Water, one of the most crucial inputs of irrigation, should be utilized judiciously to identify appropriate strategies for planning and management of irrigated farmland. The present study was conducted for the crop maize (Zea mays), grown mainly in the rabi-season (July–October), to evaluate the irrigation water requirements in the temperate region of Kashmir Valley, India during the last 20 years from 1993 to 2012. The crop evapotranspiration values have been determined using the universally accepted Penman–Monteith method. The reference evapotranspiration varied by 93 mm, which accounts for variation of 20.12% for a temperature change of 1.61 °C. Net irrigation requirement of the crop is influenced greatly due to the possible effect of climate change, observed through varying temperature in different crop periods. The number of irrigations required in sandy loam soil is much more than the required number of irrigations in clay loam soil. The irrigation scheduling was analyzed using meteorological data through FAO-56 Penman–Monteith method as a guiding force for irrigation water management in order to save water and increase crop water use efficiency. The time series analysis reveals that maize crop in sandy loam and clay loam needs to be advanced by 5 days and 4 days in order to adapt for the climate change.

INTRODUCTION

Water resource has become a prime concern for the development and planning, including food production and flood control. The impact of climate change may be quite severe with the reduction in the water availability in different parts of the world and affecting the effectiveness of the existing water management practices as well (Vorosmarty 2002; Jhajharia et al. 2014). Water availability in different parts of India will be one of the important issues of the 21st century. In recent past, people have died in various water-related conflicts in different states, for example, death of five people in police firing on farmers demanding adequate irrigating waters for their crops from the Beesalpur dam to their farm-lands located in the desert state of Rajasthan. Therefore, managing scarce water resources has become one of the emerging environmental issues for the ecosystem as we move into the 21st century. Plant growth depends on the use of two important natural resources, soil and water. The availability, movement and retention of water are governed by the properties of soil. Effective water resources management of crop production requires the understanding of the relationship between soil, water and plants (Kumar et al. 2012, 2013a, 2013b). The impact of the changing climate on one of the most precious natural resources needs to be studied and combated before it causes irreparable damage.

Water resources planning and management is concerned with the accurate assessment, identification and development of water from different sources for human beings and agriculture uses (Kumar et al. 2012, 2013a, b; Shankar et al. 2013). The objective of water resources planning and management is to provide the supplies in accordance with the temporal and spatial distribution of the demand (Bogachan et al. 2009; Gamal et al. 2010). Changes in climate are witnessed on many fronts as the rise or fall of temperature and non-uniform distribution of rainfall both spatially and temporally are likely to influence irrigation requirements (Kumar & Gautam 2014). A number of researchers (Dinpashoh et al. 2011; Jhajharia et al. 2012; McVicar et al. 2012) have analysed trends in evapotranspiration (ET) under warmer climates around the globe using data of different durations at different locations under different types of climate. Various researchers reported significant decreases in either (both) pan evaporation (Epan) or (and) potential evapotranspiration (PET) over various parts of Russia, the USA, India and Australia (Peterson et al. 1995; Chattopadhyay & Hulme 1997; Lawrimore & Peterson 2000; Golubev et al. 2001; Roderick & Farquhar 2004).

Crop water requirements vary during the growing period, mainly due to variation in crop canopy and climatic conditions, and related to both the cropping technique and irrigation methods. About 99% of the water uptake by plants from soil is lost as ET. It can be stated that the measurement of actual crop evapotranspiration (ETc) on a daily scale for the whole vegetative cycle is equal to the water requirement of the given crop. ET is defined as the water lost as vapor by an unsaturated vegetative surface and it is the sum of evaporation from soil and transpiration by plants. To avoid the underestimation or overestimation of crop water consumption, the knowledge of the exact water loss through actual ET is necessary for sustainable development and environmentally sound water management in the temperate region.

To adapt the crop to the changing climate, the options available are to either modify the genetic composition or modify its environment by shifting the irrigation schedules. Future climate change could have the potential to significantly alter the conditions of crop production, with significant implications for the global food security (Rosenzweig & Hillel 1998). Changes in yield behavior in relation to shift in climate may prove critical for the economy of farmers (Torriani et al. 2007a, b). Therefore, climate change urgently needs to be assessed at the farm level, so that poor and vulnerable farmers dependent on agriculture can be appropriately targeted in research and development activities on poverty alleviation (Jones & Thornton 2013). Assessing the possible impact of climate change on production risks is therefore necessary to help decision makers and stakeholders identify and implement suitable measures of adaption (Torriani et al. 2007a, b). The present study was undertaken with the objectives of climatic ecohydrological modeling of irrigation scheduling using time series analysis in temperate region of India.

MATERIAL AND METHODS

Study area and data

Maize, one of the three most important cereal crops, is grown throughout a wide range of climate. The present study was conducted for the maize crop in Srinagar located in the temperate region of Kashmir valley, India. Srinagar lies between 74.816° and 74.902° E longitudes and 34.153° and 34.234°N latitudes with elevation of 1,700 m from the mean sea level. The data of various meteorological parameters, namely, rainfall (in mm), temperature (maximum and minimum, in °C), relative humidity (minimum and maximum, in %), sunshine duration (in hours) and wind speed (in km/h), were obtained from the meteorology station situated in the campus of the University. Figure 1 shows a sample picture of a meteorology station of Kashmir valley (India) showing different types of recording equipment for measuring different types of meteorological parameters. The wind speed data are recorded in km/h at a 2 m height. The station is equipped with the mercury and alcohol thermometers, a three-cup anemometer, a Campbell sunshine recorder, a wet-bulb thermometer, USWB Class A pan evaporimeter, rain-gauge recorder and some other meteorological instruments. All the instruments in the meteorology station are installed as per the guidelines of the India Meteorological Department, Pune for the proper installations and operations during the observations. The mean annual precipitation is 774 mm with mean monthly temperatures ranging from about 20 °C in summer to 3 °C in winter. The precipitation in the spring season is usually of high intensity, leading to excessive surface runoff in the Kashmir valley. The rainfall pattern of the present study area during 2001–2012 is shown in Figure 2.

Figure 1

The meteorology station in Srinagar (Kashmir valley, India) situated in the vicinity of the Himalaya for recording of various meteorological parameters.

Figure 1

The meteorology station in Srinagar (Kashmir valley, India) situated in the vicinity of the Himalaya for recording of various meteorological parameters.

Figure 2

Total rainfall over Srinagar (Kashmir valley, India) during 2001–2012.

Figure 2

Total rainfall over Srinagar (Kashmir valley, India) during 2001–2012.

The analysis of the ETc was carried out for the irrigation scheduling in the temperate region. The effect of climate change is mainly influenced by climatological factors and water balance over a period of time. The FAO 56 Penman–Monteith method was used to estimate ET0 for a period of 20 years from 1993 to 2012. The Penman–Monteith equation is expressed as 
formula
1
where, ET0 = the reference evapotranspiration (mm), Δ = the slope of saturation vapor pressure temperature curve (kPa), Rn = the net radiation (MJ m−2), γ = the psychrometric constant (kPa), T = mean air temperature (°C), G = the heat flux density to the ground (MJ m−2), u2 = the wind speed at a 2 m height above the ground (m s−1) and esea = the saturation vapor pressure deficit.

The crop coefficient (Kc) for maize has been taken from the FAO-56 irrigation manual and modified as per the agro-climatic conditions of Srinagar as suggested by Allen et al. (1998). The modified Kc values depend on wetting frequency of crop, wind speed measuring height, crop height and maximum and minimum relative humidity.

The available moisture content on any particular day was estimated using the following equation 
formula
2
where, MC = available moisture content (%), ETc = crop evapotranspiration (mm), d = available depth of water (mm), dfc = the available depth of water at field capacity (mm) and FC = the field capacity (%).
The available depth of water on any particular day was estimated using Equation (3), which is given as 
formula
3
where, Γb = the bulk specific gravity and D = the root zone depth (mm).
The water retention was calculated by subtracting the runoff from the rainfall. 
formula
4
where, W = the water retention, P = rainfall (mm) and R = runoff (mm).
Runoff is calculated by using the curve number method, which is based on the maximum water retention of the watershed 
formula
5
where, S = the potential maximum retention or retention capacity of the watershed (mm).
The net irrigation requirement (NIR) is given as 
formula
6
where, NIR = the net irrigation requirement, LR = the leaching requirement and DP = deep percolation.

If the moisture content of the soil on a particular day goes below 50% depletion of the readily available water, then the irrigation has to be given to the extent of the deficiency to bring the moisture content to the field capacity. If the moisture content of the soil is more than the field capacity due to excess rainfall, then the deep percolation losses will be considered for calculation of the NIR. The crop coefficient curves were developed by plotting the ratios of ETc and ET0 with respect to time (Kumar et al. 2012). The details of the soil characteristics of the study area are summarized in Table 1.

Table 1

Soil characteristics

Soil typeBulk density (g/cc)Field capacity (%)Permanent wilting point (%)Ultimate wilting point (%)
Sandy loam 1.51 18 10 
Clay loam 1.30 32 16 11 
Soil typeBulk density (g/cc)Field capacity (%)Permanent wilting point (%)Ultimate wilting point (%)
Sandy loam 1.51 18 10 
Clay loam 1.30 32 16 11 

RESULTS AND DISCUSSION

The quantitative study of water movement in the soil–root system is an important component in the modeling of root water uptake by crops. Such studies provide key information for optimum irrigation scheduling and water resources management. Improved water management practices require precise scheduling of irrigation including accurate computations of daily ETc. ET0 have been computed by the FAO 56 Penman–Monteith method, which is supposed to give more consistent ET0 estimates and has been shown to perform better than other ET0 computation methods (Smith et al. 1992).

The present study shows considerable variations in the ET0 for Srinagar region over a period of 20 years, as it largely depends on climatic conditions rather than soil and crop properties. The time series of the ETo during the last 20 years from 1993 to 2012 in the Kashmir valley is shown in Figure 3. It is observed that the ETo values remain in the range of 525–542 mm during the first 10 years, i.e., from 1993 to 2002. The next 10 years witnessed many variations in the ET0, with the occurrence of the highest value (555 mm) in the year 2005 and the lowest value (462 mm) in 2010 in the Kashmir valley. The ETo values determined through the FAO-56 Penman–Monteith method witnessed decreased trends at the rate of 16 mm/decade during the last 20 years from 1993 to 2012. It is evident from Figure 3 that the ET0 vary by 93 mm for maize during the period of 20 years. During the crop period of maize, there is a variation in ET0 ranging from 555 to 462 mm, which means that there is a net variation of 20.12% in the evaporative demand in the valley, which in turn affects the ETc and NIRs.

Figure 3

Annual time series of ET0 obtained through the Penman–Monteith and NIRs in sandy and clay soils in Kashmir valley of India.

Figure 3

Annual time series of ET0 obtained through the Penman–Monteith and NIRs in sandy and clay soils in Kashmir valley of India.

The time series of the ETc along with the annual time series of minimum and maximum temperatures are shown in Figure 4. ETc variations for clay and sandy soils are shown in Figure 5. It is also evident from Figures 4 and 5 that the ETc values vary in the range 528–600 mm.

Figure 4

Annual time series of ETc, minimum and maximum temperatures in Kashmir valley of India.

Figure 4

Annual time series of ETc, minimum and maximum temperatures in Kashmir valley of India.

Figure 5

NIRs for clay and sandy loam soils for maize (Zea mays).

Figure 5

NIRs for clay and sandy loam soils for maize (Zea mays).

Crop coefficient's values vary with the climatic conditions prevailing over the region because it depends on the climatic data and crop parameters (Kumar et al. 2012). The Kc graph was developed for initial, development, middle and late stages of the maize crop. The graphical representation between Kc, ET0 and ETc is shown in Figure 6. ETc is greatly affected by the prevailing climatic conditions over the region for a given time period. Due to the variations in the climatic conditions each year, the ET0 value tends to deviate from its previous year's observed value, which causes changes in ETc. The variation in temperature, an important climatic parameter, plays a significant role in the fluctuations of ETc of the Kashmir valley in the northern Himalaya, India. The percentage change in ET0 and ETc in 20 years' duration from 1993 to 2012 is 20.12% and 22.53%, respectively. The maximum change of ETc is found for the maize (Zea mays) to the tune of about 22.53% for a change in 1.6 °C of temperature over 20 years from 1993 to 2012 in the temperate region of Himalaya.

Figure 6

ETc, ET0 and Kc values for maize.

Figure 6

ETc, ET0 and Kc values for maize.

NIR of the crops is affected greatly due to the possible effect of climate change, which may be observed due to varying temperatures and changes in other meteorological parameters during the crop growing period. The temperature changes the NIR during the crop period, as seen from the annual time series of the last 20 years from the duration of 1993 to 2012. It is worth mentioning that the ETc values in the valley are observing marginal decreases at the rate of (–) 4.6 mm/decade along with the cooling trends in maximum temperature in the valley during the last 20 years. The minimum temperature, is usually observed just before the sunrise, has increased considerably in the valley at the rate of 2.10 °C/decade (see Figure 4). However, the maximum temperature observed during the day-time, especially around noon or afternoon time, has witnessed decreasing trends at the rate of (−) 0.60 °C/decade.

It is evident that the values of the NIR for maize are varying from 527.96 mm to 646.30 mm for sandy loam soil and 528 mm to 648.3 mm for clay loam soil, which causes changes to the tune of about 22.41% and 22.78% in the NIR in sandy loam and clay loam soil, respectively. The total numbers of irrigations applied for sandy loam and clay loam soil in case of rainfall and in case of no rainfall are nine and six, respectively, based on the water requirements of the crop. An attempt was made for the irrigation scheduling of the maize during the period from 1993 to 2012. The graphs plotted between available depth of water and crop period are shown in Figures 7 and 8.

Figure 7

Irrigation scheduling for maize in clay loam soil. RAW = readily available water.

Figure 7

Irrigation scheduling for maize in clay loam soil. RAW = readily available water.

Figure 8

Irrigation scheduling for maize in sandy loam soil.

Figure 8

Irrigation scheduling for maize in sandy loam soil.

The time series analysis for the last 20 years (1993–2012) depicts a clear picture of irrigation scheduling for the maize crop. The time series analysis of the irrigation scheduling was carried out to study the effect of climate change and options available to the farmers for crop adaptation to the changing temperature and rainfall patterns in the valley to avoid crop water stress. As climate change is a very uncertain phenomenon, while the irrigation requirements of a crop cannot be uncertain, it is studied to develop the guidelines to the farming community to combat the ill effects of climate change on the crop production. The required numbers of irrigations for clay and sandy soils without and with irrigation are illustrated in Table 2. It is illustrated in Table 2 that the numbers of irrigations applied are nine and six with or without rainfall for sandy loam and clay loam type soils based on water requirements of the crop. Irrigation scheduling reduced the number of irrigations by five and four with and without rainfall conditions on the basis of total water requirements of the crop.

Table 2

Required numbers of irrigations and advancement in sowing

CropWithout rainfall
With rainfall
Number of irrigations
Advancement in sowing
Number of irrigations
Advancement in sowing
Sandy loamClay loamSandy loamClay loamSandy loamClay loamSandy loamClay loam
Maize 
CropWithout rainfall
With rainfall
Number of irrigations
Advancement in sowing
Number of irrigations
Advancement in sowing
Sandy loamClay loamSandy loamClay loamSandy loamClay loamSandy loamClay loam
Maize 

Plant-available water is the difference between the volume of water stored when the soil is at field capacity and the volume still remaining when the soil reaches the permanent wilting point. The plants are unable to extract moisture below certain moisture levels, which lie between field capacity and permanent wilting point. About 65–70% of the water used by a crop is obtained from the upper half of the root zone (Shankar et al. 2013). This root zone is referred to as the effective root depth. Irrigation is practiced when the average moisture content within the root zone depth attains a certain value between the field capacity and permanent wilting point. This value of moisture content is called the allowable depletion level. Irrigation scheduling criterion is an important parameter in determining the frequency of irrigation events. The hypothetical condition of no rainfall and rainfall was considered during the corresponding crop periods. The allowable moisture depletion level is dependent on the type of crop and the moisture retention capacity of the soil. At 50% allowable moisture depletion level, irrigation is required to be provided whenever the average soil moisture in the effective root depth is reduced to a certain limit. Figure 9(a)–9(d) shows the irrigation schedules developed using the moisture uptake prediction based on the time series analysis for the maize crop with rainfall. During mid-season and late season stages, frequent irrigations are needed. It may be concluded that if the accurate moisture depletion by the crops can be estimated, optimal irrigation schedules for the crop can be developed by using data on soil retention characteristics and plant parameters, i.e., field capacity, permanent wilting point and root depth. Irrigation scheduling at different allowable moisture depletion levels can be devised as per the requirement of the crop, water availability and moisture retention capacity of the soil. Accurate prediction of the moisture uptake pattern helps in planning of the optimal irrigation schedules.

Figure 9

Time series analysis between depths of water applied during the crop period of maize.

Figure 9

Time series analysis between depths of water applied during the crop period of maize.

CONCLUSIONS

The analysis of irrigation scheduling was carried out using the meteorological data for a period of 20 years from 1993 to 2012. The ETc value has been determined using the modified value of crop coefficient. The following conclusions were drawn based on the results obtained from the analysis:

  1. The ET0 varied by 93.2 mm for maize between 1993 and 2012, which accounts for variation of 20.12% for a temperature change of 1.61 °C. Decreases in ET0 are witnessed in the valley at the rate of about 16 mm/decade. This change is independent of soil and crop parameters.

  2. NIR of the crops are influenced greatly due to the possible effect of climate change, which is observed due to the varying temperature in different crop periods to the level of average 1.61 °C. Decreases in the NIR are witnessed for both the cases of the sandy and clay soils in the valley at the rate of about 15.5 mm/decade and 18.62 mm/decade, respectively.

  3. The numbers of irrigations required for the maize are almost constant with rainfall and without rainfall consideration, which infers that the schedules of crop and rainfall distribution are not matching.

  4. The number of irrigations required in sandy loam soil is much more than the required number of irrigations in clay loam soil in all the cases, which suggests that the choice of crop for a particular soil type can be optimized, based on lower numbers of irrigations.

  5. The time series analysis reveals that the maize crop in sandy loam and clay loam needs to be advanced by 5 days and 4 days in order to adapt to the climate change, and this forms a guiding force for irrigation water management in order to save water and increase crop water use efficiency in the temperate environments of Kashmir valley in Indian Himalayan region.

ACKNOWLEDGEMENTS

The authors are highly thankful to the Division of Agricultural Engineering, SKUAST – Kashmir for providing all necessary facilities to conduct this study. The authors gratefully acknowledge the critical reviews of anonymous reviewers and the Editor, which improved the manuscript significantly.

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