=2450 km2

Ugam, DArea=866 km2

Kurshab, DArea=2010 km2

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M3/S M3/S

Pamir mountains, Amu Daria upstream annual discharge variations

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Kafirnigan At Tartki, F=9780 km2 Zeravshan At Dupuli, F=10200 km2

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Magiyandar'ya At Sudzhina, F=1100 km2

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Varzob At Dagana, F=1270 km2

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Yakhsu At Karboztonak, F=1440 km2

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Yagnob At Takfon, F=1490 km2

Courtesy to V. Aizen

AVHRR-MODIS era Observed winter precipitation (University of Delaware gridded fields) shows insignificant decreasing tendency over the long-term period (1936-2008)

Ensemble of 8-GCMs projects increase of winter and decrease of annual precipitation

Change in precipitation (%) relative to 1959-1999

Deviations of Annual Air Temperature (left) and Precipitation (right) over 2031-60 from 1959-1999

Deviations of Annual Runoff (left) and Evapotranspiration (right) over 2031-60 from 1959-1999

SRES A1b

WBMPlusSimulations

+35 mm

+5 mm

-30 mm

+10 mm

UKMO

NCAR

ECHAM

8GCMs

+90 mm

+120 mm

+70 mm

+70 mm

Change in Fergana Valley (most populated area in Central Asia ~ 12 mlnpeople) by 2031-2060 relative to 1959-1999 according to different GCMsfor SRES A1b

GCM Model Precipitation Evapotranspiration

Humans have drastically changed hydrology in the region by the decisions they make

Combination of human decisions and changing climate will compound regional impacts

We can track historical changes with ground and remote sensing data but for the future there is large uncertainty.

COLD REGIONS

Shiklomanov A.I., T. J. Bohn, D. P. Lettenmaier, R. B. Lammers, P. Romanov, M. A. Rawlins, J. C. Adam: Chapter 7: Interactions between land cover/use change and hydrology

Annual discharge variabilities for largest Russian rivers flowing to the Arctic Ocean over 1936-2008. Dash lines show linear trend lines over 1936-2008 (blue) and over 1980-2008 (red). (html://R-ArcticNet.sr.unh.edu)

Acceleration of water cycle in the Eurasian pan-Arctic

Annual time series of spatially aggregated river discharge over the 6 largest Russian basins, precipitation, air temperature and aggregated Arctic Ocean sea ice coverage.(Updated from Shiklomanov & Lammers, 2009 ERL )

Basin averaged anomalies in late winter (February–March) SWE (mm mo−1) averaged for the Ob, Yenisei, Lena and all six Eurasian

basins over the period 1980–2007. (Rawlins et al, ERL, 2009).

Variability of mean precipitations over the cold period (November – April)

P=0.0006

“Change-detection” figure (color merge of 1974 Landsat and

1998 RESURS) illustrating disappearing lakes. Disappeared

lakes appear in red.

Disappearing of lakes in Western Siberia

Courtesy Laurence Smith, UCLA

•Examining temporal variability

of ~10,000 West Siberian lakes

and ponds

•Comparing archived Landsat

data from early 1970’s w/

contemporary RESURS and

MODIS data

Why did the lakes disappear?

• Overall reduction in total lake

area since 1970’s, including permanent drainage of 125 large lakes (>40 ha)

● Most interestingly, these suddenly drained lakes are most prevalent along the continuous-discontinuous permafrost boundary, supporting “permafrost breaching” idea proposed by Larry Hinzman

Example of a hydrological anomaly during the summer of 2007 in the Alazeya river basin. Significant flooding at Andrushkino (lower right) resulting from anomalously high summer river discharge (red arrow, upper left) was not the result of basin-wide precipitation (lower left). Subsequent searches for causes yielded drained lakes (upper right).

Pan-Arctic Spring Thaw Trend (SSM/I, 1988-2001)

Timing and trend in the timing of spring thaw derived from SSM/I have elucidated the thaw correspondence with regional anomalies in annual NPP derived from MODIS and AVHRR. Mean annual variability in springtime thaw for Northern Eurasia (above) is on the order of ±7 days, with corresponding impacts to annual productivity of approximately 1% per day.

Spring Thaw Monitored with Microwave Remote Sensing

McDonald, Kimball, et al., 2004

Advance in Thaw Day for Northern Eurasia (SSM/I, 1988-2001)

Diagram of anomalies in the winter river discharge (% of the

normal) over 1978-2005

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Thawing of Transition Layer (cm)

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Total Summer Presipitation (mm)

Released Water (mm)

Contribution Released Water (% of precipitation)

Dynamic of water release from ice-rich transition layer

Data by Davydov from Circum Polar Active Layer Monitoring (CALM) Sites in Chersky

The percent of buildings with deformations in some of the cites on permafrost:

Location Population* Buildings withdeformations**, %

Yakutsk 284,000 9

Norilsk 205,000 10

Tiksi 5,600 22

Dikson 600 35

Amderma 500 50

Magadan 99,000 55

Vorkuta 71,000 80

Chita 307,000 60

*Federal Department of Statistics on 01.01.2009 (www.gks.ru)**Moscow State University of Civil Engineering (2001)

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Calculations made for standard foundation pile with following assumptions:•No active engineering solutions to control ground temp (e.g. thermosiphons)•No snow and vegetation under city buildings •Ground type: sand, loam, clay •Ice content: hi/low for each ground type

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Decrease of bearing capacity for typical sandy soil from 1965 to 2005

Conclusions

1) Water Cycle across Northern Eurasia is intensifying.2) The intensification is more significant in winter and summer-fall

periods.3) Changes in land cover across cold regions significantly modify

regional hydrological processes.4) Climate change threatens the regional infrastructure built on

permafrost.5) Projected warming under any of the IPCC scenarios will further

enhance the loss of bearing capacity of the ground

New Integrated Mapping and Analysis System for Northern Eurasia (NEESPI RIMS) and regional analysis applications

http://neespi.sr.unh.edu/maps/

6) data interpolation and shading tools;

7) point/station data list with clickable symbols that open station pages in a separate browser window;

8) fold-out section to run the Data Calculator application to perform mathematical and logical functions over gridded or vector datasets;.

NEESPI RIMSRegional Integrated Mapping and Analysis System

1) data search/selection, spatial navigation, metadata link, etc.;

2) coordinate and map data value reader;

3) pixel query tool (i-tool) gets coordinates, country, watershed, and map data value;

4) time series navigation tool;

5) map size and base layer choices;

Deviation of mean July-August air temperature in 2010 from LTM over 1948-2010 (NCEP data)

Deviation of sum of precipitation over July-August 2010 from LTM over 1948-2010 (NCEP data)

Distribution of cropland area

Air Temperature

Precipitation

Croplands

Analysis of hot summer 2010 in Russia

Analysis of air temperature and population in summer 2010Deviation of daily max air temperature over July2-Aug18, 2010 from LTM

Distribution of population density Calculation of area and population in Russia where mean daily air temperature over the period 07-02-2010 to 08-18-2010 was 40C higher then LTM. This heat effected about 90 million people or ~ 60% of total Russian population

Max Air Temperature

Population Density

Anomalies of air temperature and precipitations in summer 2010 from long-term mean over 1985-2010 for Russian cropland area (cropland >10% per grid cell)

Air Temperature

Precipitation

Anomalies of summer 2010 from LTM

Anomalies of summer 2010 from LTM

Anomalies of over 1985-2010

2010 wheat yield in Russia was ~40% less than in 2008, 2009

Carbon monoxide concentrations in the atmosphere between 2 and 8 km above Russia as recorded from 1 to 8 August 2010 by NASA (MOPITT). Ground concentrations of this dangerous gas are reported to be much higher, causing people to report headaches, dizziness, and other more serious conditions.

Using air temperature and precipitation data in NEESPI RIMS we evaluated index of wild fire probability for summer months from 1985 to 2010

1972

2010

2010

Summary

1) Integration of in situ data, remote sensing information and modeling in one on-line system is a fast way to address many interdisciplinary problems;

2) NEESPI RIMS ( Regional Integrated Mapping and Analysis System) contains a set of Web based and online research and data analysis services and tools that can be used for scientific gridded, vector, and point (station) datasets. It is integrated into a hydrological modeling framework that combines data mining, model runs, and data delivery to end users.

3) Rapid analysis of various phenomena and events can be done with NEESPI RIMS using automatically updated near real-time products.

4) Analysis of meteorological characteristics of summer 2010 in Russia shows: a) the summer was extremely warm and dry; b) these conditions impacted most Russian cropland;

c) about 60% of Russian population was affected by this hot weather.5) NEESPI RIMS also allows analysis of a wide range of future scenarios and

models online.