Building on the global patterns presented in previous chapters, this chapter assesses the situation of crops in 30 key countries that represent the global major producers and exporters or otherwise are of global or CropWatch relevance. In addition, the overview section (3.1) pays attention to other countries worldwide, to provide some spatial and the matic detail to the overall features described in section 1.1. In section 3.2, the CropWatchmonitored countries are presented, and for each country maps are included illustrating NDVI-based crop condition development graphs, maximum VCI, and spatial NDVI patterns with associated NDVI profiles. Additional detail on the agroclimatic and BIOMSS indicators, in particular for some of the larger countries, is included in Annex A, tables A.2-A.11. Annex B includes 2015production estimates for Argentina, Brazil, Canada, and the United States.

3.1 Overview

Figures 3.1-3.4 illustrate the global distribution of CropWatch indicators for rainfall, temperature, radiation, and biomass—respectively the RAIN, TEMP, RADPAR, and BIOMSS indicators, show in gtheir increase or decrease for this monitoring period compared to last year’s April-July period. Details by country are presented in table 3.1.

Figure 3.1. Global map of rainfall(RAIN) by country and sub-national areas, departure from 14YA (percentage), April-July2015

Figure 3.2. Global map oftemperature (TEMP) by country and sub-national areas, departure from 14YA (degrees),April-July 2015

Figure 3.3. Global map of PAR (RADPAR)by country and sub-national areas, departure from 14YA (percentage), April-July2015

Figure 3.4. Global map of biomass (BIOMSS)by country and sub-national areas, departure from 14YA (percentage), April-July2015

Among the 31 countries monitored by CropWatch (see the detailed analyses in section 3.2), several countries experienced nationwide favorable or unfavorable conditions, starting with a group of western European countries (France, Poland, Romania, Germany, and Ukraine; figure 3.1) where spring and early summer rainfall (RAIN) was about 26% below average (-38% in France to -20% in Ukraine) with slightly below average temperature (TEMP,-0.1°C), average sunshine as indicated by RADPAR, and a biomass production potential (BIOMSS) decrease of 24% compared to average. In Romania, cropped arable land fraction (CALF) fell 3 percentage point compared with the recent five-year average while the maximum Vegetation Condition Index (VCIx) was justfair (0.76), indicating that, among the listed countries, Romania is likely to be one of the most affected by the adverse conditions. In Ukraine, on the otherhand, CALF increased 2%, and the fair crop condition (VCIx=0.86) points to a more limited impact.

Below average water supply affected two Asian countries:Iran (-41%) and Thailand (-24%), both with above average temperature (+1.4°Cand +0.8°C, respectively) and above average sunshine (+2% and +8%), resulting in decreased production potentials of -13% (Thailand) and -33% (Iran). In Thailand, however, CALF was identical to the average of the last five seasons,accompanied by “good” VCIx (0.81), which is not compatible with a serious impact. In contrast, Cambodia, with a slight rainfall deficit (RAIN, -3%) and abundant sunshine (RADPAR, +5%), displays a low CALF value of 5 percentage points below average and a VCIx of 0.83; in this case non-weather factors may have played a part.

Table 3.1. CropWatch agroclimaticand agronomic indicators for April-July 2015, departure from 5YA and 14YA

Note: Departures are expressed in relative terms (percentage) for all variables, except for temperature, for which absolute departure in degrees Celsius is given. Zero means no change from the average value; Relative departures are calculated as(C-R)/R*100, with C=current value and R=reference value, which is the five-year(5YA) or fourteen-year average (14YA) for the same period (April-July).

Two African countries were also affected by poor water availability: Ethiopia and South Africa. The first recorded a water deficit of25%, with above average sunshine (+4%) and a drop in BIOMSS of 22%. The impacton cultivated land fraction is slight (-2%) and condition is generally rather satisfactory (VCIx=0.88). In the second country, the precipitation deficit inthe late months of the growing season was severe (reaching -50%) with are sulting biomass production potential deficit of 42% but nevertheless close to normal sunshine and temperature. South Africa is the only country among those monitored by CropWatch that shows both a marked drop in cultivated land fraction (-10%) and poor crop condition (VCIx=0.35), leaving little doubt thatcrops suffered seriously from the drought.

In Australia and Canada, the rainfall deficit reached 22%and 30%, respectively. In Australia this was combined with above average temperature (+0.7°C) and sunshine (+4%), while Canada experienced relatively cool weather and a correlated sunshine drop of 3%. CALF dropped by 6% in Canada, which is one of the largest drops among all CropWatch monitored countries, although VCIx seems to be rather favorable, indicating a decrease incropped area but satisfactory condition in planted areas.

At the national scale, significant above-average precipitation is reported from the United States, where it affected mostlysouthern and central western states (RAIN, +33%) with about average temperature and low RADPAR, resulting in a BIOMSS increase estimate of 19%. CALF rose 2% ofthe average of the recent five years, and VCIx was rather favorable (0.88),indicating at least fair conditions globally in spite of local floods and drought.

Kazakhstan also recorded excess rainfall (+41%) but otherwise average conditions, with a positive impact on BIOMSS (+42%).Considering that CALF markedly increased (+9%) and that VCIx shows goodconditions (0.89), the condition of the country's crop and rangeland can beassessed as favorable. Finally, Bangladesh received large excesses ofprecipitation compared to average (+71%), which led to floods and also affected neigh boring areas in India, Myanmar, and Nepal, as discussed in more detail inthe respective country sections in this chapter and in section 5.2 on disasterevents. Bangladesh suffered a very significant drop in RADPAR (-9%) butapparently no drop in cropland (as assessed by CALF and indicated by good VCIx)

When considering all countries worldwide (see also figures3.1 to 3.4), additional detail emerges in terms of global patterns, as already indicated at a coarser spatial resolution in Chapter 1 as well as on a sub-national scale for the largest countries. Drought affected several countries in theMiddle East and North Africa with negative RAIN departures in Oman (-53%),Cyprus (-68%), Lebanon (-63%), Israel (-53%) and Tunisia[1](-60%). Drought also affected the Caribbean islands (Dominica -90%, Jamaica-54%, and Trinidad and Tobago -52%) as well as Uruguay (-61%), although the country is mostly surrounded by areas with average or above average rainfall,sometimes significantly so especially in southern Brazil and northern Argentina. Poor water supply also affected Lesotho[2](-50%, similar to the deficit in South Africa), Eritrea (also -50%), and ComoroIsl and (-58%), an Indian Ocean nation that is part of the same climatic belt as Madagascar and southern Africa.

Finally, the Republic of Korea (RAIN, -51%) and the Democratic People’s Republic of Korea (-63%) also experienced water deficits. The two countries are part of a cluster also involving adjacent areas in China, inparticular parts of north-east and east China (Shanxi, Henan, Hebei, Tianjin,Shandong, Taiwan, Liaoning, and Jilin) where the deficit typically ranged from44% to 26%, with the largest value recorded in Hebei (-55%). Unconnected spatially to the previous provinces, Yunnan also suffered a deficit of 36% in arainfall deficit area that extended into Laos (RAIN -25%) and the already mentioned Thailand.

Areas where excess precipitation occurred include mostlycoastal areas in south-east China (refer to section 5.1), with excess RAIN valuesin the range from 32% to 54% (Hunan, Guangxi, Anhui, Jiangxi, and Shanghai), as well as the western regions of Tibet (+78%) and in Xinjiang-Uygur. The latterexperienced a spectacular in RAIN of +165% compared to average. The combination of favorable and unfavorable conditions in areas in China results in a slightdrop in the fraction of cropped arable land (-2 percentage points) butaltogether rather favorable crop condition as assessed by VCIx (0.9).

The areas of Tibet and Xinjiang-Uygur are part of acontiguous region of excess precipitation starting in north-east India withexcesses between 27% in Assam and reaching 55% in Uttarakhand over Bihar,Meghalaya, Himachal Pradesh, Chhattisgarh, and Haryana. The largest rainfall excesses were recorded in Uttarakhand (+55%), Jharkhand (+60%), Sikkim (+64%), West Bengal(+75%), and Tripura (+93%). West India, on the other hand, suffered poor rainfall, especially Goa (-70%) and Gujarat (-51%), but also Maharashtra,Kerala, Puducherry, and Karnataka (-27%). Although biomass is average, based ona low value for CALF (-6%) and a fair VCIx (0.84), slightly below average condition is expected.

North of the Xinjiang-Uygur region, precipitation excesseshave benefited the mostly pastoral economies in Kyrgyzstan (RAIN, +63%) and Kazakhstan (Oblasts of Vostok (+80%) and Kyzylorda (+118%)), with rainfall excesses extending into Russia (Kurgan +68% and Tyumen +68%) as well as most areas in between and extending west up to—but not including—Finland. Conditions were generally unfavorable in southeast Siberia, including the Amur (-22%) and Chita (-35%) Oblasts as well as the Buryatia (-35%) and Tyva (-26) Republics.

[1]Neighboring Algeria and Libya also suffered; the three countries (Algeria,Libya and Tunisia) can be considered as part of the same set of countriesexperiencing a rainfall deficit as the European countries for which only themost severely affected were listed. Mediterranean Europe also recorded arainfall deficit.

[2]In contrast, both Zimbabwe (RAIN, +94%) and Zambia (RAIN, +122%) enjoyedunusually good late cropping season conditions.