The Impact of Irrigation on Land-Atmosphere Interactions and Indian Monsoon Precipitation
description
Transcript of The Impact of Irrigation on Land-Atmosphere Interactions and Indian Monsoon Precipitation
The Impact of Irrigation on The Impact of Irrigation on Land-Atmosphere Interactions Land-Atmosphere Interactions
and Indian Monsoon and Indian Monsoon PrecipitationPrecipitation
Ellen Douglas Ellen Douglas UMass Boston UMass Boston
Adriana Beltrán-Przekurat Adriana Beltrán-Przekurat CIRES UColorado Boulder CIRES UColorado Boulder
Dev Niyogi Dev Niyogi Purdue University Purdue University
Roger Pielke, Sr. Roger Pielke, Sr. CIRES, UColorado Boulder CIRES, UColorado Boulder
Charles VörösmartyCharles Vörösmarty UNHUNH
Magnitude of agricultural land Magnitude of agricultural land use conversionuse conversion
Humans have transformed one-third to one-half Humans have transformed one-third to one-half the earth’s land surface (Avissar et al., 2005). the earth’s land surface (Avissar et al., 2005). Cropland and pasture land ~40% of land Cropland and pasture land ~40% of land surface (FAOSTAT)surface (FAOSTAT) Similar spatial scale as SST anomalies Similar spatial scale as SST anomalies
associated with ENSO (Pielke, 2005)associated with ENSO (Pielke, 2005)
Source: Marshall et al., 2004
Magnitude of agricultural land Magnitude of agricultural land use conversionuse conversion
Humans have transformed one-third to one-half Humans have transformed one-third to one-half the earth’s land surface (Avissar et al., 2005). the earth’s land surface (Avissar et al., 2005). Cropland and pasture land ~40% of land Cropland and pasture land ~40% of land surface (FAOSTAT)surface (FAOSTAT) Similar spatial scale as SST anomalies Similar spatial scale as SST anomalies
associated with ENSO (Pielke, 2005)associated with ENSO (Pielke, 2005)
Irrigated agriculture has Irrigated agriculture has
expanded from 0.5 toexpanded from 0.5 to
2.8 million km2.8 million km22 in 20 in 20thth C C
(Postel 1993; FAOSTAT)(Postel 1993; FAOSTAT)
Source: Marshall et al., 2004
Magnitude of agricultural land Magnitude of agricultural land use conversionuse conversion
Humans have transformed one-third to one-half Humans have transformed one-third to one-half the earth’s land surface (Avissar et al., 2005). the earth’s land surface (Avissar et al., 2005). Cropland and pasture land ~40% of land surface Cropland and pasture land ~40% of land surface (FAOSTAT)(FAOSTAT) Similar spatial scale as SST anomalies Similar spatial scale as SST anomalies
associated with ENSO (Pielke, 2005)associated with ENSO (Pielke, 2005)
Irrigated agriculture has Irrigated agriculture has expanded from 0.5 toexpanded from 0.5 to2.8 million km2.8 million km22 in 20 in 20thth C C(Postel 1993; FAOSTAT)(Postel 1993; FAOSTAT)
Irrigation water use Irrigation water use comprises 70-80% of comprises 70-80% of human water use globally.human water use globally. Source: Marshall et al., 2004
5 to possibly 25% of global freshwater use exceeds long-term accessible 5 to possibly 25% of global freshwater use exceeds long-term accessible supplies (supplies (low to medium certainty)low to medium certainty)
15 - 35% of irrigation withdrawals exceed supply rates and are therefore 15 - 35% of irrigation withdrawals exceed supply rates and are therefore unsustainable (unsustainable (low to medium certainty)low to medium certainty)
Recent analysis indicates 10-15% unsustainable globally.Recent analysis indicates 10-15% unsustainable globally.
(Source: Gordon et al., 2005)
- Increase in global vapor fluxes due to irrigated agriculture estimated to be ~2600 BCM/yr (Gordon et al., 2005). - Irrigation consumptive losses ~1200 BCM/yr (Vörösmarty et al,
2005)What are the impacts on regional weather and climate?How do these impacts affect human vulnerabilty?
Difference in Difference in moisture moisture patterns patterns between between natural natural vegetation and vegetation and agricultural agricultural landscape landscape (Pielke et al., (Pielke et al., 1997)1997)
Increased Increased moisture flux moisture flux increases increases CAPE, which CAPE, which affects affects convection and convection and precipitation precipitation patternspatterns
In India, 1 billion people In India, 1 billion people live on 2.3% of global live on 2.3% of global
land mass.land mass.
GLC2000 (aggregated to 5-min resolution)
In India, 1 billion people In India, 1 billion people live on 2.3% of global live on 2.3% of global
land mass.land mass.
Food production andFood production and
livelihoods are highlylivelihoods are highly
dependent on occurrence dependent on occurrence and timing ofand timing of
summer monsoon rains.summer monsoon rains.
GLC2000 (aggregated to 5-min resolution)
In India, 1 billion people In India, 1 billion people live on 2.3% of global live on 2.3% of global
land mass.land mass.
Food production andFood production and
livelihoods are highlylivelihoods are highly
dependent on occurrence dependent on occurrence and timing ofand timing of
summer monsoon rains.summer monsoon rains.
> 90% of water use > 90% of water use goes to irrigation, a goes to irrigation, a great deal is due to great deal is due to groundwater mininggroundwater mining
GLC2000 (aggregated to 5-min resolution)
Indian Monsoon and societyIndian Monsoon and society South Asian human development has South Asian human development has
responded to millenial scale variability of responded to millenial scale variability of Indian MonsoonIndian Monsoon Wet phase ~10,000 Wet phase ~10,000
to 7000 yr BPto 7000 yr BP coincides coincides
with first human settlementswith first human settlements
in Pakistanin Pakistan
Source: Gupta et al., 2006
Indian Monsoon and societyIndian Monsoon and society South Asian human development has South Asian human development has
responded to millenial scale variability of responded to millenial scale variability of Indian MonsoonIndian Monsoon Wet phase ~10,000 Wet phase ~10,000
to 7000 yr BPto 7000 yr BP coincides coincides
with first human settlementswith first human settlements
in Pakistanin Pakistan Dry phase since ~4000 yr Dry phase since ~4000 yr
BP BP eastward migration eastward migration
and irrigation developmentand irrigation development
possibly as mitigation possibly as mitigation
strategy.strategy.
Source: Gupta et al., 2006
Vulnerability of the Indian Vulnerability of the Indian MonsoonMonsoon
Moisture-advection feedbackMoisture-advection feedback Pressure gradient between land and Pressure gradient between land and
ocean (driver) reinforced by moisture ocean (driver) reinforced by moisture carried by Monsooncarried by Monsoon
Two possible stable states Two possible stable states (Zickfield et al., 2005)(Zickfield et al., 2005) Wet state: > 4mm/day (current state)Wet state: > 4mm/day (current state) Dry state: < 1mm/day Dry state: < 1mm/day
Water Resource
Vulnerability
SocialStructure
PropertyRights
LandManagement
Economy
WaterAccess
WaterPolicy
WaterQuality
WeatherPattern
Variability
Water Resource
Vulnerability
SocialStructure
PropertyRights
LandManagement
Economy
WaterAccess
WaterPolicy
WaterQuality
WeatherPattern
Variability
The Impacts of Water Resource Vulnerability in India (Douglas et al., 2006).
Possible tipping point Possible tipping point mechanisms for the Indian mechanisms for the Indian
MonsoonMonsoon Planetary albedoPlanetary albedo
Vegetation + cloudsVegetation + clouds
COCO2 2 concentrationconcentration AerosolsAerosols Any perturbation in Any perturbation in
the radiative the radiative budget over the budget over the sub-continentsub-continent
Source: Zickfeld et al., 2005
POT CRP
IRR
WWF Ecoregions (Olson et al, 2001)
Estimated seasonal (Kharif and Rabi) cropland Estimated seasonal (Kharif and Rabi) cropland and irrigated land areas by Indian stateand irrigated land areas by Indian state
Computed differences in 1-D, uncoupled latent Computed differences in 1-D, uncoupled latent heat (LH) fluxes between POT and IRR heat (LH) fluxes between POT and IRR scenarios using terrestrial water balance modelscenarios using terrestrial water balance model
Proportioned changes in LH flux between Proportioned changes in LH flux between surface water and groundwater irrigation.surface water and groundwater irrigation.
Changes in moisture and energy fluxes due to Changes in moisture and energy fluxes due to agricultural land use and irrigation in the Indian agricultural land use and irrigation in the Indian
Monsoon Belt (Douglas et al., 2006)Monsoon Belt (Douglas et al., 2006)
Latent heat fluxDifference (W/ m 2 )
State Kharif Rabi AnnualAndhra Pradesh 10.97 4.77 8.18Arunachal Pradesh 0.15 -1.32 -0.51Assam 2.30 -11.12 -3.75Bihar 0.00 11.03 4.97Gujarat 13.14 6.75 10.26Haryana 54.72 95.66 73.18Himachal Pradesh 0.34 -0.82 -0.18Jammu & Kashmir 1.38 -1.71 -0.01Karnataka 7.02 -4.60 1.78Kerala 2.94 -10.59 -3.16Madhya Pradesh -1.99 25.46 10.38Maharashtra -0.61 11.56 4.87Manipur 1.09 -3.52 -0.99Meghalaya 2.57 -22.86 -8.89Mizoram 0.19 -2.72 -1.12Nagaland 0.87 -7.74 -3.01Orissa 2.02 -7.71 -2.36Punjab 36.74 92.06 61.68Rajasthan 10.77 12.54 11.57Sikkim 4.14 -6.91 -0.84Tamil Nadu 21.33 -21.67 1.95Tripura -0.58 -5.44 -2.77Uttar Pradesh 1.86 54.07 25.39West Bengal 7.15 12.35 9.49
India 5.82 13.40 9.24
Area-averaged Area-averaged mean annual vapor mean annual vapor (LH) flux increased (LH) flux increased by 17% (9 Wmby 17% (9 Wm-2-2)) 7% in wet season7% in wet season 55% in dry season55% in dry season
Two-thirds (6 WmTwo-thirds (6 Wm-2-2) ) of this increase was of this increase was due to irrigation.due to irrigation.
About twice that About twice that reported by reported by deRosnay et al. deRosnay et al. (2003).(2003).
Kharif(wet)
Rabi(dry)
Changes in latent heat flux (W m-2)
no
n-c
rop
irri
ga
ted
-g
rou
nd
wat
er
irri
ga
ted
-su
rfa
ce w
ate
r
rain
fed
fallo
w
KharifRabi0.0
0.1
0.2
0.3
0.4
Performed preliminary 3-D analysis of three land Performed preliminary 3-D analysis of three land cover/ land use scenarios: POT, CRP, IRRcover/ land use scenarios: POT, CRP, IRR
Computed differences in LH, SH, VP, Prec, Computed differences in LH, SH, VP, Prec, Temp, PBL between each scenarioTemp, PBL between each scenario
Analysis over smaller domain (to avoid Analysis over smaller domain (to avoid influences of terrain)influences of terrain)
Analysis over larger domain (to compare with Analysis over larger domain (to compare with Douglas et al, 2006)Douglas et al, 2006)
The Impact of Agricultural Intensification and The Impact of Agricultural Intensification and Irrigation on Land-Atmosphere Interactions and Irrigation on Land-Atmosphere Interactions and Indian Monsoon Precipitation – A Mesoscale Indian Monsoon Precipitation – A Mesoscale Modeling Perspective (Douglas et al, GPC Modeling Perspective (Douglas et al, GPC special issue)special issue)
IRR - POT
IRR - CRP
CRP - POT
IRR - POT
IRR - CRP
CRP - POT
a)
b)
c)
LATENT HEAT SENSIBLE HEAT
CRP
IRR
BOWEN RATIO (SH/LH)
POT
Temp Vapor
PBL
CRP-POT IRR-POT IRR-CRP
LH (Wm-2) -1.5 1.3 2.8
SH (Wm-2) -1.7 -11.7 -10.0
Precipitation (mm) -0.1 -1.1 -1.0
Vapor (g/kg) -0.01 0.08 0.09
Similar to Similar to deRosnay et al (2003)deRosnay et al (2003)Findings of 3.2 WmFindings of 3.2 Wm-2-2
Similarities and Similarities and difference difference between WBM between WBM and RAMS resultsand RAMS results
RAMS
WBM(kharif)
Similarities Differences
Similar representation of terrrestrial water cycle
WBM : monthly input; 30-min spatial scale; uncoupled L-A processes RAMS : sub-daily time-step, 5-min spatial scale; coupled L-A processes
Increases in POT to IRR latent heat fluxes
WBM = 5.9 Wm-2 (not water or energy limited)
RAMS = 1.3 Wm-2
PBL suppression proportional to sensible heat fluxes
POT to IRRCRP to IRR
Effect of land cover conversionEffect of land cover conversionon albedoon albedo
CountryChange
in albedo
Pakistan -0.02
India -0.01
Summary and conclusionsSummary and conclusions Surface energy and moisture fluxes are Surface energy and moisture fluxes are
sensitive to the irrigation intensity. sensitive to the irrigation intensity. Change from potential vegetation to Change from potential vegetation to
irrigated agriculture resulted in a irrigated agriculture resulted in a statistically significant reduction in SH = statistically significant reduction in SH = 11.7 Wm11.7 Wm-2-2 over all of India over all of India
Increased regional moisture flux (1 g/kg) Increased regional moisture flux (1 g/kg) caused reduction in the surface temperature caused reduction in the surface temperature (1-3 (1-3 C) and changes in mesoscale C) and changes in mesoscale precipitationprecipitation..
Albedo (prescribed parameter) slightly Albedo (prescribed parameter) slightly reduced, but further analysis needed.reduced, but further analysis needed.
Affect on PBL may affect pressure gradient Affect on PBL may affect pressure gradient that drives the Monsoon circulation.that drives the Monsoon circulation.