Climate Change and Global Food Security - Section 2 ppsx

Section II Climate Change and Net Primary Productivity © 2005 by Taylor & Francis Group, LLC 147 6 Climate Change Effects on the Water Supply in Some Major River Basins RANJAN S. MUTTIAH AND RALPH A. WURBS CONTENTS 6.1 Introduction 147 6.2 Methodology 152 6.3 Results 159 6.3.1 Two Basins in Texas 159 6.3.2 Ten Major Basins of the World 161 6.4 Discussion 165 6.5 Conclusions 168 Acknowledgments 169 References 169 6.1 INTRODUCTION While the Green Revolution during the latter part of the 20th century may have been facilitated by higher-yield grain vari- eties, the impact of increased water harvesting techniques © 2005 by Taylor & Francis Group, LLC 148 Muttiah and Wurbs (dams, irrigation systems) on agricultural production cannot be ignored. The promotion of agriculture to sequester carbon will require the careful evaluation of future water availability. The following are widely thought to impact the water cycle in a future climate: (1) greenhouse gases (GHGs) such as CO 2 , CH 4 , and N 2 O, are expected to increase from human related activities such as fuel emission and fertilizer application; (2) air and sea surface temperatures (SST) will rise due to GHGs; (3) the number of extreme events (flooding, drought, tornados due to SST-related El Niño/Southern Oscillation [ENSO] events) precipitation intensity may increase, that is, the wet periods will get wetter and the dry periods will get drier; (4) the quality of arable land may decline due to increased salin- ization, erosion, and poor management; and (5) urban popu- lation growth will continue at or above current rates. Iraq serves as an example of point 4. While about 3.5 million ha are potentially cultivable in irrigated agriculture, roughly half, 1.94 million ha, are actually cultivated due to water logging and salinization problems (Food and Agriculture Organization [FAO], 1997). Recent extreme events from the late 1990s to the present — such as the flooding of the Elbe in Central Europe in August 2002, the 1998 flooding of the Yangzte in China, the 2000 and 2002 droughts in monsoon- dependent India, and the highest recorded tornado activity in the United States in 2003 — are visible signs of potential trends in extreme events. During 2003, the World Meteoro- logical Organization took the unprecedented step of announc- ing likely changes in extreme events in its reporting. Historical analysis has traced changes in civilization from changes in the Holocene climate (DeMenocal, 2001). This chapter examines the likely consequences of climate change on the water supply in Texas and in ten major basins of the world. The scope of this chapter is to investigate how climate change may affect water supply systems in Texas for a highly urbanized watershed (San Jacinto with drainage area 7300 km 2 ), a large basin (Brazos with drainage area 118,000 2 Although the focus of this chapter is on evaluation of water resources, the potential of irrigated crops to sequester carbon, © 2005 by Taylor & Francis Group, LLC km ), and in ten other basins worldwide (Figures 6.1 and 6.2). Climate Change Effects on the Water Supply in Some Major River Basins 149 and of the water supply in these basins to meet future water demands are also discussed. Assessment of water resources should consider both water supply and demand. In many natural and human systems such as irrigated agriculture, Figure 6.1 Brazos and San Jacinto Basins in Texas. San Jacinto Brazos Legend Reservoir Control Point 1:2M Stream Cataloging Unit N 085170 340 510 680 Kilometers © 2005 by Taylor & Francis Group, LLC 150 Muttiah and Wurbs Figure 6.2 The ten basins of the world. (Map reproduced with permission of Aaron T. Wolf, Department of Geosciences, Oregon State University.) Missouri & Mississippi Amazon Danube Congo Volga E &T Ganges Indus Yangtze Chang Jiang Meleuka © 2005 by Taylor & Francis Group, LLC Climate Change Effects on the Water Supply in Some Major River Basins 151 water supply and demand are in some form of equilibrium through an evolutionary process for natural systems or trial and error experimentation for human systems. When one side of this equation is changed, there is bound to be a temporary imbalance before onset of another equilibrium state. The sources of consumptive water are streams, reservoirs (or storage systems), and groundwater wells. While aquifer groundwater supply is sensitive to climate recharge, we exam- ine surface water supplies only. A comprehensive assessment of water supply requires water rights and flow databases. The databases contain hydrologic information by control points (CPs). A CP is a point of water transfer or storage (reservoir) in a stream network. Hydrologic information consists of his- torical stream flows, water diversion amounts, reservoir stor- age, hydropower generation, and priority of water rights. Due to lack of intensive data, water supply analysis on a worldwide basis is currently not possible. Compilation of water supply and demand data for all major river basins in a comprehensive database is therefore highly desirable. The Texas examples highlight the importance of comprehensive water allocation databases for effective estimation of likely changes to water supply under climate change. To date, water resource assess- ments during climate change have ignored the influence of storage systems. Hydrologic assessments depend on global circulation mil- lion models (GCMs) for downscaled weather data. The GCMs range from models that consider the atmosphere only (AGCMs) such as the Goddard Institute for Space Studies GISS Models I and II (Hansen et al., 1983), to coupling between oceans and atmosphere with terrestrial biosphere feed back such as the Canadian Climate Center model, CCCma (Flato et al., 2000) and the U.K. Meteorological Office Hadley Centre models HadCM2 (Johns et al., 1997) and HadCM3 (Gordon et al., 2000). Since the GCMs capture physical processes of atmo- spheric circulation from the surface boundary layers to the upper layers involving atmospheric chemistry and radiation physics, model results are generated at coarse grid resolutions of about 2 to 3 degrees at the equator. The Japanese Earth Simulator (called AGCM/AFES), run jointly by the National © 2005 by Taylor & Francis Group, LLC 152 Muttiah and Wurbs Space Development Agency (NASDA), Japanese Atomic Energy Research Institute (JAERI), and Japanese Marine Sci- ence and Technology Center (JAMSTEC) has the ambitious goal of simulating Earth’s climate on 10-km grids (see 2002; Ohfuchi, 2003). Depending on the size of the hydrologic basin, downscaling techniques range from direct use of GCM output (Arora and Boer, 2001), interpolation between grids (Jones and Thornton, 1999), regional circulation models forced with GCM boundary conditions (Giorgi et al., 1994), and use of surrogate variables such as GCM atmospheric pressures to estimate precipitation (Burlando and Rosso, 1991). Whether any one downscaling technique is superior to another is unre- solved at the moment. 6.2 METHODOLOGY Our methodology for the Texas examples consisted of obtaining CCCma (model CGCM1) daily precipitation and temperatures for the Brazos and San Jacinto regions between 2040 and 2060 (2050). The climate was supplied to a watershed model called the Soil and Water Assessment Tool (SWAT) (Arnold et al., 1993, 1998) to generate naturalized flows in watersheds under flows are defined as stream flows obtained after subtracting flow influences due to manufactured structures. The SWAT flows were calibrated to measured flows using observed his- torical climate from 1960 to 1989. The SWAT model was run with future (2040 to 2060) weather generated by the CCCma (at about 2.5° × 2.5°) model for a GHG increase of 1% per year plus aerosols. A separate SWAT control run was made with 2040–2060 weather from CCCma with GHGs set at 1995 lev- els. Monthly flow multiplication factors were generated by ratio of SWAT flows with and without GHG change (Muttiah and Wurbs, 2002; Wurbs et al., 2003). The flow multipliers were then multiplied against historical naturalized flows (monthly flows, 1940 to 1996) in the Water Rights and Analysis Package (TAMU-WRAP). The TAMU-WRAP program accounts for water allocation by control points (CPs) in a river network © 2005 by Taylor & Francis Group, LLC www.es.jamstec.go/jp/esc/eng/index.html) (Shingu et al., historical climate conditions (see Figure 6.3). Naturalized Climate Change Effects on the Water Supply in Some Major River Basins 153 (Wurbs, 2001). Increased water abstraction due to population changes were based on Texas Water Development Board (TWDB) projections. The volume reliability for flow diversions were expressed as (v/V) 100, where v is the water volume supplied, and V is the amount demanded by the water right holder; equivalently, the period of reliability was defined as (n/N) 100, where n was the period (in months) during which the demand target was fully met, and N the total number of months in the simulation. Flow changes in the ten basins of the world were based on literature review, especially the work of Arora and Boer (2001) who modeled flows using CCCma, and Arnell (1999) who used weather generated from Hadley Centre circulation models. Arnell generated six different scenarios with five sce- narios coming from the Hadley HadCM2 and one from HadCM3. In the HadCM3, flux adjustments are made Figure 6.3 Flow chart describing the linkage between the Soil and Water Assessment Tool (SWAT) model for generating naturalized flows, and the water rights and analysis package (WRAP) model. Land use and cover Soils Surficial Hydro-Geology Elevation Stream characteristics Priority Order Reservoirs Diversions and Return flows Demands Water Rights/Supply Analysis, WRAP model (monthly) GIS Naturalized Flows From SWAT (daily time step) SWAT Calibration For Historical Climate Regulated and Unregulated flows, Storage, Hydropower Volume and Period Reliabilities GCM (CCCma) Downscale, Y2040-60 © 2005 by Taylor & Francis Group, LLC 154 Muttiah and Wurbs automatically. The HadCM2 scenarios differed in the model initial conditions. To discern the likely impact of regulations on stream flows, the dams in the basins were classified into major and minor. The lower limit capacity of major dams was set at 200 million m 3 . While the International Commission on Large Dams (ICOLD) based in Paris has a lower limit of 1 million m 3 or 15 m in height; the higher 200 million m 3 was selected, since the FAO country descriptions on which we relied had many instances of the 200 million m 3 capacity as the lower limit for a “major” dam. For the Danube, Mekong, and Mississippi and Missouri (MMR) basins we obtained dam data from previous basin-wide studies, respectively, from the Danube River Basin Pollution Reduction Program (Interna- tional Commission for the Protection of the Danube River, 1999; Zinke, 2003), the International Water Management Institute in Sri Lanka (Kite, 2000), and the U.S. Army Corp of Engineers. The dam estimates for the Volga River Basin were obtained from Volga Ltd. Consulting Engineers (Galant, 2003). Since dam capacity data were not available for all the dams in the Amazon–Tocantins Basin, the hydropower gen- eration potential was prorated against known capacities using Fearnside (1995). In final consideration, the dam estimates in our opinion are not very reliable at present due to different definitions, and lack of a common dam database. The major and minor dams in our analysis include main stem and trib- utary dams; in brief, we did not distinguish between main stems and tributaries for the worldwide basins. The irrigated areas and crops within basins were obtained from several sources including the FAO-AQUASTAT (data from the mid-1990s), World Resources Institute (WRI) and the 1998 special irrigated area census done by the National Agricultural Statistics Service (NASS) of the U.S. Department of Agriculture for the MMR. The irrigated areas were also checked against those supplied by Mark Rosegrant (2003) from the International Food Policy Research Institute. The WRI estimates were based on satellite (AVHRR) esti- mates, while the AQUASTAT (countrywide) estimates were based on country surveys. In the case of large discrepancies, © 2005 by Taylor & Francis Group, LLC basin assessments (http://earthtrends.wri.org/pdf_library), Climate Change Effects on the Water Supply in Some Major River Basins 155 characteristics of the ten basins and dams. The carbon uptake potential of irrigated areas was deter- mined by selecting the dominant crops from the basins, and using dry matter estimates from ambient and above-ambient CO 2 open-top chambers (OTC), and free-air CO 2 enrichment (FACE) experiments for rice (De Costa et al., 2003; Kim et al., 2001), CO 2 OTC for wheat (Hakala, 1998), soil plant atmo- sphere units (SPAR) for cotton (Reddy et al., 1998), and OTC the biomass and new soil organic carbon additions from exper- iments. The corn biomass in the MMR was estimated from reported yields for the 1997 census year from NASS (at harvest index 0.5). The change to corn biomass under doubled CO 2 was estimated by assuming a 3% increase based on experiments reported by Ziska and Bunce (1997). A conversion factor of 0.42 was used to estimate amount of organic carbon in biomass (Izzauralde, 2003). The change in cumulative water use through a growing season due to increase in CO 2 is not well documented. While water use efficiency (biomass fixed per unit of water use by plants) has been observed to significantly increase (upward of 20%) under CO 2 fertilization, the seasonal cumulative water use of wheat in FACE experiments has been observed to be significantly (P > F = 0.3) lower by only 4% for well-fertilized (350 kg N/ha) and watered conditions (Hun- saker et al., 2000). The new soil organic carbon (SOC) input to the soil at the time of crop harvest was determined from the lower limit given in Leavitt et al. (2001) for wheat, and the mean value given in Torbert et al. (1997) for soybeans and grain sorghum (as surrogate for C 4 crops corn and maize). Since no SOC data were found for crops such as rice and barley, the C 3 wheat estimates were used. Our SOC estimates differ from those of Sperow et al. (2003) and Lal and Bruce (1999), since we did not account for soil C savings from reduced erosion and management practices (no-till, reclamation, set-asides). Our carbon uptake estimates also assume cropping conditions similar to the CO 2 experiments. © 2005 by Taylor & Francis Group, LLC we selected the FAO survey estimates. Table 6.1 summarizes experiments for barley (Fangmeier et al., 2000). Table 6.2 gives [...]... 0.34 1. 42 1.56 1.06 0.94 1.10 0.90 0.43 0.66 0.54 0.39 0.68 1.00 2. 66 2. 18 0.96 1.65 0.95 1.08 0.41 0. 72 0.57 0.34 0.94 0.88 2. 84 2. 27 1.43 1.77 0.76 0.66 0. 42 0.51 0.38 0 .27 0.53 0. 42 1.58 1.88 1 .29 1.13 1.6 5.8 24 .5 22 .1 19.5 22 .4 13.8 3.8 27 .4 –18.7 6.6 –7.7 2. 0 5.8 23 .4 21 .6 19.1 22 .4 15.5 6.3 22 .7 –15.3 7.0 –6.4 3 .2 7.5 27 .3 26 .1 23 .7 26 .6 18.9 8.6 22 .8 –15.0 9.1 –6.1 4 .2 9.3 31.4 30.8 28 .6 30.0... Navigation 4(70) U . 0.39 0.34 0 .27 22 .4 22 .4 26 .6 30.0 Jul 0.35 0.68 0.94 0.53 13.8 15.5 18.9 19.1 Aug 0.34 1.00 0.88 0. 42 3.8 6.3 8.6 7.4 Sep 1. 42 2.66 2. 84 1.58 27 .4 22 .7 22 .8 27 .2 Oct 1.56 2. 18 2. 27 1.88 –18.7. 0.76 1.6 2. 0 3 .2 4 .2 Feb 0.71 0.90 1.08 0.66 5.8 5.8 7.5 9.3 Mar 0.61 0.43 0.41 0. 42 24.5 23 .4 27 .3 31.4 Apr 0.59 0.66 0. 72 0.51 22 .1 21 .6 26 .1 30.8 May 0.37 0.54 0.57 0.38 19.5 19.1 23 .7 28 .6 Jun. Finland OTC 700 12. 22 14.33 NA NA Hakala (1998) Maricopa, Arizona FACE 700 29 –41 g C m -2 year -1 29 –41 g C m -2 year -1 Leavitt et al. (20 01) Cotton Mississippi State SPAR units 700 19 26 .5