Irrigation induced surface cooling in the context of modern and increased greenhouse gas forcing

There is evidence that expected warming trends from increased greenhouse gas (GHG) forcing have been locally ??masked?? by irrigation induced cooling, and it is uncertain how the magnitude of this irrigation masking effect will change in the future. Using an irrigation dataset integrated into a global general circulation model, we investigate the equilibrium magnitude of irrigation induced cooling under modern (Year 2000) and increased (A1B Scenario, Year 2050) GHG forcing, using modern irrigation rates in both scenarios. For the modern scenario, the cooling is largest over North America, India, the Middle East, and East Asia. Under increased GHG forcing, this cooling effect largely disappears over North America, remains relatively unchanged over India, and intensifies over parts of China and the Middle East. For North America, irrigation significantly increases precipitation under modern GHG forcing; this precipitation enhancement largely disappears under A1B forcing, reducing total latent heat fluxes and the overall irrigation cooling effect. Over India, irrigation rates are high enough to keep pace with increased evaporative demand from the increased GHG forcing and the magnitude of the cooling is maintained. Over China, GHG forcing reduces precipitation and shifts the region to a drier evaporative regime, leading to a relatively increased impact of additional water from irrigation on the surface energy balance. Irrigation enhances precipitation in the Middle East under increased GHG forcing, increasing total latent heat fluxes and enhancing the irrigation cooling effect. Ultimately, the extent to which irrigation will continue to compensate for the warming from increased GHG forcing will primarily depend on changes in the background evaporative regime, secondary irrigation effects (e.g. clouds, precipitation), and the ability of societies to maintain (or increase) current irrigation rates.     

Impact of climate change on irrigation water demand of dry season Boro rice in northwest Bangladesh

Climate change will affect irrigation water demand of rice via changes in rice physiology and phenology, soil water balances, evapotranspiration and effective precipitation. As agriculture is the main sector of water use in Bangladesh, estimation of the agricultural water demand in the changing environment is essential for long-term water resources development and planning. In the present paper, a study has been carried out to estimate the change of irrigation water demand in dry-season Boro rice field in northwest Bangladesh in the context of global climate change. The study shows that there will be no appreciable changes in total irrigation water requirement due to climate change. However, there will be an increase in daily use of water for irrigation. As groundwater is the main source of irrigation in northwest Bangladesh, higher daily pumping rate in dry season may aggravate the situation of groundwater scarcity in the region.     

Impact of temperature and precipitation variability on crop model predictions

Future climate changes, as well as differences in climates from one location to another, may involve changes in climatic variability as well as changes in means. In this study, a synthetic weather generator is used to systematically change the within-year variability of temperature and precipitation (and therefore also the interannual variability), without altering long-term mean values. For precipitation, both the magnitude and the qualitative nature of the variability are manipulated. The synthetic daily weather series serve as input to four crop simulation models. Crop growth is simulated for two locations and three soil types. Results indicate that average predicted yield decreases with increasing temperature variability where growing-season temperatures are below the optimum specified in the crop model for photosynethsis or biomass accumulation. However, increasing within-year variability of temperature has little impact on year-to-year variability of yield. The influence of changed precipitation variability on yield was mediated by the nature of the soil. The response on a droughtier soil was greatest when precipitation amounts were altered while keeping occurrence patterns unchanged. When increasing variability of precipitation was achieved through fewer but larger rain events, average yield on a soil with a large plant-available water capacity was more affected. This second difference is attributed to the manner in which plant water uptake is simulated. Failure to account for within-season changes in temperature and precipitation variability may cause serious errors in predicting crop-yield responses to future climate change when air temperatures deviate from crop optima and when soil water is likely to be depleted at depth.     

Satellite evidence on the trade-offs of the food-water–air quality nexus over the breadbasket of India

Access to food, water, and good air quality is indispensable for human life, as reflected in various United Nations Sustainable Development Goals (SDGs); however, pursuing food security may pose threats to water security and/or air quality. An important case is northwest India including the Punjab and Haryana states, which is the ‘breadbasket’ of India with a significantly increasing paddy rice area. The rapid expansion of rice farming has stressed groundwater resources and impacted air quality. Satellite observations have the potential to provide data for better decisions on food security, water storage, and air pollution, which would be vital for regional sustainable development. Based on observations from multiple satellites from 2001 to 2018, we found that paddy rice expansion (+22%) increased groundwater depletion (−1.50 cm/yr), residue burning (+500%), and air pollution (+29%, PM_2.5) in the breadbasket of India. Moreover, satellite observations showed changes in these interactions after the enactment of a groundwater protection policy in 2009, which decelerated groundwater depletion (−1.20 cm/yr) due to delayed rice planting and harvest dates (∼15d); the latter elevated air pollution in November (+29%, PM_2.5). Our finding stresses the need to reconcile the trade-offs and consider the interactions among SDGs 2 (food), 3 (good health), 6 (clean water), and 11 (air quality in cities), in policy-making for sustainable development. An efficient crop residue ultilization and management system, bottom-up groundwater use regulations, and cropping system shift towards less water-consuming crops are critically required to resolve the trade-offs of the food-water–air quality nexus in the northern India. Our study also showcases remote sensing approaches and methods to support and aid the achievement of the SDGs and track their progreses to support regional sustainable development.     

我国西南地区干旱变化及对贵州水稻产量影响

近几年,我国西南地区干旱频繁发生,严重影响农业生产。为了探讨干旱和水稻产量之间关系的复杂性,采用中国气象局国家气象信息中心提供的西南地区348个站气象数据,计算了西南地区干旱的变化趋势,并利用2000—2011年贵州省县级水稻产量资料分析了干旱对水稻单产的影响,探讨了干旱、水资源灌溉以及水稻产量之间的关系。结果表明:1951—2012年西南地区降水量平均减少16.9 mm/10 a,特别是8—10月降水量明显减少。同时,西南地区干旱日数呈上升趋势,平均增加3.3 d/10 a。对比水稻产量发现,当累计干旱日数少于40 d时,干旱对水稻产量一般不会造成影响;当累计干旱日数超过86 d时,干旱造成水稻减产20%~73%,这意味着当累计干旱日数超过3个月时,江河塘库蓄水将受到影响,进而影响水稻的灌溉,造成水稻严重减产;当累计干旱日数为40~86 d时,水稻减产一般少于20%,但地区差异较大。     

Impacts of irrigation on dry season precipitation in India

There is a lack of observed data-based studies examining the role of enhanced soil moisture conditions (due to irrigation) on the prevailing precipitation. Therefore, in the present study, we have examined the impacts of the Green Revolution (GR) related expansion of irrigation and changes in dry season (the rabi (November to May) and the zaid (March to June)) precipitation in India. The results for some regions indicated decreasing and increasing trend in precipitation during the pre- and post-GR periods, respectively. For example, in eastern Madhya Pradesh, the pre- and post-GR precipitation trends for the zaid season were ?0.45 and 2.40?mm?year^?1, respectively. On the other hand, some regions reported lower rate of decline in precipitation during the post-GR period. This paper suggests that both positive and lower declining trend during the post-GR period were linked to increased precipitation due to the introduction of irrigation. The study has found up to 69?mm (121%) increase in total amount of precipitation for growing seasons during the post-GR period. Moreover, a 175% increase in average precipitation was also recorded. All irrigated regions show a notable increase in precipitation during post-GR growing seasons. It was found that differences in growing season average precipitation between the pre- and post-GR periods were statistically significant for most of the regions. For further verification of results, the MM5 and Noah land surface model were applied. These applications show changes in precipitation and various precipitation controlling factors due to changes in soil moisture.     

High resolution modeling of the regional impacts of climate change on irrigation water demand

In the Arkansas River Basin in southeastern Colorado, surface irrigation provides most of the water required for agriculture. Consequently, the region’s future could be significantly affected if climate change impacts the amount of water available for irrigation. A methodology to model the expected impacts of climate change on irrigation water demand in the region is described. The Integrated Decision Support Consumptive Use model, which accounts for spatial and temporal variability in evapotranspiration and precipitation, is used in conjunction with two climate scenarios from the Vegetation-Ecosystem Modeling and Analysis Project. The two scenarios were extracted and scaled down from two general circulation models (GCMs), the HAD from the Hadley Centre for Climate Prediction and Research and the CCC from the Canadian Climate Centre. The results show significant changes in the water demands of crops due to climate change. The HAD and CCC climate change scenarios both predict an increase in water demand. However, the projections of the two GCMs concerning the water available for irrigation differ significantly, reflecting the large degree of uncertainty concerning what the future impacts of climate change might be in the study region. As new or updated predictions become available, the methodology described here can be used to estimate the impacts of climate change.     

Influence of mid-latitude circulation on upper Indus basin precipitation: the explicit role of irrigation

Since much of the flow of the Indus River originates in the Himalayas, Karakoram and Hindu Kush Mountains, an understanding of weather characteristics leading to precipitation over the region is essential for water resources management. This study examines the influence of upper level mid-latitude circulation on the summer precipitation over upper Indus basin (UIB). Using reanalysis data, a geopotential height index (GH) is defined at 200 hPa over central Asia, which has a significant correlation with the precipitation over UIB. GH has also shown significant correlation with the heat low (over Iran and Afghanistan and adjoining Pakistan), easterly shear of zonal winds (associated with central Asian high) and evapotranspiration (over UIB). It is argued that the geopotential height index has the potential to serve as a precursor for the precipitation over UIB. In order to assess the influence of irrigation on precipitation over UIB, a simplified irrigation scheme has been developed and applied to the regional climate model REMO. It has been shown that both versions of REMO (with and without irrigation) show significant correlations of GH with easterly wind shear and heat low. However contrary to reanalysis and the REMO version with irrigation, the REMO version without irrigation does not show any correlation between GH index and evapotranspiration as well as between geopotential height and precipitation over UIB, which is further confirmed by the quantitative analysis of extreme precipitation events over UIB. It is concluded that although atmospheric moisture over coastal Arabian sea region, triggered by wind shear and advected northward due to heat low, also contribute to the UIB precipitation. However for the availability of necessary moisture for precipitation over UIB, the major role is played by the evapotranspiration of water from irrigation. From the results it may also be inferred that the representation of irrigated water in climate models is unavoidable for studying the impact of global warming over the region.     

Regional changes in extreme monsoon rainfall deficit and excess in India

With increasing concerns about climate change, the need to understand the nature and variability of monsoon climatic conditions and to evaluate possible future changes becomes increasingly important. This paper deals with the changes in frequency and magnitudes of extreme monsoon rainfall deficiency and excess in India from 1871 to 2005. Five regions across India comprising variable climates were selected for the study. Apart from changes in individual regions, changing tendencies in extreme monsoon rainfall deficit and excess were also determined for the Indian region as a whole. The trends and their significance were assessed using non-parametric Mann–Kendall technique. The results show that intra-region variability for extreme monsoon seasonal precipitation is large and mostly exhibited a negative tendency leading to increasing frequency and magnitude of monsoon rainfall deficit and decreasing frequency and magnitude of monsoon rainfall excess.     

Understanding the causes and consequences of differential decision-making in adaptation research: Adapting to a delayed monsoon onset in Gujarat,India

Weather variability poses numerous risks to agricultural communities, yet farmers may be able to reduce some of these risks by adapting their cropping practices to better suit changes in weather. However, not all farmers respond to weather variability in the same way. To better identify the causes and consequences of this heterogeneous decision-making, we develop a framework that identifies (1) which socio-economic and biophysical factors are associated with heterogeneous cropping decisions in response to weather variability and (2) which cropping strategies are the most adaptive, considering economic outcomes (e.g., yields and profits). This framework aims to understand how, why, and how effectively farmers adapt to current weather variability; these findings, in turn, may contribute to a more mechanistic and predictive understanding of individual-level adaptation to future climate variability and change. To illustrate this framework, we assessed how 779 farmers responded to delayed monsoon onset in fifteen villages in Gujarat, India during the 2011 growing season, when the monsoon onset was delayed by three weeks. We found that farmers adopted a variety of strategies to cope with delayed monsoon onset, including increasing irrigation use, switching to more drought-tolerant crops, and/or delaying sowing. We found that farmers’ access to and choice of strategies varied with their assets, irrigation access, perceptions of weather, and risk aversion. Richer farmers with more irrigation access used high levels of irrigation, and this strategy was associated with the highest yields in our survey sample. Poorer farmers with less secure access to irrigation were more likely to push back planting dates or switch crop type, and economic data suggest that these strategies were beneficial for those who did not have secure access to irrigation. Interestingly, after controlling for assets and irrigation access, we found that cognitive factors, such as beliefs that the monsoon onset date had changed over the last 20 years or risk aversion, were associated with increased adaptation. Our framework illustrates the importance of considering the complexity and heterogeneity of individual decision-making when conducting climate impact assessments or when developing policies to enhance the adaptive capacity of local communities to future climate variability and change.     

Impact of Climate Change and Variability on Irrigation Requirements: A Global Perspective

Anthropogenic climate change does not only affect water resources but also water demand. Future water and food security will depend, among other factors, on the impact of climate change on water demand for irrigation. Using a recently developed global irrigation model, with a spatial resolution of 0.5° by 0.5°, we present the first global analysis of the impact of climate change and climate variability on irrigation water requirements. We compute how long-term average irrigation requirements might change under the climatic conditions of the 2020s and the 2070s, as provided by two climate models, and relate these changes to the variations in irrigation requirements caused by long-term and interannual climate variability in the 20th century. Two-thirds of the global area equipped for irrigation in 1995 will possibly suffer from increased water requirements, and on up to half of the total area (depending on the measure of variability), the negative impact of climate change is more significant than that of climate variability.     

Analysing temporal trends in the Indian Summer Monsoon and its variability at a fine spatial resolution

Temporal trends between 1951 and 2007 in annual Indian Summer Monsoon (ISM) precipitation, frequency of severe drought years and onset date of ISM were analysed on a 0.25°?×?0.25° grid cell basis across India using APHRODITE daily gridded precipitation data. Locations which experienced temporal trends of increasing or decreasing inter-annual variation in annual ISM precipitation and onset date of ISM were detected using the non-parametric Mann-Kendall test. A new method of defining local onset of ISM from daily precipitation data was developed to enable countrywide temporal trend analysis of onset date. India was characterised by a heterogeneous spatial distribution in the magnitude of inter-annual variation and location of significant temporal trends in the examined facets of ISM precipitation. A greater extent of the country experienced significant trends (p?<?0.05) of increasing inter-annual variation rather than simple increasing or decreasing trends in annual ISM precipitation and onset date of ISM. Field significance tests showed grid cells reporting significant trends were significant (p?<?0.05) at the global or field level (except trends of increasing, i.e. later, ISM onset date). This research provides finer spatial detail regarding trends and variation in annual ISM precipitation, severe drought years and onset date of ISM complementing recent studies on trends in extreme precipitation events over India to produce a comprehensive overview of recent behaviour of ISM precipitation. These findings will benefit water managers charged with managing water resources sustainably at a fine spatial scale (the watershed or basin level).     

Trend analysis of precipitation in Jharkhand State,India

Jharkhand is one of the eastern states of India which has an agriculture-based economy. Uncertain and erratic distribution of precipitation as well as a lack of state water resources planning is the major limitation to crop growth in the region. In this study, the spatial and temporal variability in precipitation in the state was examined using a monthly precipitation time series of 111 years (1901–2011) from 18 meteorological stations. Autocorrelation and Mann–Kendall/modified Mann–Kendall tests were utilized to detect possible trends, and the Theil and Sen slope estimator test was used to determine the magnitude of change over the entire time series. The most probable change year (change point) was detected using the Pettitt–Mann–Whitney test, and the entire time series was sub-divided into two parts: before and after the change point. Arc-Map 9.3 software was utilized to assess the spatial patterns of the trends over the entire state. Annual precipitation exhibited a decreasing trend in 5 out of 18 stations during the whole period. For annual, monsoon and winter periods of precipitation, the slope test indicated a decreasing trend for all stations during 1901–2011. The highest variability was observed in post-monsoon precipitation (77.87 %) and the lowest variability was observed in the annual series (15.76 %) over the 111 years. An increasing trend in precipitation in the state was found during the period 1901–1949, which was reversed during the subsequent period (1950–2011).     

Assessing climate change impacts on the Iberian power system using a coupled water-power model

Climate change is expected to have a negative impact on the power system of the Iberian Peninsula; changes in river runoff are expected to reduce hydropower generation, while higher temperatures are expected to increase summer electricity demand, when water resources are already limited. However, these impacts have not yet been evaluated at the peninsular level. We coupled a hydrological model with a power market model to study three impacts of climate change on the current Iberian power system: changes in hydropower production caused by changes in precipitation and temperature, changes in temporal patterns of electricity demand caused by temperature changes, and changes in irrigation water use caused by temperature and precipitation changes. A stochastic dynamic programming approach was used to develop operating rules for the integrated system given hydrological uncertainty. We found that changes in precipitation will reduce runoff, decrease hydropower production (with accompanying increases in thermal generation), and increase irrigation water use, while higher temperatures will shift power demand from winter to summer months. The combined impact of these effects will generally make it more challenging to balance agricultural, power, and environmental objectives in the operation of Iberian reservoirs, though some impacts could be mitigated by better alignment between temporal patterns of irrigation and power demands.     

The Effects of Climatic Variability on US Irrigation Adoption

This paper contributes to the literature underscoring the importance of climatic variance by developing a framework for incorporating the means and tails of the distributions of rainfall and temperature into empirical models of agricultural production. The methodology is applied to estimate the impact of climate change on the discrete choice decision to adopt irrigation since it is an important adaptation to climate change. We develop a discrete choice model for the decision to install irrigation capacity that captures the effects of both climate means and extremes. Climatic means and frequencies of climatic events in the upper tails of the temperature and precipitation distributions are used to estimate the parameters of a normal distribution for temperature and a Weibull distribution for precipitation. Using estimates from a probit model, we examine the independent effects of changing climatic mean and variance on the probability of adopting irrigation. Increasing the mean temperature, holding variance constant, shifts the entire distribution toward warmer temperatures—increasing the frequency of extreme temperatures. For precipitation, the specification captures the separate effects of mean rainfall, frequency of rainfall, and frequency of extreme events. The results show that the tails of the temperature and precipitation distributions, not the means, are the dominant climatic determinants in irrigation adoption. The results also show that water availability, soil characteristics, farm size and operator demographics are important determinants of irrigation.     

International trade buffers the impact of future irrigation shortfalls

There is increasing interest in the water–food nexus, especially the restrictive effect of water on food production in hot spots where irrigation stress is growing. However, little is known about the larger-scale implications of future irrigation shortfalls for global trade and economic welfare, as well as of the potential buffering impacts of international trade on the local impacts of irrigation shortage. In this paper, we utilize a recently developed model, GTAP-BIO-W, to study the economic effects of changes in irrigation outlook for 126 river basins, globally by 2030. Projected irrigation availability is obtained from the IMPACT-WATER model, and imposed upon the present-day economy. Irrigation availability in 2030 is expected to drop by 30–60% in several key rivers basins, including: Hai He, Indus, Luni, and the Eastern Mediterranean basin, leading to significant output declines in China, South Asia, and the Middle East. We find that the regional production impacts of future irrigation water shortages are quite heterogeneous, depending on the size of the shortfall, the irrigation intensity of crop production, the possibility of expanding rainfed areas, as well as the crop mix. These changes in regional output significantly alter the geography of international trade. To compensate for the loss of productivity caused by the irrigation constraint, an estimated 7.6 million hectares of cropland expansion is needed to meet the demand for food. In spite of the remarkable reduction of irrigation in some basins, the resulting welfare impact is relatively modest as a result of the buffering capacity of global markets. The global welfare loss amounts to $3.7 billion (2001 prices) and results from a combination of the reduction in irrigation availability as well as the interplay with agricultural support policies.     

Understanding the spatial differences in terrestrial water storage variations in the Tibetan Plateau from 2002 to 2016

Climate change has been driving terrestrial water storage variations in the high mountains of Asia in the recent decades. This study is based on Gravity Recovery and Climate Experiment (GRACE) data to analyse spatial and temporal variations in terrestrial water storage (TWS) across the Tibetan Plateau (TP) from April 2002 to December 2016. Regional averaged TWS anomaly has increased by 0.20 mm/month (p?<?0.01) during the 2002–2012 period, but decreased by ??0.68 mm/month (p?<?0.01) since 2012. The seasonal variations in TWS anomalies also showed a decreasing trend from May 2012 to December 2016. TWS variations in the TP also showed significant spatial differences, which were decreasing in southern TP but increasing in the Inner TP. And a declining trend was clearly evident in the seasonal variability of TWS anomalies in the south TP (about ??30 to ??55 mm/a), but increasing in the inner TP (about 10–35 mm/a). Meanwhile, this study links temperature/precipitation changes, glacial retreat and lake area expansion to explain the spatial differences in TWS. Results indicated that precipitation increases and lake area expansion drove increasing TWS in the Inner TP during the 2002–2016 period, but temperature increases and glacial retreat drove decreasing TWS in southern TP.     

高分辨率MRI模式对青藏高原夏季降水及水汽输送通量的模拟

本文使用MRI模式在不同分辨率下(180 km、120 km、60 km、20 km)的AMIP试验结果, 分析了该模式对青藏高原夏季降水及水汽输送通量的模拟, 并考察模式分辨率的影响。结果表明:MRI模式能够较为合理地模拟出青藏高原夏季气候平均的降水空间分布, 但对气候平均水汽输送通量以及降水年际变化的模拟却存在较大的误差。随着分辨率的提高, 该模式对青藏高原气候平均降水的模拟有明显改进, 包括降水年循环以及夏季降水的空间分布等。分辨率为180 km、120 km、60 km、20 km的MRI模式模拟的青藏高原7月平均降水绝对误差分别为2.2 mm/d、1.2 mm/d、0.7 mm/d、0.2 mm/d。另外, 高分辨率模式模拟的青藏高原夏季水汽输送通量的年际变化也更接近观测。当分辨率达到20 km时, MRI模式模拟的西风水汽输送指数与观测的相关系数达到0.43, 通过了0.1显著性水平的显著性检验。但MRI模式对青藏高原夏季降水的年际变化以及气候平均水汽输送通量的模拟技巧并不随分辨率的增加有明显提高。低分辨率模式中模拟降水量偏大、印度季风槽偏强的现象在高分辨率模式中仍然存在。     

Deforestation,climate change and sustainable nutrition security: A case study of India

Wheat and rice are the most important crops from the point of view of maintaining a sustainable nutrition security system for India, a country whose population may reach one billion by the year 2000. The implications of climate change deriving from tropical deforestation, particularly as concerns temperature and precipitation, with reference to the yield of wheat and rice in different parts of India are hence being studied carefully. Any possible positive gain arising from increased CO₂ concentration is likely to be offset by the yield decline induced by higher temperature and shorter growing period.Professor of Eminence, Water Technology Centre, IARI.President, National Academy of Agricultural Sciences of India and Past President of the International Union for the Conservation of Nature and Natural Resources (IUCN).     

Long-term trend and variability of precipitation in Chhattisgarh State,India

Spatial and temporal precipitation variability in Chhattisgarh State in India was examined by using monthly precipitation data for 102 years (1901–2002) from 16 stations. The homogeneity of precipitation data was evaluated by the double-mass curve approach and the presence of serial correlation by lag-1 autocorrelation coefficient. Linear regression analysis, the conventional Mann–Kendall (MK) test, and Spearman’s rho were employed to identify trends and Sen’s slope to estimate the slope of trend line. The coefficient of variation (CV) was used to analyze precipitation variability. Spatial interpolation was done by a Kriging process using ArcGIS 9.3. Results of both parametric and non-parametric tests and trend tests showed that at 5 % significance level, annual precipitation exhibited a decreasing trend at all stations except Bilaspur and Dantewada. For both annual and monsoon precipitation, Sen’s test showed a decreasing trend for all stations, except Bilaspur and Dantewada. The highest percentage of variability was observed in winter precipitation (88.75 %) and minimum percentage variability in annual series (14.01 %) over the 102-year periods.