Table Of ContentsNext Page

A comparative analysis of Crop Water Productivity of rice-wheat and cotton-wheat rotations in Rechna Doab, Punjab, Pakistan

Mobin-ud-Din Ahmad1, Ilyas Masih2 and Hugh Turral1

1 International Water Management Institute (IWMI), Global Research Division, P O Box. 2075, Colombo, Sri Lanka. www.iwmi.cgiar.org, Email: a.mobin@cgiar.org (Mobin-ud-Din Ahmad) and h.turral@cgiar.org (Hugh Turral)

2 International Water Management Institute (IWMI), Regional office for Pakistan, 12 km Multan Road, Chowk Thokar Niaz Baig, Lahore, Pakistan. Email: i.masih@cgiar.org

Abstract

This paper compares the crop water productivity of rice-wheat and cotton-wheat rotations both in terms of individual crops and system perspective. The results are based on in-depth field scale analysis conducted at two locations in Rechna Doab Punjab, Pakistan. A comprehensive set of water balance components and water productivity indicators were used to evaluate the water use performance in terms of physical yield as well as economic returns. The analysis suggests that although actual evapotranspiration was lower in the rice-wheat system as compared to the cotton-wheat system, yet, water inputs were higher. Lower physical water productivity (Kg/m3), measured in terms of yield per unit of irrigation and gross inflow, was observed for rice compared to cotton and wheat. However, in terms of depleted water rice showed better performance than cotton and comparable results to wheat. Economic productivities (US$/m3), measured in terms of gross value of produce, or gross margins per unit of irrigation and gross inflow, were higher for cotton followed by wheat and rice crops. From a system perspective, gross value, or, gross margin per unit of input water were higher for cotton-wheat rotation, while comparable values were observed when measured in terms of depleted water. The study indicates that using a combination of water balance components with physical and economic water productivity indicators can better help in comparing performance of individual crops, cropping systems at various scales and contribute in improving the physical and economic productivity of water.

Media summary

A presented water productivity approach has the potential to improve crop water productivity at various scales, thereby, contributing to more productive and economical use of water.

Key Words

Performance analysis, cropping system, water balance, input water, depleted water, field scale

Introduction

Improving the productivity of water is vital to meet the global challenges of food and livelihood security under increasing water scarcity, sectoral competition and climatic variability. The agriculture sector will have to provide more food, fibre and livelihoods with the same or less water resources, for a growing population across the globe in the 21st century. Therefore, it is extremely important to devise methodologies for estimating the productivity of water, generate evidence from various regions of the world and devise strategic actions for its improvement. Molden (1997) and Molden et al. (1998) developed a water accounting framework and a set of performance indicators, which have been increasingly used for water productivity evaluation, contributing to improved water resources management at various scales of river basins. Various water balance components and water productivity indicators are in use depending upon the available information and scope of the study. Droogers and Kite (1999) conducted a simulation modelling study at field, irrigation scheme and basin scales in western Turkey to describe the water balance analysis and calculate water productivity. They used four performance indicators for water productivity (WP) i.e., WPirrigated (yield/irrigation), WPinflow (yield/net inflow), WPdepletion (yield/depletion) and WPprocess (yield/process depletion), all expressed in Kg yield per m3 water. The reported values for field scale analysis for cotton crop ranged from 0.24 Kg/m3 to 0.57 Kg/m3. Recently, Cabongon et al. (2002) have compared the water productivity of rice under various crop establishment methods for the Muda Irrigation scheme in Malaysia. The water productivities, measured in terms of irrigation, net inflow, depletion and process depletion were in the range of 0.26-1.00 Kg/m3 for transplanted rice, 0.26-0.62 Kg/m3 for wet seeded rice and 0.28-1.48 Kg/m3 for direct dry seeded rice, at irrigation system unit level. Tuong and Bouman (2003) reported the water productivity on the basis of yield per unit of irrigation water and yield per unit of evapotranspiration for various field scale experiments across different countries of the world. Field scale water productivity per unit of irrigation for rice, wheat and maize crops emerged as 0.2-1.1 Kg/m3, 0.79-1.6 Kg/m3 and 1.6-3.9 Kg/m3, respectively. Most of the previous studies have mainly focused on water productivity in terms of yield per unit of water, using a limited number of water balance and water productivity indicators. Such types of comparison can be misleading due to differences in physical yield and market value e.g. comparison of basmati rice (fine variety) with coarse varieties. There is a need to look at economic water productivity of individual crops as well as from a cropping system perspective. This paper presents a comprehensive evaluation of water balance components and water productivity of rice, cotton and wheat crops in rice-wheat and cotton-wheat systems from field scale case studies in Rechna Doab, Punjab, Pakistan.

Methods

Study locale

This research work was carried out in the Rechna Doab area of the Indus Basin irrigation system, which is the oldest and most intensively developed irrigated area of Punjab, Pakistan (Figure 1). The gross area of this Doab (land between two rivers) is 2.97 million hectare (Mha), of which 2.3 Mha is cultivated. The area falls in the rice-wheat and sugarcane-wheat agro-ecological zones of Punjab Province, with rice, cotton and forage crops dominating in the summer season (kharif), ?? wheat and forage in the winter season (rabi). Sugarcane is an annual crop sown in winter and spring seasons. The climate is characterized by large seasonal fluctuations of air temperatures and rainfall. The summer is long and hot, lasting from April through September, with maximum air temperature ranging from 21C to 49C. Whereas, winter lasts from December to February, with maximum air temperature ranging from 25C to 27C during the day and sometimes falling below zero at night. The spring and fall months are generally limited to March and October. The mean annual rainfall ranges from 1100 mm in the upper parts of the doab to 250 mm downstream. The monsoon occurs from June to September and accounts for about 75 % of the rainfall. In this study, two fields representing rice-wheat (co-ordinates: 7320’50.2” E. 3152’34.2” N) and cotton-wheat (co-ordinates: 732’49.8” E. 3123’26.2” N) cropping systems were selected from the Rechna Doab area.

Figure 1. Location of Rechna Doab in Punjab, Pakistan.

Data collection and analysis

Field data on various water balance components, agronomic practices, crop yields and farm market prices were collected for two growing seasons, kharif 2000 and rabi 2000-1. Bowen ratio towers for measuring the actual evapotranspiration rates (ETa) were installed and operated between June 21 (2000) and March 21 (2001). A physically based field scale numerical model, SWAP (Soil-Water-Atmosphere-Plant (van Dam et al. 1997)) was applied to understand the transient interaction between different water balance components. The SWAP model was calibrated and verified with in situ measurements of soil moisture content and evapotranspiration fluxes (Ahmad et al., 2002). The information from field observations and simulation modelling was used to calculate the water productivity of rice, cotton and wheat crops. The water productivity was estimated in physical terms (Kg/m3) and economic terms (US$/m3).

Results and Discussions

Water balance

Water balance results are given in Table 1 and indicate that irrigation constitutes the major portion of the gross inflow for meeting crop water demand compared to rainfall, at both locations. Rice received about 50 percent more irrigation water than cotton and wheat. Although the actual evapotranspiration for rice (544 mm in 123 days) was 16 percent lower than cotton (648 mm in 194 days), considerably higher water inputs are needed for traditional wet-rice cultivation. Consequently, a larger volume of water moves as deep percolation from the crop root zone in rice compared to cotton and wheat crops. The water balance analysis for wheat shows that gross inflow (296 mm) was lower than the actual evapotranspiration in the field. This gap in crop water demand was met through water stored in the root zone during the rice season as is evident from a negative change in soil moisture storage. In the cotton-wheat field, the cotton suffered from under-irrigation, whereas wheat was over-irrigated. Looking from a system perspective, the rice-wheat rotation received about 20 percent more irrigation water (912 mm) on an annual basis compared to the cotton-wheat rotation (768 mm). Contrary to this, actual evapotranspiration was 10 % lower in the case of the rice-wheat system compared to cotton-wheat. From the system perspective this reveals that overall water depletion, process (transpiration) and non-process (evaporation), is less in a rice-wheat system than a cotton-wheat system.

Table 1. Water balance analysis of rice-wheat and cotton-wheat crop rotations in Rechna doab, Pakistan.

Parameters/Indicators

Rice

Wheat

Rice-Wheat

Cotton

Wheat

Cotton-Wheat

Inflow measured in field (mm)
Rainfall
Irrigation
Gross Inflow


187
650
837


34
262
296


221
912
1133


197
332
529


93
436
529


290
768
1058

Outflow, simulated (mm)
Evaporation
Transpiration
Evapotranspiration
Rainfall Interception
Bottom flux


272
272
544
4
307


32
314
346
6
43


304
586
890
10
350


116
532
648
7
106


38
288
326
4
74


154
820
974
11
180

Storage change

- 19

- 98

- 117

- 23.15

13

- 10.15

Productivity gains

The results of land and water productivity analysis are presented in Table 2. The yields of rice and cotton crops were 2794 Kg/ha and 2563 Kg/ha respectively. The rice yield was comparable to the areal average whereas cotton yield was higher than the average yield in the area. This could be attributed to high a yielding crop variety and good on farm management operations regarding input use, weed and pest management. Wheat yields were 3146 Kg/ha at experimental field 1 under rice-wheat rotation and 2054 Kg/ha at experimental field 2 under cotton-wheat rotation. The lower yield of wheat at field 2 was mainly attributed to delayed planting, as cotton was harvested in the latter half of December. The cotton-wheat rotation resulted in higher gross value of produce and gross margins per unit of land compared to rice followed by wheat. The gross value of production on an annual basis was higher in the cotton-wheat rotation (1067 $/ha) when compared to the rice-wheat rotation (871 $/ha).

Water productivity was examined from two perspectives: 1) mass of produce, or, economic value per unit of input water (irrigation and gross inflow); 2) mass of produce, or, economic value per unit of depleted water (evapotranspiration and transpiration). In physical terms, input water productivity of rice (WPY_Ig : 0.334 Kg/m3 and WPY_Irr : 0.430 Kg/m3) was lower than cotton (WPY_Ig : 0.484 Kg/m3 and WPY_Irr : 0.772 Kg/m3) and wheat (field 1: WPY_Ig : 1.063 Kg/m3 and WPY_Irr : 1.201 Kg/m3; field 2: WPY_Ig : 0.388 Kg/m3 and WPY_Irr : 0.471 Kg/m3). However, the productivity of depleted water of rice (WPY_ETa: 0.514 Kg/m3 and WPY_Ta: 1.027 Kg/m3), especially relative to transpiration (process depletion), was higher than cotton (WPY_ETa: 0.396 Kg/m3 and WPY_Ta: 0.482 Kg/m3). Wheat showed comparable physical water productivity, measured in terms of yield per unit of transpired water with rice and was higher than cotton. Economic water productivity, measured in terms of gross value per unit of input water, was highest for cotton (WPGVP_Ig : 151 US$/“000”m3 and WPGVP_Irr : 241 US$/“000”m3) followed by wheat (field 1: WPGVP_Ig : 138 US$/“000”m3 and WPGVP_Irr : 155 US$/“000”m3; field 2: WPGVP_Ig : 50 US$/“000”m3 and WPGVP_Irr : 61 US$/“000”m3) and rice (WPGVP_Ig : 55 US$/“000”m3 and WPGVP_Irr : 71 US$/“000”m3). In terms of depleted water, wheat showed higher WPGVP_ETa compared to rice and cotton and this was attributed to the lower evapotranspiration of wheat. The least water use in terms of transpiration (process depletion) for rice resulted in highest WPGVP_Ta compared to cotton and wheat crops. From a system perspective, the cotton-wheat rotation (WPGVP_Ig : 101 US$/“000”m3 and WPGVP_Irr : 139 US$/“000”m3) indicated higher input water productivity compared to rice-wheat rotation (WPGVP_Ig : 77 US$/“000”m3 and WPGVP_Irr : 96 US$/“000”m3 ). The gross margins per unit of input water and depleted water for cotton were higher than wheat and rice and were due to considerably higher gross value of production. However, at a system scale, both rotations give comparable values.

Table 1. Land and water productivity of rice-wheat and cotton-wheat crop rotations in Rechna doab, Pakistan.

Parameters/Indicators

Rice

Wheat

Rice-Wheat

Cotton

Wheat

Cotton-Wheat

Land productivity
Yield (Kg/ha)
Gross value ($/ha)
Gross margin ($/ha)


2794
464
193


3146
407
175



871
368


2563
801
414


2054
266
13



1067
426

Water productivity
Physical terms (Kg/m3)
WPY_Ig
WPY_Irr
WPY_ETa
WPY_Ta
Economic productivity ($/m3)
WPGVP_Ig
WPGVP_Irr
WPGVP_ETa
WPGVP_Ta
WPGM_Ig
WPGM_Irr
WPGM_ETa
WPGM_Ta



0.334
0.430
0.514
1.027

0.055
0.071
0.085
0.171
0.023
0.030
0.035
0.071



1.063
1.201
0.909
1.002

0.138
0.155
0.118
0.130
0.059
0.067
0.051
0.056








0.077
0.096
0.098
0.149
0.032
0.040
0.041
0.063



0.484
0.772
0.396
0.482

0.151
0.241
0.124
0.151
0.078
0.125
0.064
0.078



0.388
0.471
0.630
0.713

0.050
0.061
0.082
0.092
0.002
0.003
0.004
0.005








0.101
0.139
0.110
0.130
0.040
0.055
0.044
0.052

(Y = yield; Ig = gross inflow; Irr = irrigation; ETa = actual evapotranspiration; Ta = Actual transpiration; GVP = gross value of produce; GM = gross margins or net income)

Conclusion

The study indicates that rice shows comparatively lower physical and economic water productivity measured in terms of irrigation and gross inflow compared to cotton and wheat crops. However, rice performs better in terms of depleted water productivity when compared to cotton. This happens because a large volume of water is recycled but not depleted in order to maintain ponded conditions in rice production. A portion of this may be evaporated in early growth stages, but the apparent over irrigation is not a net loss to the system, as groundwater quality is acceptable for irrigation and is recycled. For the farming system perspective, the cotton-wheat rotation gives higher gross value of produce and gross margins per unit of land and per unit of input water compared to the rice-wheat rotation. Nevertheless, the economic returns to depleted water were comparable for both cropping systems. The contribution of water stored in the root zone and groundwater domains during the rice growth season needs further investigations for water productivity analysis, from cropping system perspective as well as at various scales of the irrigation system. Water productivity approaches combining water balance, physical and economic water productivity indicators could be very useful in increasing the understanding of water demand, supply and productivity, thereby, helping formulate strategies leading towards more productive and economical use of water.

References

Ahmad MD, Bastiaanssen WGM and Feddes RA (2002). Sustainable use of groundwater for irrigation: A numerical analysis of sub-soil water fluxes. Irrigation and Drainage 51(3), 227-241.

Cabangon RJ, Tuong TP and Abdullah NB (2002). Comparing water input and water productivity of transplanted and direct-seeded rice production systems. Agricultural Water Management 57, 11-31.

Droogers P and Kite G (1999). Water productivity from integrated basin modeling. Irrigation and Drainage Systems13, 275-290.

Molden D (1997). Accounting for water use and productivity. SWIM paper 1. Colombo, Sri Lanka: International Water Management Institute.

Molden DJ, Sakthivadivel R, Perry CJ, de Fraiture C and Kloezen WH (1998). Indicators for comparing performance of irrigated agricultural systems. Research Report 20. Colombo, Sri Lanka: International Water Management Institute.

Tuong TP and Bouman BAM (2003). Rice production in water scarce environments. In: Kijne JW, Barker R and Molden D. (eds) Water productivity in agriculture: Limits and opportunities for improvement, CABI publishing in association with International Water Management Institute.

Van Dam JC, Hygen J, Wesseling JG, Feddes RA, Kabat P, Van Walsum PEV, Groenendijk P, and Van Diepen CA (1997). Simulation of water flow, solute transport and plant growth in the Soil-Water-Atmosphere-Plant environment. SWAP user’s manual DLO-Winand Staring Centre, Wageningen, The Netherlands.

Top Of PageNext Page