Study on Soil and Water Resource Management for ChiaNan Irrigation Association in Taiwan Kuo, Sheng-Feng Associate Professor, Institute ofResource and Environment, Leader College ofManagement

Chen,Yi-Wen and Shieh, Sheng-Hsien Graduate Student, Institute ofResource and Environment, Leader College ofManagement

ABSTRACT ChiaNan irrigated area is the most important production region in Taiwan and the irrigated area operated by ChaiNan Irrigation Association is 77,822 ha. This study installs the data-logger and watermark soil sensor with seven difference depths, i.e. 10cm, 20cm, 30 cm, 40cm, 60 cm, 90 cm, 120 em, in the HsuehChai Experiment Station of ChaiNan Irrigation Association to collect and analyze the soil moisture variation on the field. The basic data used to evaluate the water management technical and estimate the agricultural water resource requirements in ChaiNan irrigated area. The results from CROPWAT model show that the annual potential evapotranspiration and effective rainfall in ChaiNan irrigated area are 1444 mm and 897 mm, respectively. In the paddy fields, the crop water requirements and deep percolation are respectively 962 mm and 295 mm for the first rice crop, and 1114 mm and 296 mm for the second rice crop. Regarding the upland crops, the crop water requirements for spring and autumn corns are 358 mm and 273 mm, for sorghum 332 mm and 366 mm, 350 and 264 mm for soybean, respectively. Keywords : crops water requirements, soil moisture variation, field experiment, irrigation association

1. INTRODUCTION Paddy is the important crop to growth in Taiwan, whenever irrigation water is available. Due to the recent socio-economic changes, the water demand has been increasing with the expansion of industrialization and urbanization. The acquisition of new water supplies for agricultural irrigation has become more difficult and costly. For effectively and efficiently using the available water sources to meet the possible variation of cropping patterns, irrigation management plays an important role. To facilitate the management practice, experimental data based irrigation management model can be applied to estimate the crop water demand and to upgrade the capability of irrigation management in 17 Irrigation Associations in Taiwan. ChiaNan Irrigation Association (IA) is the biggest IA among the 17 lAs in Taiwan. It has a total service area of 78,422 ha as of 1999. The Association, to service 182,903 farmer members, has employed 678 staff members and assigned to 72 working stations located in the service area of subtropical zone. The area has an average annual temperature of 21 °-24°C, and annual rainfall of2500 mm of which 80% are concentrated in the wetseason from May to September The area of similar meteorological condition above in Taiwan totals about 595,415 ha which is about 68.6% of total Taiwan's agriculture land. There were also occasions of shortages of

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water, after 1978 in Taiwan. In order to balance the food production, a lot of agriculture lands were changed to planting upland crops from paddy rice, such as com, sorghum etc. Accordingly, a lot of experiments for upland crop irrigation were done in this station. The results can be applied in the large area of agricultural land in Taiwan, but also in other sub-tropic zone in the world. The upland crop irrigation requirement is much less than that for paddy rice. The water saved from upland crop irrigation can be thus diverted to irrigate paddy rice, so that the upland crops and paddy rice cropping pattern is used in this district. Many existing models conduct on-farm simulation of water demands based on climate-soil-plant systems. George, et al. (2000) developed an irrigation scheduling model (ISM) for perforating irrigation scheduling. The model was tested against field data and the CROPWAT model. The results showed that the two models, ISM and CROPWAT, gave similar values of soil moisture but some variation after second irrigation. Anadranistakis, et al. (2000) used a model for estimating crop water requirements and the model has been validated with meteorological and crop data collected from experiment fields. Results were verified for three crops (cotton, wheat and maize) against soil moisture profile changes with very satisfactory results. Agreement between observed and estimated crop water requirements are within 8%. Abdelhadi, et al. (2000) used Penman-Monteith equation with derived crop coefficients to estimate the crop water requirements in arid region. Arora and Gajri (2000) used a crop growth-water balance model to predict maize growth and yield in a SUbtropical environment. Model assessment showed that simulated biomass and grain yield of maize wereclose to the measured data in medium water-retentive sandy loam. Shae, et aL (1999) executed a four year field study of four irrigation scheduling and application methods for potatoes on a sandy loam soiL The study showed that improved irrigation methods can save water without compromising potato yield or quality. Prajamwong (1994) developed the Command Area Decision Support Model (CADSM) and consists of three main sub-models: (1) weather and field generation; (2) on-field crop-soil water balance simulation; and, (3) water allocation and distribution. Kuo (1995) developed the Irrigation Simulation and Optimization Model (ISOM) based on the implementation of genetic algorithm (GA) method to on-farm irrigation simulation for optimizing the allocation of irrigated area to alternative crops for maximum net benefit of irrigated project. Pleban and Israeli (1989) stated that the on-farm water balance is the normal method to decide the amount of water to apply at each irrigation. Chen (1999) censused that the practical irrigation water requirements of single rice crop in HsuehChia Working Station are 1386 mm in 1999. Field experiments provide the basic data essential for irrigation management. Therefore, the HsuehChia Experiment Station of ChiaNan Irrigation Association in Taiwan conducted field experiments to evaluate the crop water requirements and crop coefficients for com, sorghum and soybean respectively for the year from 1985 to 1995. Shih (1986, 1997) stated the experiment procedures and results from HsuehChia Experiment Station of ChiaNan Irrigation Association in Taiwan. The CROPWAT, developed by Smith (1991 ) of the Food Agricultural Organization (FAO), was used in this study to evaluate the crop water requirements in the ChiaNan irrigation district by use of field experiment data from HsuehChia experiment station.

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2. FIELD EXPERIMENT The experiment site was at HsuehChia Experimental Station in southern Taiwan, which is 0 located at 23°13N, 120 11E and 4 m above MSL in sub-tropic area. The experiment station's monthly mean temperatures vary from 18.2°C in February to 28.SoC in June, monthly mean relative humidity ranges from 76.9% in February to 7S.5% in June, and monthly mean solar radiation varies from 221.2 callcrn2.day in February to 283.1 cal/cm2.day in June. A weather station set up at the experiment site recorded regularly the air temperature, solar radiation, as well as wind speed and direction from 1964 to 1999. Crop evapotranspiration was measured both in the field and lysimeters, the same crops were also planted in both sites in the same growing seasons. The lysimeters were constructed with concrete of 3m * Sm * 3 m in size and layered with filters at the bottom, to measure runoff and deep percolation water. The soil textures of the packed soil were of silty loam and loam. In Table 1 are listed the soil textures and soil moisture constants at different soil layers. The overall system consisted of twelve lysimeter blocks, and 10 plots in the field which were supplied irrigation water with pipes. All irrigation was carried out by the corrugation method. Irrigation water was applied to maintain the soil moisture at SO% of maximum available soil moisture during the crop growth season. The gravimetric method was employed to determine the soil moisture content. Soil moisture was determined by weighing the soil sample before and after irrigation using oven drying for 24 hours. The soil sampling was made at 0.1 m intervals to a depth of 0.6 m. The crop coefficient (Kc) was determined by dividing the measured actual ET by reference crop ET0, as computed from the modified Penman equation. Table 2 shows the length of crop growth stage in ChiaNan irrigation district. Tables 3,4 and S show the experimental results of actual evapotranspiration and crop coefficient for com, sorghum and soybean from 1986 to 1995, respectively. Related to the 1999 water management data from HsuehChia Working Station, the on farm irrigation efficiency is 70% that also the required input data for modeL This study also installs the data-logger and watermark soil sensor with seven difference depths, i.e. 10 cm , 20 cm , 30 cm , 40 cm , 60 em, 90 cm , 120 cm , in the experiment station of ChaiNan Irrigation Association to collect and analyze the soil moisture variation on the field. The basic data used to evaluate the water management technical and estimate the agricultural water resource requirements in ChiaNan irrigated area. Figure 1 shows the watermark with seven different depth install on the field of HusehChai Experiment Station of ChiaNan Irrigation Association. Figure 2 shows computer connect to data-logger to download data. Figures 3 &4 demonstrate the soil moisture variation on the field.

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3. METHODOLOGY Figure 3 shows the flowchart of CROPWAT model to evaluate the crop water requirement in ChaiNai irrigated area. In Fig. 1, it can be seen that the input data cover crop, climate, and soil. The climate data includes: (1) maximum and minimum temperature; (2) wind speed; (3) sunshine hours; (4) relativity humidity; and (5) rainfall. Based on the monthly meteorology data, CROPWAT model can used Penman-Monteith explicit equation to calculate the potential evapotranspiration (ET0)' The basal crop coefficient (Kcb) represents the effects of the crop canopy on evapotranspiration and varies with time of year. The rate of change of the basal crop coefficient with time can be approximated as a linear increase (or decrease), as expressed in the Eq. 1 (prajamwing 1994):

(1) and,

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jk-l ~j ~jk where K~b denotes the basal crop coefficient for day j; K:b-1 represents the basal crop coefficient at the current stage; jk-l is the beginning day of current crop stage; jk denotes the beginning day of the next crop growing stage; k represents the stage of development of the crop; and j is the day of year. The daily reference crop evapotranspiration (ET0) is used to calculate the potential crop evapotranspiration (ETc) and actual crop evapotranspiration (ETca), as given in Eqs. 2 and 3,

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(4) In(101) where ETca denotes the "actual" crop evapotranspiration; Ka represents the soil moisture stress coefficient; Ks is the coefficient for evaporation rate from a wet soil surface after irrigation and or rainfall; ej denotes the soil moisture by volume at the day; efc and ewp represent the soil moistures by volume at the field capacity and wilting point. For on-demand irrigation scheduling, irrigation should be performed when the Soil Moisture Depletion (SMD) initially exceeds the allowable depletion (AD). The required amount, or application depth, in a given irrigation (IRR), and allowable depletion (AD), can be mathematically described by Eqs. 5 and 6, respectively. SMD. j IR (Ee*~) (5)

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AD J=(e !c--f)wp fRZ /MADslage (6) where IRj denotes the irrigation requirement on the day~ SMDj represents the soil moisture depletion on the jth day; Ec is the conveyance coefficient; Ea denotes the water application efficiency; RZj represents the crop's root depth on the jth day; and MAD stage is the maximum allowable soil water depletion on each stage. Given the input of the requirement data, the CROPWAT model can be used to calculate crop-related data in each decade of a month, such as: (1) crop coefficient, (2) crop leaf index, (3) crop evapotranspiration, (4) percolation, (5) effective rainfall, and (6) crop water requirements. Also, the model can be applied to estimate the irrigation schedule for each crop with 5 different options: (1) each irrigation defined by irrigation manager, (2) irrigation at below or above critical soil depletion (% RAM), (3) irrigation at fixed interval per crop growing stage, (4) deficit irrigation, and (5) no irrigation. Afterwards, the CROPWAT model can simulate the on-farm crop water balance, including: (1) irrigation times, dates and depths, (2) soil moisture depletion, (3) amount of percolation, (4) actual crop evapotranspiration, and (5) crop yield. The on-farm water balance was based on the theory ofEq (7) below:

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ETc: actual crop evapotranspiration (mm)

PE : effective rainfall (mm)

IR: irrigation depth (mm)

RO: runoff (mm)

DP: deep percolation (mm)

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