V1I1 IJASD Water stress

IJASD Logo High Resolution JPG copy

V1-I1-IJASD Water Stress by M Saif Ullah
Size: 0.5 MB

Estimation of Water Stress on Rice Crop Using Ecological Parameters.                       

Muhammad Saifullah1, Bilal Islam4, Saif-ul-Rehman3, Muhmmad Shoaib2, Ehsan ul Haq1, Syeda Areeba Gillani1, Nida Farooq1 and Memoona Zafar1.

1 Remote sensing and GIS group, Department of Space Science, University of the Punjab Lahore, Pakistan.

2 Geomatics, Collage of Earth & Environmental Science Punjab University Lahore.

3 Department of Geography, GC University, Lahore.

4 Department of Physics, University of the Punjab Lahore. 

* Correspondence: Muhammad Saifullah     E-mail:     saifafridi1994@gmail.com

Citation | Saifullah M, Islam.B, Rehman.S, Shoaib M, Haq.E, Gillani.S.A, Farooq.N,  Zafar.M”. Estimation of Water Stress on Rice Crop Using Ecological Parameters. International Journal of Agriculture and Sustainable Development, Vol 01 Issue 01: pp 17-29, 2019.

DOI | https://doi.org/10.33411/IJASD/20190103

Received | Dec 12, 2018; Revised |Jan 27, 2019 Accepted | Jan 30, 2019; Published | Feb, 4 2019.

___________________________________________________________________________

Abstract.

About half of world’s population intake rice as a staple food. As being water baby, rice need surplus of water to get targeted yield. Water scarcity has become a global issue therefore it has become a need to enhance the rice yield with reduced amount of water. In this research we used ecological parameters e.g., temperature, pressure, actual vapor pressure, sunshine hours and the extraterrestrial radiation to compute net radiations, ground and sensible heat fluxes on daily basis. Net shortwave radiations were observed as 23087 w/m2 in comparison to net longwave radiations which were 4387 w/m2 for the complete Rice Growth Period (RGP). The soil heat flux Go was observed as 3104 w/m2. Go was observed dependent upon the Leaf Area Index (LAI) with inverse relationship between them. Sensible heat flux (H) was measured as 1771 w/m2 throughout the RGP. H was observed dependent upon net radiations with a direct relationship between them. Rn, Go and H were used as input parameters to compute water stress which determines the excess of water in early growth stages of rice crop and water scarcity in the ripening stage. The flow of methodology is easily applicable at domestic level to determine water stress in rice fields.  

Keywords: Net radiations, Soil heat flux, Shortwave radiations, long wave radiations, water stress.

 

  • Introduction.

Rice (Oriza Stiva L) has become a staple food for half of the world’s population [1]. Global food security is largely dependent upon the supply of lowland irrigated rice [2]. Rice is considered as water baby that consumes plenty of water for its growth and development [3]. Various factors are the influencing the availability of fresh water for irrigation to paddy rice crop such as the addition of industrial discharge into rivers and canals [4, 5, 6]. The contribution of Asian countries toward rice production is about 90% in global market that intakes almost 91% of total fresh water for its preparation [7]. About 15 million hectors of irrigated rice area and 22 million hectors of dry season rice area in Asia is projected to suffer with water scarcity by 2025 [8]. Fresh water is the basic and most significant constituent that plays a vital role to obtain targeted agricultural productivity therefore, water conservation and sustainability has become the need of green future. Various techniques and methods have been suggested by many researchers to manage water demand by provision of optimized supply of water to crops to get acceptable yield [9]. All the techniques and methods were related to water saving for future. Kima et al 2014 [10] evaluated the quality of ground water available at various depths suitable for different crops [9]. A mutual finding of these researches was the achievement of healthy yield with reduced amount of water.

Sustainable rice production is related to increase productivity with reduced amount of water to fulfill the demands of increasing population [11]. Different parameters are essential to improve the rice productivity with reduce amount of water. These parameters include 1) soil type 2) soil pH and 3) soil Electric Conductivity (EC). Soil type is significant to improve to reduce the provision of water to rice crop e.g., sand is perfectly drained which is not suitable for rice crop plantation while sandy clay is highly drained which is considered less suitable, silty clay is well drained therefore considered moderately suitable and clay is imperfectly drained therefore considered as highly suitable for rice cultivation [12]. To reduce the amount of water, the rice land should be clayish because clay has highest water holding capacity. The electric conductivity of rice fields should be between 0.75- 1.50 and the EC values are considered less suitable above or below this range. Soil pH should be between 5.5-7.2 which is considered highly suitable for rice cultivation.

The main objective of this research was to estimate the water stress in rice fields using ecological parameters and to evaluate various factors affecting the water intake by rice crop.

  • Material and Methods.

Investigation site.

This research was conducted in district Sheikhupura in Punjab Pakistan. Sheikhupura is located at (31-32.5 N) latitude and (73-75E) longitude spatially mapped in figure 1. It is located at 230m above the sea level with paved network of water channels administered by Punjab Irrigation Department for irrigation purpose to crops. Climate is severe with a wide range of variations in temperature that crosses 45oC in summer and declines to 1 oC in winter. The test site is in range of monsoon therefore, it receives 500 mm rainfall annually [13]. It is a plain area where slop does not affect the water distribution process. Crop information is maintained by a person natively named as patwari.

V1I1Water Stress Fig1

Figure 1. Spatial extent of the study site.

Methodology.

Flow of methodology to estimate water stress is described in the figure below:

V1I1Water Stress Fig2

Figure 2. Flow of methodology used in this research to estimate water stress on rice crop.

Various parameters are significant to evaluate the water stress on rice crop. These parameters include the variations in temperature on daily basis, pressure, Leaf Area Index (LAI) actual sunshine hours in comparison to total sunshine hours and the actual vapor pressure.

Net Radiations (Rn)

Rn describes the energy balance of earth which is signification to determine the physical nature of features laying on the surface of earth. It is the ratio of incoming to outgoing solar radiations. Evapo-transpiration in plants is affected by this energy balance, therefore it is significant to estimate Rn to investigate agro climatic interactions [14]. All the physical & chemical reactions occurring in plant are derived by solar radiations [15]. Net radiations can be computed by calculation of sum of incoming and outgoing radiations. Incoming radiation are called net shortwave (Rns) and outgoing are known as net long wave (Rnl) radiations [16, 17, 18].

Rn = Rns + Rnl                                               (1)

Rns can be computed by the interaction of actual incoming actual radiations with albedo of rice crop canopy.

Rns = (1-α)Rs                                                                            (2)

Where α represents albedo by rice plant and Rs is actual incoming solar radiation. According to Stephen Boltzmann Law, Rnl is four times proportional to earth’s surface temperature, as below [19].

V1I1Water Stress Eq3

 

Where σ is Boltzman constant (σ = 4.903 x 10-9MJK-4M-2Day-1), Tmax and Tmin represents the maximum and minimum temperature, Rso and Rs are incoming raditions in comparison to actual incoming radiations respectively and ea is the actual vapor pressure. We collected Tmax, Tmin and ea by Local Weather Station (L W S) for the complete Rice Growth Period (R G P) and averaged. Ra is extraterrestrial radiations which strike on the Top of Atmosphere (T O A) before entering in to earth’s atmosphere [20]. Considerable variations can be measured in Ra due to change in solar angle [21]. Ra can be computed using the website

http://www.engr.scu.edu/~emaurer/tools/calc_solar_cgi.pl.

Radiations that actually strike the surface of earth after interaction with atmospheric gases are called actual incoming radiations that can be computed according to [16, 20, 21, 22, 23, 24, 25].

Rs  = [As + Bs (n/N)] Ra                       (4)

Where As and Bs represents calibration constants, n and N are actual sunshine hours in comparison to possible sunshine hours on daily basis. We obtained the data about n, N through LWS. It is observed that 75% of extraterrestrial radiations approach the earth’s surface in a cloud free day. Remaining 25% are scattered due to atmospheric interactions. Rso can be computed using Angstrom’s formula [20, 22].

Rso = (As + Bs) Ra                          (5)

Soil heat flux (Go)

Go is related to heat conduction in to the soil due to variations in temperature which depends upon the soil composition. Penetration of heat into the soil is more if it has high concentration of elements that can conduct heat. All the biochemical reactions happening in soil are controlled by Go. The contribution of Go in energy balance is smallest therefore this factor is often ignored but this ignorance may lead to considerable errors. Go can be computed as follows [25].

                        Go = Rn × (0.05 + 0.18 × exp (−0.521 × LAI))                   (6)

Where LAI is leaf area index of rice crop that varies from germination to ripening. Go largely depends upon LAI because the density of leaves influence the heat penetration into the soil. We obtained 21 field observations with a temporal window of five days from rice fields to estimate the variations in leaf area, e.g., leaf area was observed 0.23 m2m-2 on July 13, 2017 that was assumed same for the next five days (13-17) July 2017. Variations in LAI throughout the RGP are mapped in figure 3 as below.

V1I1Water Stress Fig3

Figure 3. Variations in leaf area throughout the RGP.

Sensible and latent heat flux.

The exchange of heat in plant’s body without changing its state is called sensible heat flux. Bowen ratio (β) is an important indicator to estimate sensible heat flux (H). To evaluate β, we need daily variations in temperature with actual vapor pressure as below [26, 27, 28].

V1I1Water Stress Eq4

Where γ is known as psychometric constant which is 0.000665th portion of atmospheric pressure [29]. Δe and Δt represents the actual vapor pressure and temperature gradients respectively. The expression to evaluate γ is as follows 

γ=0.000665xP                                        (8)

We obtained the variation in atmospheric pressure, temperature and actual vapor pressure from LWS and averaged. The expression to estimate H is as follows [27]

V1I1Water Stress Eq5

Where Rn, Go and H are the basic input factors to evaluate water stress (W) on the rice crop. W determines the amount of moisture in the soil. A range of 0 to 1 is used for determination of W where 0 indicates oven dry soil and 1 as penalty of water. W can be compute using the following expression [11].

V1I1Water Stress Eq6

Results and discussion.

We used equations to compute 1-5 to compute Ra, Rso, Rns, Rnl, Rn and mapped the results in Figure 4.

V1I1Water Stress Fig4

Figure 4. Variations in various fluxes throughout the RGP.

Figure 4 shows the variations in various fluxes throughout the RGP. Extraterrestrial radiations are showing a decline to flux which is due to the change in solar angle. Figure 4 determines that a total flux of 55625 w/m2 was received as extraterrestrial radiations and 415 w/m2 as average. A fraction of about 25% of Ra was scattered/reflected into the atmosphere due to interaction with gases and 41718 w/m2 was available to approach the surface of earth. A flux of about 27474 w/m2 could approach the crop canopy throughout the RGP including 23087 w/m2 as Rns and 4387 as Rnl radiations. Peaks and dips in Rn, Rns and Rnl resemble with the variation in n/N ratio in figure 5. It determines that more flux was received by the crop canopy on the day where n/N ratio approached 1 and vice versa. 

Figure 5 describes the cloud activity throughout the RGP. Cloud activity is essential for various growth stages of rice crop e.g., cumulus clouds with heavy rainfall provides a large quantity of water to the rice fields which is a nice addition in germination, leaf emergence and panicle primordia development, however, rain free clouds are considered good in ripening process of rice crop. The peaks and dips in figure 5 determine the dense cloud activity at dips and clear sky on peaks throughout the RGP.

V1I1Water Stress Fig5

Figure 5. Cloud activity throughout the RGP.

Variation in Go throughout the RGP were estimated using equation (6) as below.

V1I1Water Stress Fig6

Figure 6. Variations in Go throughout the RGP.

Figure 6 is showing the variations in ground heat flux which is showing a decreasing trend from start to the end of growth period. This decline in Go is due to inverse relationship of Go with LAI. The increment in LAI stops the sunlight to approach the earth’s surface. This trend shows that LAI of rice crop increase hence Go declined. Go again increased in the end of rice season due to decrease in LAI. A total Go was recorded as 3104 w/m2 throughout the RGP.

Variations in sensible heat flux for the complete growth period of rice crop were estimated using equations 7-9 and mapped the results in Figure 7.

V1I1Water Stress Fig7

Figure 7. Variations in sensible heat flux throughout the RGP.

Figure 7 is showing the same trend as Rn in Figure 4. Sensible heat is required to maintain the plant bloody temperature in comparison to its surroundings. The resemblance of both figures describes that more H is required on the day where a high value of Rn is recorded. Sensible heat was recorded as 1771 w/m2 and 127 w/m2 as average on the rice crop canopy throughout its growth period.

We used equation 10 to compute the variations in water stress and mapped the results in Figure 8.

V1I1Water Stress Fig8

Figure 8. Estimation of water stress throughout the RGP.

Figure 8 shows that the rice crop in the study site had surplus of water in early stages of growth. Rice crop was observed in stress toward the end of rice crop season. On ground validation it was observed that ripening period don’t need much water however, initial stages require a big quantity of water for full fledge growth. On comparison of Figure 8 with Figures 5, it was observed that cloud activity (n/N) effects the solar fluxes e.g., Rn, Rns, Rnl, H, Go and finally W. If (n/N) ratio approaches to 0, it shows that it is a complete cloudy day with less flux in term of Rn, hence a little H is required, this situation leads to the values of W greater than 0.5. Finally, we concluded that the initial stages of rice crop were observed in clouds with n/N ration near to zero and less amount of water was required as H therefore, it was not water stress in early stages however there was water stress in the end of rice season with W<0.5.

Conclusion.

Ecological parameters are of great importance to monitor the physical changes within a plant. Optimum range of these parameters will lead to enhance the capacity of a plant for generation of fruitful yield with reduced water. The research methodology is easy and handy to apply in rice fields at domestic level because it is significant to ensure the availability of water in rice fields to get much of yield.

Acknowledgement. I, as being corresponding author acknowledge all the departments which shared their valuable data to accomplish this task. Special thank to my father for his support to me in all aspects.  

Author’s Contribution. All the authors contributed equally.

Conflict of interest. We declare no conflict of interest to publish this research in IJASD.

References:

[1] Mostafa K Malesh et al., "Development of Remote Sensing Based Rice Yield Forecasting Model," Spanish Journal of Agricultural Research., vol. 14, no. 3, 2016.
[2] J. Yang and J. Zhang, "Crop management techniques to enhance harvest index in rice.," J. Exp. Bot. , vol. 61, p. 3177–3189, 2010. [Crossref]
[3] A. Thakur, R. Mohanty, D. Patil and A. Kumar, "Impact of water management on yield and water productivity with system of rice intensification (SRI) and conventional transplanting system in rice.," Paddy Water Environ, vol. 12, pp. 413-424, 2014. [Crossref]
[4] B. Bouman, "A conceptual framework for the improvement of crop water productivity at different spatial scales.," Agric. Syst., vol. 93, pp. 43-60, 2007. [Crossref]
[5] T. Chapagain, A. Risema and E. Yamaji, "Assessment of system of rice intensification (SRI) and conventional practices under organic and inorganic management in Japan.," Rice Sci, vol. 18, pp. 311-320, 2011. [Crossref]
[6] A. Thakur, S. Rath, D. Patil and A. Kumar, "Effects on rice plant morphology and physiology of water and associated management practices of the system of rice intensification and their implications for crop performance.," Paddy Water Environ. , vol. 9, no. 1, 2011. [Crossref]
[7] S. Khepar, A. Yadav, S. Sondhi and M. Siag, "Water balance model for paddy fields under intermittent irrigation practices.," Irrig. Sci., vol. 19, p. 199–208., 2000. [Crossref]
[8] T. Tuong and B. Bouman, "Rice Production in Water Scarce Environment," International Rice Research Institue: Manilla, Philippines, 2003.
[9] V. Pascual and Y.-M. Wang, "Utilizing rainfall and alternate wetting and drying irrigation for high water productivity in irrigated lowland paddy rice in southern Taiwan.," Plant Prod. Sci. , vol. 19, pp. 1-12, 2016. [Crossref]
[10] A. Kima, W. Chung, Y.-M. Wang and S. Traoré, "Evaluating water depths for high water productivity in irrigated lowland rice field by employing alternate wetting and drying technique under tropical climate conditions, southern taiwan.," Paddy Water Environ. , vol. 13, pp. 379-389, 2014. [Crossref]
[11] S. Raza and S. Mahmood, "Estimation of Net Rice Production through Improved CASA Model by Addition of Soil Suitability Constant (ħα).," Sustainability, vol. 10, p. 1788, 2018. [Crossref]
[12] R. S.M.H, "Delineation of potential sites for rice cultivation in Punjab Pakistan through Multicriteira evaluation techniques using remote sensing and GIS," International Journal of Plant Production, vol. 12, no. 1, pp. 1-12, 2018.
[13] M. Waqar and F. Rehman, "Ikram, M. Land suitability assessment for rice crop using geo spatial techniques.," in In Proceedings of the 2013 IEEE International, Geoscience and Remote Sensing Symposium (IGARSS),, Melbourne, VIC, Australia,, 2013. [Crossref]
[14] T. Oke, Boundary-Layer Climates,, 2nd ed. ed., London, UK: Methuen and Company:, 1987, pp. 1-460.
[15] J. Monteith, Unsworth, M.H. Principles of Environmental Physics, 4th ed., vol. 291, London, UK: Edward Arnold, 1990.
[16] B. Wu, S. Liu, W. Zhu, N. Yan, Q. Xing and S. Tan, "An Improved Approach for Estimating Daily Net Radiation over the Heihe River Basin.," Sensors, vol. 17, p. 86, 2017. [Crossref]
[17] S. Krishna, P. Manavalan and P. Rao, "Estimation of net radiation using satellite-based data inputs.," Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, p. 307–313. , 2014. [Crossref]
[18] G. Park, X. Gao and S. Sorooshian, "Estimation of surface longwave radiation components from ground-based historical net radiation and weather data.," J. Geophys. Res. , vol. 113, pp. 1-15, 2008. [Crossref]
[19] W. Munley and L. Hipps, "Estimation of regional evaporation for a tallgrass prairie from measurements of properties of the atmospheric layer.," Water Resour. Res., vol. 27, p. 225–230., 1991. [Crossref]
[20] S. Adnan, A. Hayat Khan, S. Haider and R. Mahmood, "Solar energy potential in Pakistan.," J. Renew. Sustain. Energy, pp. 1-7, 2012.
[21] R. Allen, L. Pereira, D. Raes and Smith, "Crop Evapotranspiration Guidelines for Computing Crop Water Requirements;," in FAO—Food and Agriculture Organization of the United Nations Rome: , Rome, Italy, 1998.
[22] A. Angstrom, "Solar and terrestrial radiation.," Q. J. R. Meteorol. Soc. , vol. 50, pp. 121-125, 1924.
[23] J. Prescott, "Evaporation from a water surface in relation to solar radiation.," Trans. R. Soc. South Aust. , vol. 64, pp. 114-125, 1940.
[24] K. Revfeim, "On the relationship between radiation and mean daily sunshine.," Agric. For. Metrol., vol. 3, pp. 183-191, 1997.
[25] J. Duffie and W. Beckman, "Solar Engineering of Thermal Processes," in Wiley, : New York, NY, USA,, 1980.
[26] M. Tasumi, "Progress in Operational Estimation of Regional Evapotranspiration Using Satellite Imagery.," Ph.D Thesis University of Idaho, Moscow, ID, USA, 2003, 2003.
[27] I. Bowen, " The ratio of heat losses by conduction and by evaporation from any water surface.," Phys. Rev. J. Achive , vol. 27, p. 779–787, 1926. [Crossref]
[28] C. Tanner, " Energy balance approach to evapotranspiration from crops.," Soil Sci. Soc. Am. Proc., vol. 24, pp. 1-9, 1960.
[29] L. Zotarelli, M. Dukes, C. Romero, K. Migliaccio and K. G. Morgan, "Step by Step Calculation of the Penman-Monteith Evapotranspiration (FAO-56 Method);," in IFAS University of Florida FL, , USA, , 2015.
Creative Commons License
Copyright by authors and 50Sea. This work is licensed under a Creative Commons Attribution 4.0 International License.