**2.7.3 Cumulative Rice Relative Water Supply (CRRWS)**

The Cumulative Rice Relative Water Supply (CRRWS) values were plotted for both seasons of 2003/04 as shown in Figs. 7a and 7b. These plots have three other curves designated as CRRWS = 1.0 staggered by one month. The relative merits and demerits between the plots CRWS and CRRWS have brought the robustness of using the new indicators for evaluating irrigation delivery performance as the season advances. The slope of the actual CRRWS curve provides useful management information, which can enhance the decision-making for the irrigation delivery. If there is an increasing slope of CRRWS line with respect to the CRRWS = 1.0 line then irrigation supply could be slightly curtailed in the next irrigation period. On the other hand, if the slope is downwards and is reaching the lower CRRWS = 1.0 line, the supply could be increased for the next irrigation period. The coinciding between actual CRRWS and CRRWS = 1.0 lines characterizes well water distribution. The CRRWS plot should be maintained at the CRRWS = 1.0 to improve irrigation delivery performance.

The CRRWS\_I, CRRWS\_II and CRRWS\_III represent Cumulative Rice Relative Water Supply (CRRWS) for Irrigation Service Area (ISA) I, II and III, respectively. In Fig. 6a, the CRRWS values obtained higher than 1.0 during the land preparation periods in ISA I, ISAII and ISA III but lower at normal irrigation periods in ISA I. The slope of CRRWS line of ISA I decreased when land preparation was started in ISA II and the slope of CRRWS line of ISA II decreased after starting the land preparation in ISA III due to water shortage in the offseason. The plot for all irrigation service areas are shown normally under supply condition after completing land preparation in ISA I from May.

In the Fig. 7b, the CRRWS values obtained were higher than 1.0 during the land preparation periods in ISA I, ISAII and ISA III but lower at normal irrigation periods in ISA I. The slope of CRRWS line of ISA I started to decrease when land preparation was started in ISA II and the slope of CRRWS line of ISA II decreased after starting the land preparation in ISA III in the main season. The irrigation supplies for all irrigation service areas were not shown under supply condition throughout the irrigation season. The slope of the CRRWS line for ISA III shows better irrigation delivery performance than ISA and ISA II. The plot shows that available water resources could not meet field water demand at the design ponding water level 10 cm during normal irrigation periods. The utilization of rainfall plays an important role to maintain target standing water depth in the fields. The oversupply conditions were normally found on rainy days.

### **2.7.4 Ponding Water Index (PWI)**

A daily analysis of Ponding Water Index (PWI) was plotted for the main and off seasons in 2003/04 as shown in Fig. 8. The PWI\_I, PWI\_II and PWI\_III represent Ponding Water Index

From this scenario, it is noticed that oversupply conditions were found only during the presaturation period in the first month for each ISA. Undersupply condition was found during the normal irrigation supply for all ISAs. If irrigation supply would follow the RRWS guideline, then it could be possible to overcome the oversupply and undersupply conditions. If irrigation supplies would be curtailed for the ISA II and increase for the ISA I then irrigation delivery might have maintained good conditions as shown in the middle of

The Cumulative Rice Relative Water Supply (CRRWS) values were plotted for both seasons of 2003/04 as shown in Figs. 7a and 7b. These plots have three other curves designated as CRRWS = 1.0 staggered by one month. The relative merits and demerits between the plots CRWS and CRRWS have brought the robustness of using the new indicators for evaluating irrigation delivery performance as the season advances. The slope of the actual CRRWS curve provides useful management information, which can enhance the decision-making for the irrigation delivery. If there is an increasing slope of CRRWS line with respect to the CRRWS = 1.0 line then irrigation supply could be slightly curtailed in the next irrigation period. On the other hand, if the slope is downwards and is reaching the lower CRRWS = 1.0 line, the supply could be increased for the next irrigation period. The coinciding between actual CRRWS and CRRWS = 1.0 lines characterizes well water distribution. The CRRWS plot should be maintained at the CRRWS = 1.0 to improve irrigation delivery performance. The CRRWS\_I, CRRWS\_II and CRRWS\_III represent Cumulative Rice Relative Water Supply (CRRWS) for Irrigation Service Area (ISA) I, II and III, respectively. In Fig. 6a, the CRRWS values obtained higher than 1.0 during the land preparation periods in ISA I, ISAII and ISA III but lower at normal irrigation periods in ISA I. The slope of CRRWS line of ISA I decreased when land preparation was started in ISA II and the slope of CRRWS line of ISA II decreased after starting the land preparation in ISA III due to water shortage in the offseason. The plot for all irrigation service areas are shown normally under supply condition

In the Fig. 7b, the CRRWS values obtained were higher than 1.0 during the land preparation periods in ISA I, ISAII and ISA III but lower at normal irrigation periods in ISA I. The slope of CRRWS line of ISA I started to decrease when land preparation was started in ISA II and the slope of CRRWS line of ISA II decreased after starting the land preparation in ISA III in the main season. The irrigation supplies for all irrigation service areas were not shown under supply condition throughout the irrigation season. The slope of the CRRWS line for ISA III shows better irrigation delivery performance than ISA and ISA II. The plot shows that available water resources could not meet field water demand at the design ponding water level 10 cm during normal irrigation periods. The utilization of rainfall plays an important role to maintain target standing water depth in the fields. The oversupply

A daily analysis of Ponding Water Index (PWI) was plotted for the main and off seasons in 2003/04 as shown in Fig. 8. The PWI\_I, PWI\_II and PWI\_III represent Ponding Water Index

**2.7.3 Cumulative Rice Relative Water Supply (CRRWS)** 

after completing land preparation in ISA I from May.

conditions were normally found on rainy days.

**2.7.4 Ponding Water Index (PWI)** 

the plot in Fig. 6.

(a) Main Season in 2003/04

(b) Off Season in 2003/04

Fig. 7. Characterizing Daily Irrigation Delivery Performance using CRRWS

Paddy Water Management for Precision Farming of Rice 125

weakness of using the Relative Water Supply (RWS) and Cumulative Relative Water Supply (CRWS) and its adverse implications on irrigation management and operation was also highlighted. Each performance indicator has its own strengths and weaknesses, which may be relevant under particular conditions. The RRWS and CRRWS parameters instead of RWS and CRWS were found to be more useful for the irrigation managers and water users to

The RRWS and CRRWS can simply and distinctly characterize irrigation delivery performance with respect to the RRWS = 1.0. It gives the following interpretation over periodic irrigation

RRWSj = 1.0 Good irrigation delivery

RRWSj > 1.0 Oversupply condition

RRWSj < 1.0 Undersupply condition • The RWSj concept shows the over supply condition for not considering the depleted water depth (WSmaxj – WSj) of the denominator in RWS given by Levin (1982) when

• The utility of RRWS and CRRWS justify the weakness of RWS and CRWS to evaluate

• It recommends that irrigation supply should be curtailed for increasing the slope of the actual CRRWS line than the CRRWS = 1.0 line to improve the irrigation delivery

• Irrigation system can be operated even at RRWS = 0.5 to irrigate wider areas due to water shortage if the Ponding water depth is retained more than the field water

The Ponding Water Index (PWI) also can simply characterize irrigation delivery performance. It gives the following interpretation over periodic irrigation supply at the end of a period:

PWIj = 0 Good irrigation delivery condition

PWIj > 0 Oversupply condition

PWIj < 0 Undersupply condition The new indicators have successfully been evaluated for various water management scenarios in the study area. Therefore, they can be adopted to evaluate irrigation delivery performance and proper decision for water allocation for irrigated paddy. GIS interface coupled with new performance indicators has explicitly helped in integrating spatial and temporal information for evaluating the daily irrigation delivery performances for paddy cultivation. The new irrigation performance indicators are able to provide useful information and can be adopted to evaluate irrigation delivery performance and proper decision for water allocation in the paddy irrigation system. The availability of such a quantitative tool for irrigation systems operation can have a powerful impact on the overall

characterize the water delivery performance for the paddy irrigation systems.

supply at the end of a period:

performance.

WSj < WSmaxj in the paddy fields.

demand for the next period.

the irrigation water delivery for paddy irrigation systems.

water management strategy in an irrigation project area.

The following conclusions can be drawn from the study on performance indicators:

(PWI) for Irrigation Service Area (ISA) I, II and III, respectively. The undersupply condition was obtained due to shortage of water resources. The extreme values computed due to continuing irrigation deliveries while sufficient water remained in the fields. The oversupply condition is shown during land preparation period and especially rainy days. The peak negative values are due to severe shortage of water.

Fig. 8. Characterizing Daily Irrigation Delivery Performance using Ponding Water Index (PWI) for the Main Season in 2003/04

Irrigation deliveries have shown oversupply due to more rainfall from 20-24 November and end of the season in the main season. The days on the x-axis at zero value shows the wellwatered condition. Irrigation deliveries will be considered as over supply or under supply if PWI is more or less than zero, respectively. The irrigation manager can simply identify and quantify the performance of irrigation deliveries for a given day and what decision has to be made for the next period. Both the PWI and RRWS can quantify and identify irrigation deliveries simultaneously. The average variation of the PWI values is higher in the off season than in the main season. The PWI also represents under supply condition in the off season as more severe than in the main season. Besides, the values of PWI are very close to PWI = 0 for the main season. The peak values are shown due to heavy rainfall.

### **2.8 New water management tool**

This book chapter illustrates new irrigation performance indicators known as the Rice Relative Water Supply (RRWS) and Cumulative Rice Relative Water Supply (CRRWS) to evaluate irrigation water delivery performance of the paddy rice irrigation systems. The

(PWI) for Irrigation Service Area (ISA) I, II and III, respectively. The undersupply condition was obtained due to shortage of water resources. The extreme values computed due to continuing irrigation deliveries while sufficient water remained in the fields. The oversupply condition is shown during land preparation period and especially rainy days.

Fig. 8. Characterizing Daily Irrigation Delivery Performance using Ponding Water Index

PWI = 0 for the main season. The peak values are shown due to heavy rainfall.

Irrigation deliveries have shown oversupply due to more rainfall from 20-24 November and end of the season in the main season. The days on the x-axis at zero value shows the wellwatered condition. Irrigation deliveries will be considered as over supply or under supply if PWI is more or less than zero, respectively. The irrigation manager can simply identify and quantify the performance of irrigation deliveries for a given day and what decision has to be made for the next period. Both the PWI and RRWS can quantify and identify irrigation deliveries simultaneously. The average variation of the PWI values is higher in the off season than in the main season. The PWI also represents under supply condition in the off season as more severe than in the main season. Besides, the values of PWI are very close to

This book chapter illustrates new irrigation performance indicators known as the Rice Relative Water Supply (RRWS) and Cumulative Rice Relative Water Supply (CRRWS) to evaluate irrigation water delivery performance of the paddy rice irrigation systems. The

(PWI) for the Main Season in 2003/04

**2.8 New water management tool** 

The peak negative values are due to severe shortage of water.

weakness of using the Relative Water Supply (RWS) and Cumulative Relative Water Supply (CRWS) and its adverse implications on irrigation management and operation was also highlighted. Each performance indicator has its own strengths and weaknesses, which may be relevant under particular conditions. The RRWS and CRRWS parameters instead of RWS and CRWS were found to be more useful for the irrigation managers and water users to characterize the water delivery performance for the paddy irrigation systems.

The following conclusions can be drawn from the study on performance indicators:

The RRWS and CRRWS can simply and distinctly characterize irrigation delivery performance with respect to the RRWS = 1.0. It gives the following interpretation over periodic irrigation supply at the end of a period:

> RRWSj = 1.0 Good irrigation delivery RRWSj > 1.0 Oversupply condition RRWSj < 1.0 Undersupply condition


The Ponding Water Index (PWI) also can simply characterize irrigation delivery performance. It gives the following interpretation over periodic irrigation supply at the end of a period:

PWIj = 0 Good irrigation delivery condition

PWIj > 0 Oversupply condition

PWIj < 0 Undersupply condition

The new indicators have successfully been evaluated for various water management scenarios in the study area. Therefore, they can be adopted to evaluate irrigation delivery performance and proper decision for water allocation for irrigated paddy. GIS interface coupled with new performance indicators has explicitly helped in integrating spatial and temporal information for evaluating the daily irrigation delivery performances for paddy cultivation. The new irrigation performance indicators are able to provide useful information and can be adopted to evaluate irrigation delivery performance and proper decision for water allocation in the paddy irrigation system. The availability of such a quantitative tool for irrigation systems operation can have a powerful impact on the overall water management strategy in an irrigation project area.

Paddy Water Management for Precision Farming of Rice 127

strategies that allow them to manage variability precisely. Blackmore (1999) stated the three types of variability that have been identified are spatial variability, which can be found through changes across the field, temporal variability which means changes over time and predictive variability, that identifies the difference between predicted and what actually

One of the precision farming approaches to manage spatial variability is site specific crop management (SSM). In order to match application of farm practices with soil and crop requirements, zone management was suggested. Zone management represents sub-fields with similar characteristics including soil properties, topography, slope, nutrient levels and

Soil variability in paddy fields is well recognized. The spatial description is an important component of the precision farming cycle for zone management practices. Precision farming requires topping up of only the nutrients that are lacking in the soil to attain the optimum yield with the least inputs. Manual soil sampling and the consequent laboratory analysis are expensive, labour intensive and requires a long time. The use of an on-the-go electrical conductivity (ECa) sensor can replace the traditional way of acquiring data in a more efficient way. Research results have confirmed the usefulness of the ECa data as a summary

Soil ECa measurements can provide information on soil texture, in addition to estimating soil water content. Maps of soil physical properties and yield maps have shown visible correlation. Soil ECa can serve as a proxy for soil physical properties such as organic matter (Jaynes, et al., 1994), clay content (Williams and Hoey, 1987), and cation exchange capacity (McBride, et al., 1990). These properties have a significant effect on water and nutrientholding capacity, which are major drivers of yield (Jaynes, 1995). The relationship between soil ECa and yield has been reported (Kitchen and Sudduth, 1996; Fleming, et al., 1998). Sudduth et al. (1998) found that within field variation in soil properties could be explained with soil conductivity measurements. They found a significant relationship between soil conductivity and topsoil depth and Fraisse et al. (1999) added to this work by using soil electrical conductivity for zone delineation. Both of these works concentrated on using soil ECa to characterize local spatial variability. Lund et al. (1998) show that sampling according to soil management zones identified with a soil conductivity map can be more effective than

This study uses an on-the-go ECa sensor for producing ECa map and to use it for soil nutrients assessment. The field soil salinity readings can be obtained through this soil-toinstrument contact device that permits rapid soil ECa measurement without requiring a permanently buried detector. The study was conducted in paddy fields at Tanjung Karang, Selangor, Malaysia. The study site has 118 plots covering 144 ha with an average plot size of about 1.2 ha (Figs. 10 and 11). The EC sensor was pulled by a tractor at a speed of about 15 km h-1 in a U-shape pattern 15 m apart. The data was later transferred to a notebook computer for generation of ECa maps using Surfer 7.0 software and ArcGIS 8.3 with Spatial

indicator for zoning paddy soils to facilitate water and fertilizer management.

happen in the field.

**3.2 Paddy soil variability** 

so on.

grid sampling.

**3.3 Materials and methods** 
