Toward Sustainable Land Use in China. -Highlights of LU/GEC Phase II-

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1 1 Toward Sustainable Land Use in China -Highlights of LU/GEC Phase II- Kuninori OTSUBO* * National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki , Japan Abstract: The Land Use for Global Environment Conservation project (LU/GEC) is one of the Global Environmental Research Program projects funded by the Environment Agency of Japan since The final objective of LU/GEC is to propose policy options for global environmental conservation in terms of sustainable land use in East Asia. This paper outlines the achievements within the LU/GEC second phase. Four topics were picked-up here among many topics in the project, which are current and future food balances in mainland China, arable land area to be cultivated and potential land productivity in northern and northeastern China, groundwater resource deterioration in northern China, and decrease of arable land and grain yield due to urban growth in the lowest basin area of the Yangtze river. The methodology and major results of the four topics are introduced, respectively. Keywords: food balance, potential productivity, groundwater resources, urban growth, digital map, GIS, China 1. Introduction The major questions for the second phase of LU/GEC ( ) were: i) For how long and to what extent will land productivity in China continue to increase? ii) Does sufficient land area in China remain for crop production? iii)what are the main environmental concerns resulting from increases in crop production and options for the increases? The second phase had the following 4 sub-themes to answer these questions. (1) GIS-based, long-term projection of changes in land use in China. The objective was to produce 20-km grid maps (20 km x 20 km grid size maps) of land use and the balance between grain yield and consumption (food balance) in 1990 and 2025 for given socio-economic scenarios. (2) Digital database for diagnostic analysis of the environment in northern and northeastern China. This work concerned the natural and socio-economic factors related to crop production and sustainable land use in northern and northeastern China. We produced 1-km grid scale digital maps of these factors and developed a geographic information system for estimating the land productivities in this area (LPGIS) 1). (3) Environmental degradation in northern and northeastern China due to changes in land use. This sub-theme was concerned with environmental degradation in Hebei Province, focusing on groundwater issues with 2-km grid resolution. We forecast the temporal changes in the water table within the province for given groundwater pumping scenarios. (4) Analysis of changes in land use in the lower Yangtze River basin due to industrialization and urbanization. We analyzed changes in land use in the lower Yangtze River basin by remote sensing, GIS, and modeling using a 100-m grid scale. Our target outputs were 2-km grid maps of food demand and supply and of arable land to be extinguished by industrialization and urbanization. In the first phase of LU/GEC, we projected long-term changes in land use in China as a whole, simulating future changes in land use for 5 land-use types (grassland, forest, arable land, industrial or urban use, and other)

2 2 for the scenarios of future arable land area and population given by the Chinese Government. The simulations suggested that, despite increases in food demand due to population and GDP increases, grasslands will not need to be converted into new arable land 2),3). However, the given arable land scenario assumes continuous increases in land productivity similar to those of the last decade. There is some room for discussion about this assumption. We were thus interested in how long and to what extent land productivity in China will continue to increase, and whether there is sufficient remaining land area in China for crop production. To answer these questions, we needed to study the natural grain productivity. Sub-themes (1) and (2) are related to these questions. We have identified 7 possible important environmental problems in northern and northeastern China due to increasing pressure of food demands 3). The semi-arid north and northeast are the most important grain crop-producing areas in China. These areas also have vast grasslands and forests. Therefore, it is expected that grasslands will be converted to croplands in the near future as demand exceeds the capacity of the existing croplands. Water is the key resource for agricultural development, and the demand for groundwater will increase in these areas. This environmental pressure may cause serious environmental problems related to water resources in these areas. Here, we describe the environmental degradation in Hebei Province in relation to the following processes (sub-theme (3), relating to question iii)): i) Conversion of grasslands or more intensive use of arable land. ii) Well irrigation and selfish and excessive use of groundwater. iii) Loss of groundwater resources and land salinization. iv) Deterioration of arable land and grasslands. We have been also concerned about the following processes in areas of rapid economic growth (relating to sub-theme (4)): i) Reduction in area of productive croplands due to industrialization/urbanization in coastal regions of China. ii) Reductions in grain production in the biggest grain belt. iii) Increases in demand for food, due to population increase and adoption of western life styles. iv) National policies of forest conservation and self-sufficiency in food supply. v) Need to produce more crops in other areas, such as northern and northeastern China. 2. Methods 2.1 GIS-based study on food balance in China We created 20-km grid maps (based on 10' 15' latitude longitude grid scale) of production and consumption of rice, wheat, and maize (corn) in the 1990s in China, based on agricultural censuses of China at the county administrative level 4),5). When allocating census data to each grid cell, we adopted a population weighting interpolative method 6). Therefore, we also created 20-km grid maps of population in 1990 by distributing current and predicted populations at the county level to each cell with the help of improved DMSP/OLS Stable Light Images (SLI) 7). Based on these maps and national maps of impact factors, we created maps of the balance between grain yield and consumption (food balance) in mainland China for 1990 and 1995, and analyzed spatial variation of the balances, their dependences on grain type and socio-economic factors. We aimed to predict the balance of grain supply and demand in 2025 in China. For this purpose, two kinds of maps of China in 2025 were required; one was 20-km grid maps of grain yield, and, the other, those of grain consumption. To draw the future grain yield maps, we needed to predict the future grain yield in We proposed three methods to predict the future grain yields and defined the minimum predicted value as the future grain yield for each grid cell 5). On the process of this prediction, we created 20-km grid maps of possible arable land determined by natural conditions, and those of potential productivities depending on limiting factors, such as light, temperature, soil moisture, and soil fertility. To create the grain demand map for 2025, we need distribution maps of population and consumption rate per capita for the target year. Because the latter value is so much dependent on socio-economic factors, dieting habits and policies in regions, only the scenario approach is feasible at present to create the future distribution of grain consumptions 8).

3 3 2.2 Diagnostic analysis of land productivity in northern and northeastern China The potential crop productivity was defined in terms of the potential photosynthetic productivity (P Q ), potential thermal l productivity (P T ), potential climatic productivity (P W ), and potential land productivity (P L ). Here, P Q refers to the biomass (dry matter) produced by C4 plants under the hypothesis that all environmental factors are most suitable for the growth of plants except for the restriction of light. P T is mainly restricted by light and temperature. P W is restricted by the availability of water as well as light and thermal conditions. Finally, P L is estimated by revising P W with the coefficient for the effect of soil, f(l), which describes the status of land quality as related to soil properties and land degradation. These concepts can be theoretically expressed as P L = ΣQ m f(q) f(t) f(w) f(l) = P Q f(t) f(w) f(l) = P T f(w) f( L) = P W f(l) (1) where Q m is the solar radiation of each month during growing period; f(q) is the coefficient for the effect of photosynthesis; f(t) is the coefficient for the effect of temperature; f(w) is the coefficient for the effect of moisture. Firstly, f(q) can be estimated according to Yu and Zhao (1982) as follows: f ( Q) = Ω H 1 ε ϕ (1 α) (1 β ) (1 γ ) (1 ρ ) (1 ϖ ) (1 + 8%) s, (2) where Ω is a plant s ability to fix CO 2 ; ε is the ratio of visible radiation to total radiation; φ is the light quantum efficiency; α is the albedo; β is the ratio of radiation penetrating a crop canopy and arriving at the ground surface to the total radiation; ρ is the absorptivity of non-photosynthetic organs; γ is the degree of light saturation; ϖ is the ratio of respiration, s is the economic coefficient, and H is the energy required for creating 1g dry matter (10 6 J/kg). All the parameters in formula (2) vary with crop type 9). Secondly, f(t) also varies depending on the plants, and is a function of temperature and growing period as shown by formula (3) 10) f(t) = f t (T) f t (N) (3) where, ft(t) = [(T T 1 ) (T 2 T) a ]/[(T 0 T 1 ) (T 2 T 0 ) a ], a = ( T 2 T 0 ) (T 0 T 1 ), and ft(n) = 1+(N N 0 )/(1.7N 0 ). T is temperature in each growing period; T 0 is the most s uitable temperature; T 1 is the lower t emperature limit; T 2 is the upper temperature limit 9) ; N is the effective growing period (days), and N 0 is the number of days from May to September (growing season). Thirdly, f(w) was determined by the ratio of actual evapotranspiration (ET α ) and potential evapotranspiration (ET 0 ), which describes the water deficit status of crops and is defined in terms of the water deficit index (WDI) 11). K y is a crop index: f ( W ) = K ET / ET = K (1 WDI ) (4) y a o y The soil coefficient, f(l), describes the land quality and is related to soil texture, soil nutrition, land degradation, and so on. Simply, it can be estimated according to formula (5): f(l) = a 1 F 1 + a 2 F 2 + a 3 F 3. (5) Here F 1, F 2, and F 3 refer to proportions of first, second, and third class arable land, and a 1, a 2, and a 3 are empirical coefficients of 1.0, 0.8, and 0.6, respectively 12). 2.3 Groundwater problems in northern China We have focused on groundwater problems, choosing Hebei Province because it has one of the best sets of groundwater statistics and well stations under observation. We evaluated the groundwater resources of the Hebei Plain, using agricultural statistics and spatial and temporal data on groundwater and natural conditions. A hydraulic model of the unconfined and confined flow of groundwater was constructed with the objective of predicting the future groundwater distribution in the Plain. To validate this model, the changes in the water table from 1985 to 1997 were simulated and compared with the observed data 13).

4 4 2.4 Analysis of changes in land use in the lower Yangtze River basin Many studies have modeled urban dynamics, but few are application-oriented 14),15),16),17),18). Most current urban growth models are small scale with local application or in micro-economy. Such models require developers to know the mechanism of changes in land use and require very detailed data. There are several problems associated with applying local models at a regional scale. Firstly, in most cases, we know only the general category of the driving factors rather than the specific factors responsible for changes in land use. Secondly, the human element involved in decision-making about land use introduces stochastic, as well as non-determinative, factors, creating difficulties for simulations. Thirdly, even if we knew the specific factors, it is not easy to consistently quantify them. It would be more difficult to give a quantitative relationship between those factors and range of changes in land use than to give a qualitative description. In our case study, we compared urban growth in the study area with a physical diffusion process 19) Urban growth If the development or growth of a city is projected in two-dimensional space, the spatial extent of the city will usually increase. If we divide the ground surface into two land types, urban land and non-urban land, we may find the changes between urban and non-urban land are mostly in one direction, namely from non-urban to urban land. In view of changes in city shape, urban areas spread in continuous form in space, which looks like a flow on a two-dimensional space. Careful examination of the expansion of urban areas within the study area revealed that urban growth is similar to a two -dimensional diffusion process in the following aspects: i) Unidirectional flow: non-urban to urban. ii) Continuous increase in urban area. iii) Expansion happens on the edges of urban land. iv) Expansion is characterized by continuity over a number of years Basic Theory Basic diffusion is described as the rate of transfer of a substance through a unit length of a section and is proportional to the density gradient measured normal to the section, i.e., f e = ρ ( m / e) (6) where f e is the rate of transfer per unit length of section, m is the density of the diffusing substance, e is the spatial coordinate measured normal to the section, and ρ is the diffusion coefficient or parameter with domain [0,1]. This equation in two-dimensional (x, y) space becomes m / t = / x (ρ ( m / x))+ / y (ρ ( m/ y)) (7) In practice, we often use an approximate numerical solution to calculate the amount of a substance at a given place based on a discrete spatial grid system. Commonly, we choose square grids embedded in a plane and set the grid to a unit area such that x = y = 1. The numerical solution or diffusion formula is : m ij (t + t) = m ij (t) + ρ 2 m ij (t) (8) where i and j are the row and column number, respectively, for a given grid (i,j), 2 m is the second-order difference in the space. In a diffusion equation, density m is the main element to describe a diffusion process. Therefore, population density is adopted as demographic data in such a diffusion model. In general, a higher density occupies less space and a density decline leads to occupation of more space. The degree of density decline can be linked to the extent of urban growth. In addition, socio-economic factors act as key exogenous forces, leading to density decline and driving expansion of urban areas.

5 5 If we limit population density only in urban areas (i.e., built-up areas), a region can be divided into two areas according to density: built -up areas Ω 1,and non-built-up areas Ω 0 where the density is 0. At time t 0, the total population (sum of density) is m ij (t 0 ) ; at time t 1 (>t 0 ), the total population will become m ij ( t 1 ). Ω 1 ( t 0 ) Ω 1 ( t 1 ) An urban area Ω 1 (t 1 ) consists of two parts: the old urban area and the newly increased area, namely Ω 1 (t 1 ) = Ω 1 (t 0 ) Ω 1 (where Ω 1 is the newly increased urban area), so that m ij (t 1 ) = τ m ij ( t 0 ) + m ij ( t 1 ) (9) Ω 1 ( t 1 ) Ω 1 ( t 0 ) Ω 1 In this way, parameter τ denotes the integrated influence of socio -economic factors on urban growth (the exogenous force). Since the transformation of land use is usually unidirectional (non-urban land to urban land), the value of τ should be larger than Study area The study area was located in the southern part of Jiangsu province (China) by the Yangtze River. The economy in Jiangsu province is ranked among the highest provincial economies in China. The area is characterized by three features: high population density, rapid urbanization, and a base for agricultural production. The total study area was about 25,000 km 2, spanning 24 counties. We examined urban growth between 1990 and Simulating process The value of a population plays a key role in the recursive process according to which, once the initial state is set, the process will keep going until the aggregation of people over a certain area is no less than the given population for the area (Figure 1). In Figure1, U ij represents the state of each pixel, 1 (dark) = urban, 0 (white) = non-urban, T is the density threshold for converting non-urban land into urban land, which is determined by minimal density in a unit (county or city), and S is the total population in a given year. m = τ m(t 0 ) m ij =m ij + ρ 2 m ij U ij =1 if m ij T S= m ij (U ij =1) S S Yes No Figure 1 Simulating procedure U ij represents the state of each pixel, 1 (dark) = urban, 0 (white) = non-urban, T is the density threshold for converting non-urban land into urban land, which is determined by minimal density in a unit (county or city), and S is the total population in a given year. 3. Results and Discussion 3.1 GIS-based study on food balance in China We created 20-km grid maps of the production of rice, wheat, and corn in 1990 and 1995, using three data sources: The FAOSTAT food balance sheets ( Chinese statistics on grain yields, and the Columbia University Center for International Earth Science Information Network ( CIESIN) 20). There were some discrepancies in the total production data from the different organizations for the three grains. Consequently, we chose the FAOSTAT data as the standard and adjusted the Chinese statistics and CIESIN data to that standard.

6 6 Grain Balance at 1995 Figure 2 Food balance in mainland China for 1995 Figure 3 20-km grid map of convertible or vulnerable lands for agricultural use We also created 20-km grid maps of the consumption of rice, wheat, and corn in 1990 and Consumption includes human food consumption and agricultural stock consumption. There were very few provincial or national grain consumption statistics available, and, consequently, we had to make several assumptions based on FAOSTAT data to allocate the total human consumption of the three grains to each grid cell. Additionally, we estimated stock consumption of each grain in each grid cell from the national statistics of meat production data from CIESIN. There is, thus, some room for improvement in these maps. Ideally, we need food consumption rates of each grain per capita for different provinces or regions.

7 7 The 20-km grid map of the balance of all grains yield and consumption in 1995 was produced from the maps of all grains yield and consumption for 1995 (Figure 2). Green colored cells show that grain yield is higher than grain consumption, and red colored cells show that grain yield is lower than consumption. The national total of all grains yields exceeded that of all grains consumptions in However, in terms of cereal grains, t he budget of imports and exports of grains for China was negative (imports > exports) from the early 1980s until The budget became positive (imports < exports) in 1996 and has remained positive since then. On the other hand, China has continued to import good quality grains for human consumption. Furthermore, it should be noted that the consumption rate per capita in China is much lower than that of Western countries, but it is continually increasing. The balance distribution map shows that there were so many locations where all grains consumptions exceeded all grains yields, which suggests us that domestic transportation of all grains between counties and provinces took an important role to feed people in China. As previously mentioned, a possible arable land map determined by natural conditions gives us basic information to predict future grain supplies. Potential land for grain production was determined by light, temperature, slope, and precipitation. Consequently, the distributions of potential arable land differed among grains, depending on the natural growth conditions of each grain. By combining potential land-area maps for rice, wheat, corn, and bean production into a single map and overlaying it on a map of actual farmland, we can identify the areas available for cultivation and vulnerable areas that are likely to be deteriorated by unsuitable cultivation (Figure 3) 21). All areas identified to be suitable for cultivation in Figure 3 will not necessarily be cultivated in the future. According to provincial plans of future land use, most provinces have planned to preserve or even increase forests and grassland rather than to increase arable land. The general trend of future changes in land use in China is that urban and residential areas will continue to increase around cities, but expansion of arable land will be restricted, even though suitable land for cultivation remains 22). Regardless, to create maps of future grain supplies and land productivity for each grain type, potential land use should be specified for each grid cell. Keeping these things in mind, we created 20-km grid maps of the yield of the 3 major grains for 2025 by using the lowest value among our three projections for each cell as the final projection of grain yields in ). We also created 20-km grid maps of the consumption of the 3 major grains for 2025 preparing two scenarios for food consumption patterns in China for ). We have produced a 20-km grid distribution map of population in China for ). Therefore, if grain consumption per capita had been given for each grid cell, we would have created 20-km grid maps of grain consumption for 2025 by overlying these maps on the map of population distribution. However, it was impossible for us to get the precise data on future grain consumption per capita for each grid cell. Thus, we had to adopt a scenario aided approach to create the consumption distribution map in We assumed two patterns for a Chinese food consumption pattern (intake of food per capita) in ) : Scenario 1: China-Japan food balance based on the averages of grain and meat consumptions Scenario 2: China-USA food balance based on the averages of grain and meat consumption The 20-km grid maps of the balance of yield and consumption for rice, wheat and corn in 2025 are shown in Figure 4 a, b, c (scenario 1) and d, e, f (scenario 2), respectively. Green colored cells show that grain yield is higher than grain consumption, and red colored cells show that grain yield is lower than consumption. The national total of all grains yields exceeded that of all grains consumptions in 2025 for both consumption scenarios. There are not so much differences between the cases of consumption scenario 1 (China-Japan type) and scenario 2(China-USA type) in the distribution patterns of the food balance. In terms of the balance distribution of corn (maize ), consumption will exceed yield pretty much in southern China and yield will exceed consumption in northern China. This tendency is particularly remarkable in scenario 2 in which the amount of meat intake dramatically increases. We should remind that these balance maps do not include any elements of

8 8 domestic and international transport of grains. Therefore, real situation of the food balance distribution may be different from that shown here. However, the maps shown here give us very basic information to discuss current and future food balance distribution comprehensively. Figure 4 20-km grid maps of the balance of yield and consumption for rice, wheat and corn in mainland China for 2025

9 9 3.2 Diagnostic analysis of land productivity in northern and northeastern China We developed 1-km grid maps of potential productivities for the main crops under different limiting factors, and possible increases in crop production due to improvement of limiting factors. County or province administrative boundaries were overlaid and a statistical database of potential productivities and possible increases in production for each crop were produced at both county and provincial levels Potential productivities We found that neither P Q nor P T showed much difference between areas within our study area, which might be the reflection of homogeneity of temperature and solar radiation conditions in the region. In contrast, P W and P L showed a wide range of spatial variation, which might be the reflection of the heterogeneity of water and soil conditions. P Q for each crop increased gradually from northeast to southwest, correlated with the distribution of solar radiation, and P T for each crop decreased gradually from south to north according to the spatial change in temperature. P W and P L generally decreased from southeast to northwest, but both fluctuated spatially, depending on the complex interactions between heat, water, and soil conditions. Comparing among crops, we found that the potential productivities of corn and rice were much higher than those of sorghum and beans. This is largely due to the shorter growing periods of sorghum and beans relative to those of corn and rice, and the less effective transfer of radiation into organic matter in the latter than the former Possible increases in crop production As mentioned above, our model can estimate possible increases in the production of each crop under different conditions, such as improved heat, water, or soil conditions or improved agricultural techniques. This is illustrated here with maps of possible increases in grain production (Figure 5), where grain production refers to the average values of the production of corn, rice, wheat, beans, and sorghum and Y96 is the average yield of four crops. P T P Q P T a P W P T - P W b c P L P W - P L P G P L Y 96 d Figure 5 Example maps showing the possible increases in crop production under different conditions

10 10 Measures to improve thermal conditions include, for example, use of glass houses or ground-surface coverings, and supply of an artificial heat source. The possible increase in grain production by improving thermal conditions, P T, increases gradually from southeast to northwest (Figure 5a), which correlates well with the distribution of temperature. Namely, P T is large in the north where temperatures are low, but low in the warmer south. Comparing P T with P Q, we find that temperature limitations result in approximately 10% 30% decreases in crop production in the south, such as in Liaoning, Hebei, and Shangdong provinces, and >50% decreases in the north, such as in Heilongjiang province and in the Inner Mongolia autonomous region. One effective measure to improve water conditions is to convert rain-fed cultivation into irrigated cultivation, leading to large increases in crop production. The possible increase in P W is achieved by improved heat and water conditions, and is, therefore, spatially complex (Figure 5b). P W is very large in the western arid and semi -arid areas, where precipitation is less than 400 mm. In such areas, the water deficit causes a more than 50 % reduction in production of crops such as corn, beans, sorghum, and millet. Conversely, water conditions are relatively good in the Northeast China Plain, so P W is small because the water deficit causes a reduction in crop production of only < 20%. Natural soils are not very suitable for crop production, but can be improved by changing soil texture, soil nutrition, and soil degradation conditions. Crop production can be greatly increased by improving soil conditions in both the coastal area around the Bohai Sea, where coastal colonchaks with high salt content naturally dominate, and in the mountainous area, where soils are easily eroded ( P L, Figure 5c). Conversely, P L is relatively small in the vast plains, where soil conditions are relatively good for cultivation. Possible increases in P G can be achieved by the development of new seed, rational application of fertilizers, improvement of planting techniques, and protection from plant disease. A map of the difference in evaluated land productivity and the actual grain yield in 1996 for arable land, derived from county-level statistics (Figure 5d), shows that the actual yield was less than the potential yield in most areas, suggesting that land productivity can be improved. Some small areas where the actual yield was greater than P L are considered to have well-organized irrigation systems, or good management and high technology. Finally, we believe that crop production in northern and northeastern China will eventually increase 2- to 3-fold and reach the potential thermal productivity (P T ) in the future. According to Gao 10), the actual yield of corn and rice at several experimental fields in the Northeast China Plain has reached 1500 t/km 2, equivalent to the potential thermal productivity. However, from the trends in increases in crop yields during , we predict that it will take more than years for whole northern and northeastern China to achieve the potential thermal productivity. 3.3 Groundwater problems in northern China The National Institute of Hydrogeology & Engineering Geology, China, conducted a geological survey, including boreholes, for the Huang-Huai-Hai Plain (lat N, long 'E) from 1982 to The survey results showed that the Quaternary deposits in the Hebei Plain are deep, generally reaching m in depth, and comprise four aquifers. The depths of the four aquifers are 20 40, , , and m below the surface. The Hebei Plain is one of the largest agricultural areas in China, belonging to the Haihe River drainage area of eastern China. The water resources of the Hebei Plain are not abundant; the amount of usable unconfined and confined groundwater resources are billion m 3 /y and billion m 3 /y, respectively. The amount of surface water is strongly affected by fluctuations in annual precipitation and varies greatly, and thus is not a stable source of water. Before the 1970s, pumping of groundwater was low, and neither unconfined nor confined groundwater was affected by human activities. Thus, the groundwater level fluctuated within a specific range in accordance with the annual precipitation. After the 1970s, increased pumping of groundwater began to result in the fall of the water table, land subsidence, and other environmental problems. The greatest decrease in the unconfined

11 11 groundwater level during the past 30 years in the Hebei Plain was seen at the foot of the western mountains, where the water table was lowered by m. The decrease was less extreme in the central and coastal regions, where the water table was lowered by 2 10 m. For example, the rates of decrease of the unconfined groundwater level at Shijiazhuang, Hengshui, and Cangzhou were 0.67 m/y, 0.17 m/y, and 0.11 m/y, respectively. Through the routine monitoring of groundwater levels in hundreds of wells, we found that the flow of unconfined groundwater has changed. The unconfined groundwater used to flow naturally in the SEE direction, however, it now flows toward urban areas because of the funnel-shaped curvature of the water table 24). We simulated future temporal changes in the water table for given groundwater usage scenarios 25), 26). Three scenarios of groundwater pumping were used in the simulations: (1) Scenario 1: The amount of groundwater pumping is zero for each cell up to No land-use change. (2) Scenario 2: The amount of groundwater pumping is the same as that in 1994 for each cell up to No land-use change. (3) Scenario 3: The amount of groundwater pumping for irrigation is the same as that in 1994 for each cell up to However, the amount for industrial usage continues increasing at the rate of 6%/y (past trend), and that for domestic usage, at the rate of 2%/y up to No land-use change. (4) Scenario 4: The same groundwater pumping scenario as that of Scenario 3. Urban area will expand to twice bigger than that of 1987 by the end of (5) Scenario 5: The amount of groundwater pumping for irrigation is the same as that in 1994 for each cell up to However, the amount for industrial usage is times more than that of 1994 in urban areas, or times, in rural areas by the end of The amount for domestic usage is 2.9 times more than that of 1994 by the end of No land-use change. (6) Scenario 6: The same groundwater pumping scenario as that of Scenario 5. Urban area will expand to twice bigger than that of 1987 by the end of The initial conditions of unconfined and confined groundwater tables are based on 1994 observed data. The simulated results for Scenario 1 are as follows: i) The central and eastern areas of the plain would recover their previous groundwater table within 5 years from the beginning of the simulation. ii) The recovering groundwater table is around 3 m below the surface. The capillary height of the plain is around 5 m. Therefore, if the groundwater table recovers to pre-pumping levels, salinization would become a problem. iii) Sustainable amounts of groundwater pumping would be desirable in the central and eastern areas for sustainable agriculture. Under the simulation for Scenario 3, the unconfined groundwater table would fall by more than 20 m in the western area of the plain by 2030, where several cities (population: 1 2 million) are located along the foothills of the western mountains (Figure 6). Such decreases may entirely deplete unconfined groundwater supplies in those areas. Similarly, the head of the confined groundwater would fall by more than 40 m in the eastern area of the plain by 2030 (Figure 7), falling below sea level in most areas of the plain except for the western foothills region. Simulated temporal changes in the unconfined groundwater level in three cities for the three scenarios showed that the decrease in the groundwater level for scenario 2 was less than that for scenario 3, although the magnitude of the decrease was extreme in both cases (Figure 8). Unless strong countermeasures are taken to conserve groundwater resources in China, s cenarios 2 and 3 may be realistic predictions of future groundwater pumping in the plain, resulting in serious deterioration of groundwater resources and the environment in the future.

12 12 Figure 6 Simulated results of falls in water level of the unconfined aquifer in 2030 (based on 2-km grid scale, Scenario 3). Figure 7 Simulated results of falls in the head of the confined aquifer in 2030 (based on 2-km grid scale, Scenario 3). Cangzhou Hengshui Shijiazhuang Shijiazhuang Hengshui Cangzhou Scenario 1 Scenario 2 Scenario 3 Figure 8 Simulated temporal changes in water level of the unconfined aquifer in three cities (Shijiazhuang, Henghsui, and Cangzhuo) for different scenarios 3.4 Analysis of changes in land use in the lower Yangtze River basin Once we have identified the driving factors for urban growth, it is possible to simulate urban growth on the basis of those factors. We first estimate changes in the trends of these factors, and then use their values as input into the simulation process, with simulated growth as the output. An example of simulated urban growth for 2020 is shown in Figure 9.This figure may reveal the spatial patterns of future urban expansion. From this figure, it may be found that urban expansion will occur mainly around the cities, especially on the cities along the main roads, such as Changzhou, Wuxi and Suzhou. These three cities trend to be likely connected with each by urban area along the roads.

13 13 Figure 9 Simulation result of future urban growth in the lowest Yangtze river basin 4. Conclusions (1) GIS-based study on food balance in China To discuss the current and future food balances for mainland China with the help of a GIS, the following 20-km grid maps were produced: 1) Population distribution maps for the 1990 and 2025; 2) Grain yield maps for rice, wheat, corn, and all grains (all cereal grains, beans and potatoes) in 1990, 1995 and 2025; 3) Grain consumption maps for rice, wheat, corn and all grains in 1990, 1995 and 2025; 4) Maps of actual arable land in 1997; 5) Map of land potentially available for cultivation; and 6) Map of predicted land use in Overlaying these maps, we created the food balance map for mainland China. The national total of all grains yields exceeded that of all grains consumptions in However, this does not necessarily mean that grain yields exceed gra in consumptions everywhere in China. The balance distribution map shows that there were so many locations where grain consumptions exceeded grain yields. The national total of all grains yields also exceeded that of all grains consumptions in 2025 for both consumption scenarios; however, there are so many areas where consumption exceeds yield. For instance, in the case of rice, consumption will exceed yield pretty much in northern China, on the contrary, in the cases of wheat and corn, consumption will exceed yield pretty much in southern China. This tendency of corn is particularly remarkable in scenario 2 in which the amount of meat intake dramatically increases. The created 20-km balance maps do not include any elements of domestic and international transport of grains. Nevertheless, they suggest us that domestic transportation between counties and provinces took an important role to feed people in China and will do so in the future. (2) Diagnostic analysis of land productivity in northern and northeastern China In order to evaluate the potential productivities and possible increases in crop production, we developed a set of digital maps including base maps, socio -economic maps, meteorological maps, soil maps, and land-use/cover maps at a scale of 1:1,000,000 (a ground resolution of about 1 km). We then created a set of maps that include crop potential productivities under different limiting factors, and the possible increase of production for each crop by improving those limiting factors. Although crop production can be increased by improving temperature, water, and soil conditions and agricultural technology, we must keep in mind that many environment problems might result from these activities. For example, (1) huge amounts of plastic materials are used for improving thermal conditions, which may became direct pollutants in the field; (2) application of large amounts of chemicals and fertilizer for the improvement of soil nutrition may cause serious soil and water pollution; (3) relocation of water and cultivation on sloping land for the improvement of water conditions may cause many environmental problems, such as soil erosion, salinization, and desertification. All these problems will then feed back into the agricultural production system and disturb the regional sustainable development.

14 14 (3) Groundwater problems in northern China The unconfined groundwater level and the confined groundwater head have continuously fallen in cities and their surrounding areas in the western part of the Hebei Plain. The confined groundwater head has fallen faster in the eastern than in the western area of the plain. According to the simulation for given future groundwater-pumping and land-use scenarios, the western area would experience serious shortages of unconfined groundwater and the eastern area would experience very serious salinization problems in the confined aquifer, owing to the fall of the groundwater head to m below sea level. (4) Analysis of changes in land use in the lower Yangtze River basin Through simulations and analyses, we know that the driving factors of urban expansion in the southern region of Jiangsu Province were population and industry in townships/villages in that period The case study also shows that urban expansion can be estimated by changes in land cover by using remote sensing and GIS. Additionally, a diffusion-based model can be applied to urban growth on a regional scale, where only coarse data are used. 5. Acknowledgments The author is very grateful to Prof. Lin Li, Dr. Qinxue Wang, and Dr. Zhaoji Zhang, former Eco-Frontier fellows of the Environment Agency of Japan, for their great help in creating the digital maps presented in this report. To conduct research projects on environmental problems in Asia, inevitably research collaboration with scientists and researchers of several nations is involved. I thank my collaborators. References 1) Wang, Q. and Otsubo, K. (2000): Estimation of Potential Land Productivity in North and Northeast China by GIS, LU/GEC Project Report VI, CGER-REPORT, CGER-I (ISSN ), pp ) Gong, J. and Otsubo, K. (1999): A New Approach to Modeling Land-use Change Applicable to a Limitied Data Set, LAND USE FOR GLOBAL ENVIRONMENTAL CONSERVATION (LU/GEC) - FINAL REPORT OF THE LU/GEC FIRST PAHSE ( )-, CGER-REPORT, CGER-I032-'99 (ISSN ), pp ) Otsubo, K. (1999): Outline of the LU/GEC Project, Proceedings of 1999 NIES Workshop on Information Bases and Modeling for Land-use and Land-cover Change Studies in East Asia, CGER-REPORT, CGER-I036-'99 (ISSN ), pp ) Otsubo, K., Nakaya, T. and Shimizu, Y.(2001): Human impact and land use/cover change, Global Mapping Forum 2000 proceedings(cd). 5) Otsubo, K., Wang, Q., Shimizu, Y., Bito, A. and Kondo, A. (2002): Distributions of Major Grain Yields in Mainland China in the 1990s and in 2025, LU/GEC Project Report IIX, CGER-I (ISSN ), pp ) Otsubo, K., Wang, Q., Nakaya, T., Shimizu, Y., Bito, A., Ichinose, T. and Kondo, A. (2002): 20-km Grid Analysis on Current and Future Situations of Food Balance in Mainland China, LU/GEC Project Report IIX, CGER-I (ISSN ), pp ) Nakaya, T. (2000): Projection of geographical Distribution of the Chinese Population up to 2025, LU/GEC Project Report VI, CGER-I (ISSN ), pp (in Japanese). 8) Nakaya, T. and Shimizu, Y. (2002): A Grid-surface Projection of Major Grain Consumption in China, LU/GEC Project Report IIX, CGER-I (ISSN ), pp ) Yu, H and Zhao, F. (1982): Light and Thermal Resources and Photosynthetic Thermal Productivity, Acta Meteologica Sinica, p ) Gao, S. (1995): Research on Agro -climatic Productivity and Strategy of Utilization in Northern China, China Meteorological Press, Beijing.

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