Chapter 3

3.1 Introduction

The current reporting period recorded relatively few extreme conditions among the 30+11+1 countries specifically monitored by CropWatch and described in the current chapter. Some of them, however, are part of the large anomaly patterns described in Chapter 1 and they are often surrounded by less important countries in terms of agricultural production where conditions may be more extreme.

Rainfall anomalies (Figure 3.1)

The current reporting period is characterised by an unusually large number of countries with anomalous rainfall. Interestingly, few water-related disasters were reported, including essentially drought in parts of South America (Uruguay with RAIN at -14% and N. Argentina, with the national RAIN departure at -18%) and some floods in Europe and, especially the Horn of Africa (Chapter 5.XXXX).  Table 3.1 provides an overview of countries and groups of countries with positive and negative rainfall departures in excess of 25%.

[LEGEND Table 3.1: Groups of countries with rainfall anomalies in excess of -25% and +25%. Numbers between square brackets indicate the number of countries where the departure for each variable has the same sign as the average. Countries and territories are identified by their ISO 3166-1 alpha-3 codes given at the end of the table.

Notes. Region codes: afe east Africa, afo west Africa, amc central America and Caribbean including Mexico, ams south America, asc central Asia, ass southern Asia, asse south-east Asia, asw western Asia, eur Europe, med Mediterranean including Portugal. Country codes: ARE United Arab Emirates, ARM Armenia, AZE Azerbaijan, BEN Benin, BFA Burkina Faso, BLZ Belize, CRI Costa Rica, CUB Cuba, CYP Cyprus, DMA Dominica, ECU Ecuador, ERI Eritrea, GBR United Kingdom, GMB Gambia, GNB Guinea Bissau, GTM Guatemala, GUF French Guyana, HTI Haiti, IRL Ireland, IRQ Iraq, ISR Israel, JAK Jammu and Kashmir, JAM Jamaica, JOR Jordan, KEN Kenya, KWT Kuwait, MDA Macedonia, MEX Mexico, MNE Montenegro, MNG Mongolia, MRT Mauritania, NER Niger, NIC Nicaragua, OMN Oman, PAN Panama, PHL Philippines, PRT Portugal, SDN North Sudan, SLV Slovenia, SOM Somalia, SSD South Sudan, SVN Slovenia, TCD Chad, TGO Togo, TTO Trinidad and Tobago, TUN Tunisia, YEM Yemen.]

A first observation is that the 15 country groups based on their rainfall departures from average are rather consistent for other variables as well. For instance, in group 12 which groups five west African countries (BFA, TGO, BEN, GMB, GNB), the departures for TEMP, RADPAR and BIOMASS indicate colder than average weather, low sunshine and larger than average biomass production potential in all five countries.

The three first groups do not rise concern as they are currently in their dry seasons or normally do not practice much agriculture.

Group 4 (RAIN -37%), is part of the Mediterranean  basin where the current winter season is also the  main cereal growing period. Rainfall was nevertheless fair over Slovenia (201 mm) , Montenegro (333 mm) and Portugal (179 mm) where evapotranspiration and crop water demand were low. In Cyprus and Tunisia, however, crop water requirement reaches 50 to 100 mm per month, so that the recorded amounts (97 mm and 74 mm over the 4 months JFMA reporting period) may result in crop water stress.

In Jammu and Kashmir (Group 5), the winter crop season is coming to an end in the lowlands. High temperature, however, which is part of the heatwave which has affected Pakistan and surrounding areas, has increased crop water requirements and water stress is likely to have occurred.

The two countries in Group 6 (French Guyana and Ecuador) are basically unrelated, and they are separated by countries with above average precipitation such as Colombia and Venezuela. The deficit should not have seriously affected crops, which are at the end of their growing season in the Pacific lowlands in Ecuador. The Amazonian (eastern) part of Ecuador and French Guyana have very long equatorial seasons which are rather resilient against water stress.    

Group 7 (Eritrea and Sudan) are currently beyond harvest, with Sudan cultivating winter crops which are, however, mostly irrigated.

Among the remaining groups, many are semi arid and excess rainfall – with the exception of possible local floods – is  mostly a useful source of soil moisture, even if present temperature (i.e. winter) conditions do not permit much biomass development. This applies, for instance, to Mongolia (Group 8). The countries of Group 11 (+46% RAIN on average) as well as 13 (Macedonia) mostly cultivate winter crops and the additional moisture is welcome, especially where irrigated crops dominate the agricultural landscape (Israel, Jordan…).

Some of the west African countries in Group 12 (Burkina Faso, Gambia and Guinea) are currently not in their rainy season, which will start in Summer. The abundant rainfall can be interpreted as an early start of the season. Togo and Benin have two rainy seasons in the south, with the first starting around March. Both countries have benefited from the abundant precipitation which has provided a good start for the first season.

Of the countries of Group 14, two have large semi-arid stretches (Kenya, Somalia) where drought staples are livestock prevail. Both are at planting stage for their main season (long rains in Kenya and Gu season in Somalia). South Sudan normally enjoys much wetter conditions, especially in the west. Kenya and Somalia floods are mentioned in the section on disasters (Chapter 5.X) but much of the problems are linked to large displaced populations. In general, the abundant precipitation should have benefited farming and food production.

A wide diversity of crop situations exists among the 10 countries of Group 15. Most of them grow winter crops (including winter maize) and it can be assumed that the abundant precipitation was favourable to winter crops nearing the end of their cycles, especially in Mexico where normal winter rainfall tends to be low.

Temperature anomalies (Figure 3.2)

Some below average temperatures close to larger than 2.0 °C occurred in Norway, Ireland (as part of the cold spell referred to as “The  Beast from the East” (refer to Chapter 5.X on Disasters) and Yemen, where a marked excess of rainfall was recorded. The “Beast of the East” also affected much of western Russia and Kazakhstan, Scandinavia and western Europe from France to Spain as well as Morocco.  

The highest temperature departures are those associated with the late March- early April heat wave centred around Iran (refer to figure 5XB in the section on disasters). They include Syria (+2.9°C), Turkey (+2.8°C), Armenia (+2.4°C), Iraq  and Jammu and Kashmir (both at +2.0°C). Other countries of the same group, although they report smaller temperature excesses , include Iran, Mongolia, Jordan, Tajikistan and Georgia with departures increasing from +1.4°C to +1.9°C. Spatially, the area is easy to recognise in Figure 5.2.

RADPAR anomalies  (figure 3.3)

As stressed in chapter 1, at the global scale negative sunshine departures predominate. In India, for instance, all States had below average sunshine, resulting in a national departure of -6%. Individual States had record negative departures between 10 and 13% (Meghalaya, Mizoram, Manipur, Tripura, Nagaland, Assam, Sikkim and West Bengal). Neighbouring Bangladesh reached -12%, one of the lowest values at the national level, comparable to the United Kingdom and Ireland (also at -12%) and exceeded only by Liberia (-13%).

Countries with positive departures are few; they include Uruguay (+4% RADPAR) and Ecuador (+3%; both suffered drought conditions) and Poland (+3%, accompanied by a 19% drop in rainfall). Uruguay is part of an area that stretches from Buenos Aires to the north-western provinces of Argentina.  Poland, on the the hand, is the westernmost part of an area that reaches north as far as Finland (+2%) and Norway (+1%) and east  to Ukraine (+2%) and Russia (Mordovia +3% and the Oblasts of Kursk +3%, Ryazan +3%,  Nizhny Novgorod +4%  and Kirov 7%.

BIOMSS (figure 3.4)

Due to the dominant role of water as a limiting factor of biomass production, the distribution of the BIOMSS indicator closely follows the distribution of RAIN… at least as long as TEMP does not interfere too much. For the present reporting period, we noted  in chapter 1 that, globally, “80% of its variations or BIOMSS can be ascribed to RAIN variations and 20% only to TEMP”.

Because of the large temperature anomaly associated with the “Beast from the East” , it appears clearly, when comparing figures 3.1 and 3.4, that rainfall excesses over Russia are associated with BIOMSS deficits. In fact, as clearly shown in Figures 3.5 and 3.6, temperature dominates BIOMSS: in the major production zones of Russia, the role of RAIN in the variability of BIOMSS is negligible during the current reporting period, just 1% (R²=0.0079). TEMP, on the other hand,  accounts for 72%. It is likely that higher percentages would be achieved if the reference periods for TEMP and RAIN (2003-2017) and BIOMSS (2013-2017) were identical.  

Figure 3.5 : Dependence of percent BIOMSS departure from 2013-17 average on RAIN percent departure from 2003-2017 average.

Figure 3.6 : Dependence of percent BIOMSS departure from 2013-17 average on TEMP percent departure from 2003-2017 average.