Assessment of climate change impact on crop yield and irrigation water requirement of two major cereal crops (rice and wheat) in Bhaktapur district, Nepal

Rice and wheat are major cereal crops in Nepal. Climate change impacts are widespread and farmers in developing countries like Nepal are among the most vulnerable. A study was carried out to assess the impact of climate change on yield and irrigation water requirement of these cereal crops in Bhaktapur, Nepal. Laboratory and soil-plant-air-water analysis showed silt-loam being the most dominant soil type in the study area. A yield simulation model, AquaCrop, was able to simulate the crop yield with reasonable accuracy. Future (2030–2060) crop yield simulations, on forcing the Providing Regional Climates for Impacts Studies (PRECIS) based on regional circulation model simulation indicated decreased (based on HadCM3Q0 projection) and increased (based on ECHAM5 projection) yield of monsoon rice for A1B scenario, and rather stable yield (for both projection) of winter wheat. Simulation results for management strategies indicated that the crop yield was mainly constrained by water scarcity and fertility stress emphasizing the need for proper water management and fertilizer application. Similarly, a proper deficit irrigation strategy was found to be suitable to stabilize the wheat yield in the dry season. Furthermore, an increase in fertilizer application dose was more effective in fully irrigated conditions than in rainfed conditions. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/). doi: 10.2166/wcc.2016.153 om https://iwaponline.com/jwcc/article-pdf/8/2/320/522791/jwc0080320.pdf 2020 Lajana Shrestha Narayan Kumar Shrestha (corresponding author) Center for Post-Graduate Studies, Nepal Engineering College (necCPS), Kathmandu, Pokhara University, Nepal E-mail: shrestha.narayan@hotmail.com Narayan Kumar Shrestha Faculty of Science and Technology, Athabasca University, Edmonton, Alberta, Canada


INTRODUCTION
It is increasingly becoming clear that climate change is a real phenomenon and human activities such as burning of fossil fuel, deforestation, and so on are primarily to blame.
As such, the recent anthropogenic emission of greenhouse gases is at its highest level (IPCC ). The impacts of increased temperature and elevated CO 2 level, intense or no rainfall, are widespread on natural systems and on humans (IPCC , ). Water resources are affected, and hence the agricultural sector which could have longterm effects on food security (Malla ; IFPRI ). It is evident that increase in temperature and carbon dioxide (CO 2 ) have a positive impact on some crops, but the nutrient levels, soil moisture conditions, water availability for irrigation, and other crop-related conditions should be favorable in order to have better crop yield (Maximay ). Moreover, changes in precipitation pattern such as intense rainfall during a particular month are becoming more frequent and such events could have a devastating effect on crop production especially if they occurred in a sensitive phase of the crop, e.g., the flowering stage ( Joshi et al. ).
All these events associated with climate change would pose further stress on farmers to produce more and more food for an increasingly growing and wealthier population (FAO ). The case is even more severe in peri-urban areas like Bhaktapur district, Nepal, which has experienced rapid urbanization of late (Shrestha et al. b). To cope with such adverse effects (of climate change), different adaptive management practices especially applying proper fertilizer dose and water application need to be adopted.
Furthermore, adaptation practices such as shifting of crop plantation date, adjusting cropping area and intensity might need to be considered (Iizumi & Ramankutty ).
There have been some studies which have quantified the impact of climate change on cereal crop yields at regional and national scale. In this context, this paper analyzes the impact of climate change on yield response of main cereal cropsrice and wheat in Bhaktapur district, Nepal. It also aims to find ways to stabilize the yield with plausible water and fertilizer application scenarios. An understanding of the impacts of recent climate trends on major cereal crops would help to anticipate impacts of future climate on the agriculture sector. We believe that the outcome of the study will facilitate in formulating suitable adaptation strategies to cope up with the adverse effects of climate change, thereby increasing food security of the district.

Study area
The Bhaktapur district (Figure 1) is the smallest district of Kathmandu Valley, Nepal. Although peri-urban, the district has about 80% of its total area as agricultural land (10,240 ha). Only 30% of the agricultural land has roundthe-year irrigation facilities (Poudel et al. ). Because of the very fertile nature of the land, the district is also known as the grain and vegetable store of the valley. Rice, wheat, and maize are the major cereal crops of the district and are grown in land areas of 4,326, 3,665 and 1,793 ha, respectively. The annual production of these cereal crops is 4.5, 2.69 and 2.93 t/ha, respectively (Poudel et al. ).

Data collection
Several different techniques were applied for the data collection and will be discussed in the next sections.

Questionnaire survey, field visits and soil samples
Altogether 30 soil samples (see Figure 1) from different locations of the district were taken based on snowball sampling technique. Moreover, farmers of the sampled land were also supplied with questionnaires in order to collect information regarding farming practices, main factors affecting the plantation of crops, crop yield, variety of crops, crop phonological stages, and period, time and irrigation practices. To determine the soil texture class, collected soil samples were submitted to the Agricultural Technology Center (ATC), Nepal. Although the soil samples were taken from 30 cm depth, uniform soil profile is considered as suggested by Shrestha ().

Climate data
Daily historical climate data were collected from the Department of Hydrology and Meteorology (DHM), Nepal, for the period 1979-2013 of nearby station named Tribhuvan International Airport (TIA), Nepal. It should however be noted that there exist several meteorological stations in and around the Kathmandu Valley. Considering the fact that the Bhaktapur district is the smallest district of the valley and the TIA station is the nearest to the district, and most of the other stations are lying either on foothills or on the hills, use of only one station (the TIA) located on a similar altitude as that of study area can be justified. The climate data included daily rainfall, maximum and minimum air temperature, sunshine hours, wind speed and relative humidity. Figure 2 shows time series plots of annual rainfall, and minimum and maximum temperature at the station during 1979-2013.

ETo calculator
The ETo calculator, developed by the Land and Water Division of the Food and Agriculture Organization (FAO), is used to calculate the potential evapotranspiration (ETo). The tool is based on a theoretical method proposed by Penman and Monteith (Allen et al. ) to calculate the ETo. The tool requires several climatic data such as temperature (maximum and minimum), relative humidity, wind speed, solar radiation etc., at user defined time steps. In this study, the tool was run for a daily time scale. Besides calculating the ETo, temperature data are also produced in a format suitable for the AquaCrop model (see below for details on the model).

Tested management scenarios
Different water and fertilizer scenarios (Table 1)  . As such, we tested two deficit irrigation scenarios -D1 and D2 (see description in Table 1). While RF and FI conditions are applicable for monsoon rice, the D1 and D2 are only applicable for winter wheat. Under the fertilizer management scenarios, different fractions of fertilizer as per National Recommended Fertilizer Dose (NRFD) were formulated (Table 1). Finally, all possible permutations of water and fertilizer application scenarios were tested.

Results from social survey
It was found that 100% of the farmers grow rice during the monsoon season (June to September), and the overwhelming majority (>80%) grow wheat during the winter season.
During winter, the rest (20%) grow maize. The statistics indeed justified our selection of rice and wheat being two major cereal crops of the study area. Besides, 80% of the respondents reported that they waited for rainfall in order to sow the crops, and the rest (20%) first examined moisture content in the soil and then fixed a sowing date.
Respondents agreed that there had been a decrease in the crop yield, due to several factors including (see Figure 3): (a) spreading of disease (40%), (b) water scarcity (30%), (c) Monsoon rice (a) RF (a) 150% of NRFD/Non-

ETo-calculator results
ETo calculator revealed that the daily ETo have a decreasing trend for the base period  which is contrary to expectation as it is perceived that there would be rise in temperature due to climate change. However, as can be seen in Figure 2, the maximum and minimum temperatures are rather stable in the last decade or so. The decreasing ETo trend could then be due to the higher humidity levels in the atmosphere and decreased amount of solar radiation reaching the Earth's surface. It is well perceived that a small change in solar radiation can bring large amount of change in evapotranspiration (Gad & Gyar ).

SPAW model results
Based on the soil physical characteristics as determined using Pedo-transfer functions from soil texture using the SPAW model (Saxton & Rawls ), we classified the soil samples into three classes namely S1, S2 and S3. The classification was based on the range of TAW values (refer Before 10 years 11.9 3.0 8.2 Last year 8.9 2.5 5.8 This year 6.9 1.9 4.9 Year (  to Table 3). Other characteristics of the soil are presented in the Table 3. Spatial distribution of soil samples is presented in Figure 1. It is clear that S3 was the most dominant type in the study area.
AquaCrop model resultsmodel calibration The calibration results of monsoon rice and winter wheat yield, for soil type S1 are shown in Figures 5 and 6  Figure 6 | AquaCrop model calibration results for winter wheat (soil type S1).
the variation in the monsoon rice yield (2.9-4.2 t/ha) is suppressed ( Figure 5). The coefficient of correlation (r 2 ) between them is thus very low (0.04). However, winter wheat yield is very sensitive to total rainfall occurring during crop season ( Figure 6). Large variation in rainfall (25-210 mm) is also reflected in large variation in the yield (0.1-4.4 t/ha) with higher r 2 value of 0.37 between them.
It therefore implies that RF irrigation can be practiced for monsoon rice while winter wheat needs irrigation infrastructure to ensure timely irrigation and better yield.
Although the calibration result for soil type S1 is presented in Figure 5 (for monsoon rice) and Figure 6 (for winter wheat), the yield scenario for each soil type is shown in Figure 7. As can be seen, the yield on type S3 is the highest and has the lowest variation in terms of maximum and minimum yields, which are mainly due to the higher TAW retaining capacity of S3 (see Table 3). Higher TAW means that the soil can hold more moisture in a prolonged no-rain case.
The monsoon rice yield in different fertilizer and water management scenarios is presented in Table 4. As can be seen, in the RF case, increment in fertilizer application from 0% to 150% of the NRFD resulted in a significant increment in the yield (up to 65%), and the result for the irri- The same for the winter wheat (Table 5) illustrated a rather different picture. Winter wheat yield could substantially be increased (up to 110%) by providing optimal fertilizer dose, and the contribution of irrigation is also  showed þ20.5% increment (see Table 6). Such significant differences in the yield when using two different climate   The HadCM3Q0  ) reported the opposite. As can be seen in Figure 8, the yield would even drop to near zero level. The yield improved when full irrigation was introduced but is still lower than current yield. Unlike that observed in the base period (see Table 4), increasing fertilizer application did not improve the yield in future. These findings ( wider error bars of the box plots as compared to that of current case. As expected, the width or variation in box plots are less in the FI case than that in the RF case which is apparently due to lower water stress on the crop. Such a significant decrease (À36%, for highest fertilizer application case À150% NRFD) even for full irrigation (see Table 6) would mean that temperature stress is the main factor behind such a decrease.
In contrast, the ECHAM5 based simulation showed and all fertilizer application conditions), the ECHMA5 based simulation showed higher yield than current yield.
Furthermore, there exists less variation, as indicated by narrower box plots, in the yield which indicates that there would be sufficient rainfall in the monsoon rice growing season, should the ECHAM5 projection prevail in future.
The future simulation results for winter wheat showed different results than that observed for summer rice ( Figure 9). The HadCM3Q0 based future simulation showed increment in winter wheat yield in all water management and fertilizer application scenarios which indicates that rainfall and temperature during the winter wheat growing season would be favorable. The ECHAM5 based future simulation however showed increment in certain scenarios and drop in others. In improved water management scenarios (e.g., full irrigation, D1), the future yield is always expected to be higher than current yield (see Figure 9(b) and 9(c), and Table 7). The HadCM3Q0 based simulation results also showed that even deficit irrigation schemes (D1 and D2) would result in better yields (see Figure 9(c) and 9(d), and Table 7). The ECHAM5 based simulation results however showed that the yield would decrease (Table 7) especially in D2 case.
While it is not clear if the monsoon rice yield would increase or decrease in future as both future climate data set indicated contrasting result, it is rather clear that the yield of winter wheat can easily be stabilized or even increased adopting proper water management scenarios (FI or D1). Such significant uncertainty in future yield of monsoon rice is indeed a dilemma for policy makes, hence, an effort was made in investigating what caused such a drastic decrease in monsoon rice yield when forcing the HadCM3Q0 projection.
It was found that significant temperature stress (consequently higher evapotranspiration and higher the demand of irrigation water) would be the main reason behind the sharp decrease in yield if HadCM3Q0 projection prevail in future (see Figure 10, left). During the base period the temperature stress is very low (almost near zero) and variation of temperature stress is also very low (as indicated by narrower box plots). In contrast, the HadCM3Q0 based projected would lead to rather significant temperature stress, ranging from nearly 40% to 10% (Figure 10, left). Extreme To further analyze the case, for a purposively selected year (2044), it was found that temperature seems to drop  an earlier plantation date (mid-March, see Figure 11). As an adaptation measure for the climate change impact, and in order to stabilize the monsoon rice yield, crop plantation months were arbitrarily shifted and simulations with both water management scenarios, RF and FI, are carried out.
It has to be noted that the worst future climatic scenario (HadCM3Q0 projection) has been considered here, as simulation based on ECHAM5 projection showed increment in monsoon rice yield.
Simulations showed that the March plantation of monsoon rice would result in the maximum yield for both RF and FI conditions under optimal fertilizer application dose ( Figure 12). Even under FI conditions, the tradition plantation date (July) of monsoon rice would give almost the lowest yield, mainly due to temperature stress as minimum temperature in subsequent crop growing months tends to reach below 8 W C.

AquaCropnet irrigation water requirement
The simulation result of net irrigation water requirement (I net ) also indicates the severe water stress that the monsoon  On the other hand, the main reasons for a rather stable winter wheat yield (based on HadCM3Q0 projection) are due to favorable rainfall distribution and lessened temperature stress (Figure 10, left). However, the wider range of the error bars of the box plot of I net , meaning higher variability, is of concern to policy makers. Furthermore, the I net based on ECHAM5 projection is higher than base period indicating that less rainfall is expected during winter wheat's growing season which is also evident in Figure 11 (bottom left).

CONCLUSIONS
An assessment of climate change impact on irrigation water requirement and crop yield of two widely used cereal crops in Bhaktapur district, Nepal, was made with the help of social and analytical (using various models) techniques.
Questionnaire survey with 30 farmers, selected using snowball sampling technique, was carried out to gain insights on the crop, water and fertilizer management practices, and harvested yield. Moreover, soil samples from the croplands of the selected farmers were taken and later analyzed in a laboratory to determine texture composition and organic matter content. SPAW tool was used to determine physical  This study therefore recommends shifting of crop plantation date, temperature resilient crop genotype (to overcome temperature stress), and proper water and fertilizer management to stabilize the crop yield.